Ecology

In a region under consideration, let at any instant (t >0), x and y represent the prey and predator population densities, respectively. The rate of change of each model species density at time t is made on the following assumptions:

1.

Prey population grow logistically in the absence of predator with birth rate r, which is affected by the fear ((f_1)) of predator (when predators are around).

2.

There is a reduction in the rate of prey density change due to three types of death, namely, natural death with the rate (d_1), fear related death5 with the level of fear (f_2) and over crowding death with the rate (d_2).

3.

Also, the rate of change of prey density decreases due to predation of predator population following a predator-dependent functional response describing both predatory and prey schooling behaviors10. Response function is expressed in functional form describing as (zeta (x, y)=frac{cxy}{1+chxy}), where c denotes the rate of consumption and h represents handling time of predator for one prey.

4.

Predator population survive in the system by consuming prey population only. They grow with conversion efficiency (c_1) of prey biomass into predator biomass.

5.

Predator population harvested from the system which reduces its rate of density. We consider a nonlinear harvesting term (Michaelis-Menten type) given by, (H(y)=dfrac{qEy}{p_1E+p_2y}). Here, parameters q and E, respectively, represent the catchability rate and harvesting effort. It is easy to observe that (Hrightarrow frac{q}{p_1}y) as (Erightarrow infty) for a fixed value of y. Also, (Hrightarrow frac{q}{p_2}E) as (yrightarrow infty) for a fixed value of E. Therefore, at higher effort levels, (p_1) is proportional to the stock level-catch rate ratio and at higher levels of stock, (p_2) is proportional to the effort level-catch rate ratio.

6.

Lastly, we assume that the predator population experience natural as well as over crowding related death with the rates (d_3) and (d_4), respectively.

Keeping all these above assumptions in mind, we formulate the following prey–predator model:$$begin{aligned} frac{dx}{dt}= & {} frac{rx}{1+f_1y}-(1+f_2y)d_1x-d_2x^2-frac{cxy^2}{1+chxy}nonumber ,\ frac{dy}{dt}= & {} frac{c_1cxy^2}{1+chxy}-d_3y-d_4y^2-frac{qEy}{p_1E+p_2y}. end{aligned}$$
(1)
System (1) is to be analyzed with the initial conditions (x(0),y(0) >0). All the model parameters are assumed to be positive constants and their hypothetical values that we used for numerical calculations are as follows:$$begin{aligned}{} & {} r=3.1, f_1=1, f_2=0.4, d_1=0.1, d_2=0.08, c=0.11, h=0.1, c_1=0.5, d_3=0.1,nonumber \{} & {} d_4=0.06, q=0.65, E=0.5, p_1=0.5, p_2=0.65. end{aligned}$$
(2)
In Table 1, we have provided system’s equilibria, sufficient conditions of their existence and stability. Mathematically, it is difficult to determine the existence of coexistence (interior) equilibrium point(s) by the given nullclines. So, we visualize it numerically (see Fig. 1). It is apparent from the figure that on increasing the value of E, number of coexistence equilibrium points reduces and after a certain range there is no coexistence equilibrium point.Table 1 Sufficient conditions for the existence and stability of different equilibrium points of system (1).Full size tableFigure 1Nullclines for different values of E. Other parameters are same as in (2).Full size image
Transcritical bifurcationFrom Table 1, it is clear that the equilibrium (E_0) is stable if (rr^{TB}=d_1=0.1)) then (E_0) becomes unstable and the equilibrium point (E_1) exists and becomes stable.Figure 2Transcritical bifurcation with respect to r. Rest of the parameters are same as in (2).Full size imageHopf bifurcationOne of the most common dynamics in interacting population dynamics is oscillating behavior, which implies that there is a Hopf bifurcation. By local changes in equilibrium properties, Hopf bifurcation describes when a periodic solution appears or disappears. In this section, we study the Hopf bifurcation through the coexistence equilibrium (E^*) with respect to the model parameter E. Discussion for the existence of Hopf bifurcation is as follows:As it is easy to follow, we verify Hopf bifurcation numerically. We have considered the parameters value same as in (2) except (c=0.1) and E. At (E=E^{[HB]}=0.1196559641), the trace of the Jacobian matrix at (E^*(2.618402886, 2.352228027)) is zero and determinant, (Det(J_{E^*})=0.4474794791 >0). The value of (dfrac{d(Tr(J_{E^*}))}{dE}Big |_{E=E^{[HB]}}=-0.02965188514ne 0). Therefore, the transversality condition for Hopf bifurcation is also satisfied at (E=E^{[HB]}). Thus, these results confirm that the system (1) experiences a Hopf bifurcation2 around (E^*(2.618402886, 2.352228027)).Moreover, we obtain Lyapunov number (L_1=-0.04728284756pi More

The contributions of SMFEs to the local economy and developmentSMFEs are characterized by limited resources, hence their inability to employ more people however, the few being employed to aid in the operations of the businesses contribute to the reduction of the employment gap among the youth in the study areas. The employment opportunities provided by SMFEs supplement the central government’s efforts to offer employment to the people. Subsequently, the people in the area depend on it for their livelihood to improve their living standards. The study found a diverse number of SMFEs in terms of wood and non-wood-related activities (Fig. 3) that people engage in as primary or secondary jobs. Some evidence has proved that SMFE’s contribution to forest employment is above 50% in some countries like Brazil, Uganda, Guyana, and China, and almost 80 to 90% of all forest-based enterprises in most countries7. This may directly impact efforts to reduce poverty by improving the living standards of people who form and operate SMFEs as a livelihood.Zada et al.10 also reported that households who own SMFEs had a wealth index increase from 5.4 to 7.4 whereas those without SMFEs had an index of 4.9. SMFEs do have the potential to improve household income levels which can lead to reinvesting and expansion. This study found that the monthly expenses of SMFEs contribute to 46.2% of their monthly sales. Therefore, if SMFEs can increase significantly, their ability to reinvest while observing the best practices in operating their businesses then they will be able to maximize their turnovers. This can result in expansion and more employment opportunities for others hence, reducing the burden on the government to provide employment.There is a direct positive and significant relationship between SMFEs and local economic development11. SMFEs were reported to positively and significantly mediate the relationships between government support, entrepreneurship knowledge, and local economic development. SMFEs with informal or formal training can ensure government support is efficiently used in tapping into entrepreneurial knowledge to drive their impacts on local economies. This will also allow them to grow into sustainable businesses while also promoting the sustainability of forest resources which they depend on for raw materials.Operational characteristics and impacts of SMFEs on sustainabilityAround the globe and per the laws of Ghana, businesses are required to fulfill certain obligations to enable them to run smoothly12. Failure to undertake these tasks may attract severe penalties, including criminal charges that may carry significant jail terms. An example is failure to pay taxes and adhere to certain regulations. This section looks at certain characteristics of SMFEs in this study that project their impact on sustainable forest management.Firstly, the laws of Ghana make it mandatory for all business categories to pay tax and as such, SMFEs are not left out. However, the major challenge with taxes in Ghana and by extension, the world, is compliance. Mantey13 reported that 59.1% of small business owners did not understand the Ghanaian Tax System. The key lesson drawn from this observation is that, as SMFEs, one of their characteristics is that they generate a smaller income compared to larger companies or corporate bodies. This goes a long way in determining the amount they pay as taxes. In addition, by their nature, they can under-declare the revenue they make to influence the amount they will be taxed. This calls for the development and flawless implementation of mechanisms to monitor and audit these SMFEs to ensure that they comply with tax directives and regulations.Mantey13 further reported that 57.4% of the surveyed business owners are not aware of most tax laws and guidelines on the taxation of incomes for organizations. Some blamed their inability to pay taxes on the business being slow and others were unwilling to give a response to why they were unable to pay their taxes. In this study, majority (77.5%) indicated that they pay taxes. It was also established in this study that payment of taxes has a significantly weak correlation with the educational background of the respondents. Though the majority of the SMFEs paid taxes, it may not be directly linked to all respondents having some form of formal education and vice versa. However, this may be factored in when considering the training and mentoring of SMFEs to contribute to local development by paying their taxes. More SMFEs may endeavor to pay their taxes regularly if they understand what these taxes can do to improve their work environment.Governments in recent times have stepped up revenue mobilization efforts to capture more businesses into the tax bracket of the country. This has seen the revenue authorities recruit and train more revenue officers to reach businesses like SMFEs which are mostly not reachable due to their inability to register their businesses.Secondly, the majority (71.25%) of SMFEs in this study was not registered. This adds to the general belief that most businesses operate without the required licenses or have failed to renew their expired licenses. Some studies also made similar observations and arrived at the lack of enforcement of laws, as a key reason why many businesses in developing countries remained unregistered contrary to the requirements of the law14,15. Further analysis showed SMFEs who belong to associations are likely to register their businesses because it is a requirement to join them. The benefits of belonging to an association include access to loan facilities and other credit programs and therefore some SMFEs do not want to risk missing out through failure to get their business registered16.SMFEs need to get registered for them to be considered legitimate business entities however, this seems to be a challenge in most developing countries. Tomaselli et al.17 found this assertion relevant when investigating SMFEs access to microfinance. Registration of business is a key requirement to access loan facilities and so is belonging to a recognized association. Associations are known to serve as guarantors for members who want loan facilities from banks and other financial institutions to expand their businesses16. Unregistered, unregulated, and unmonitored SMFEs are those whose activities tend to compromise the sustainability of forest resources18. Therefore, registration of SMFEs does that only serve the interest of governments but also the interests of these SMFEs themselves.The third has to do with the sourcing of raw materials. Ghana being a tropical country is blessed abundantly with forest resources but over the decades, the overexploitation of these forests has brought to the brink of extinction, various species of both plant and animal life19. The dependence of SMFEs on the forests cannot be underestimated as literature, citing Osei Tutu et al.20, posits that SMFEs contribute to 95% of the income of some rural households. This study shows that 68.8% of SMFEs get their raw materials directly from the forest. Both woody and non-woody materials are in abundance and can be extracted with minimal cost.In sourcing raw materials from the forests in Ghana, SMFEs are required to obtain permits or licenses from the relevant authorities such as the forestry commission. This permit/license is what allows or gives this SMFEs access to otherwise inaccessible forest reserves to harvest raw materials20. Additionally, these documents can go as far as determining the type and quantity of materials to harvest. It can also determine the type of access granted as these accesses can vary or differ depending on the time or season of harvest18. The issuance of permits and licenses is meant to monitor and regulate resource harvesting with the primary goal of checking the overexploitation of these resources. However, this is not possible due to the high levels of non-compliance by SMFEs21. Evident in this study is the 78.2% of SMFEs who gather raw materials from the forest without permits/licenses.Osei Tutu et al.18 concluded that the neglect of the SMFEs sub-sector is responsible for the loss of state revenue because of their unwillingness to register and pay appropriate taxes and permit fees for their illegal and unsustainable business operations. The report further posits that “despite the numerous support channels (national and international) available to them, the roles played by SMFEs in poverty reduction are significantly unimpactful hence the need to intensify capitalizing on all opportunities to address challenges they present.” The government institutions in charge of these forest resources depend on these permits and license fees to supplement their already insufficient government subventions for the operations. Therefore, losing revenues may undermine their sustainability programs.Driving factors of SMFEsThe ability of a business to thrive highly depends on its ability to overcome certain challenges within its operating environment22. That alone, however, is not enough as certain factors ignite the ambition of a business. These factors decisively influence the success or the failure of the business hence, they are identified as determinants. The study sought to identify some determinants that drive the activities of SMFEs. Responses from the SMFEs concluded that economic and social factors such as resource availability, profits/revenue, employment, and labor are the key determinants that drive the SMFEs.Resource availability was the major driver of their activities cited by 91.3% of SMFEs. This is because, the numerous forests the nation is endowed with provide abundantly, the raw materials needed for them to use. Due to the favorable climatic conditions prevailing in the high forest zones, there is a constant supply of materials needed by SMFEs to produce their products for business23. In addition, availability means less competition for limited resources and therefore it boils down to the ability to process these raw materials into finished goods for market consumption hence, reducing the costs of production24.SMFEs also pointed to profits/revenue, as the factor driving their activities to engage in, and sustain their business. The abundance and readily availability of raw materials are very important to the growth of their business and in turn, help them maximize their returns. This is because the inputs they make to acquire the raw materials are relatively low in comparison to the total revenues they generate. This observation is also reflected in the captured expenditures they make as inputs or investments into their businesses.SMFEs that need technologically advanced mechanisms and equipment are those that are required or inclined to make heavy investments whereas those that need simple tools and equipment invest less. Whichever the case, the nature of SMFEs suggests that a business that requires raw materials with very minimal or no costs involved at all, yet yields very high profits, is how people can improve their living25. Badini et al.26 classified enabling environment of SMFEs into external and internal factors where financial capital, business management, and organizational capacities form internal factors. On the other hand, external factors include regulatory frameworks, forest law enforcement, and natural capital which refers to the stock of natural resources or environmental assets. The success of any SMFE is largely dependent on these factors.Finally, 8.75% of the SMFEs view labor and employment, as the determinants driving their existence. For them, compared to other labor-intensive ventures, their business does not require huge labor to get work done. The few hands needed means most of the revenues do not go to paying workers. They can dictate and bargain to their advantage because there are many people without jobs hence a job turned down, because of less encouraging benefits is gladly accepted by another25. Ultimately, the study finds that labor is cheap in some areas of the SMFEs’ environs primarily, due to unemployment.Sustainability challenges in forest management relative to SMFEs activitiesSince the United Nations Conference on Environment and Development (UNCED) in Rio de Janeiro, Brazil in 1992, key challenges of SFM have broadly covered the sustainability of forest resources through the reduction of deforestation and forest degradation, conservation and protection of biological diversity, genetic resources sustainability and improving forest goods and services valuation27. It is important to note that SMFEs have played an overlooked role in these challenges as it seems its contributions to poverty reduction have taken center stage in international discourses, with its negative impacts on the environment being relegated to the backseat when considering the causes of environmental degradation. Attempts to effectively manage the activities of SMFEs have witnessed the emergence of a lot of challenges that threaten the very sustainability the globe yearns for. Some reasons point to the source of the challenges that have plagued these efforts, some of which are highlighted below.First is the lack of resources to recruit and train the needed personnel to constantly monitor the activities of these SMFEs during the harvesting of raw materials. This makes it easier for them to enter restricted forest areas without the necessary documentation and proceed to harvest more than they are required to at any given time. Secondly, it is difficult to track their activities because many SMFEs currently, do not register their businesses as required by law.A typical example is the use of unapproved trails or routes and the use of inappropriate harvesting techniques such as burning. This leads to the destruction of various lifeforms that are critical to the regenerative capabilities of the forests28. The study also found that the supervision of the activities of SMFEs is very poor as only 12% of SMFEs had their activities supervised on certain occasions. This buttresses the assertion by Acheampong et al.29 who posited that the lack of supervision is a major issue that needs to be vigorously addressed if we need to achieve forest sustainability in developing countries.There is a need to educate SMFEs on the laws and regulations governing the use of forest resources. It was revealed that only 16% of the respondents have some knowledge of the regulations governing the harvest and use of both woody and non-woody forest resources. This knowledge gap is being exploited by SMFEs as an excuse for not doing what is expected of them. However, a study found that 69% of respondents claimed to have good knowledge of the regulations governing their activities14. This can be attributed to self-learning or the action of the supervising authorities who for one reason or another other can perform their mandate of educating the SMFEs. There is a need to properly equip the supervising agencies to carry out this mandate.The research, therefore, cites the non-registering of SMFEs as an underlying cause of the flouting of these regulations and laws. The research also suggests that some form of training can be done at the point of registering even before the certification is done. As observed in the area of training, there is not enough emphasis on the need to train SMFEs in sustainability issues in terms of harvesting raw materials. It was noted that the majority (67%) of SMFEs (Table 8) have no training on how to harvest, process, and adequately market their products to ensure maximum profits while sustaining the resources for future harvests. There is a need to institute training and capacity-building programs for SMFEs that will empower them to succeed and yet aim to ensure sustainable forest management.The role of sustainable forest management in climate change mitigationSustainable forest management (SFM) can play a significant role in climate change mitigation, as forests are an important sink for carbon dioxide and other greenhouse gases. By sequestering carbon in their biomass and soils, forests can help to remove carbon dioxide from the atmosphere, which can help to mitigate the impacts of climate change30.There are a number of ways in which SFM can support climate change mitigation, including through the conservation and expansion of forests, the sustainable management of forests, and the use of forest-based products and practices that reduce greenhouse gas emissions. Policymakers and stakeholders at local, national, and international levels are increasingly recognizing the role of forests in climate change mitigation, and there is growing interest in developing strategies and policies that support the use of forests for this purpose.However, there are challenges that impede the efficient leveraging of SFM for climate change mitigation and one of such challenges is the need to balance economic, social, and environmental considerations31. Forests provide a range of goods and services that are vital for human well-being and economic development, including timber, non-timber forest products, and ecosystem services such as carbon sequestration, water regulation, and habitat for wildlife32. However, these resources can be in high demand, and managing forests sustainably can be difficult, particularly in developing countries where there may be limited access to financial and technical resources33.Another challenge is the impact of external factors such as climate change on the health and productivity of forests34. Rising temperatures and changing weather patterns can affect the growth and survival of forests, and may also increase the risk of forest fires and pests35. Policymakers must consider the role of forests in mitigating and adapting to climate change, as well as the potential impacts on forest-dependent communities32.One way in which SMFEs can contribute to climate change mitigation is through the sustainable management of forests. By practicing sustainable forestry, SMFEs can help to maintain and enhance the carbon sequestration capacity of forests, which can help to remove carbon dioxide from the atmosphere and mitigate the impacts of climate change31. This can involve practices such as planting and reforestation, soil and water conservation, and the use of sustainable harvesting techniques32. However, this study revealed the majority of these SMFEs are unregistered and therefore not monitored. Meaning their activities cannot be regulated to ensure practices that promote climate change mitigation.SMFEs can also contribute to climate change mitigation by using forest-based products and practices that reduce greenhouse gas emissions. For example, the use of wood products as a substitute for fossil fuel-based products can help to reduce emissions, as wood products sequester carbon over their lifetime and do not release it into the atmosphere when they are used34. In addition, the use of biomass energy in place of fossil fuels can help to reduce emissions, provided that the biomass is sourced sustainably and the emissions associated with its transportation and use are accounted for35.Another way in which SMFEs can contribute to climate change mitigation is through the development of innovative solutions and technologies that support sustainable forestry practices and reduce greenhouse gas emissions. This could include the use of precision forestry techniques, which use advanced technology to improve the efficiency and sustainability of forestry operations34. It could also involve the development and commercialization of new forest-based products or practices that have a lower carbon footprint32.Policies can have a significant impact on the way in which forests are managed for climate change mitigation31. For example, policies that promote sustainable forestry practices, such as the use of certification schemes or incentive programs, can help to ensure that forests are managed in a way that meets the needs of current and future generations33. On the other hand, policies that do not adequately consider the needs and interests of all stakeholders, or that do not provide sufficient support for sustainable forestry practices, may have negative impacts on the ability of forests to contribute to climate change mitigation34.Overall, addressing the inter-challenges of SFM for climate change mitigation and the impact of policies is an important part of ensuring the sustainability and long-term viability of forests as a tool for mitigating climate change.Development of SMFEs within the forest-based economy of Ghana through policyDespite the global consensus on the sustainability of forest resources and their utmost importance regarding the sustenance of present and future generations, the situation remains unclear at the field level36. The application of criteria and indicators of sustainability provides support for a small but crucial clarification on achieving sustainable forest management (SFM). A meaningful basis for assessing SFM at operational levels will require clarification together with management prescriptions and performance standards while providing linkage to voluntary timber certification.Currently, many environment-based non-governmental organizations (ENGOs) like Global Footprint Network and Fauna & Flora International who are concerned about natural resource exploitation, are convinced by the international debate on criteria and indicators that timber harvesting and ecosystem services of the forests can be sustained37. Stakeholders of the forestry franchise agree that environmental conservation can be accommodated through a necessary and reasonable modification and adaptation of forest-harvesting practices. Therefore, multi-resource forest management as a new paradigm replaces the indigenous sustained-yield management approach that bases on growth-harvest equilibrium using policy as a vehicle38.Food and Agriculture Organization (FAO) is assisting countries through policy advice, technical assistance, capacity building, workshop, and hands-on training, to overcome the challenges of sustainable forest management39. The assistance is provided through the assessment of forest resources and the elements of SFM, as well as the monitoring of progress toward it. FAO also identifies, tests, and modern scientific SMF approaches and techniques to address climate change mitigation and adaptation challenges such as increasing demand for wood and non-wood forest products and services, pest, and diseases.The views held by the Forestry Commission and National Board for Small Scale Industries (NBSSI) during interviews are in line with the suggestions and actions by the World Bank and FOA that involve training and other support systems for managers of forest resources in tropical countries like Ghana that depends heavily on its natural forests. Despite the availability of some of the avenues needed to execute these strategies, the non-compliance by SMFEs makes it difficult for these targets to be met. The general thought is that, if all relevant authorities and stakeholders perform their roles effectively, the current challenges of maximizing the contributions of SMFEs to development and sustainable forest management can be realized.The impact of forest policies is evident in countries like Gabon, a country rich in forest resources, which regards forests as a critical economic resource. World Bank-supported reforms have helped make concessions awarding procedures more competitive and transparent40. Forest taxation recovery has been bolstered, with tax collection rates increasing from 40 to 80% between 2005 and 2010. Sustainable forest management is presently practiced in around 85% of productive forest areas and as a result of these reforms, the forestry sector’s contribution to Gabon’s GDP increased from 2.5% in 2004 to 4.7% in 200940.Support for small and medium forest-based firms raised actual cash income among forest user groups by 53% in India’s Andhra Pradesh throughout the project duration. Seasonal outmigration decreased by 23%, and the quality of thick forest cover in these places improved40,41.Ghana has made significant progress toward sustainable management of its forest resources via the adoption of different forest regulations like the Forest and Wildlife Policy of 1994, Timber Resources Management Act, of 2002, etc. The problem with most of the country’s forest resource policies is the lack of attention paid to the human component; the emphasis is on sustainable timber extraction, even if it is destructive to the livelihoods of forest-dependent populations. Forest policies have historically been determined by successive administrations’ economic interests, which essentially focused on the exploitation of wood resources for income production. This has been a significant impediment to the creation and development of non-timber forest products which the majority of SMFEs depend on in Ghana. This has allowed the number SMFEs rapidly increase due to the lack of coverage by forest policies42. The policy interventions in Gabon and India have yielded results that can provide the foundation needed for Ghana to formulate its policies for the development of SMFEs in a way that does not threaten sustainable forest management. More

