Philippa Kaur

Butchart, S. H. M. et al. Shortfalls and solutions for meeting national and global conservation area targets. Conserv. Lett. 8, 329–337 (2015).Article 

Google Scholar 
McDonald-Madden, E. et al. ‘True’ conservation progress. Science 323, 43–44 (2009).Article 
CAS 
PubMed 

Google Scholar 
Corson, C. et al. Everyone’s Solution? Defining and redefining protected areas at the Convention on Biological Diversity. Conservation and Society 190–202. https://www.jstor.org/stable/26393154?seq=1#metadata_info_tab_contents (Accessed 1st March 2022) (2014).Caro, T. & Berger, J. Can behavioural ecologists help establish protected areas?. Philos. Trans. R. Soc. B 374, 20180062 (2019).Article 

Google Scholar 
Barnes, M. D. et al. Wildlife population trends in protected areas predicted by national socio-economic metrics and body size. Nat. Commun. 7, 12747 (2016).Article 
ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Watson, J. E. M. et al. Bolder science needed now for protected areas. Conserv. Biol. 30, 243–248 (2016).Article 
PubMed 

Google Scholar 
Joppa, L. N. & Pfaff, A. High and far: Biases in the location of protected areas. PLoS One 4, e8273 (2009).Article 
ADS 
PubMed 
PubMed Central 

Google Scholar 
Runge, C. A., Martin, T. G., Possingham, H. P., Willis, S. G. & Fuller, R. A. Conserving mobile species. Front. Ecol. Environ. 12, 395–402 (2014).Article 

Google Scholar 
Thirgood, S. et al. Can parks protect migratory ungulates? The case of the Serengeti wildebeest. Anim. Conserv. 7, 113–120 (2004).Article 

Google Scholar 
Craigie, I. D. et al. Large mammal population declines in Africa’s protected areas. Biol. Conserv. 143, 2221–2228 (2010).Article 

Google Scholar 
Geldmann, J. et al. Effectiveness of terrestrial protected areas in reducing habitat loss and population declines. Biol. Conserv. 161, 230–238 (2013).Article 

Google Scholar 
Hansen, A. J. & DeFries, R. Ecological mechanisms linking protected areas to surrounding lands. Ecol. Appl. 17, 974–988 (2007).Article 
PubMed 

Google Scholar 
Beresford, A. E. et al. Poor overlap between the distribution of Protected Areas and globally threatened birds in Africa. Anim. Conserv. 14, 99–107 (2011).Article 

Google Scholar 
Haynes, G. Elephants (and extinct relatives) as earth-movers and ecosystem engineers. Geomorphology 157–158, 99–107 (2012).Article 
ADS 

Google Scholar 
Terborgh, J., Davenport, L. C., Ong, L. & Campos-Arceiz, A. Foraging impacts of Asian megafauna on tropical rain forest structure and biodiversity. Biotropica 50, 84–89 (2018).Article 

Google Scholar 
Galanti, V., Preatoni, D., Martinoli, A., Wauters, L. A. & Tosi, G. Space and habitat use of the African elephant in the Tarangire-Manyara ecosystem, Tanzania: Implications for conservation. Mamm. Biol. 71, 99–114 (2006).Article 

Google Scholar 
Williams, C. et al. Elephas maximus. The IUCN Red List of Threatened Species. e.T7140A45818198. https://doi.org/10.2305/IUCN.UK.2020-3.RLTS.T7140A45818198.en. Accessed on 15 February 2022. (2020)Stokke, S. & Du Toit, J. T. Sexual segregation in habitat use by elephants in Chobe National Park, Botswana. Afr. J. Ecol. 40, 360–371 (2002).Article 

Google Scholar 
Chowdhury, S. et al. Protected areas in South Asia: Status and prospects. Sci. Total Environ. 811, 152316 (2022).Article 
ADS 
CAS 
PubMed 

Google Scholar 
Goswami, V. R. et al. Community-managed forests and wildlife-friendly agriculture play a subsidiary but not substitutive role to protected areas for the endangered Asian elephant. Biol. Conserv. 177, 74–81 (2014).Article 

Google Scholar 
Fernando, C., Weston, M. A., Corea, R., Pahirana, K. & Rendall, A. R. Asian elephant movements between natural and human-dominated landscapes mirror patterns of crop damage in Sri Lanka. Oryx https://doi.org/10.1017/S0030605321000971 (2022).Article 

Google Scholar 
Santini, L., Saura, S. & Rondinini, C. Connectivity of the global network of protected areas. Divers. Distrib. 22, 199–211 (2016).Article 

Google Scholar 
Brennan, A. et al. Functional connectivity of the world’s protected areas. Science 376, 1101–1104 (2022).Article 
ADS 
CAS 
PubMed 

Google Scholar 
Kumar, M. A. & Singh, M. Behavior of Asian elephant (Elephas maximus) in a land-use mosaic: Implications for human-elephant coexistence in the Anamalai Hills, India. Wildl. Biol. Pract. 6, 69–80 (2010).
Google Scholar 
Rathnayake, C. W. M., Jones, S., Soto-Berelov, M. & Wallace, L. Human–elephant conflict and land cover change in Sri Lanka. Appl. Geogr. 143, 102685 (2022).Article 

Google Scholar 
Chan, A. N. et al. Landscape characteristics influence ranging behavior of Asian elephants at the human-wildlands interface in Myanmar. Mov. Ecol. 10, 1–15 (2022).Article 

Google Scholar 
Magioli, M. et al. Land-use changes lead to functional loss of terrestrial mammals in a Neotropical rainforest. Perspect. Ecol. 19, 161–170 (2021).
Google Scholar 
Fernando, P. et al. The future of Asian elephant conservation: Setting sights beyond protected area boundaries. in Conservation Biology in Asia 252–260 (2006).Kumar, M. A., Vijayakrishnan, S. & Singh, M. Whose habitat is it anyway? Role of natural and anthropogenic habitats in conservation of charismatic species. Trop. Conserv. Sci. 11, 194008291878845 (2018).Article 

Google Scholar 
Sirua, H. Nature above people: Rolston and “fortress” conservation in the South. Ethics Environ. 11, 71–96 (2006).Article 

Google Scholar 
Keerthipriya, P. et al. Musth and its effects on male–male and male–female associations in Asian elephants. J. Mammal. 101, 259–270 (2020).Article 

Google Scholar 
Eisenberg, J. F., Mckay, G. M. & Jainudeen, M. R. Reproductive behavior of the Asiatic elephant (Elephas maximus maximus). Behaviour 38, 193–225 (1971).Article 
CAS 
PubMed 

Google Scholar 
Fernando, P. et al. Ranging behavior of the Asian elephant in Sri Lanka. Mamm. Biol. Zeitschrift für Säugetierkd. 73, 2–13 (2008).Article 

Google Scholar 
Hollister-Smith, J. A., Alberts, S. C. & Rasmussen, L. E. L. Do male African elephants, Loxodonta africana, signal musth via urine dribbling?. Anim. Behav. 76, 1829–1841 (2008).Article 

Google Scholar 
LaDue, C. A., Vandercone, R. P. G., Kiso, W. K. & Freeman, E. W. Behavioral characterization of musth in Asian elephants (Elephas maximus): Defining progressive stages of male sexual behavior in in-situ and ex-situ populations. Appl. Anim. Behav. Sci. 251, 105639 (2022).Article 

Google Scholar 
LaDue, C. A., Goodwin, T. E. & Schulte, B. A. Concentration-dependent chemosensory responses towards pheromones are influenced by receiver attributes in Asian elephants. Ethology 124, 387–399 (2018).Article 

Google Scholar 
Goldenberg, S. Z., de Silva, S., Rasmussen, H. B., Douglas-Hamilton, I. & Wittemyer, G. Controlling for behavioural state reveals social dynamics among male African elephants, Loxodonta africana. Anim. Behav. 95, 111e119 (2014).Article 

Google Scholar 
Chave, E. et al. Variation in metabolic factors and gonadal, pituitary, thyroid, and adrenal hormones in association with musth in African and Asian elephant bulls. Gen. Comp. Endocrinol. 276, 1–13 (2019).Article 
CAS 
PubMed 

Google Scholar 
Glaeser, S. S. et al. Characterization of longitudinal testosterone, ocrtisol, and musth in male Asian Elephants (Elephas maximus), effects of aging, and adrenal responses to social changes and health events. Animals 12, 1332 (2022).Article 
PubMed 
PubMed Central 

Google Scholar 
de Silva, S., Ranjeewa, A. D. G. & Kryazhimskiy, S. The dynamics of social networks among female Asian elephants. BMC Ecol. 11, 17 (2011).Article 
PubMed 
PubMed Central 

Google Scholar 
Nandini, S., Keerthipriya, P. & Vidya, T. N. C. Group size differences may mask underlying similarities in social structure: A comparison of female elephant societies. Behav. Ecol. 29, 145–159 (2018).Article 

Google Scholar 
de Silva, S. & Wittemyer, G. A comparison of social organization in Asian elephants and African Savannah elephants. Int. J. Primatol. 33, 1125–1141 (2012).Article 

Google Scholar 
Nandini, S., Keerthipriya, P. & Vidya, T. N. C. Seasonal variation in female Asian elephant social structure in Nagarahole-Bandipur, southern India. Anim. Behav. 134, 135–145 (2017).Article 

Google Scholar 
de Silva, S., Schmid, V. & Wittemyer, G. Fission-fusion processes weaken dominance networks among female Asian elephants in a productive habitat. Behav. Ecol. 28, 243–252 (2017).Article 

Google Scholar 
de Silva, S., Ranjeewa, A. D. G. & Weerakoon, D. Demography of Asian elephants (Elephas maximus) at Uda Walawe National Park, Sri Lanka based on identified individuals. Biol. Conserv. 144, 1742–1752 (2011).Article 

Google Scholar 
Ginsberg, J. R. & Young, T. P. Measuring association between individuals or groups in behavioural studies. Anim. Behav. 44, 377–379 (1992).Article 

Google Scholar 
Csardi, G. & Nepusz, T. The igraph software package for complex network research. InterJournal, Complex Syst. 5, 1–9 (2014).
Google Scholar 
Liechti, J. I. & Bonhoeffer, S. A time resolved clustering method revealing longterm structures and their short-term internal dynamics. arXiv:1912.04261 (2020).Farine, D. R. & Whitehead, H. Constructing, conducting and interpreting animal social network analysis. J. Anim. Ecol. 84, 1144–1163 (2015).Article 
PubMed 
PubMed Central 

Google Scholar 
Wikramanayake, E. D. et al. An ecology-based method for defining priorities for large mammal conservation: The tiger as case study. Conserv. Biol. 12, 865–878 (2008).Article 