Alerstam, T., Hedenström, A. & Åkesson, S. Long-distance migration: Evolution and determinants. Oikos 103, 247–260. https://doi.org/10.1034/j.1600-0706.2003.12559.x (2003).Article 

Google Scholar 
Somveille, M., Rodrigues, A. S. L. & Manica, A. Why do birds migrate? A macroecological perspective. Glob. Ecol. Biogeogr. 24, 664–674. https://doi.org/10.1111/geb.12298 (2015).Article 

Google Scholar 
Tatner, P. & Bryant, D. M. Flight cost of a small passerine measured using doubly labeled water: Implications for energetics studies. Auk 103, 169–180. https://doi.org/10.2307/4086976 (1986).Article 

Google Scholar 
Boisclair, D. & Leggett, W. C. The importance of activity in bioenergetics models applied to actively foraging fishes. Can. J. Fish. Aquat. Sci. 46, 1859–1867. https://doi.org/10.1139/f89-234 (1989).Article 

Google Scholar 
Karasov, W. H. Daily energy expenditure and the cost of activity in mammals. Am. Zool. 32, 238–248. https://doi.org/10.1093/icb/32.2.238 (1992).Article 

Google Scholar 
Castro, G., Myers, J. P. & Ricklefs, R. E. Ecology and energetics of sandlerlings migrating to four latitudes. Ecology 73, 833–844. https://doi.org/10.2307/1940161 (1992).Article 

Google Scholar 
Fayet, A. L. et al. Ocean-wide drivers of migration strategies and their influence on population breeding performance in a declining seabird. Curr. Biol. 27, 3871-3878.e3. https://doi.org/10.1016/j.cub.2017.11.009 (2017).Article 
CAS 

Google Scholar 
Alves, J. A. et al. Costs, benefits, and fitness consequences of different migratory strategies. Ecology 94, 11–17. https://doi.org/10.1890/12-0737.1 (2013).Article 

Google Scholar 
Carneiro, C., Gunnarsson, T. G., Méndez, V., Soares, A. M. & Alves, J. A. Linking range wide energetic tradeoffs to breeding performance in a long-distance migrant. Ecography 44, 521–524. https://doi.org/10.1111/ecog.05152 (2021).Article 

Google Scholar 
Fort, J. et al. Energetic consequences of contrasting winter migratory strategies in a sympatric Arctic seabird duet. J. Avian Biol. 44, 255–262. https://doi.org/10.1111/j.1600-048X.2012.00128.x (2013).Article 

Google Scholar 
Garthe, S. et al. Energy budgets reveal equal benefits of varied migration strategies in northern gannets. Mar. Biol. 159, 1907–1915 (2012).Article 

Google Scholar 
Pelletier, D. et al. So far, so good… Similar fitness consequences and overall energetic costs for short and long-distance migrants in a seabird. PLoS One 15, e0230262. https://doi.org/10.1371/journal.pone.0230262 (2020).Article 
CAS 

Google Scholar 
Tinbergen, J. M. & Verhulst, S. A fixed energetic ceiling to parental effort in the great tit?. J. Anim. Ecol. 69, 323–334 (2000).Article 

Google Scholar 
Drent, R. H. & Daan, S. The prudent parent: Energetic adjustments in avian breeding 1. Ardea 68, 225–252 (1980).
Google Scholar 
Weiner, J. Physiological limits to sustainable energy budgets in birds and mammals: Ecological implications. Trends Ecol. Evol. 7, 384–388 (1992).Article 
CAS 

Google Scholar 
Hammond, K. A. & Diamond, J. Maximal sustained energy budgets in humans and animals. Nature 386, 457–462 (1997).Article 
ADS 
CAS 

Google Scholar 
Speakman, J. R. & Król, E. Maximal heat dissipation capacity and hyperthermia risk: Neglected key factors in the ecology of endotherms. J. Anim. Ecol. 79, 726–746. https://doi.org/10.1111/j.1365-2656.2010.01689.x (2010).Article 

Google Scholar 
Deerenberg, C. et al. Parental energy expenditure in relation to manipulated brood size in the European kestrel. Zool. Anal. Complex Syst. 99, 38–47 (1995).
Google Scholar 
Daan, S., Deerenberg, C. & Dijkstra, C. Increased daily work precipitates natural death in the kestrel. J. Anim. Ecol. 65, 539–544. https://doi.org/10.2307/5734 (1996).Article 

Google Scholar 
Newton, I. Migration within the annual cycle: Species, sex and age differences. J. Ornithol. 152, 169–185 (2011).Article 

Google Scholar 
Wingfield, J. C. Organization of vertebrate annual cycles: Implications for control mechanisms. Philos. Trans. R. Soc. Lond. B Biol. Sci. 363, 425–441. https://doi.org/10.1098/rstb.2007.2149 (2008).Article 

Google Scholar 
Barta, Z. et al. Optimal moult strategies in migratory birds. Philos. Trans. R. Soc. B Biol. Sci. 363, 211–229. https://doi.org/10.1098/rstb.2007.2136 (2008).Article 

Google Scholar 
Wingfield, J. C. Flexibility in annual cycles of birds: Implications for endocrine control mechanisms. J. Ornithol. 146, 291–304. https://doi.org/10.1007/s10336-005-0002-z (2005).Article 

Google Scholar 
Bryant, D. M. Energy expenditure in wild birds. Proc. Nutr. Soc. 56, 1025–1039. https://doi.org/10.1079/PNS19970107 (1997).Article 
CAS 

Google Scholar 
Lustick, S. Energy requirements of molt in cowbirds. Auk 87, 742–746. https://doi.org/10.2307/4083708 (1970).Article 

Google Scholar 
Murphy, M. E. & King, J. R. Energy and nutrient use during moult by white-crowned sparrows Zonotrichia leucophrys gambelii. Ornis Scand. (Scand. J. Ornithol.) 23, 304–313. https://doi.org/10.2307/3676654 (1992).Article 

Google Scholar 
Lindström, Å., Visser, G. H. & Daan, S. The energetic cost of feather synthesis is proportional to basal metabolic rate. Physiol. Zool. 66, 490–510. https://doi.org/10.1086/physzool.66.4.30163805 (1993).Article 

Google Scholar 
Buttemer, W. A., Nicol, S. C. & Sharman, A. Thermoenergetics of pre-moulting and moulting kookaburras (Dacelo novaeguineae): They’re laughing. J. Comp. Physiol. B. 173, 223–230 (2003).Article 
CAS 

Google Scholar 
Hedenström, A. & Sunada, S. On the aerodynamics of moult gaps in birds. J. Exp. Biol. 202, 67–76. https://doi.org/10.1242/jeb.202.1.67 (1999).Article 

Google Scholar 
Cherel, Y., Quillfeldt, P., Delord, K. & Weimerskirch, H. Combination of at-sea activity, geolocation and feather stable isotopes documents where and when seabirds molt. Front. Ecol. Evol. 4, 3. https://doi.org/10.3389/fevo.2016.00003 (2016).Article 

Google Scholar 
Rohwer, S., Butler, L. K., Froehlich, D. R., Greenberg, R. & Marra pp., Ecology and demography of east–west differences in molt scheduling of Neotropical migrant passerines. In Birds of Two Worlds: The Ecology and Evolution of Migration (eds Greenberg, R. & Marra, P. P.) 87–105 (Johns Hopkins University Press, 2005).
Google Scholar 
Norris, D. R., Marra, P. P., Kyser, T. K., Sherry, T. W. & Ratcliffe, L. M. Tropical winter habitat limits reproductive success on the temperate breeding grounds in a migratory bird. Proc. R. Soc. Lond. B Biol. Sci. 271, 59–64. https://doi.org/10.1098/rspb.2003.2569 (2004).Article 

Google Scholar 
Ramenofsky, M. & Wingfield, J. C. Behavioral and physiological conflicts in migrants: The transition between migration and breeding. J. Ornithol. 147, 135 (2006).Article 

Google Scholar 
Kiat, Y., Izhaki, I. & Sapir, N. The effects of long-distance migration on the evolution of moult strategies in Western-Palearctic passerines. Biol. Rev. 94, 700–720. https://doi.org/10.1111/brv.12474 (2019).Article 

Google Scholar 
Newton, I. The Migration Ecology of Birds (Academic Press, 2008).
Google Scholar 
Klaassen, R. H. G., Ens, B. J., Shamoun-Baranes, J., Exo, K.-M. & Bairlein, F. Migration strategy of a flight generalist, the Lesser Black-backed Gull Larus fuscus. Behav. Ecol. 23, 58–68. https://doi.org/10.1093/beheco/arr150 (2012).Article 

Google Scholar 
Martín-Vélez, V. et al. Functional connectivity network between terrestrial and aquatic habitats by a generalist waterbird, and implications for biovectoring. Sci. Total Environ. 705, 135886. https://doi.org/10.1016/j.scitotenv.2019.135886 (2020).Article 
ADS 
CAS 

Google Scholar 
Baert, J. M. et al. High-resolution GPS tracking reveals sex differences in migratory behaviour and stopover habitat use in the Lesser Black-backed Gull Larus fuscus. Sci. Rep. 8, 1–11. https://doi.org/10.1038/s41598-018-23605-x (2018).Article 
CAS 

Google Scholar 
Spelt, A. et al. Habitat use of urban-nesting lesser black-backed gulls during the breeding season. Sci. Rep. 9, 1–11. https://doi.org/10.1038/s41598-019-46890-6 (2019).Article 
ADS 
CAS 

Google Scholar 
Tyson, C., Shamoun-Baranes, J., Van Loon, E. E., Camphuysen, K. & Hintzen, N. T. Individual specialization on fishery discards by lesser black-backed gulls (Larus fuscus). ICES J. Mar. Sci. 72, 1882–1891. https://doi.org/10.1093/icesjms/fsv021 (2015).Article 

Google Scholar 
Shamoun-Baranes, J., Burant, J. B., Loon, E. E., Bouten, W. & Camphuysen, C. J. Short distance migrants travel as far as long distance migrants in lesser black-backed gulls Larus fuscus. J. Avian Biol. 48, 49–57. https://doi.org/10.1111/jav.01229 (2017).Article 

Google Scholar 
Brown, J. M. et al. Long-distance migrants vary migratory behaviour as much as short-distance migrants: An individual-level comparison from a seabird species with diverse migration strategies. J. Anim. Ecol. 90, 1058–1070. https://doi.org/10.1111/1365-2656.13431 (2021).Article 