Google Scholar 
Chundawat, R. S., Sharma, K., Gogate, N., Malik, P. K. & Vanak, A. T. Size matters: Scale mismatch between space use patterns of tigers and protected area size in a tropical dry forest. Biol. Conserv. 197, 146–153 (2016).Article 

Google Scholar 
Tucker, M. A. et al. Moving in the Anthropocene: Global reductions in terrestrial mammalian movements. Science 359, 466–469 (2018).Article 
ADS 
CAS 
PubMed 

Google Scholar 
Karanth, K. K. & DeFries, R. Nature-based tourism in Indian protected areas: New challenges for park management. Conserv. Lett. 4, 137–149 (2011).Article 

Google Scholar 
Brown, J. L. et al. Comparative endocrinology of testicular, adrenal and thyroid function in captive Asian and African elephant bulls. Gen. Comp. Endocrinol. 151, 153–162 (2007).Article 
CAS 
PubMed 

Google Scholar 
Slotow, R. et al. Older bull elephants control young males. Nature 408, 425–426 (2000).Article 
ADS 
CAS 
PubMed 

Google Scholar 
Poole, J. H., Lee, P. C., Njiraini, N. & & Moss, C. J. Longevity, competition, and musth: A long-term perspective on male reproductive strategies. in The Amboseli Elephants: A Long‐Term Perspective on a Long‐Lived Mammal 272–286 (2011).Poole, J. H. Announcing intent: The aggressive state of musth in African elephants. Anim. Behav. 37, 153–155 (1989).Article 

Google Scholar 
Poole, J. H. Mate guarding, reproductive success and female choice in African elephants. Anim. Behav. 37, 842–849 (1989).Article 

Google Scholar 
Poole, J. H. Rutting behavior in elephants: The phenomenon of musth in African elephants. Anim. Behav. 102, 283–316 (1987).
Google Scholar 
Foley, A. M. et al. Reproductive effort and success of males in scramble-competition polygyny: Evidence for trade-offs between foraging and mate search. J. Anim. Ecol. 87, 1600–1614 (2018).Article 
PubMed 

Google Scholar 
Fernando, P., Leimgruber, P., Prasad, T. & Pastorini, J. Problem-elephant translocation: Translocating the problem and the elephant?. PLoS One 7, e50917 (2012).Article 
ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Archie, E. A., Morrison, T. A., Foley, C. A. H., Moss, C. J. & Alberts, S. C. Dominance rank relationships among wild female African elephants, Loxodonta africana. Anim. Behav. 71, 117–127 (2006).Article 

Google Scholar 
Wittemyer, G. & Getz, W. M. Hierarchical dominance structure and social organization in African elephants, Loxodonta africana. Anim. Behav. 73, 671–681 (2007).Article 

Google Scholar 
Wittemyer, G., Getz, W. M., Vollrath, F. & Douglas-Hamilton, I. Social dominance, seasonal movements, and spatial segregation in African elephants: A contribution to conservation behavior. Behav. Ecol. Sociobiol. 61, 1919–1931 (2007).Article 

Google Scholar 
Gunaryadi, D., Sugiyo, & Hedges, S. Community-based human-elephant conflict mitigation: The value of an evidence-based approach in promoting the uptake of effective methods. PLoS One 12, e0173742 (2017).Article 
PubMed 
PubMed Central 

Google Scholar 
Wilson, G. et al. Between a rock and a hard place: Rugged terrain features and human disturbance affect behaviour and habitat use of Sumatran elephants in Aceh, Sumatra, Indonesia. Biodivers. Conserv. 30, 597–618 (2021).Article 

Google Scholar 
de Silva, S. et al. Demographic variables for wild Asian elephants using longitudinal observations. PLoS One 8, e82788 (2013).Article 
ADS 
PubMed 
PubMed Central 

Google Scholar 
LaDue, C. A., Eranda, I., Jayasinghe, C. & Vandercone, R. P. G. Mortality patterns of Asian elephants in a region of human–elephant conflict. J. Wildl. Manag. 85, 794–802 (2021).Article 

Google Scholar 
Ram, A. K. et al. Tracking forest loss and fragmentation between 1930 and 2020 in Asian elephant (Elephas maximus) range in Nepal. Sci. Rep. 11, 1–13 (2021).Article 
ADS 

Google Scholar 
Neupane, D., Kwon, Y., Risch, T. S. & Johnson, R. L. Changes in habitat suitability over a two decade period before and after Asian elephant recolonization. Glob. Ecol. Conserv. 22, e01023 (2020).Article 

Google Scholar 
de Silva, S. & Leimgruber, P. Demographic tipping points as early indicators of vulnerability for slow-breeding megafaunal populations. Front. Ecol. Evol. 7, 171 (2019).Article 

Google Scholar 
Rodrigo, M. Farmers move to occupy a critical elephant corridor in Sri Lanka. Mongabay (2021).de la Torre, J. A. et al. There will be conflict—Agricultural landscapes are prime, rather than marginal, habitats for Asian elephants. Anim. Conserv. 24, 720–732 (2021).Article 

Google Scholar 
Rood, E., Ganie, A. A. & Nijman, V. Using presence-only modelling to predict Asian elephant habitat use in a tropical forest landscape: Implications for conservation. Divers. Distrib. 16, 975–984 (2010).Article 

Google Scholar 
Evans, L. J., Goossens, B., Davies, A. B., Reynolds, G. & Asner, G. P. Natural and anthropogenic drivers of Bornean elephant movement strategies. Glob. Ecol. Conserv. 22, e00906 (2020).Article 

Google Scholar 
Morales-Hidalgo, D., Oswalt, S. N. & Somanathan, E. Status and trends in global primary forest, protected areas, and areas designated for conservation of biodiversity from the Global Forest Resources Assessment 2015. For. Ecol. Manag. 352, 68–77 (2015).Article 

Google Scholar 
Ellis, E. C. et al. People have shaped most of terrestrial nature for at least 12,000 years. Proc. Natl. Acad. Sci. U.S.A. 118, 1–8 (2021).Article 

Google Scholar 
Goswami, V. R., Vasudev, D. & Oli, M. K. The importance of conflict-induced mortality for conservation planning in areas of human–elephant co-occurrence. Biol. Conserv. 176, 191–198 (2014).Article 

Google Scholar 
de Silva, S. & Leimgruber, P. Demographic tipping points as early indicators of vulnerability for slow-breeding megafaunal populations. Front. Ecol. Evol. 7, 1–13 (2019).Article 
CAS 

Google Scholar 
Hettiarachchi, K. ‘Gathering’ shuns ‘brimming’ Minneriya. The Sunday Times (2021).Srinivasaiah, N., Kumar, V., Vaidyanathan, S., Sukumar, R. & Sinha, A. All-male groups in Asian elephants: A novel, adaptive social strategy in increasingly anthropogenic landscapes of southern India. Sci. Rep. 9, 1–11 (2019).Article 
ADS 
CAS 

Google Scholar 
de Silva, E. M. K. et al. Feasibility of using convolutional neural networks for individual-identification of wild Asian elephants. Mamm. Biol. https://doi.org/10.1007/S42991-021-00206-2 (2022).Article 

Google Scholar 
de Silva, S. The Elephant Attribute Recording System (EARS): A tool for individual-based research on Asian elephants. Gajah 40, 46 (2014).
Google Scholar 
Jainudeen, M. R., Katongole, C. B. & Short, R. V. Plasma testosterone levels in relation to musth and sexual activity in the male Asiatic elephant, Elephas maximus. J. Reprod. Fertil. 29, 99–103 (1972).Article 
CAS 
PubMed 

Google Scholar 
Farine, D. R. Animal social network inference and permutations for ecologists in R using asnipe. Methods Ecol. Evol. 4, 1187–1194 (2013).Article 

Google Scholar 
Whitehead, H. Analyzing Animal Societies (University of Chicago Press, 2008).Book 

Google Scholar 
Bates, D., Mächler, M., Bolker, B., & Walker, S. Fitting Linear Mixed-Effects Models Using lme4. J. Stat. Softw. 67(1), 1–48. https://doi.org/10.18637/jss.v067.i01 (2015).Article 

Google Scholar 
Dekker, D., Krackhardt, D. & Snijders, T. A. B. Sensitivity of MRQAP tests to collinearity and autocorrelation conditions. Psychometrika 72, 563–581 (2007).Article 
MathSciNet 
PubMed 
PubMed Central 
MATH 

Google Scholar  More

NEWS AND VIEWS
02 November 2022

Predicting the risk of extinction from climate change requires an understanding of the interactions between species. An analysis of how changes in rainfall affect competition between plant species offers a way of tackling this challenge. More

The link between SDGs and NRRPThe Italian National Recovery and Resilience Plan (NRRP) is part of the Next Generation EU (NGEU) program, the 750-billion-euro package, consisting of about half of grants, agreed by the European Union in response to the pandemic crisis. The main component of the NGEU program is the Recovery and Resilience Facility (RRF), which has a duration of six years, from 2021 to 2026, and a total size of €672.5 billion (€312.5 billion grants, the remaining €360 billion loans at subsidized rates).The Plan is developed around three strategic axes shared at European level: digitalization and innovation, ecological planning and social inclusion.The missions of the NRRP are as follows:

Mission 1: Digitalization, innovation, competitiveness, culture and tourism

Mission 2: Green revolution and ecological transition

Mission 3: Infrastructure for sustainable mobility

Mission 4: Education and research

Mission 5: Cohesion and inclusion

Mission 6: Health.

With the aim of encouraging the debate on the use of sustainability indicators for monitoring the progress of the PNRR, a mapping of the correspondences between the 17 Sustainable Development Goals and the 6 Missions provided for by the NRRP is proposed (Fig. 1). In this way it is possible to identify the SDGs indicators that can be useful tools for achieving the missions of the NRRP.Figure 1Relationships between SDGs indicators and NRRP missions.Full size imageOf particular interest for the purposes of our work is Mission 2 (Green Revolution and Ecological Transition) of NRRP. It provides for investments and reforms for the circular economy and to improve waste management, strengthen separate collection infrastructure and modernize or develop new waste treatment plants. Substantial tax incentives are provided to increase the energy efficiency of buildings, to achieve progressive decarbonization, to increase the use of renewable energy sources. In addition, the Mission devotes resources to enhancing the capacity of electricity grids, their reliability, security, and flexibility (Smart Grid) and water infrastructure. The Mission also includes the issues of territorial security, with prevention and restoration interventions in the face of significant hydrogeological risks, the protection of green areas and biodiversity, and those related to the elimination of water and soil pollution, and the availability of water resources.The main components of this mission are:

M2C1: Circular economy and sustainable agriculture

M2C2: Renewable energy, hydrogen, grid, and sustainable mobility

M2C3: Energy efficiency and upgrading of buildings

M2C4: Protection of land and water resources.