Google Scholar 
Brown, J. M., Bouten, W., Camphuysen, K. C. J., Nolet, B. A. & Shamoun-Baranes, J. Acceleration as a proxy for energy expenditure in a facultative-soaring bird: Comparing dynamic body acceleration and time-energy budgets to heart rate. Funct. Ecol. 36, 1627–1638. https://doi.org/10.1111/1365-2435.14055 (2022).Article 

Google Scholar 
Somveille, M., Manica, A. & Rodrigues, A. S. L. Where the wild birds go: Explaining the differences in migratory destinations across terrestrial bird species. Ecography 42, 225–236. https://doi.org/10.1111/ecog.03531 (2019).Article 

Google Scholar 
Levin, S. A. The problem of pattern and scale in ecology: The Robert H MacArthur award lecture. Ecology 73, 1943–1967 (1992).Article 

Google Scholar 
Shepard, E. L. et al. Energy landscapes shape animal movement ecology. Am. Nat. 182, 298–312. https://doi.org/10.1086/671257 (2013).Article 

Google Scholar 
Sage, E., Bouten, W., Hoekstra, B., Camphuysen, K. C. & Shamoun-Baranes, J. Orographic lift shapes flight routes of gulls in virtually flat landscapes. Sci. Rep. 9, 1–10. https://doi.org/10.1038/s41598-019-46017-x (2019).Article 
ADS 
CAS 

Google Scholar 
Stephens, D. W. & Krebs, J. R. Foraging Theory (Princeton University Press, 2019).Book 

Google Scholar 
Piersma, T. Why marathon migrants get away with high metabolic ceilings: Towards an ecology of physiological restraint. J. Exp. Biol. 214, 295–302. https://doi.org/10.1242/jeb.046748 (2011).Article 

Google Scholar 
Shamoun-Baranes, J., Bouten, W., Camphuysen, C. J. & Baaij, E. Riding the tide: Intriguing observations of gulls resting at sea during breeding. Ibis 153, 411–415. https://doi.org/10.1111/j.1474-919X.2010.01096.x (2011).Article 

Google Scholar 
Kavelaars, M. M. et al. Simultaneous GPS-tracking of parents reveals a similar parental investment within pairs, but no immediate co-adjustment on a trip-to-trip basis. Mov. Ecol. 9, 42. https://doi.org/10.1186/s40462-021-00279-1 (2021).Article 

Google Scholar 
Humphreys, E. M., Wanless, S. & Bryant, D. M. Elevated metabolic costs while resting on water in a surface feeder: The Black-legged Kittiwake Rissa tridactyla. Ibis 149, 106–111. https://doi.org/10.1111/j.1474-919X.2006.00618.x (2007).Article 

Google Scholar 
Lustick, S., Battersby, B. & Kelty, M. Behavioral thermoregulation: Orientation toward the sun in herring gulls. Science 200, 81–83. https://doi.org/10.1126/science.635577 (1978).Article 
ADS 

Google Scholar 
Green, J. A., Boyd, I. L., Woakes, A. J., Green, C. J. & Butler, P. J. Do seasonal changes in metabolic rate facilitate changes in diving behaviour?. J. Exp. Biol. 208, 2581–2593. https://doi.org/10.1242/jeb.01679 (2005).Article 
CAS 

Google Scholar 
Green, J. A. et al. An increase in minimum metabolic rate and not activity explains field metabolic rate changes in a breeding seabird. J. Exp. Biol. 216, 1726–1735. https://doi.org/10.1242/jeb.085092 (2013).Article 
CAS 

Google Scholar 
White, C. R., Grémillet, D., Green, J. A., Martin, G. R. & Butler, P. J. Metabolic rate throughout the annual cycle reveals the demands of an Arctic existence in Great Cormorants. Ecology 92, 475–486 (2011).Article 

Google Scholar 
Guillemette, M. & Butler, P. J. Seasonal variation in energy expenditure is not related to activity level or water temperature in a large diving bird. J. Exp. Biol. 215, 3161–3168. https://doi.org/10.1242/jeb.061119 (2012).Article 

Google Scholar 
Dunn, R. E., Wanless, S., Daunt, F., Harris, M. P. & Green, J. A. A year in the life of a North Atlantic seabird: Behavioural and energetic adjustments during the annual cycle. Sci. Rep. 10, 1–11. https://doi.org/10.1038/s41598-020-62842-x (2020).Article 
CAS 

Google Scholar 
Camphuysen, C. J. Lesser Black-backed gulls nesting at Texel. Final report (Royal Netherlands Institute for Sea Research, 2011).
Google Scholar 
Camphuysen, C. J., Shamoun-Baranes, J., van Loon, E. E. & Bouten, W. Sexually distinct foraging strategies in an omnivorous seabird. Mar. Biol. 162, 1417–1428. https://doi.org/10.1007/s00227-015-2678-9 (2015).Article 

Google Scholar 
Dunn, R. E., White, C. R. & Green, J. A. A model to estimate seabird field metabolic rates. Biol. Lett. 14, 20180190. https://doi.org/10.1098/rsbl.2018.0190 (2018).Article 

Google Scholar 
Catry, P., Dias, M. P., Phillips, R. A. & Granadeiro, J. P. Carry-over effects from breeding modulate the annual cycle of a long-distance migrant: An experimental demonstration. Ecology 94, 1230–1235. https://doi.org/10.1890/12-2177.1 (2013).Article 

Google Scholar 
Gutowsky, S. E. et al. Daily activity budgets reveal a quasi-flightless stage during non-breeding in Hawaiian albatrosses. Mov. Ecol. 2, 23. https://doi.org/10.1186/s40462-014-0023-4 (2014).Article 

Google Scholar 
Harris, M. P. Ecological adaptations of moult in some British gulls. Bird Study 18, 113–118 (1971).Article 

Google Scholar 
Verbeek, N. A. Timing of primary moult in adult herring gulls and lesser black-backed gulls. J. Ornithol. 118, 87–92 (1977).Article 

Google Scholar 
Sorensen, M. C., Hipfner, J. M., Kyser, T. K. & Norris, D. R. Carry-over effects in a Pacific seabird: Stable isotope evidence that pre-breeding diet quality influences reproductive success. J. Anim. Ecol. 78, 460–467. https://doi.org/10.1111/j.1365-2656.2008.01492.x (2009).Article 

Google Scholar 
Lok, T., Overdijk, O., Tinbergen, J. M. & Piersma, T. The paradox of spoonbill migration: Most birds travel to where survival rates are lowest. Anim. Behav. 82, 837–844 (2011).Article 

Google Scholar 
Reneerkens, J. et al. Low fitness at low latitudes: Wintering in the tropics increases migratory delays and mortality rates in an Arctic breeding shorebird. J. Anim. Ecol. 89, 691–703. https://doi.org/10.1111/1365-2656.13118 (2020).Article 

Google Scholar 
Bouten, W., Baaij, E. W., Shamoun-Baranes, J. & Camphuysen, K. C. A flexible GPS tracking system for studying bird behaviour at multiple scales. J. Ornithol. 154, 571–580. https://doi.org/10.1007/s10336-012-0908-1 (2013).Article 

Google Scholar 
Thaxter, C. B. et al. A trial of three harness attachment methods and their suitability for long-term use on Lesser Black-backed Gulls and Great Skuas. Ring. Migr. 29, 65–76. https://doi.org/10.1080/03078698.2014.995546 (2014).Article 

Google Scholar 
Shamoun-Baranes, J., Bouten, W., van Loon, E. E., Meijer, C. & Camphuysen, C. J. Flap or soar? How a flight generalist responds to its aerial environment. Philos. Trans. R. Soc. B 371, 20150395. https://doi.org/10.1098/rstb.2015.0395 (2016).Article 

Google Scholar 
Buchhorn, M., Smets, B., Bertels, L., Lesiv, M., Masiliunas, D., Linlin, L., Herold, M. & Fritz S. Copernicus Global Land Service: Land Cover 100m: Collection 3: epoch 2016–2019: Globe (2020).Wilson, R. P. et al. Estimates for energy expenditure in free-living animals using acceleration proxies: A reappraisal. J. Anim. Ecol. 89, 161–172. https://doi.org/10.1111/1365-2656.13040 (2019).Article 

Google Scholar 
Cartar, R. V. & Morrison, R. G. Estimating metabolic costs for homeotherms from weather data and morphology: An example using calidridine sandpipers. Can. J. Zool. 75, 94–101 (1997).Article 

Google Scholar 
Baveco, J. M., Kuipers, H. & Nolet, B. A. A large-scale multi-species spatial depletion model for overwintering waterfowl. Ecol. Model. 222, 3773–3784 (2011).Article 

Google Scholar 
Hersbach H et al. ERA5 hourly data on single levels from 1979 to present. Copernicus Climate Change Service (C3S) Climate Data Store (CDS). https://doi.org/10.24381/cds.adbb2d47 (2018).Bevan, R. M., Butler, P. J., Woakes, A. J. & Prince, P. A. The energy expenditure of free-ranging black-browed albatrosses. Philos. Trans. R. Soc. Lond. B Biol. Sci. 350, 119–131. https://doi.org/10.1098/rstb.1995.0146 (1995).Article 
ADS 

Google Scholar 
Bevan, R. M. & Butler, P. J. The effects of temperature on the oxygen consumption, heart rate and deep body temperature during diving in the tufted duck Aythya fuligula. J. Exp. Biol. 163, 139–151. https://doi.org/10.1242/jeb.163.1.139 (1992).Article 

Google Scholar 
Stahel, C. D. & Nicol, S. C. Temperature regulation in the little penguin, Eudyptula minor, in air and water. J. Comp. Physiol. 148, 93–100 (1982).Article 

Google Scholar 
Bates, D., Maechler, M., Bolker, B. & Walker, S. Fitting linear mixed-effects models using lme4. J. Stat. Softw. 67, 1–48. https://doi.org/10.18637/jss.v067.i01 (2015).Article 

Google Scholar 
Wood, S. mgcv: Mixed GAM Computation Vehicle with Automatic Smoothness Estimation (2021).Zuur, A. F. Beginner’s Guide to Spatial, Temporal, and Spatial-Temporal Ecological Data Analysis with R-INLA (Highland Statistics Ltd., 2017).
Google Scholar 
Brown, J. M., Bouten, W., Camphuysen, K., Nolet, B. A. & Shamoun-Baranes, J. Z. Data and code archive for ‘Energetic and behavioral consequences of migration: An empirical evaluation in the context of the full annual cycle’. https://doi.org/10.21942/uva.21583926.v1 (2022).Wickham, H. ggplot2: Elegant Graphics for Data Analysis. https://ggplot2.tidyverse.org (Springer, 2016).South, A. rworldmap: Mapping Global Data. http://cran.r-project.org/web/packages/rworldmap (2016).Natural Earth. V 1.4.0. Free vector and raster map data at 1:10m, 1:50m, and 1:110m scales. https://www.naturalearthdata.com/downloads/. More

Holt, R. D. Predation, apparent competition, and the structure of prey communities. Theor. Popul. Biol. 12, 197–229 (1977).Article 
CAS 

Google Scholar 
Dugatkin, L. A. & Godin, J. G. J. Prey approaching predators: A cost-benefit perspective. Ann. Zool. Fennici 29, 233–252 (1992).
Google Scholar 
Portalier, S. M. J., Fussmann, G. F., Loreau, M. & Cherif, M. The mechanics of predator–prey interactions: First principles of physics predict predator–prey size ratios. Funct. Ecol. 33, 323–334 (2019).Article 

Google Scholar 
Achrai, B., Bar-On, B. & Wagner, H. D. Biological armors under impact—effect of keratin coating, and synthetic bio-inspired analogues. Bioinsp. Biomim. 10, 016009 (2015).Article 
CAS 

Google Scholar 
Stankowich, T. & Campbell, L. A. Living in the danger zone: Exposure to predators and the evolution of spines and body armor in mammals. Evolution 70, 1501–1511 (2016).Article 

Google Scholar 
Tollrian, R. & Harvell, C. D. The ecology and evolution of inducible defenses. Q. Rev. Biol. 65, 323–340 (1990).Article 

Google Scholar 
Nordlund, D. A. & Lewis, W. J. Terminology of chemical releasing stimuli in intraspecific and interspecific interactions. J. Chem. Ecol. 2, 211–220 (1976).Article 

Google Scholar 
Poulin, R. X. et al. Chemical encoding of risk perception and predator detection among estuarine invertebrates. Proc. Natl. Acad. Sci. USA 115, 662–667 (2018).Article 
ADS 
CAS 

Google Scholar 
Tollrian, R. & Dodson, S. I. Inducible defenses in Cladocera: Constraints, costs, and multipredator environments. Ecol. Evol. Inducible Defenses 177, 177–202 (1999).Article 

Google Scholar 
Von Elert, E. & Loose, C. J. Predator-induced diel vertical migration in Daphnia: Enrichment and preliminary chemical characterization of a kairomone exuded by fish. J. Chem. Ecol. 22, 885–895 (1996).Article 

Google Scholar 
Barry, M. J. Effects of endosulfan on Chaoborus-induced life-history shifts and morphological defenses in Daphnia pulex. J. Plankton Res. 22, 1705–1718 (2000).Article 
ADS 
CAS 

Google Scholar 
Riessen, H. P. & Gilbert, J. J. Divergent developmental patterns of induced morphological defenses in rotifers and Daphnia: Ecological and evolutionary context. Limnol. Oceanogr. 64, 541–557 (2019).Article 
ADS 

Google Scholar 
Sperfeld, E., Nilssen, J. P., Rinehart, S., Schwenk, K. & Hessen, D. O. Ecology of predator-induced morphological defense traits in Daphnia longispina (Cladocera, Arthropoda). Oecologia 192, 687–698 (2020).Article 
ADS 

Google Scholar 
Tollrian, R. Neckteeth formation in Daphnia pulex as an example of continuous phenotypic plasticity: Morphological effects of Chaoborus kairomone concentration and their quantification. J. Plankton Res. 15, 1309–1318 (1993).Article 

Google Scholar 
Laforsch, C. & Tollrian, R. Inducible defenses in multipredator environments: Cyclomorphosis in Daphnia cucullata. Ecology 85, 2302–2311 (2004).Article 

Google Scholar 
Petrusek, A., Tollrian, R., Schwenk, K., Haas, A. & Laforsch, C. A ‘crown of thorns’ is an inducible defense that protects Daphnia against an ancient predator. Proc. Natl. Acad. Sci. USA 106, 2248–2252 (2009).Article 
ADS 
CAS 

Google Scholar 
Engel, K. & Tollrian, R. Inducible defences as key adaptations for the successful invasion of Daphnia lumholtzi in North America?. Proc. R. Soc. B Biol. Sci. 276, 1865–1873 (2009).Article 

Google Scholar 
Barry, M. J. & Bayly, I. A. E. Further studies on predator induction of crests in australian Daphnia and the effects of crests on predation. Mar. Freshw. Res. 36, 519–535 (1985).
Google Scholar 
Rabus, M. & Laforsch, C. Growing large and bulky in the presence of the enemy: Daphnia magna gradually switches the mode of inducible morphological defences. Funct. Ecol. 25, 1137–1143 (2011).Article 

Google Scholar 
Herzog, Q. & Laforsch, C. Modality matters for the expression of inducible defenses: Introducing a concept of predator modality. BMC Biol. 11, 113 (2013).Article 

Google Scholar 
Riessen, H. P. et al. Changes in water chemistry can disable plankton prey defenses. Proc. Natl. Acad. Sci. USA 109, 15377–15382 (2012).Article 
ADS 
CAS 

Google Scholar 
Tollrian, R., Duggen, S., Weiss, L. C., Laforsch, C. & Kopp, M. Density-dependent adjustment of inducible defenses. Sci. Rep. 5, 12736 (2015).Article 
ADS 
CAS 

Google Scholar 
Weiss, L. C. et al. Rising pCO2 in freshwater ecosystems has the potential to negatively affect predator-induced defenses in Daphnia. Curr. Biol. 28, 327-332.e3 (2018).Article 
CAS 

Google Scholar 
Hanazato, T. Pesticide effects on freshwater zooplankton: An ecological perspective. Environ. Pollut. 112, 1–10 (2001).Article 
CAS 

Google Scholar 
Coors, A. & DeMeester, L. Erratum: Synergistic, antagonistic and additive effects of multiple stressors: Predation threat, parasitism and pesticide exposure in Daphnia magna. J. Appl. Ecol. 46, 1138 (2009).
Google Scholar 
Schriever, C. A., von der Ohe, P. C. & Liess, M. Estimating pesticide runoff in small streams. Chemosphere 68, 2161–2171 (2007).Article 
ADS 
CAS 

Google Scholar 
Lobstein, A. et al. Quantitative determination of naphthoquinones of Impatiens species. Phytochem. Anal. 12, 202–205 (2001).Article 
CAS 

Google Scholar 
Kisielius, V. et al. The invasive butterbur contaminates stream and seepage water in groundwater wells with toxic pyrrolizidine alkaloids. Sci. Rep. 10, 19784 (2020).Article 
ADS 
CAS 

Google Scholar 
Yoneyama, K. & Natsume, M. 4.13 Allelochemicals for Plant—Plant and Plant—Microbe Interactions. Interactions (Elsevier Inc., 2010).Griffiths, M. R., Strobel, B. W., Hama, J. R. & Cedergreen, N. Toxicity and risk of plant-produced alkaloids to Daphnia magna. Environ. Sci. Eur. 33, 10 (2021).Article 
CAS 

Google Scholar 
Callaway, R. M. & Ridenour, W. M. Novel weapons: Invasive success and the evolution of increased competitive ability. Front. Ecol. Environ. 2, 436–443 (2004).Article 

Google Scholar 
Beerling, D. J. & Perrins, J. M. Impatiens glandulifera Royle (Impatiens Roylei Walp.). J. Ecol. 81, 367–382 (1993).Article 

Google Scholar 
Roy, B., Popay, A.I., Champion, P.D., James, T.K. & Rahman, A. An Illustrated Guide to Common Weeds of New Zealand. 2nd Edn. (New Zealand Plant Protection Society, 2004). Ruckli, R., Hesse, K., Glauser, G., Rusterholz, H. P. & Baur, B. Inhibitory potential of naphthoquinones leached from leaves and exuded from roots of the invasive plant Impatiens glandulifera. J. Chem. Ecol. 40, 371–378 (2014).Article 
CAS 

Google Scholar 
Gruntman, M., Pehl, A. K., Joshi, S. & Tielbörger, K. Competitive dominance of the invasive plant Impatiens glandulifera: Using competitive effect and response with a vigorous neighbour. Biol. Invasions 16, 141–151 (2014).Article 

Google Scholar 
Bieberich, J. et al. Species- and developmental stage-specific effects of allelopathy and competition of invasive Impatiens glandulifera on cooccurring plants. PLoS ONE 13, e0205843 (2018).Article 

Google Scholar 
Wright, D. A., Dawson, R., Cutler, S. J., Cutler, H. G. & Orano-Dawson, C. E. Screening of natural product biocides for control of non-indigenous species. Environ. Technol. 28, 309–319 (2007).Article 
CAS 

Google Scholar 
Kayashima, T., Mori, M., Yoshida, H., Mizushina, Y. & Matsubara, K. 1,4-naphthoquinone is a potent inhibitor of human cancer cell growth and angiogenesis. Cancer Lett. 278, 34–40 (2009).Article 
CAS 

Google Scholar 
Jentzsch, J. et al. New antiparasitic bis-naphthoquinone derivatives. Chem. Biodivers. 17, e1900597 (2020).Article 
CAS 

Google Scholar 
Mitchell, M. J., Brescia, A. I., Smith, S. L. & Morgan, E. D. Effects of the compounds 2-methoxynaphthoquinone, 2-propoxynaphthoquinone, and 2-isopropoxynaphthoquinone on ecdysone 20-monooxygenase activity. Arch. Insect Biochem. Physiol. 66, 45–52 (2007).Article 
CAS 

Google Scholar 
Westfall, B. A., Russell, R. L. & Auyong, T. K. Depressant agent from walnut hulls. Science 134, 1617 (1961).Article 
ADS 
CAS 

Google Scholar 
Diller, J. G. P. et al. The Beauty is a beast: Does leachate from the invasive terrestrial plant Impatiens glandulifera affect aquatic food webs?. Ecol. Evol. 12, e8781 (2022).Article 

Google Scholar 
Elendt, B. P. Selenium deficiency in Crustacea—an ultrastructural approach to antennal damage in Daphnia magna Straus. Protoplasma 154, 25–33 (1990).Article 
CAS 

Google Scholar 
Ebert, D. The trade-off between offspring size and number in Daphnia magna: The influence of genetic, environmental and maternal effects. Arch. Fur Hydrobiol. 90, 453–473 (1993).
Google Scholar 
Trotter, B., Ramsperger, A. F. R. M., Raab, P., Haberstroh, J. & Laforsch, C. Plastic waste interferes with chemical communication in aquatic ecosystems. Sci. Rep. 9, 5889 (2019).Article 
ADS 
CAS 

Google Scholar 
Laforsch, C., Beccara, L. & Tollrian, R. Inducible defenses: The relevance of chemical alarm cues in Daphnia. Limnol. Oceanogr. 51, 1466–1472 (2006).Article 
ADS 

Google Scholar 
Miner, B. E., de Meester, L., Pfrender, M. E., Lampert, W. & Hairston, N. G. Linking genes to communities and ecosystems: Daphnia as an ecogenomic model. Proc. R. Soc. B Biol. Sci. 279, 1873–1882 (2012).Article 

Google Scholar 
Altshuler, I. et al. An integrated multi-disciplinary approach for studying multiple stressors in freshwater ecosystems: Daphnia as a model organism. Integr. Comp. Biol. 51, 623–633 (2011).Article 
CAS 

Google Scholar 
Diel, P., Kiene, M., Martin-Creuzburg, D. & Laforsch, C. Knowing the enemy: Inducible defences in freshwater zooplankton. Diversity 12, 147 (2020).Article 
CAS 

Google Scholar 
Pestana, J. L. T., Loureiro, S., Baird, D. J. & Soares, A. M. V. M. Pesticide exposure and inducible antipredator responses in the zooplankton grazer, Daphnia magna Straus. Chemosphere 78, 241–248 (2010).Article 
ADS 
CAS 

Google Scholar 
Grant, J. W. G. & Bayly, I. A. E. Predator induction of crests in morphs of the Daphnia carinata King complex. Limnol. Oceanogr. 26, 201–218 (1981).Article 
ADS 

Google Scholar 
Dodson, S. I. Zooplankton competition and predation: An experimental test of the size-efficiency hypothesis. Ecology 55, 605–613 (1974).Article 

Google Scholar 
Klotz, L. O., Hou, X. & Jacob, C. 1,4-naphthoquinones: From oxidative damage to cellular and inter-cellular signaling. Molecules 19, 14902–14918 (2014).Article 

Google Scholar 
Subramoniam, T. Crustacean ecdysteriods in reproduction and embryogenesis. Comp. Biochem. C Physiol. Pharmacol. Toxicol. Endocrinol. 125, 135–156 (2000).Article 
CAS 

Google Scholar 
De Coen, W. M. & Janssen, C. R. The missing biomarker link: Relationships between effects on the cellular energy allocation biomarker of toxicant-stressed Daphnia magna and corresponding population characteristics. Environ. Toxicol. Chem. 22, 1632–1641 (2003).Article 

Google Scholar 
Palma, P. et al. Effects of atrazine and endosulfan sulphate on the ecdysteroid system of Daphnia magna. Chemosphere 74, 676–681 (2009).Article 
ADS 
CAS 

Google Scholar 
Mount, D. I. & Norberg, T. J. A seven-day life cycle Cladoceran toxicity test. Environ. Toxicol. Chem. 3, 425–434 (1984).Article 
CAS 

Google Scholar 
Elnabarawy, M. T., Welter, A. N. & Robideau, R. R. Relative sensitivity of three daphnid species to selected organic and inorganic chemicals. Environ. Toxicol. Chem. 5, 393–398 (1986).Article 
CAS 

Google Scholar 
Jaikumar, G., Baas, J., Brun, N. R., Vijver, M. G. & Bosker, T. Acute sensitivity of three Cladoceran species to different types of microplastics in combination with thermal stress. Environ. Pollut. 239, 733–740 (2018).Article 
CAS 

Google Scholar 
Gama-Flores, J. L., Salas, M. E. H., Sarma, S. S. S. & Nandini, S. Demographic responses of Cladocerans (Cladocera) in relation to different concentrations of humic substances. J. Environ. Sci. Heal. Part A Toxic/Hazardous Subst. Environ. Eng. 54, 1311–1317 (2019).CAS 

Google Scholar 
Cohen, J. E., Pimm, S. L., Yodzis, P. & Saldana, J. Body sizes of animal predators and animal prey in food webs. J. Anim. Ecol. 62, 67–78 (1993).Article 

Google Scholar 
Hunt, R. J. & Swift, M. Predation by larval damselflies on Cladocerans. J. Freshw. Ecol. 25, 345–351 (2010).Article 

Google Scholar 
Riessen, H. P. & Trevett-Smith, J. B. Turning inducible defenses on and off: Adaptive responses of Daphnia to a gape-limited predator. Ecology 90, 3455–3469 (2009).Article 

Google Scholar 
Pijanowska, J. Cyclomorphosis in Daphnia: An adaptation to avoid invertebrate predation. Hydrobiologia 198, 41–50 (1990).Article 

Google Scholar 
Gu, L. et al. Coping with antagonistic predation risks: Predator-dependent unique responses are dominant in Ceriodaphnia cornuta. Mol. Ecol. 31, 3951–3962 (2022).Article 
CAS 

Google Scholar 
Jeziorski, A. et al. The jellification of north temperate lakes. Proc. R. Soc. B Biol. Sci. 2014, 282 (2014).
Google Scholar 
Ponti, B., Piscia, R., Bettinetti, R. & Manca, M. Long-term adaptation of Daphnia to toxic environment in Lake Orta: The effects of short-term exposure to copper and acidification. J. Limnol. 69, 217–224 (2010).Article 

Google Scholar 
Wright, D. A., Mitchelmore, C. L., Dawson, R. & Cutler, H. G. The influence of water quality on the toxicity and degradation of juglone (5-hydroxy 1,4-naphthoquinone). Environ. Technol. 28, 1091–1101 (2007).Article 
CAS 

Google Scholar  More

Cardinale, B. J. et al. Biodiversity loss and its impact on humanity. Nature 486, 59–67 (2012).Article 
ADS 
CAS 

Google Scholar 
Schumaker, N. H. Using landscape indices to predict habitat connectivity. Ecology 77, 1210–1225 (1996).Article 

Google Scholar 
Pacifici, M. et al. Assessing species vulnerability to climate change. Nat. Clim. Chang. 5, 215–224 (2015).Article 
ADS 

Google Scholar 
Fahrig, L. Effects of habitat fragmentation on biodiversity. Annu. Rev. Ecol. Evol. Syst. 34, 487–515 (2003).Article 

Google Scholar 
Clavero, M., Brotons, L., Pons, P. & Sol, D. Prominent role of invasive species in avian biodiversity loss. Biol. Conserv. 142, 2043–2049 (2009).Article 

Google Scholar 
Soroye, P., Ahmed, N. & Kerr, J. T. Opportunistic citizen science data transform understanding of species distributions, phenology, and diversity gradients for global change research. Glob. Change Biol. 24, 5281–5291 (2018).Article 
ADS 

Google Scholar 
Gotelli, N. J. & Colwell, R. K. Quantifying biodiversity: Procedures and pitfalls in the measurement and comparison of species richness. Ecol. Lett. 4, 379–391 (2001).Article 

Google Scholar 
Dickinson, J. L., Zuckerberg, B. & Bonter, D. N. Citizen science as an ecological research tool: Challenges and benefits. Annu. Rev. Ecol. Evol. Syst. 41, 149–172 (2010).Article 

Google Scholar 
Kelling, S. et al. Using semistructured surveys to improve citizen science data for monitoring biodiversity. Bioscience 69, 170–179 (2019).Article 

Google Scholar 
Steen, V. A., Elphick, C. S. & Tingley, M. W. An evaluation of stringent filtering to improve species distribution models from citizen science data. Divers. Distrib. 25, 1857–1869 (2019).Article 

Google Scholar 
Crall, A. W. et al. Assessing citizen science data quality: An invasive species case study. Conserv. Lett. 4, 433–442 (2011).Article 

Google Scholar 
Bird, T. J. et al. Statistical solutions for error and bias in global citizen science datasets. Biol. Conserv. 173, 144–154 (2014).Article 

Google Scholar 
MacKenzie, D. I. et al. Estimating site occupancy rates when detection probabilities are less than one. Ecology 83, 2248–2255 (2002).Article 

Google Scholar 
Kellner, K. F. & Swihart, R. K. Accounting for imperfect detection in ecology: A quantitative review. PLoS ONE 9(10), E111436 (2014).Article 
ADS 

Google Scholar 
Weisshaupt, N., Lehikoinen, A., Mäkinen, T. & Koistinen, J. Challenges and benefits of using unstructured citizen science data to estimate seasonal timing of bird migration across large scales. PLoS ONE 16, e0246572 (2021).Article 
CAS 

Google Scholar 
Kéry, M. & Schmid, H. Estimating species richness: Calibrating a large avian monitoring programme. J. Appl. Ecol. 43, 101–110 (2006).Article 

Google Scholar 
Chao, A. & Chiu, C. H. Species richness: Estimation and comparison 1–26 (Wiley StatsRef: Statistics Reference Online, 2014).
Google Scholar 
Walther, B. A. & Moore, J. L. The concepts of bias, precision and accuracy, and their use in testing the performance of species richness estimators, with a literature review of estimator performance. Ecography 28, 815–829 (2005).Article 

Google Scholar 
Chao, A. & Lee, S.-M. Estimating the number of classes via sample coverage. J. Am. Stat. Assoc. 87, 210–217 (1992).Article 
MATH 

Google Scholar 
Walther, B. A. & Morand, S. Comparative performance of species richness estimation methods. Parasitology 116, 395–405 (1998).Article 

Google Scholar 
Walther, B. A. & Martin, J. L. Species richness estimation of bird communities: How to control for sampling effort?. Ibis 143, 413–419 (2001).Article 

Google Scholar 
Walther, B. A., Cotgreave, P., Price, R., Gregory, R. & Clayton, D. H. Sampling effort and parasite species richness. Parasitol. Today 11, 306–310 (1995).Article 
CAS 

Google Scholar 
Colwell, R. K. & Coddington, J. A. Estimating terrestrial biodiversity through extrapolation. Philos. Trans. R. Soc. Lond. Ser. B Biol. Sci. 345, 101–118 (1994).Article 
ADS 
CAS 

Google Scholar 
Bean, W. T., Stafford, R. & Brashares, J. S. The effects of small sample size and sample bias on threshold selection and accuracy assessment of species distribution models. Ecography 35, 250–258 (2012).Article 

Google Scholar 
Flather, C. Fitting species–accumulation functions and assessing regional land use impacts on avian diversity. J. Biogeogr. 23, 155–168 (1996).Article 

Google Scholar 
White, P. E. et al. A comparison of the species–time relationship across ecosystems and taxonomic groups. Oikos 112, 185–195 (2006).Article 

Google Scholar 
McGlinn, D. J. & Palmer, M. W. Modeling the sampling effect in the species–time–area relationship. Ecology 90, 836–846 (2009).Article 

Google Scholar 
Isaac, N. J. et al. Statistics for citizen science: Extracting signals of change from noisy ecological data. Method Ecol. Evol. 5, 1052–1060 (2014).Article 

Google Scholar 
Ding, T. et al. The 2020 CWBF checklist of the birds of Taiwan (Chinese Wild Bird Federation, 2020).
Google Scholar 
Lin, M.-M. et al. Bird records database of a Taiwanese non-governmental organization, the Chinese wild bird federation, from 1972 to 2017. TW. J. Biodivers. 21, 83–101 (2019).
Google Scholar 
Dokter, A. M., Desmet, P., Van Hoey, S. (2022) bioRad: Biological analysis and visualization of weather radar data: v0. 6.0Strimas-Mackey, M. et al. (2020) Best practices for using eBird Data. Version 1.0. Cornell Laboratory of Ornithology, Ithaca, New York, 10.5281/zenodo.3620739Robinson, O. J. et al. Using citizen science data in integrated population models to inform conservation. Biol. Conserv. 227, 361–368 (2018).Article 

Google Scholar 
Callaghan, C. T., Martin, J. M., Major, R. E. & Kingsford, R. T. Avian monitoring–comparing structured and unstructured citizen science. Wildl. Res. 45, 176–184 (2018).Article 

Google Scholar 
Robinson, W. D., Hallman, T. A. & Hutchinson, R. A. Benchmark bird surveys help quantify counting accuracy in a citizen-science database. Front. Ecol. Evol. 9, 568278 (2021).Article 

Google Scholar 
Neate-Clegg, M. H., Horns, J. J., Adler, F. R., Aytekin, M. Ç. K. & Şekercioğlu, Ç. H. Monitoring the world’s bird populations with community science data. Biol. Conserv. 248, 108653 (2020).Article 