The analysis of Mission 2 (Green Revolution and Ecological Transition) finds ample space in the SDGs creating important interconnections between the different indicators present in the individual Goals and the objectives of the Mission itself.The SDGs indicators to support the NRRPThe SDGs indicators selected for the analysis of Mission 2 (Green Revolution and Ecological Transition) of the NRRP, are descripted in Table 1. We considered 13 indicators, selected from Goals 2, 6, 7, 11, 12 and 15 which may be of significant interest for the achievement of Mission 2. These indicators will then be attributed to the individual components of the mission.Table 1 Goal, indicators, measures e source of SDGs data.Full size tableThe indicators were chosen based on their relevance to the objectives of the mission and on the availability of data on a regional basis. For each main component we can use the following indicators:

M2C1: Circular economy and sustainable agriculture:

– Share of utilized agricultural area invested by organic crops

– Growth rate of organic crops

– Delivery of municipal waste to landfill.

– Separate waste collection

M2C2: Renewable energy, hydrogen, grid and sustainable mobility:

M2C3: Energy efficiency and upgrading of buildings

M2C4: Protection of land and water resources

– Irregularities in water distribution

– Sealing and soil consumption per capita

– Soil sealing from artificial cover

– Fragmentation of the natural and agricultural territory

– Incidence of urban green areas on the urbanized surface of cities.

The SDGs indicators at the level of territorial distribution in ItalyWe carry out a first analysis by territorial distribution for the different sets of main components of Mission 2.From a first analysis of the M2C1 indicators (Circular Economy and Sustainable Agriculture) it emerges that the share of agricultural area destined for organic crops is greater, especially in the Center and in the South of Italy. In 2019, the extent of organic farming in Italy reached 15.8% of the utilized agricultural area, almost double the EU average. However, the annual growth rate of the areas converted to organic farming or in the process of conversion (+ 1.8%) is the lowest since 2012 and is negative in the South, where for the second consecutive year there is a decrease (− 2.1% in the 2-year period 2017–2019). The dynamics of organic farming is an index of the spread of sustainable agricultural practices, which must be accompanied by measures that also consider the pressure on the environment generated by agriculture (Table 2).Table 2 M2C1 indicators—Circular economy and sustainable agriculture by territorial distribution (year 2019).Full size tableAlso, in the Central and Southern Italy area there is the greatest delivery of waste to landfills. Waste cycle management is crucial for living conditions and global health. The share of municipal waste landfilled is steadily decreasing at national level. In 2019, in fact, the part sent to landfill is equal to 20.9% of the total, down compared to the previous year (21.5%). The separate collection of municipal waste represents a further important step in view of the objective of reducing the amount of waste returned to the environment and, more specifically, of the delivery of waste to landfills. The 18.5 million tons of differentiated RU in 2019 represent 61.3% of national production, a share almost doubled compared to ten years ago and up from last year by 3.1 percentage points. Despite the evident progress, Italy is still marked by a considerable delay compared to the regulatory objectives, having not yet reached, in 2019, the target of 65% of separate collection planned for 2012. Critical issues are also observed in relation to the substantial territorial gaps, which disadvantage the Center and the South compared to the North, despite the distances have been reduced in recent years.
Regarding the M2C2 Mission (Renewable Energy, Hydrogen, Network and Sustainable Mobility), national and international energy policies have been committed for years to the enhancement of renewable energy sources, with the aim of decarbonizing the economy and guaranteeing the commitments made in the field of climate change. In 2019, one year after the expiry of the objectives of the European Union’s Climate-Energy Package, fourteen Member States, including Italy, exceeded the target assigned at national level. In Italy, the overall share of energy from renewable sources in gross final consumption (CFL) of energy, equal to 18.2% (Table 3), a percentage slightly lower than the average of the EU27 (19.7%), is placed for the sixth consecutive year above the 17% target set for our country. However, for Italy to achieve the ambitious programs defined by the 2020 National Integrated Energy and Climate Plan, which set a 30% target for renewables by 2030, a further boost to production from renewable sources is necessary. The resources introduced by the National Recovery and Resilience Plan (NRRP) to achieve the “green revolution and ecological transaction” include significant investments in the energy field, focusing, among other components, on a further strengthening of the Sources from Renewable energy (FER).Table 3 M2C2 indicators—Renewable energy, hydrogen, network and sustainable mobility by territorial distribution (year 2019).Full size tableThe M2C3 Mission (Energy Efficiency and Upgrading of Buildings) devotes resources to enhancing the capacity of electricity grids, their reliability, safety, and flexibility (Smart Grid). Consistent with the objectives of reducing energy consumption pursued by European policies, the Italian figure for 2019 confirms the process of reducing Italian energy intensity, which marks a further contraction of 1.3%, reaching an overall negative balance compared to the last decade of 11.8%, with an average annual rate of change of − 1.2% (Table 4). The reduction in energy intensity is largely attributable to the effect of the measures in favor of energy efficiency, which, between 2011 and 2019, resulted in energy savings of 12 Mtoe/year, equal to 77% of the 2020 target set by the National Action Plan for Energy Efficiency 2017. A further acceleration of energy efficiency is expected, in the coming years, because of the investment plan envisaged by the NRRP, also linked to the redevelopment of the public and private building stock. At the sectoral level, the reduction in energy intensity is driven by improvements in industry, which, despite the slight increase in the last year, in 2019, with 92 toes per million euros, shows a decrease compared to 2009 of 17%, with an average annual rate of change of − 1.8%.Table 4 M2C3 indicators—Energy efficiency and requalification of buildings by territorial distribution (year 2019).Full size tableThe M2C4 Mission (Protection of the territory and water resources) also includes the issues of territorial safety, with prevention and recovery interventions, the protection of green areas and those related to the elimination of water and soil pollution.Italy is among the European countries of the Mediterranean area that use groundwater, springs and wells the most; these represent the most important resource of fresh water for drinking water use on the Italian territory (84.8% of the total withdrawn). The efficiency of municipal drinking water distribution networks has been steadily deteriorating since 2008 for more than half of the regions. The share of families who complain of irregularities in the water supply service in their home is stable (equal to 8.6% in 2019) with more accentuated values in the Center and South of Italy (Table 5).Table 5 M2C4 indicators—Protection of land and water resources by territorial distribution (year 2019).Full size tableLand degradation, understood as loss of ecological functionality, is monitored through the dynamics of land consumption, which Italy has committed to zero by 2030 with the National Strategy for Sustainable Development (2017). The “consumed” soil is that occupied by urbanization and made impermeable by artificial roofing (soil sealing). Excessive fragmentation of open spaces, however, is also a factor of degradation, since the barriers made up of buildings and infrastructures interrupt the continuity of ecosystems, making even unoccupied but not large enough spaces ecologically inert and unproductive. Moreover, in a fragile territory such as Italy, land consumption is also a significant factor of hydrogeological risk and deterioration of the landscape. The index of sealing and land consumption per capita in 2019 increases for the fifth consecutive year, resulting in 357 m2 per inhabitant. The soil sealed by artificial covers is equal to 7.1% of the national territory (8.5% in the North, 6.7% in the Center, 5.9% in the South).According to Ispra estimates, 44.3% of Italy’s natural and agricultural land has a high or very high degree of fragmentation. A joint representation of the variations in fragmentation and soil sealing over the last two years summarizes recent trends in land consumption and their impact on the environment and landscape.A further objective for 2030 is to provide universal access to safe, inclusive, and accessible public green spaces, for women and children, the elderly, and people with disabilities. In 2019 the incidence of urban green areas on the urbanized surface of cities is equal to 8.5% in Italy with slightly higher values in the North and less elevated in the South. More