Google Scholar 
Chao, A. Nonparametric estimation of the number of classes in a population. Scand. J. Stat 1, 265–270 (1984).
Google Scholar 
Hsieh, T., Ma, K. & Chao, A. iNEXT: An R package for rarefaction and extrapolation of species diversity (Hill numbers). Methods Ecol. Evol. 7, 1451–1456 (2016).Article 

Google Scholar 
Team, R. C. (2013).R: A language and environment for statistical computing.James, G., Witten, D., Hastie, T. & Tibshirani, R. An Introduction to Statistical Learning Vol. 112 (Springer, 2013).Book 
MATH 

Google Scholar 
Magurran, A. E. & McGill, B. J. Biological diversity: Frontiers in measurement and assessment (OUP Oxford, 2010).
Google Scholar 
Spiess, A.-N. (2018) Package ‘propagate’RC Team, C Worldwide. The R stats package (R Foundation for Statistical Computing, 2002).
Google Scholar 
Guralnick, R. & Van Cleve, J. Strengths and weaknesses of museum and national survey data sets for predicting regional species richness: Comparative and combined approaches. Divers. Distrib. 11, 349–359 (2005).Article 

Google Scholar 
Dar, T. A. et al. Bird community structure in Phakot and Pathri Rao watershed areas in Uttarakhand. India. Int. J. Environ. Sci. 34, 193–205 (2008).
Google Scholar 
Azevedo, G. H. et al. Effectiveness of sampling methods and further sampling for accessing spider diversity: A case study in a Brazilian Atlantic rainforest fragment. Insect. Conserv. Divers. 7, 381–391 (2014).Article 

Google Scholar 
Bonter, D. N. & Cooper, C. B. Data validation in citizen science: A case study from project feederwatch. Front. Ecol. Environ. 10, 305–307 (2012).Article 

Google Scholar 
Gómez-Martínez, C. et al. Forest fragmentation modifies the composition of bumblebee communities and modulates their trophic and competitive interactions for pollination. Sci. Rep. 10, 1–15 (2020).Article 

Google Scholar 
Sullivan, B. L. et al. eBird: A citizen-based bird observation network in the biological sciences. Biol. Conserv. 142, 2282–2292 (2009).Article 

Google Scholar 
Newson, S. E., Woodburn, R. J., Noble, D. G., Baillie, S. R. & Gregory, R. D. Evaluating the breeding bird survey for producing national population size and density estimates. Bird Study 52, 42–54 (2005).Article 

Google Scholar 
Robbins, C. S. Effect of time of day on bird activity. Stud. Avian Biol. 6, 275–286 (1981).
Google Scholar 
Farmer, R. G., Leonard, M. L. & Horn, A. G. Observer effects and avian-call-count survey quality: Rare-species biases and overconfidence. Auk 129, 76–86 (2012).Article 

Google Scholar 
Gardiner, M. M. et al. Lessons from lady beetles: Accuracy of monitoring data from US and UK citizen-science programs. Front. Ecol. Environ. 10, 471–476 (2012).Article 

Google Scholar 
Swanson, A., Kosmala, M., Lintott, C. & Packer, C. A generalized approach for producing, quantifying, and validating citizen science data from wildlife images. Conserv. Biol. 30, 520–531 (2016).Article 

Google Scholar 
Ratnieks, F. L. et al. Data reliability in citizen science: Learning curve and the effects of training method, volunteer background and experience on identification accuracy of insects visiting ivy flowers. Methods Ecol. Evol. 7, 1226–1235 (2016).Article 

Google Scholar 
Lopez, L. C. S., de Aguiar Fracasso, M. P., Mesquita, D. O., Palma, A. R. T. & Riul, P. The relationship between percentage of singletons and sampling effort: A new approach to reduce the bias of richness estimates. Ecol. Indicators 14, 164–169 (2012).Article 

Google Scholar 
Bunge, J. & Fitzpatrick, M. Estimating the number of species: A review. J. Am. Stat. Assoc. 88, 364–373 (1993).
Google Scholar 
SoberónM, J. & LlorenteB, J. The use of species accumulation functions for the prediction of species richness. Conserv. Biol. 7, 480–488 (1993).Article 

Google Scholar 
Magurran, A. E. Species abundance distributions over time. Ecol. Lett. 10, 347–354 (2007).Article 

Google Scholar 
de Caprariis, P., Lindemann, R. & Haimes, R. A relationship between sample size and accuracy of species richness predictions. J. Int. Assoc. Math. Geol. 13, 351–355 (1981).Article 

Google Scholar 
Klemann-Junior, L., Villegas Vallejos, M. A., Scherer-Neto, P. & Vitule, J. R. S. Traditional scientific data vs. uncoordinated citizen science effort: A review of the current status and comparison of data on avifauna in Southern Brazil. PLoS ONE 12, e0188819. https://doi.org/10.1371/journal.pone.0188819 (2017).Article 
CAS 

Google Scholar 
Tulloch, A. I. & Szabo, J. K. A behavioural ecology approach to understand volunteer surveying for citizen science datasets. Emu 112, 313–325 (2012).Article 

Google Scholar 
Boakes, E. H. et al. Distorted views of biodiversity: Spatial and temporal bias in species occurrence data. PLoS Biol. 8, e1000385 (2010).Article 

Google Scholar 
Kamp, J. et al. Unstructured citizen science data fail to detect long-term population declines of common birds in Denmark. Divers. Distrib. 22, 1024–1035. https://doi.org/10.1111/ddi.12463 (2016).Article 

Google Scholar 
Lin, Y.-P. et al. Uncertainty analysis of crowd-sourced and professionally collected field data used in species distribution models of Taiwanese moths. Biol. Conserv. 181, 102–110 (2015).Article 

Google Scholar 
Fletcher, R. J. Jr. et al. A practical guide for combining data to model species distributions. Ecology 100, e02710 (2019).Article 

Google Scholar  More

Lal, R. Soil Carbon sequestration impacts on global climate change and food security. Science 30, 1623–1627 (2004).ADS 

Google Scholar 
Stockmann, U. et al. The knowns, known unknowns and unknowns of sequestration of soil organic carbon. Agric. Ecosyst. Environ. 164, 80–99 (2013).CAS 

Google Scholar 
Batjes, N. H. Total carbon and nitrogen in the soils of the world. Eur. J. Soil Sci. 47(2), 151–163 (1996).CAS 

Google Scholar 
Michalzik, B., Kalbitz, K., Park, J. H., Solinger, S. & Matzner, E. Fluxes and concentrations of dissolved organic carbon and nitrogen: A synthesis for temperate forests. Biogeochemistry 52, 173–205 (2001).
Google Scholar 
Malik, A. A. et al. Defining trait-based microbial strategies with consequences for soil carbon cycling under climate change. ISME J. 14, 1–9 (2020).CAS 

Google Scholar 
Song, M. H. et al. Shifts in priming partly explain impacts of long-term nitrogen input in different chemical forms on soil organic carbon storage. Glob. Chang. Biol. 24, 4160–4172 (2018).ADS 

Google Scholar 
Okolo, C. C. et al. Priming effect in semi-arid soils of northern Ethiopia under different land use types. Biogeochemistry https://doi.org/10.1007/s10533-022-00905-z (2022).Article 

Google Scholar 
Eze, P. N., Udeigwe, T. K. & Stietiya, M. H. Distribution and potential source evaluation of heavy metals in prominent soils of Accra plains, Ghana. Geoderma 156(3–4), 357–362 (2010).ADS 
CAS 

Google Scholar 
Eze, P. N., Mbakwe, I. & Okolo, C. C. Ecosystem functions of the soil highlighted in Igbo proverbs. In IUSS Global Soil Proverbs: Cultural Language of the Soil (eds Yang, J. E. et al.) (Schweizerbart and Borntraeger Science Publishers, 2019).
Google Scholar 
Nottingham, A. T. et al. Adaptation of soil microbial growth to temperature: Using a tropical elevation gradient to predict future changes. Glob. Chang. Biol. 25, 827–838 (2019).ADS 

Google Scholar 
Paul, K. I., Polglase, P. J., Nyakuengama, J. G. & Khanna, P. K. Change in soil carbon following afforestation. Forest Ecol. Manag. 168, 241–257 (2002).
Google Scholar 
Batjes, N. H. Options for increasing carbon sequestration in West Africa soils: An exploratory study with special focus on Senegal. Land Degrad. Dev. 12, 131–142 (2001).
Google Scholar 
Powlson, D. S., Whitmore, A. P. & Goulding, K. W. T. Soil carbon sequestration to mitigate climate change: A critical re-examination to identify the true and the false. Eur. J. Soil Sci. 62, 42–55 (2011).CAS 

Google Scholar 
Zhang, K., Dang, H., Zhang, Q. & Cheng, X. Soil carbon dynamics following land-use change varied with temperature and precipitation gradients: Evidence from stable isotopes. Glob. Chang. Biol. 21, 2762–2772 (2015).ADS 

Google Scholar 
Gebresamuel, G. et al. Nutrient Balance of farming systems in tigray, Northern Ethiopia. J. Soil Sci. Plant Nutr. 21, 315–328 (2021).CAS 

Google Scholar 
IPCC, Climate Change: The physical science basis. Contribution of working Group I to the Fourth Assessment. In Report of the Intergovernmental Panel on Climate Change (Eds. Solomon, S., Quin, D and Manning, M). (Cambridge University Press, Cambridge, UK) (2007).Yang, Y. S., Xie, J. S. & Sheng, H. The impact of land use/cover change on storage and quality of soil organic carbon in mid-subtropical mountainous area of southern China. J. Geo. Sci. 19, 49–57 (2009).
Google Scholar 
Akinyemi, F. O., Tlhalerwa, L. T. & Eze, P. N. Land degradation assessment in an African dryland context based on the composite Land Degradation Index and mapping method. Geocarto Int. 36(16), 1838–1854 (2021).
Google Scholar 
Button, E. S. et al. Deep-C storage: Biological, chemical and physical strategies to enhance carbon stocks in agricultural subsoils. Soil Biol. Biochem. 170, 108697 (2022).CAS 

Google Scholar 
Rumpel, C. & Kögel-Knabner, I. Deep soil organic matter: A key but poorly understood component of terrestrial C cycle. Plant Soil 338(1), 143–158 (2011).CAS 

Google Scholar 
Lal, R., Lorenz, K., Huttle, R. F., Schneider, B. U. & Von, B. J. Terrestrial biosphere as a source and sink of atmospheric carbon dioxide. In Recarbonization of the Biosphere: Ecosystems and the Global Cycle (eds Lal, R. et al.) (Springer, 2012).
Google Scholar 
Shi, Z. et al. The age distribution of global soil carbon inferred from radiocarbon measurements. Nat. Geosci. 13, 555–559 (2020).ADS 
CAS 

Google Scholar 
Salome, C., Nunan, N., Pouteau, V., Lerchw, T. Z. & Chenu, C. Carbon dynamics in topsoil and in subsoil may be controlled by different regulatory mechanisms. Glob. Chang. Biol. 16, 416–426 (2010).ADS 

Google Scholar 
Sithole, N. J., Magwaza, L. S. & Thibaud, G. R. Long-term impact of no-till conservation agriculture and N-fertilizer on soil aggregate stability, infiltration and distribution of C in different size fractions. Soil Tillage Res. 190, 147–156 (2019).
Google Scholar 
Tashi, S., Singh, B., Keitel, C. & Adams, M. Soil carbon and nitrogen stocks in forests along an altitudinal gradient in the eastern Himalayas and a meta-analysis of global data. Glob. Chang. Biol. 22, 2255–2268 (2016).ADS 

Google Scholar 
Zhou, Z., Wang, C. & Luo, Y. Effects of forest degradation on microbial communities and soil carbon cycling: A global meta-analysis. Global Ecol. Biogeography 27, 110–124 (2018).
Google Scholar 
Mhete, M., Eze, P. N., Rahube, T. O. & Akinyemi, F. O. Soil properties influence bacterial abundance and diversity under different land-use regimes in semi-arid environments. Sci. African 7, e00246 (2020).
Google Scholar 
Walker, T. W. N. et al. Microbial temperature sensitivity and biomass change explain soil carbon loss with warming. Nat. Clim. Chang. 8, 885–889 (2018).ADS 
CAS 

Google Scholar 
Murty, D., Kirschbaum, M. U. F., Mcmurtrie, R. E. & Mcgilvray, H. Does conversion of forest to agricultural land change soil carbon and nitrogen? A review of the literature. Glob. Chang. Biol. 8, 105–123 (2002).ADS 

Google Scholar 
Veldkamp, E., Schmidt, M., Powers, J. S. & Corre, M. D. Deforestation and reforestation impacts on soils in the tropics. Nat. Rev. Earth Environ. 1, 590–605 (2020).ADS 

Google Scholar 
Kebonye, N. M., Eze, P. N., Ahado, S. K. & John, K. Structural equation modeling of the interactions between trace elements and soil organic matter in semiarid soils. Intl. J. Environ. Sci. Technol. 17(4), 2205–2214 (2020).CAS 

Google Scholar 
Del Galdo, L., Six, J., Peressotti, A. & Cotrufo, M. F. Assessing the impact of land-use change on soil C sequestration in agricultural soils by means of organic matter fraction and stable C isotopes. Glob. Chang. Biol. 9, 1204–1213 (2003).ADS 

Google Scholar 
Lal, R. Carbon sequestration in dry land ecosystems of West Asia and North Africa. Land Degrad. Dev. 13, 45–59 (2002).
Google Scholar 
Gebresamuel, G., Singh, B. R., Mitiku, H., Borresen, T. & Lal, R. Carbon Stocks in Ethiopian Soils in relation to land use and soil management. Land Degrad. Dev. 19(4), 351–367 (2008).
Google Scholar 
Fisseha, I., Mats, O. & Karl, S. Effect of land use changes on soil carbon status of some soil types in the Ethiopian Rift Valley. J. Drylands 4(1), 289–299 (2011).
Google Scholar 
Shiferaw, A., Hans, H. & Gete, Z. A review on soil carbon sequestration in Ethiopia to Mitigate land degradation and climate change. J. Environ. Earth Sci. 3(12), 187–201 (2013).
Google Scholar 
Bazezew, M. N., Teshome, S. & Eyale, B. Above- and below-ground reserved carbon in danaba community forest of Oromia Region, Ethiopia: Implications for CO2 emission balance. Am. J. Environ. Prot. 4(2), 75–82 (2015).
Google Scholar 
Berihu, T. et al. Soil carbon and nitrogen losses following deforestation in Ethiopia. Agron. Sust. Dev. 37, 1 (2017).CAS 

Google Scholar 
Gebresamuel, G. et al. Changes in soil organic carbon stock and nutrient status after conversion of pasture land to cultivated land in semi-arid areas of northern Ethiopia. Arch. Agron. Soil Sci. https://doi.org/10.1080/03650340.2020.1823372 (2022).Article 

Google Scholar 
Hoyle, F. C., Baldock, J. A. & Murphy, D. V. Soil organic carbon: Role in rainfed farming systems: With particular reference to Australian Conditions. In Rainfed Farming Systems (eds Tow, P. et al.) (Springer, 2011). https://doi.org/10.1007/978-1-4020-9132-2_14.Chapter 

Google Scholar 
Mekuria, W. et al. Restoration of degraded landscapes for ecosystem services in North-Western Ethiopia. Heliyon 4, e00764. https://doi.org/10.1016/j.heliyon.2018 (2018).Article 

Google Scholar 
Okolo, C. C. et al. Assessing the sustainability of land use management of Northern Ethiopian drylands by various indicators for soil health. Ecol. Indic. 112, 106092. https://doi.org/10.1016/j.ecolind.2020.106092 (2020).Article 
CAS 

Google Scholar 
WRB. International Union of Soil Science Working Group. In World Reference Base for Soil Resources 2014, update 2015 International soil classification system for naming soils and creating legends for soil maps. World Soil Resources Reports No. 106. FAO, Rome (2014).NMA 2018. National Metrological Agency (NMA), 2018. The National Metrological Agency of Ethiopia Mekelle center, Tigray Regional State, Mekelle, Ethiopia.Anikwe, M. A. N., Obi, M. E. & Agbim, N. N. Effect of crop and soil management practices soil compactibility in maize and groundnut plots in a Paleustult in Southeastern Nigeria. Plant Soils. 253, 457–465 (2003).CAS 

Google Scholar 
Anikwe, M. A. N. Carbon storage in soils of southeastern Nigeria under different management practices. Carbon Bal. Manag. https://doi.org/10.1186/1750-0680-5-5 (2010).Article 

Google Scholar 
IPCC Guidelines for National Greenhouse Gas Inventories. In Vol. 4: Agriculture, Forestry and other Land Use (eds. Eggleston, S., Buendia, K., Miwa, K., Ngara, T. and Tanabe, K.) (Institute for Global Environmental Strategies, 2006).McKenzie, N., Ryan, P., Fogarty, P. & Wood, J. Sampling, measurement and analytical protocols for carbon estimation in soil, litter and coarse woody debris. National Carbon Accounting System Technical Report No. 14. Australian Greenhouse Office, Canberra (2000).Nelson, D. W. & Sommers, L. E. Total carbon, total organic carbon and organic matter. In Methods of Soil Analysis. Part 3: Chemical Methods. Agronomy Monograph No. 9 (Ed. Sparks, D.L) 961–1010. (American Society of Agronomy, 1996).Bremner, J. M. & Mulvaney, C. S. Nitrogen-total. In Chemical and Microbiological Properties (eds Keeney, D. R. et al.) 595–624 (American Society of Agronomy and Soil Science Society of America, 1982).
Google Scholar 
McLean, E. O. Soil pH and lime requirement. In Methods of Soil Analysis, Part 2: Chemical and Microbiological Properties. 2nd edn. Agronomy monograph No. 9 (Eds. Page, A.L., Miller, R.H and Keeney, D.R). 199–224. (American Society of Agronomy, 1982).Rhoades, J. D. Cation exchange capacity. In Methods of Soil Analysis: Part 2 Chemical and Microbial Properties. Agronomy Monograph No. 9. (Eds. Page, A.L., Miller, R.H and Keeney, D.R) pp. 149–157 (American Society of Agronomy, 1982).Blake, G. R. & Hartge, K. H. Bulk density. In Methods of Soil Analysis. Part 1: Physical and Mineralogical Properties. 2nd edn. Agronomy Monograph No. 9 (ed. Klute, A) 363–382. (American Society of Agronomy, 1986).Gee, G. W. & Bauder, J. W. Particle size analysis. In Methods of Soil Analysis. Part 1: Physical and Mineralogical Properties. 2nd edn. Agronomy Monograph No. 9. (Ed. A Klute) 91–100. (American Society of Agronomy, 1986).Gelaw, A. M., Singh, B. R. & Lal, R. Soil organic carbon and total nitrogen stocks under different land uses in a semi-arid watershed in Tigray, Northern Ethiopia. Agric. Ecosyst. Environ. 188, 256–263 (2014).
Google Scholar 
Puget, P. & Lal, R. Soil organic carbon and nitrogen in a Mollisol in Central Ohio as affected by tillage and land use. Soil Tillage Res. 80, 201–213 (2005).
Google Scholar 
Chan, Y. Increasing soil organic carbon of agricultural land. Primefact 735, 1–5 (2008).
Google Scholar 
Worku, G., Bantider, A. & Temesgen, H. Effects of land use/land cover change on some soil physical and chemical properties in Ameleke micro-watershed Gedeo and Borena Zones. South Ethiopia. J. Environ. Earth Sci. 4, 13–24 (2014).
Google Scholar 
Assefa, D. et al. Deforestation and land use strongly effect soil organic carbon and nitrogen stock in Northwest Ethiopia. CATENA 153, 89–99 (2017).CAS 

Google Scholar 
Gessesse, T. A., Khamzina, A., Gebresamuel, G. & Amelung, W. Terrestrial carbon stocks following 15 years of integrated watershed management intervention in semi-arid Ethiopia. CATENA 190, 104543 (2020).CAS 

Google Scholar 
Haileslassie, A., Priess, J., Veldkamp, E., Teketay, D. & Lesschen, J. P. Assessment of soil nutrient depletion and its spatial variability on smallholders’ mixed farming systems in Ethiopia using partial versus full nutrient balances. Agric. Ecosyst. Environ. 108, 1–16 (2005).
Google Scholar 
Lemenih, M., Lemma, B. & Teketay, D. Changes in soil carbon and total nitrogen following reforestation of previously cultivated land in the highlands of Ethiopia. Ethiopian J. Sci. 28(2), 99–108 (2005).
Google Scholar 
Lemenih, M., Karltun, E. & Olsson, M. Soil organic matter dynamics after deforestation along a farm field chronosequences in southern highlands of Ethiopia. Agric. Ecosyst. Environ. 109, 9–19 (2005).
Google Scholar 
Okebalama, C. B., Igwe, C. A. & Okolo, C. C. Soil organic carbon levels in soils of contrasting land uses in Southeastern Nigeria. Trop. Subtrop. Agroecosyst. 20, 493–504 (2017).CAS 

Google Scholar 
Nwite, J. N., Orji, J. E. & Okolo, C. C. Effect of different land use systems on soil carbon storage and structural indices in Abakaliki, Nigeria. Indian J. Ecol. 45(3), 522–527 (2018).
Google Scholar 
Don, A., Schumacher, J. & Freibauer, A. Impact of tropical land-use change on soil organic carbon stocks–a meta-analysis. Glob. Chang. Biol. 17, 1658–1670 (2011).ADS 

Google Scholar 
Zinn, Y. L., Marrenjo, G. J. & Silva, C. A. Soil C: N ratos are unresponsive to land use change in Brazil: A comparative analysis. Agric. Ecosyst. Environ. 255, 62–72 (2018).CAS 

Google Scholar 
Lou, Y. L., Xu, M. G., Chen, X. N., He, X. H. & Zhao, K. Stratification of soil organic C, N and C: N ratio as affected by conservation tillage in two maize fields of China. CATENA 95, 124–130 (2012).CAS 

Google Scholar 
Xiao, X., Kuang, X., Sauer, T. J., Heitman, J. L. & Horton, R. Bare soil carbon dioxide fluxes with time and depth determined by high-resolution gradient-based measurements and surface chambers. Soil Sci. Soc. Am. 79, 1073–1083 (2015).CAS 

Google Scholar 
Wang, X. et al. Forest soil profile inversion and mixing change the vertical stratification of soil CO2 concentration without altering soil surface CO2 Flux. Forests 10, 192 (2019).
Google Scholar 
Bates, C. T. et al. Conversion of marginal land into switchgrass conditionally accrues soil carbon but reduces methane consumption. ISME J. 16, 10 (2021).
Google Scholar 
Slessarev, E. W. et al. Quantifying the effects of switchgrass (Panicum virgatum) on deep organic C stocks using natural abundance 14C in three marginal soils. GCB Bioenergy 12, 834–847 (2020).CAS 

Google Scholar 
Balesdent, J., Besnard, E., Arrouays, D. & Chenu, C. The dynamics of carbon in particle size fractions of soil in a forest-cultivation sequence. Plant Soil 201, 49–57 (1998).CAS 

Google Scholar 
Birch, H. F. & Friend, M. T. The organ matter and nitrogen status of east African soils. J. Soil Sci. 7, 156–167 (1956).CAS 

Google Scholar 
Deng, L., Zhu, G., Tang, Z. & Shangguan, Z. Global patterns of the effects of land-usechanges on soil carbon stocks. Glob. Ecol. Conserv. 5, 127–138 (2016).
Google Scholar 
Post, W. M. & Kwon, K. C. Soil carbon sequestration and land-use change: Processes and potential. Glob. Chang. Biol. 6, 317–327 (2000).ADS 

Google Scholar 
Feng, X. & Simpson, M. J. Temperature responses of individual soil organic matter components. J. Geophys. Res. Biogeosci. https://doi.org/10.1029/2008JG000743 (2008).Article 

Google Scholar 
Chen, S., Huang, Y., Zou, J. & Shi, Y. Mean residence time of global topsoil organic carbon depends on temperature, precipitation and soil nitrogen. Glob. Planet. Chang. 100, 99–108 (2013).ADS 

Google Scholar 
Alemayehu, K. & Sheleme, B. Effects of different land use systems on selected soi properties in South Ethiopia. J. Soil Sci. Environ. Manag. 4(5), 100–107 (2013).
Google Scholar 
Bockheim, J. G. Soil endemism and its relation to soil formation theory. Geoderma 129, 109–124 (2005).ADS 

Google Scholar 
Ukaegbu, E. P., Osuaku, S. K. & Okolo, C. C. Suitability assessment of soils supporting oilpalm plantations in the coastal plains sand, Imo State Nigeria. Int. J. Agric. For. 5(2), 113–120 (2015).
Google Scholar 
Okolo, C. C. et al. Impact of open cast mine land use on soil physical properties in Enyigba, Southeastern Nigeria and the implication for sustainable land use management. Niger. J. Soil Sci. 25(1), 95–101 (2015).
Google Scholar 
Nwite, J. N. & Okolo, C. C. Soil water relations of an Ultisol amended with agro-wastes and its effect on grain yield of maize (Zea Mays L.) in Abakaliki, Southeastern Nigeria. Eur. J. Sci. Res. 141, 126–140 (2016).
Google Scholar 
Nwite, J. N. & Okolo, C. C. Organic carbon dynamics and changes in some physical properties of soil and their effect on grain yield of maize under conservative tillage practices in Abakaliki, Nigeria. Afr. J. Agric. Res. 12(26), 2215–2222 (2017).CAS 

Google Scholar 
Mbah, C. N., Njoku, C., Okolo, C. C., Attoe, E. & Osakwe, U. C. Amelioration of a degraded Ultisol with hardwood biochar: Effects on soil physico-chemical properties and yield of cucumber (Cucumis sativus L). Afr. J. Agric. Res. 12(21), 1781–1792 (2017).CAS 

Google Scholar 
Nandan, R. et al. Impact of conservation tillage in rice–based cropping systems on soil aggregation, carbon pools and nutrients. Geoderma 340, 104–114 (2019).ADS 
CAS 

Google Scholar 
Sharma, K.L. Effect of agroforestry systems on soil quality–monitoring and assessment. Central Research Institute for Dryland Agriculture. 2011. http://www.crida.in/DRM1-WinterSchool/KLS.pdf/. Accessed on 30 Dec 2018.Okolo, C. C., Gebresamuel, G., Zenebe, A., Haile, M. & Eze, P. N. Accumulation of organic carbon in various soil aggregate sizes under different land use systems in a semi-arid environment. Agric. Ecosyst. Environ. 297, 106924. https://doi.org/10.1016/j.agee.2020.106924 (2020).Article 
CAS 

Google Scholar 
Okolo, C. C., Gebresamuel, G., Retta, A. N., Zenebe, A. & Haile, M. Advances in quantifying soil organic carbon under different land uses in Ethiopia: A review and synthesis. Bull. Natl. Res. Cent. 43(99), 2019. https://doi.org/10.1186/s42269-019-0120-z (2019).Article 

Google Scholar  More

Cavicchioli R, Ripple WJ, Timmis KN, Azam F, Bakken LR, Baylis M, et al. Scientists’ warning to humanity: microorganisms and climate change. Nat Rev Microbiol. 2019;17:569–86.Article 
CAS 

Google Scholar 
Myers SS, Smith MR, Guth S, Golden CD, Vaitla B, Mueller ND, et al. Climate Change and Global Food Systems: Potential Impacts on Food Security and Undernutrition. Annu Rev Pub Health. 2017;38:259–77.Article 

Google Scholar 
Brown AR, Lilley M, Shutler J, Lowe C, Artioli Y, Torres R, et al. Assessing risks and mitigating impacts of harmful algal blooms on mariculture and marine fisheries. Rev Aquac. 2020;12:1663–88.
Google Scholar 
Bates SS, Hubbard KA, Lundholm N, Montresor M, Leaw CP. Pseudo-nitzschia, Nitzschia, and domoic acid: New research since 2011. Harmful Algae. 2018;79:3–43.Article 

Google Scholar 
Silver MW, Bargu S, Coale SL. Toxic diatoms and domoic acid in natural and iron enriched waters of the oceanic pacific. Proc Natl Acad Sci. 2010;107:20762–67.Article 
CAS 

Google Scholar 
Trick CG, Bill BD, Cochlan WP, Wells ML, Trainer VL, Pickell LD. Iron enrichment stimulates toxic diatom production in high-nitrate, low-chlorophyll areas. Proc Natl Acad Sci. 2010;107:5887–92.Article 
CAS 

Google Scholar 
Hallegraeff G, Enevoldsen H, Zingone A. Global harmful algal bloom status reporting. Harmful Algae. 2021;102:101992.Article 

Google Scholar 
McKibben SM, Peterson W, Wood AM, Trainer VL, Hunter M, White AE. Climatic regulation of the neurotoxin domoic acid. Proc Natl Acad Sci. 2017;114:239–44.Article 
CAS 

Google Scholar 
Clark S, Hubbard KA, Ralston DK, McGillicuddy DJ, Stocke C, Alexander MA, et al. Projected effects of climate change on Pseudo-nitzschia bloom dynamics in the Gulf of Maine. J Mar Syst. 2022;230:103737.Article 

Google Scholar 
Trainer VL, Kudela RM, Hunter MV, Adams NG, McCabe RM. Climate extreme seeds a new domoic ccid hotspot on the US West Coast. Front Clim. 2020;2:1–11.Article 

Google Scholar 
Hinder SL, Hays GC, Edwards M, Roberts EC, Walne AW, Gravenor MB. Changes in marine dinoflagellate and diatom abundance under climate change. Nat Clim Change. 2012;2:271–75.Article 

Google Scholar 
Sun J, Hutchins DA, Feng Y, Seubert EL, Caron DA, Fu FX. Effects of changing pCO2 and phosphate availability on domoic acid production and physiology of the marine harmful bloom diatom Pseudo-nitzschia multiseries. Limnol Oceanogr. 2011;56:829–40.Article 
CAS 

Google Scholar 
Zhu Z, Qu P, Fu F, Tennenbaum N, Tatters AO, Hutchins DA. Understanding the blob bloom: warming increases toxicity and abundance of the harmful bloom diatom Pseudo-nitzschia in California coastal waters. Harmful Algae. 2017;67:36–43.Article 
CAS 

Google Scholar 
Radan RL, Cochlan WP. Differential toxin response of Pseudo-nitzschia multiseries as a function of nitrogen speciation in batch and continuous cultures, and during a natural assemblage experiment. Harmful Algae. 2018;73:12–29.Article 
CAS 

Google Scholar 
Wingert CJ, Cochlan WP. Effects of ocean acidification on the growth, photosynthetic performance, and domoic acid production of the diatom Pseudo-nitzschia australis from the California Current System. Harmful Algae. 2021;107:102030.Article 
CAS 

Google Scholar 
Auro ME, Cochlan WP. Nitrogen utilization and toxin production by two diatoms of the Pseudo-nitzschia pseudodelicatissima complex: P. cuspidate and P. fryxelliana. J Phycol. 2013;49:156–69.Article 
CAS 

Google Scholar 
Lundholm N, Clarke A, Ellegaard M. A 100-year record of changing Pseudo-nitzschia species in a sill-fjord in Denmark related to nitrogen loading and temperature. Harmful Algae. 2010;9:449–57.Article 

Google Scholar 
Ryan JP, Kudela RM, Birch JM, Blum M, Bower HA, Chavez FP, et al. Causality of an extreme harmful algal bloom in Monterey Bay, California, during the 2014–2016 northeast Pacific warm anomaly. Geophys Res Lett. 2017;44:5571–79.Article 

Google Scholar 
McCabe RM, Hickey BM, Kudela RM, Lefebvre KA, Adams NG, Bill BD, et al. An unprecedented coastwide toxic algal bloom linked to anomalous ocean conditions. Geophys Res Lett. 2016;43:10,366–76.Article 

Google Scholar 
Tatters AO, Fu FX, Hutchins DA. High CO2 and silicate limitation synergistically increase the toxicity of Pseudo-nitzschia fraudulenta. PLoS One. 2012;7:e32116.Article 
CAS 

Google Scholar 
Lundholm N, Hansen PJ, Kotaki Y. Effect of pH on growth and domoic acid production by potentially toxic diatoms of the genera Pseudo-nitzschia and Nitzschia. Mar Ecol Prog Ser. 2004;273:1–15.Article 
CAS 

Google Scholar 
Trimborn S, Lundholm N, Thoms S, Richter KW, Krock B, Hansen P, et al. Inorganic carbon acquisition in potentially toxic and non-toxic diatoms: the effect of pH-induced changes in seawater carbonate chemistry. Physiol Plant. 2008;133:92–105.Article 
CAS 

Google Scholar 
Brunson JK, McKinnie SMK, Chekan JR, McCrow JP, Miles ZD, Bertrand EM, et al. Biosynthesis of the neurotoxin domoic acid in a bloom-forming diatom. Science. 2018;361:1356–58.Article 
CAS 