Last year, female researchers received Aus$95 million less than male researchers in investigator grants from the Australian National Health and Medical Research Council.Credit: Lisa Maree Williams/Getty

Australian research agency introduces ‘Game-changing’ gender quotasIn an attempt to achieve gender equity, Australia’s leading health and medical research funding organization plans to award half of its research grants for its largest funding programme to women and non-binary applicants, starting next year.The National Health and Medical Research Council (NHMRC) announced the move last month. It will apply to researchers at the mid-career and senior level applying for the agency’s investigator grants, which fund research and salaries. Grants will also be fixed at Aus$400,000 (US$252,000) per year for five years. Many countries struggle to achieve gender equity in research funding, and the NHMRC will be one of the first agencies to introduce gender quotas at this scale, say researchers.“It’s game-changing,” says Anna-Maria Arabia, chief executive of the Australian Academy of Science in Canberra. The plan “directly removes a barrier that’s historically led to attrition in the research workforce and has led to the significant under-representation of women at senior levels”, she says.In 2021, 254 investigator grants were awarded, worth Aus$400 million in total. But when two researchers in Melbourne reviewed the data, they found that men had received 23% more of the grants, worth an extra Aus$95 million, than had women. There was an outcry from researchers. This year, the agency conducted its own review of investigator-grant outcomes from the past three years and found that the biggest gap was among the most senior researchers. A subsequent discussion paper and consultations with researchers informed the latest decision.The NHMRC has been working for a decade to address gender inequity in its grant funding. For example, in 2017, it introduced ‘structural priority funding’, which reserves extra money — around 8% of the overall grant budget — for high-quality ‘near-miss’ research applications led by women.But this did not address the gender imbalance among the most established researchers. In 2021, only 20% of the applicants in this group were women.The council will be looking to see whether awarding equal numbers of grants by gender leads to an increase in the number of senior women applying for leadership grants.No-fishing zone boosts tuna catch ratesLarge no-fishing areas can drive the recovery of commercially valuable fish species, a study suggests. Researchers examined ten years’ worth of fisheries data from the vicinity of Papahānaumokuākea Marine National Monument, a 1.5-million-square-kilometre protected area off the northwestern Hawaiian islands.They found that after the area expanded in 2016, catch rates — the number of fish caught for every 1,000 hooks deployed — went up (S. Medoff et al. Science 378, 313–316; 2022). The increases were greater the closer the boats were to the no-fishing zone. At up to 100 nautical miles, the catch rate for yellowfin tuna (Thunnus albacares) increased by 54%, and that for bigeye tuna (Thunnus obesus) by 12%. The size of the protected area probably played a part in the positive effects, as did the fact that it runs from west to east, allowing tropical fish to move in their preferred temperature range without leaving the zone.

SOURCE: S. Medoff et al. More

Schimper, A. F. W. Plant Geography upon a Physiological Basis (Clarendon Press, 1903).Alexander, J. M., Diez, J. M. & Levine, J. M. Novel competitors shape species’ responses to climate change. Nature 525, 515–518 (2015).Article 
ADS 
CAS 
PubMed 

Google Scholar 
HilleRisLambers, J., Harsch, M. A., Ettinger, A. K., Ford, K. R. & Theobald, E. J. How will biotic interactions influence climate change-induced range shifts? Ann. N. Y. Acad. Sci. 1297, 112–125 (2013).PubMed 

Google Scholar 
Chesson, P. Mechanisms of maintenance of species diversity. Annu. Rev. Ecol. Syst. 31, 343–366 (2000).Article 

Google Scholar 
Loarie, S. R., Weiss, S. B., Hamilton, H., Branciforte, R. & Kraft, N. J. B. The geography of climate change: implications for conservation biogeography. Divers. Distrib. 16, 476–487 (2010).Article 

Google Scholar 
Callaway, R. M. et al. Positive interactions among alpine plants increase with stress. Nature 417, 844–848 (2002).Article 
ADS 
CAS 
PubMed 

Google Scholar 
Dybzinski, R. & Tilman, D. Resource use patterns predict long‐term outcomes of plant competition for nutrients and light. Am. Nat. 170, 305–318 (2007).Article 
PubMed 

Google Scholar 
Hautier, Y., Niklaus, P. A. & Hector, A. Competition for light causes plant biodiversity loss after eutrophication. Science 324, 636–638 (2009).Article 
ADS 
CAS 
PubMed 

Google Scholar 
Levine, J. M. & HilleRisLambers, J. The importance of niches for the maintenance of species diversity. Nature 461, 254–257 (2009).Article 
ADS 
CAS 
PubMed 

Google Scholar 
Kraft, N. J. B., Godoy, O. & Levine, J. M. Plant functional traits and the multidimensional nature of species coexistence. Proc. Natl Acad. Sci. USA 112, 797–802 (2015).Article 
ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Knapp, A. K. et al. Rainfall variability, carbon cycling, and plant species diversity in a mesic grassland. Science 298, 2202–2205 (2002).Article 
ADS 
CAS 
PubMed 

Google Scholar 
Sandel, B. et al. Contrasting trait responses in plant communities to experimental and geographic variation in precipitation. New Phytol. 188, 565–575 (2010).Article 
PubMed 

Google Scholar 
Esch, E. H., Ashbacher, A. C., Kopp, C. W. & Cleland, E. E. Competition reverses the response of shrub seedling mortality and growth along a soil moisture gradient. J. Ecol. 106, 2096–2108 (2018).Article 

Google Scholar 
Alon, M. & Sternberg, M. Effects of extreme drought on primary production, species composition and species diversity of a Mediterranean annual plant community. J. Veg. Sci. 30, 1045–1061 (2019).Article 

Google Scholar 
Chesson, P. Updates on mechanisms of maintenance of species diversity. J. Ecol. 106, 1773–1794 (2018).Article 

Google Scholar 
Barabás, G., D’Andrea, R. & Stump, S. M. Chesson’s coexistence theory. Ecol. Monogr. 88, 277–303 (2018).Article 

Google Scholar 
Ellner, S. P., Snyder, R. E., Adler, P. B. & Hooker, G. An expanded modern coexistence theory for empirical applications. Ecol. Lett. 22, 3–18 (2019).Article 
ADS 
PubMed 

Google Scholar 
Adler, P., Hillerislambers, J. & Levine, J. A niche for neutrality. Ecol. Lett. 10, 95–104 (2007).Article 
PubMed 

Google Scholar 
Germain, R. M., Mayfield, M. M. & Gilbert, B. The ‘filtering’ metaphor revisited: competition and environment jointly structure invasibility and coexistence. Biol. Lett. 14, 20180460 (2018).Article 
PubMed 
PubMed Central 

Google Scholar 
Pau, S. et al. Predicting phenology by integrating ecology, evolution and climate science. Glob. Change Biol. 17, 3633–3643 (2011).Article 
ADS 

Google Scholar 
Fargione, J. & Tilman, D. Niche differences in phenology and rooting depth promote coexistence with a dominant C4 bunchgrass. Oecologia 143, 598–606 (2005).Article 
ADS 
PubMed 

Google Scholar 
Godoy, O., Kraft, N. J. B. & Levine, J. M. Phylogenetic relatedness and the determinants of competitive outcomes. Ecol. Lett. 17, 836–844 (2014).Article 
PubMed 

Google Scholar 
Díaz, S. et al. The global spectrum of plant form and function. Nature 529, 167–171 (2016).Article 
ADS 
PubMed 

Google Scholar 
Kunstler, G. et al. Plant functional traits have globally consistent effects on competition. Nature 529, 204–207 (2016).Article 
ADS 
CAS 
PubMed 

Google Scholar 
Diffenbaugh, N. S., Swain, D. L. & Touma, D. Anthropogenic warming has increased drought risk in California. Proc. Natl Acad. Sci. USA 112, 3931–3936 (2015).Article 
ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Swain, D. L., Langenbrunner, B., Neelin, J. D. & Hall, A. Increasing precipitation volatility in twenty-first-century California. Nat. Clim. Change 8, 427–433 (2018).Article 
ADS 

Google Scholar 
Chesson, P. Geometry, heterogeneity and competition in variable environments. Phil. Trans. R. Soc. Lond. B 330, 165–173 (1990).Article 
ADS 

Google Scholar 
Aronson, J., Kigel, J., Shmida, A. & Klein, J. Adaptive phenology of desert and Mediterranean populations of annual plants grown with and without water stress. Oecologia 89, 17–26 (1992).Article 
ADS 
CAS 
PubMed 