Google Scholar 
Boissonneault KR, Henningsen BM, Bates SS, Robertson DL, Milton S, Pelletier J, et al. Gene expression studies for the analysis of domoic acid production in the marine diatom Pseudo-nitzschia multiseries. BMC Mole Biol. 2013;14:1–19.
Google Scholar 
Pierrot DE, Lewis E, Wallace DWR MS Excel program developed for CO2 system calculations. Carbon Dioxide Information Analysis Center, Oak Ridge National Laboratory, U.S. Department of. Energy, Oak Ridge, TN. 2006; Retrieved from https://doi.org/10.3334/CDIAC/otg.CO2SYS_XLS_CDIAC105a.Brzezinski MA, Nelson DM. The annual silica cycle in the Sargasso Sea near Bermuda. Deep-Sea Res Pt I Oceanogr Res Papers. 1995;42:1215–37.Article 
CAS 

Google Scholar 
Schlüter L, Lohbeck KT, Gutowska MA, Gröger JP, Riebesell U, Reusch TBH. Adaptation of a globally important coccolithophore to ocean warming and acidification. Nat Clim Change. 2014;4:1024–30.Article 

Google Scholar 
Schaum CE, Barton S, Bestion E, Buckling A, Garcia-Carreras B, Lopez P, et al. Adaptation of phytoplankton to a decade of experimental warming linked to increased photosynthesis. Nat Ecol Evol. 2017;1:0094.Article 

Google Scholar 
Wang Z, Maucher-Fuquay J, Fire SE, Mikulski CM, Haynes B, Doucette GJ, et al. Optimization of solid-phase extraction and liquid chromatography–tandem mass spectrometry for the determination of domoic acid in seawater, phytoplankton, and mammalian fluids and tissues. Anal Chim Acta. 2012;715:71–9.Article 
CAS 

Google Scholar 
Brandenburg KM, Velthuis M, Van de Waal DB. Meta-analysis reveals enhanced growth of marine harmful algae from temperate regions with warming and elevated CO2 levels. Glob Change Biol. 2019;25:2607–18.Article 

Google Scholar 
Wohlrab S, John U, Klemm K, Rberlein T, Grivogiannis AMF, Krock B, et al. Ocean acidification increases domoic acid contents during a spring to summer succession of coastal phytoplankton. Harmful Algae. 2020;92:101697.Article 
CAS 

Google Scholar 
Zhong J, Guo Y, Liang Z, Huang Q, Lu H, Pan J, et al. Adaptation of a marine diatom to ocean acidification and warming reveals constraints and trade-offs. Sci Total Environ. 2021;771:145167.Article 
CAS 

Google Scholar 
Trainer VL, Bates SS, Lundholm N, Thessen AE, Cochlan WP, Adams NG, et al. Pseudo-nitzschia physiological ecology, phylogeny, toxicity, monitoring and impacts on ecosystem health. Harmful Algae. 2012;14:271–300.Article 

Google Scholar 
Zhu Z, Qu P, Gale J, Fu F, Hutchins DA. Individual and interactive effects of warming and CO2 on Pseudo-nitzschia subcurvata and Phaeocystis antarctica, two dominant phytoplankton from the Ross Sea, Antarctica. Biogeosciences. 2017;14:5281–95.Article 
CAS 

Google Scholar 
Hutchins DA, Walworth NG, Webb EA, Saito MA, Moran D, McIlvin MR, et al. Irreversibly increased N2 fixation in Trichodesmium experimentally adapted to high CO2. Nat Commun. 2015;6:8155.Article 

Google Scholar 
Walworth NG, Lee MD, Fu FX, Hutchins DA, Webb EA. Molecular and physiological evidence of genetic assimilation to high CO2 in the marine nitrogen fixer Trichodesmium. P Natl Acad Sci. 2016;113:E7367–74.Article 
CAS 

Google Scholar 
Schaum CE, Buckling A, Smirnoff N, Studholme DJ, Yvon-Durocher G. Environmental fluctuations accelerate molecular evolution of thermal tolerance in a marine diatom. Nat Commun. 2018;9:1719.Article 

Google Scholar 
Hutchins DA, Capone DG. The ocean nitrogen cycle: New developments and global change. Nat Rev Microbiol. 2022;20:401–14.Article 
CAS 

Google Scholar 
Xu D, Tong S, Wang B, Zhang X, Wang W, Zhang X, et al. Ocean acidification stimulation of phytoplankton growth depends on the extent of departure from the optimal growth temperature. Mar Pollut Bull. 2022;177:113510.Article 
CAS 

Google Scholar 
Hennon GMM, Sefbom J, Schaum E, Dyhrman ST, Godhe A Studying the acclimation and adaptation of HAB species to changing environmental conditions. In: Wells ML, et al. (eds.). GlobalHAB. 2021. Guidelines for the Study of Climate Change Effects on HABs. Paris: UNESCO-IOC/SCOR, 2021. pp 64–78.Collins S, Bell G. Phenotypic consequences of 1,000 generations of selection at elevated CO2 in a green alga. Nature. 2004;431:566–9.Article 
CAS 

Google Scholar 
Kremp A, Godhe A, Egardt J, Dupont S, Suikkanen S, Casabianca S, et al. Intraspecific variability in the response of bloom-forming marine microalgae to changed climate conditions. Ecol Evol. 2012;2:1195–207.Article 

Google Scholar 
Tatters AO, Schnetzer A, Fu F, Lie AY, Caron DA, Hutchins DA. Short‐versus long‐term responses to changing CO2 in a coastal dinoflagellate bloom: Implications for interspecific competitive interactions and community structure. Evolution. 2013;67:1879–91.Article 

Google Scholar 
Schaum CE, Collins S. Plasticity predicts evolution in a marine alga. P Roy Soc B-Biol Sci. 2014;281:20141486.
Google Scholar 
Moran XAG, Lopez-Urrutia Á, Calvo-Díaz A, Li WKW. Increasing importance of small phytoplankton in a warmer ocean. Glob Change Biol. 2010;16:1137–44.Article 

Google Scholar 
Thomas MK, Kremer CT, Klausmeier CA, Litchman EA. Global pattern of thermal adaptation in marine phytoplankton. Science. 2012;338:1085–88.Article 
CAS 

Google Scholar 
Toseland ADSJ, Daines SJ, Clark JR, Kirkham A, Strauss J, Uhlig C, et al. The impact of temperature on marine phytoplankton resource allocation and metabolism. Nat Clim Change. 2013;3:979–84.Article 
CAS 

Google Scholar 
Collins S. Many Possible Worlds: Expanding the Ecological Scenarios in Experimental Evolution. Evol Biol. 2011;38:3–14.Article 

Google Scholar 
Qu PP, Fu F, Wang XW, Kling JD, Elghazzawy M, Huh M, et al. Two co‐dominant nitrogen‐fixing cyanobacteria demonstrate distinct acclimation and adaptation responses to cope with ocean warming. Env Microbiol Rep. 2022;14:203–17.Article 
CAS 

Google Scholar 
Lande R. Adaptation to an extraordinary environment by evolution of phenotypic plasticity and genetic assimilation. J Evol Biol. 2009;22:1435–46.Article 

Google Scholar 
Draghi J, Whitlock MC. Phenotypic plasticity facilitates mutational variance, genetic variance, and evolvability along the major axis of environmental variation. Evolution 2012;66:2891–902.Article 

Google Scholar 
Collins S, Rost B, Rynearson TA. Evolutionary potential of marine phytoplankton under ocean acidification. Evol Appl. 2014;7:140–55.Article 
CAS 

Google Scholar 
Kim H, Spivack AJ, Menden-Deuer S. pH alters the swimming behaviors of the raphidophyte Heterosigma akashiwo: Implications for bloom formation in an acidified ocean. Harmful Algae. 2013;26:1–11.Article 
CAS 

Google Scholar 
Hennon GMM, Quay P, Morales RL, Swanson LM, Armbrust EV. Acclimation conditions modify physiological response of the diatom Thalassiosira pseudonana to elevated CO2 concentrations in a nitrate-limited chemostat. J Phycol. 2014;50:243–53.Article 
CAS 

Google Scholar 
Daufresne M, Lengfellner K, Sommer U. Global warming benefits the small in aquatic ecosystems. Proc Natl Acad Sci. 2009;106:12788–93.Article 
CAS 

Google Scholar 
Atkinson D, Ciotti BJ, Montagnes DJS. Protists decrease in size linearly with temperature: ca. 2.5% °C-1. Proc R Soc Lond B 2003;270:2605–11.Article 

Google Scholar 
Tong S, Gao K, Hutchins DA. Adaptive evolution in the coccolithophore Gephyrocapsa oceanica following 1,000 generations of selection under elevated CO2. Glob Chang Biol 2018;24:3055–64.Article 

Google Scholar 
Kelly KJ, Fu FX, Jiang X, Li H, Xu D, Yang N, et al. Interactions between ultraviolet B radiation, warming, and changing nitrogen source may reduce the accumulation of toxic Pseudo-nitzschia multiseries biomass in future coastal oceans. Front Mar Sci. 2021;8:433.Article 

Google Scholar 
Sterner R, Elser, J Ecological stoichiometry. In: Levin SA, et al. (eds) The Princeton Guide to Ecology. Princeton Univ. Press, 2009. pp 376–85.Petrou K, Baker KG, Nielsen DA, Hancock AM, Schulz KG, Davidson AT. Acidification diminishes diatom silica production in the Southern Ocean. Nat Clim Change 2019;9:781–86.Article 
CAS 

Google Scholar  More

Heyes, B. Y. C. M. Social learning in animals: Categories and mechanisms. Biol. Rev. 69(2), 207–231. https://doi.org/10.1111/j.1469-185X.1994.tb01506.x (1994).Article 
CAS 

Google Scholar 
Hoppitt, W. & Laland, K. N. Social processes influencing learning in animals: A review of the evidence. Adv. Study Behav. 38, 105–165. https://doi.org/10.1016/S0065-3454(08)00003-X (2008).Article 

Google Scholar 
Kendal, R. L., Coolen, I. & Laland, K. N. Adaptive trade-offs in the use of social and personal information. In Cognitive Ecology II (eds Dukas, R. & Ratcliffe, J. M.) 249–271 (University of Chicago Press, 2009).Chapter 

Google Scholar 
Marshall-Pescini, S. & Whiten, A. Social learning of nut-cracking behavior in East African sanctuary-living chimpanzees (Pan troglodytes schweinfurthii). J. Comp. Psychol. 122(2), 186. https://doi.org/10.1037/0735-7036.122.2.186 (2008).Article 

Google Scholar 
Hobaiter, C., Poisot, T., Zuberbühler, K., Hoppitt, W. & Gruber, T. Social network analysis shows direct evidence for social transmission of tool use in wild chimpanzees. PLoS Biol. 12(9), e1001960. https://doi.org/10.1371/journal.pbio.1001960 (2014).Article 
CAS 

Google Scholar 
Coelho, C. G. et al. Social learning strategies for nut-cracking by tufted capuchin monkeys (Sapajus spp.). Anim. Cogn. 18(4), 911–919. https://doi.org/10.1007/s10071-015-0861-5 (2015).Article 
CAS 

Google Scholar 
Boyd, R. & Richerson, P. J. Culture and the evolutionary process (University of Chicago press, 1985).
Google Scholar 
Laland, K. N. Social learning strategies. Anim. Learn. Behav. 32(1), 4–14. https://doi.org/10.3758/BF03196002 (2004).Article 

Google Scholar 
Kendal, R. L. Animal ‘culture wars’: Evidence from the Wild?. Psychologist 21(4), 312–315 (2008).
Google Scholar 
Kendal, R. L., Kendal, J. R., Hoppitt, W. & Laland, K. N. Identifying social learning in animal populations: A new ‘option-bias’ method. PLoS ONE 4(8), e6541. https://doi.org/10.1371/journal.pone.0006541 (2009).Article 
ADS 
CAS 

Google Scholar 
Giraldeau, L. A., Valone, T. J. & Templeton, J. J. Potential disadvantages of using socially acquired information. Philos. Trans. R. Soc. Lond. Series B. 357(1427), 1559–1566. https://doi.org/10.1098/rstb.2002.1065 (2002).Article 

Google Scholar 
Kendal, R. L., Coolen, I., van Bergen, Y. & Laland, K. N. Trade-offs in the adaptive use of social and asocial learning. Adv. Study Behav. 35, 333–379. https://doi.org/10.1016/S0065-3454(05)35008-X (2005).Article 

Google Scholar 
Galef, B. G. Jr. Why behaviour patterns that animals learn socially are locally adaptive. Anim. Behav. 49(5), 1325–1334. https://doi.org/10.1006/anbe.1995.0164 (1995).Article 

Google Scholar 
Kendal, R. L. et al. Social learning strategies: Bridge-building between fields. Trends Cogn. Sci. 22(7), 651–665. https://doi.org/10.1016/j.tics.2018.04.003 (2018).Article 

Google Scholar 
Rendell, L. et al. Cognitive culture: Theoretical and empirical insights into social learning strategies. Trends Cogn. Sci. 15(2), 68–76. https://doi.org/10.1016/j.tics.2010.12.002 (2011).Article 

Google Scholar 
Dindo, M., Thierry, B. & Whiten, A. Social diffusion of novel foraging methods in brown capuchin monkeys (Cebus apella). Proc. R. Soc. B 275(1631), 187–193. https://doi.org/10.1098/rspb.2007.1318 (2008).Article 

Google Scholar 
Reader, S. M. & Biro, D. Experimental identification of social learning in wild animals. Learn. Behav. 38(3), 265–283. https://doi.org/10.3758/LB.38.3.265 (2010).Article 

Google Scholar 
Hoppitt, W. & Laland, K. N. Social Learning: An Introduction to Mechanisms, Methods, and Models (Princeton University Press, 2013).Book 

Google Scholar 
Byrne, R. W. & Russon, A. E. Learning by imitation: A hierarchical approach. Behav. Brain Sci. 21(5), 667–684. https://doi.org/10.1017/S0140525X9833174X (1998).Article 
CAS 

Google Scholar 
Kendal, R. L. et al. Evidence for social learning in wild lemurs (Lemur catta). Learn. Behav. 38(3), 220–234. https://doi.org/10.3758/LB.38.3.220 (2010).Article 

Google Scholar 
Lonsdorf, E. V. & Bonnie, K. E. Opportunities and constraints when studying social learning: Developmental approaches and social factors. Learn. Behav. 38(3), 195–205. https://doi.org/10.3758/LB.38.3.195 (2010).Article 

Google Scholar 
Coussi-korbel, S. & Fragaszy, M. On the relation between social dynamics and social learning. Anim. Behav. 50(6), 1441–1453. https://doi.org/10.1016/0003-3472(95)80001-8 (1995).Article 

Google Scholar 
Franz, M. & Nunn, C. L. Network-based diffusion analysis: A new method for detecting social learning. Proc. R. Soc. Lond B 276(1663), 1829–1836. https://doi.org/10.1098/rspb.2008.1824 (2009).Article 

Google Scholar 
Hoppitt, W., Boogert, N. J. & Laland, K. N. Detecting social transmission in networks. J. Theor. Biol. 263(4), 544–555. https://doi.org/10.1016/j.jtbi.2010.01.004 (2010).Article 
ADS 
MATH 

Google Scholar 
Hoppitt, W. & Laland, K. N. Detecting social learning using networks: A users guide. Am. J. Primatol. 73(8), 834–844. https://doi.org/10.1002/ajp.20920 (2011).Article 

Google Scholar 
Hasenjager, M. J., Leadbeater, E. & Hoppitt, W. Detecting and quantifying social transmission using network-based diffusion analysis. J. Anim. Ecol. 90(1), 8–26. https://doi.org/10.1111/1365-2656.13307 (2021).Article 

Google Scholar 
Schnoell, A. V. & Fichtel, C. Wild red-fronted lemurs (Eulemur rufifrons) use social information to learn new foraging techniques. Anim. Cogn. 15(4), 505–516. https://doi.org/10.1007/s10071-012-0477-y (2012).Article 

Google Scholar 
Coelho, C. Social Dynamics and Diffusion of Novel Behaviour Patterns in Wild Capuchin Monkeys (Sapajus libidinosus) Inhabiting the Serra da Capivara National Park. (Unpublished Doctoral Dissertation) (Durham University, 2015).
Google Scholar 
Claidière, N., Messer, E. J., Hoppitt, W. & Whiten, A. Diffusion dynamics of socially learned foraging techniques in squirrel monkeys. Curr. Biol. 23(13), 1251–1255. https://doi.org/10.1016/j.cub.2013.05.036 (2013).Article 
CAS 

Google Scholar 
van Leeuwen, E. J., Staes, N., Verspeek, J., Hoppitt, W. J. & Stevens, J. M. Social culture in bonobos. Curr. Biol. 30(6), R261–R262. https://doi.org/10.1016/j.cub.2020.02.038 (2020).Article 
CAS 

Google Scholar 
Canteloup, C., Hoppitt, W. & van de Waal, E. Wild primates copy higher-ranked individuals in a social transmission experiment. Nat. Commun. 11(1), 1–10. https://doi.org/10.1038/s41467-019-14209-8 (2020).Article 
CAS 

Google Scholar 
Kawai, M. Newly-acquired pre-cultural behavior of the natural troop of Japanese monkeys on Koshima Islet. Primates 6(1), 1–30. https://doi.org/10.1007/BF01794457 (1965).Article 

Google Scholar 
Huffman, M. A., Leca, J. B. & Nahallage, C. A. Cultured Japanese macaques: A multidisciplinary approach to stone handling behavior and its implications for the evolution of behavioral tradition in nonhuman primates. In The Japanese Macaques (eds Nakagawa, N. et al.) 191–219 (Springer, 2010). https://doi.org/10.1007/978-4-431-53886-8_9.Chapter 

Google Scholar 
Drapier, M. & Thierry, B. Social transmission of feeding techniques in Tonkean macaques?. Int. J. Primatol. 23(1), 105–122. https://doi.org/10.1023/A:1013201924975 (2002).Article 

Google Scholar 
Ducoing, A. M. & Thierry, B. Tool-use learning in Tonkean macaques (Macaca tonkeana). Anim. Cogn. 8(2), 103–113. https://doi.org/10.1007/s10071-004-0240-0 (2005).Article 

Google Scholar 
Ferrari, P. F. et al. Neonatal imitation in rhesus macaques. PLoS Biol. 4(9), e302. https://doi.org/10.1371/journal.pbio.0040302 (2006).Article 
CAS 

Google Scholar 
Leca, J. B., Gunst, N. & Huffman, M. A. The first case of dental flossing by a Japanese macaque (Macaca fuscata): Implications for the determinants of behavioral innovation and the constraints on social transmission. Primates 51(1), 13. https://doi.org/10.1007/s10329-009-0159-9 (2010).Article 

Google Scholar 
Macellini, S. et al. Individual and social learning processes involved in the acquisition and generalization of tool use in macaques. Philos. Trans. R. Soc. B 367(1585), 24–36. https://doi.org/10.1098/rstb.2011.0125 (2012).Article 
CAS 

Google Scholar 
Redshaw, J. Re-analysis of data reveals no evidence for neonatal imitation in rhesus macaques. Biol. Let. 15(7), 20190342. https://doi.org/10.1098/rsbl.2019.0342 (2019).Article 

Google Scholar 
Hook, M. A. et al. Inter-group variation in abnormal behavior in chimpanzees (Pan troglodytes) and rhesus macaques (Macaca mulatta). Appl. Anim. Behav. Sci. 76(2), 165–176. https://doi.org/10.1016/S0168-1591(02)00005-9 (2002).Article 

Google Scholar 
Watanabe, K., Urasopon, N. & Malaivijitnond, S. Long-tailed macaques use human hair as dental floss. Am. J. Primatol. 69(8), 940–944. https://doi.org/10.1002/ajp.20403 (2007).Article 

Google Scholar 
Gumert, M. D., Kluck, M. & Malaivijitnond, S. The physical characteristics and usage patterns of stone axe and pounding hammers used by long-tailed macaques in the Andaman Sea region of Thailand. Am. J. Primatol. 71(7), 594–608. https://doi.org/10.1002/ajp.20694 (2009).Article 

Google Scholar 
Tan, A. W., Hemelrijk, C. K., Malaivijitnond, S. & Gumert, M. D. Young macaques (Macaca fascicularis) preferentially bias attention towards closer, older, and better tool users. Anim. Cogn. 21(4), 551–563. https://doi.org/10.1007/s10071-018-1188-9 (2018).Article 

Google Scholar 
Bandini, E. & Tennie, C. Exploring the role of individual learning in animal tool-use. PeerJ 8, e9877. https://doi.org/10.7717/peerj.9877 (2020).Article 

Google Scholar 
Leca, J. B., Gunst, N., & Huffman, M. A. Japanese macaque cultures: Inter-and intra-troop behavioural variability of stone handling patterns across 10 troops. Behaviour, 251–281. https://www.jstor.org/stable/4536445 (2007).Tanaka, I. Matrilineal distribution of louse egg-handling techniques during grooming in free-ranging Japanese macaques. Am. J. Phys. Anthropol. 98(2), 197–201. https://doi.org/10.1002/ajpa.1330980208 (1995).Article 
CAS 

Google Scholar 
Tanaka, I. Social diffusion of modified louse egg-handling techniques during grooming in free-ranging Japanese macaques. Anim. Behav. 56(5), 1229–1236. https://doi.org/10.1006/anbe.1998.0891 (1998).Article 
CAS 

Google Scholar 
Whiten, A. & van de Waal, E. The pervasive role of social learning in primate lifetime development. Behav. Ecol. Sociobiol. 72(5), 1–16. https://doi.org/10.1007/s00265-018-2489-3 (2018).Article 

Google Scholar 
Widdig, A., Streich, W. J. & Tembrock, G. Coalition formation among male Barbary macaques (Macaca sylvanus). Am. J. Primatol. 50(1), 37–51. https://doi.org/10.1002/(SICI)1098-2345(200001)50:1%3c37::AID-AJP4%3e3.0.CO;2-3 (2000).Article 
CAS 

Google Scholar 
Thierry, B. Unity in diversity: Lessons from macaque societies. Evol. Anthropol. 16(6), 224–238. https://doi.org/10.1002/evan.20147 (2007).Article 

Google Scholar 
Berghänel, A., Ostner, J., Schröder, U. & Schülke, O. Social bonds predict future cooperation in male Barbary macaques, Macaca sylvanus. Anim. Behav. 81(6), 1109–1116. https://doi.org/10.1016/j.anbehav.2011.02.009 (2011).Article 

Google Scholar 
Carne, C., Wiper, S. & Semple, S. Reciprocation and interchange of grooming, agonistic support, feeding tolerance, and aggression in semi-free-ranging Barbary macaques. Am. J. Primatol. 73(11), 1127–1133. https://doi.org/10.1002/ajp.20979 (2011).Article 

Google Scholar 
Molesti, S. & Majolo, B. Cooperation in wild Barbary macaques: Factors affecting free partner choice. Anim. Cogn. 19(1), 133–146. https://doi.org/10.1007/s10071-015-0919-4 (2016).Article 

Google Scholar 
Rebout, N., Desportes, C. & Thierry, B. Resource partitioning in tolerant and intolerant macaques. Aggress. Behav. 43(5), 513–520. https://doi.org/10.1002/ab.21709 (2017).Article 

Google Scholar 
Amici, F., Caicoya, A. L., Majolo, B. & Widdig, A. Innovation in wild Barbary macaques (Macaca sylvanus). Sci. Rep. 10(1), 1–12. https://doi.org/10.1038/s41598-020-61558-2 (2020).Article 
CAS 

Google Scholar 
Fischer, J. Emergence of individual recognition in young macaques. Anim. Behav. 67(4), 655–661. https://doi.org/10.1016/j.anbehav.2003.08.006 (2004).Article 

Google Scholar 
Seyfarth, R. M. & Cheney, D. L. Production, usage, and comprehension in animal vocalizations. Brain Lang. 115(1), 92–100. https://doi.org/10.1016/j.bandl.2009.10.003 (2010).Article 

Google Scholar 
Garcia-Nisa, I. Communication and cultural transmission in populations of semi free-ranging Barbary macaques (Macaca sylvanus). (Doctoral dissertation). Durham University, United Kingdom. http://etheses.dur.ac.uk/14140/ (2021).Hoppitt, W. The conceptual foundations of network-based diffusion analysis: Choosing networks and interpreting results. Philos. Trans. R. Soc. B 372(1735), 20160418. https://doi.org/10.1098/rstb.2016.0418 (2017).Article 

Google Scholar 
Hikami, K., Hasegawa, Y. & Matsuzawa, T. Social transmission of food preferences in Japanese monkeys (Macaca fuscata) after mere exposure or aversion training. J. Comp. Psychol. 104(3), 233. https://doi.org/10.1037/0735-7036.104.3.233 (1990).Article 
CAS 

Google Scholar 
Deaner, R. O., Khera, A. V. & Platt, M. L. Monkeys pay per view: Adaptive valuation of social images by rhesus macaques. Curr. Biol. 15(6), 543–548. https://doi.org/10.1016/j.cub.2005.01.044 (2005).Article 
CAS 

Google Scholar 
Gariépy, J. F. et al. Social learning in humans and other animals. Front. Neurosci. 8, 58. https://doi.org/10.3389/fnins.2014.00058 (2014).Article 

Google Scholar 
Barrett, B. J., McElreath, R. L. & Perry, S. E. Pay-off-biased social learning underlies the diffusion of novel extractive foraging traditions in a wild primate. Proc. R. Soc. B 284(1856), 20170358. https://doi.org/10.1098/rspb.2017.0358 (2017).Article 

Google Scholar 
Kuester, J. & Paul, A. Group fission in Barbary macaques (Macaca sylvanus) at Affenberg Salem. Int. J. Primatol. 18(6), 941–966. https://doi.org/10.1023/A:1026396113830 (1997).Article 

Google Scholar 
Whitehead, H. Analyzing Animal Societies: Quantitative Methods for Vertebrate Social Analysis (University of Chicago Press, 2008).Book 

Google Scholar 
Hoppitt, W. (2011). NBDA User Guide V1.2. https://lalandlab.st-andrews.ac.uk/freeware/ 28 Sept 2016.Fleiss, J. L., Levin, B. & Paik, M. C. Statistical Methods for Rates and Proportions 3rd edn. (Wiley, 2003).Book 
MATH 

Google Scholar 
McHugh, M. L. Interrater reliability: the kappa statistic. Biochemia medica: Biochemia medica, 22(3), 276–282. https://hrcak.srce.hr/89395 (2012).Hair, J. F., Anderson, R. E., Babin, B. J. & Black, W. C. Multivariate Data Analysis: A Global Perspective Vol. 7 (Pearson Education, 2010).
Google Scholar 
Campbell, L. A., Tkaczynski, P. J., Lehmann, J., Mouna, M. & Majolo, B. Social thermoregulation as a potential mechanism linking sociality and fitness: Barbary macaques with more social partners form larger huddles. Sci. Rep. 8(1), 1–8. https://doi.org/10.1038/s41598-018-24373-4 (2018).Article 
CAS 

Google Scholar 
Barrett, L., Henzi, S. P., Weingrill, T., Lycett, J. E. & Hill, R. A. Market forces predict grooming reciprocity in female baboons. Proc. R. Soc. Lond. Ser. B 266(1420), 665–670. https://doi.org/10.1098/rspb.1999.0687 (1999).Article 

Google Scholar 
Henzi, S. P. et al. Effect of resource competition on the long-term allocation of grooming by female baboons: Evaluating Seyfarth’s model. Anim. Behav. 66(5), 931–938. https://doi.org/10.1006/anbe.2003.2244 (2003).Article 

Google Scholar 
Ueno, M. & Nakamichi, M. Grooming facilitates huddling formation in Japanese macaques. Behav. Ecol. Sociobiol. 72(6), 1–10. https://doi.org/10.1007/s00265-018-2514-6 (2018).Article 

Google Scholar 
Carter, A. J., Tico, M. T. & Cowlishaw, G. Sequential phenotypic constraints on social information use in wild baboons. Elife 5, e13125. https://doi.org/10.7554/eLife.13125.001 (2016).Article 

Google Scholar 
Barelli, C., Reichard, U. H. & Mundry, R. Is grooming used as a commodity in wild white-handed gibbons, Hylobates lar?. Anim. Behav. 82(4), 801–809. https://doi.org/10.1016/j.anbehav.2011.07.012 (2011).Article 

Google Scholar 
Schülke, O., Dumdey, N. & Ostner, J. Selective attention for affiliative and agonistic interactions of dominants and close affiliates in macaques. Sci. Rep. 10(1), 1–8. https://doi.org/10.1038/s41598-020-62772-8 (2020).Article 
CAS 

Google Scholar 
Heesen, M., Macdonald, S., Ostner, J. & Schülke, O. Ecological and social determinants of group cohesiveness and within-group spatial position in wild Assamese macaques. Ethology 121(3), 270–283. https://doi.org/10.1111/eth.12336 (2015).Article 

Google Scholar 
Ortiz, K. M. Female feeding competition in a folivorous primate (Propithecus verreauxi) with formalized dominance hierarchies: contest or scramble? (Doctoral dissertation). University of Texas, USA. https://repositories.lib.utexas.edu/handle/2152/34120 (2015).Jurczyk, V., Fröber, K. & Dreisbach, G. Increasing reward prospect motivates switching to the more difficult task. Mot. Sci. 5(4), 295–313. https://doi.org/10.1037/mot0000119 (2019).Article 

Google Scholar 
Rathke, E. M. & Fischer, J. Differential ageing trajectories in motivation, inhibitory control and cognitive flexibility in Barbary macaques (Macaca sylvanus). Philos. Trans. R. Soc. B 375(1811), 20190617. https://doi.org/10.1098/rstb.2019.0617 (2020).Article 

Google Scholar 
Kendal, R. et al. Chimpanzees copy dominant and knowledgeable individuals: Implications for cultural diversity. Evol. Hum. Behav. 36(1), 65–72. https://doi.org/10.1016/j.evolhumbehav.2014.09.002 (2015).Article 

Google Scholar 
van de Waal, E., Claidière, N. & Whiten, A. Social learning and spread of alternative means of opening an artificial fruit in four groups of vervet monkeys. Anim. Behav. 85(1), 71–76. https://doi.org/10.1016/j.anbehav.2012.10.008 (2013).Article 

Google Scholar 
Luncz, L. V. & Boesch, C. Tradition over trend: Neighboring chimpanzee communities maintain differences in cultural behavior despite frequent immigration of adult females. Am. J. Primatol. 76(7), 649–657. https://doi.org/10.1002/ajp.22259 (2014).Article 

Google Scholar 
van Leeuwen, E. J., Acerbi, A., Kendal, R. L., Tennie, C. & Haun, D. B. A reappreciation of ‘conformity’. Anim. Behav. 122, e5–e10. https://doi.org/10.1016/j.anbehav.2016.09.010 (2016).Article 

Google Scholar 
Horner, V. & Whiten, A. Causal knowledge and imitation/emulation switching in chimpanzees (Pan troglodytes) and children (Homo sapiens). Anim. Cogn. 8(3), 164–181. https://doi.org/10.1007/s10071-004-0239-6 (2005).Article 

Google Scholar 
Wood, L. The influence of model-based biases and observer prior experience on social learning mechanisms and strategies. (Doctoral dissertation). Durham University, United Kingdom. http://etheses.dur.ac.uk/7274/ (2013).van Leeuwen, E. J., Cronin, K. A., Schütte, S., Call, J. & Haun, D. B. Chimpanzees (Pan troglodytes) flexibly adjust their behaviour in order to maximize payoffs, not to conform to majorities. PLoS ONE 8(11), e80945. https://doi.org/10.1371/journal.pone.0080945 (2013).Article 
CAS 

Google Scholar 
Vale, G. L., Flynn, E. G., Lambeth, S. P., Schapiro, S. J. & Kendal, R. L. Public information use in chimpanzees (Pan troglodytes) and children (Homo sapiens). J. Comp. Psychol. 128(2), 215–223. https://doi.org/10.1037/a0034420 (2014).Article 

Google Scholar 
Canteloup, C., Cera, M. B., Barrett, B. J. & van de Waal, E. Processing of novel food reveals payoff and rank-biased social learning in a wild primate. Sci. Rep. 11(1), 1–13. https://doi.org/10.1038/s41598-021-88857-6 (2021).Article 
CAS 

Google Scholar 
Boccaletti, S. et al. The structure and dynamics of multilayer networks. Phys. Rep. 544(1), 1–122. https://doi.org/10.1016/j.physrep.2014.07.001 (2014).Article 
ADS 
CAS 

Google Scholar 
Kivela, M. et al. Multilayer networks. J. Complex Netw. 2(3), 203e271. https://doi.org/10.1093/comnet/cnu016 (2014).Article 

Google Scholar 
Snijders, L. & Naguib, M. Communication in animal social networks: A missing link. Adv. Study Behav. 49, 297–359. https://doi.org/10.1016/bs.asb.2017.02.004 (2017).Article 

Google Scholar 
Finn, K. R., Silk, M. J., Porter, M. A. & Pinter-Wollman, N. The use of multilayer network analysis in animal behaviour. Anim. Behav. 149, 7–22. https://doi.org/10.1016/j.anbehav.2018.12.016 (2019).Article 

Google Scholar  More