Google Scholar 
Santa Barbara County Public Works water resources hydrology: historical rainfall data: daily and monthly rainfall. County of Santa Barbara http://www.countyofsb.org/pwd/water/downloads/hydro/421dailys.pdf (2019).Kandlikar, G. S., Kleinhesselink, A. R. & Kraft, N. J. B. Functional traits predict species responses to environmental variation in a California grassland annual plant community. J. Ecol. 110, 833–844 (2022).Article 
CAS 

Google Scholar 
Cleland, E. E. et al. Sensitivity of grassland plant community composition to spatial vs. temporal variation in precipitation. Ecology 94, 1687–1696 (2013).Article 
PubMed 

Google Scholar 
Usinowicz, J. et al. Temporal coexistence mechanisms contribute to the latitudinal gradient in forest diversity. Nature 550, 105–108 (2017).Article 
ADS 
CAS 
PubMed 

Google Scholar 
Kandlikar, G. S., Johnson, C. A., Yan, X., Kraft, N. J. B. & Levine, J. M. Winning and losing with microbes: how microbially mediated fitness differences influence plant diversity. Ecol. Lett. 22, 1178–1191 (2019).PubMed 

Google Scholar 
Kleinhesselink, A. R., Kraft, N. J. B., Pacala, S. W. & Levine, J. M. Detecting and interpreting higher order interactions in ecological communities. Ecol. Lett. 25, 1604–1617 (2022).Article 
PubMed 

Google Scholar 
Saavedra, S. et al. A structural approach for understanding multispecies coexistence. Ecol. Monogr. 87, 470–486 (2017).Article 

Google Scholar 
Levine, J. I., Levine, J. M., Gibbs, T. & Pacala, S. W. Competition for water and species coexistence in phenologically structured annual plant communities. Ecol. Lett. 25, 1110–1125 (2022).Article 
PubMed 

Google Scholar 
Farrior, C. E. et al. Resource limitation in a competitive context determines complex plant responses to experimental resource additions. Ecology 94, 2505–2517 (2013).Article 
PubMed 

Google Scholar 
Harrison, S., Grace, J. B., Davies, K. F., Safford, H. D. & Viers, J. H. Invasion in a diversity hotspot: exotic cover and native richness in the Californian serpentine flora. Ecology 87, 695–703 (2006).Article 
PubMed 

Google Scholar 
Pérez-Harguindeguy, N. et al. New handbook for standardised measurement of plant functional traits worldwide. Aust. J. Bot. 61, 167–234 (2013).Article 

Google Scholar 
Godoy, O. & Levine, J. M. Phenology effects on invasion success: insights from coupling field experiments to coexistence theory. Ecology 95, 726–736 (2014).Article 
PubMed 

Google Scholar  More

Dargie, G. C. et al. Age, extent and carbon storage of the central Congo Basin peatland complex. Nature 542, 86–90 (2017).Article 
ADS 
CAS 
PubMed 

Google Scholar 
Crezee, B. et al. Mapping peat thickness and carbon stocks of the central Congo Basin using field data. Nat. Geosci. 15, 639–644 (2022).Runge, J. in Large Rivers (ed. Gupta, A.) 293–309 (Wiley, 2008).Davenport, I. J. et al. First evidence of peat domes in the Congo Basin using LiDAR from a fixed-wing drone. Remote Sens. 12, 2196 (2020).Article 
ADS 

Google Scholar 
Dargie, G. C. et al. Congo Basin peatlands: threats and conservation priorities. Mitig. Adapt. Strateg. Glob. Chang. 24, 669–686 (2018).Young, D. M. et al. Misinterpreting carbon accumulation rates in records from near-surface peat. Sci. Rep. 9, 17939 (2019).Article 
ADS 
PubMed 
PubMed Central 

Google Scholar 
Young, D. M., Baird, A. J., Gallego-Sala, A. V. & Loisel, J. A cautionary tale about using the apparent carbon accumulation rate (aCAR) obtained from peat cores. Sci. Rep. 11, 9547 (2021).Article 
ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Sebag, D. et al. Monitoring organic matter dynamics in soil profiles by ‘Rock-Eval pyrolysis’: bulk characterization and quantification of degradation. Eur. J. Soil Sci. 57, 344–355 (2006).Article 
CAS 

Google Scholar 
Sebag, D. et al. Dynamics of soil organic matter based on new Rock-Eval indices. Geoderma 284, 185–203 (2016).Article 
ADS 
CAS 

Google Scholar 
Girkin, N. T. et al. Spatial variability of organic matter properties determines methane fluxes in a tropical forested peatland. Biogeochemistry 142, 231–245 (2019).Article 
CAS 
PubMed 

Google Scholar 
Dargie, G. C. Quantifying and Understanding the Tropical Peatlands of the Central Congo Basin. PhD thesis, Univ. Leeds (2015).Spiker, E. C. & Hatcher, P. G. Carbon isotope fractionation of sapropelic organic matter during early diagenesis. Org. Geochem. 5, 283–290 (1984).Article 
CAS 

Google Scholar 
Chave, J. et al. Regional and seasonal patterns of litterfall in tropical South America. Biogeosciences 7, 43–55 (2010).Article 
ADS 

Google Scholar 
Dommain, R. et al. Forest dynamics and tip-up pools drive pulses of high carbon accumulation rates in a tropical peat dome in Borneo (Southeast Asia). J. Geophys. Res. 120, 617–640 (2015).Article 
CAS 

Google Scholar 
Wotzka, H.-P. in Grundlegungen: Beiträge zur europäischen und afrikanischen Archäologie fűr Manfred K. H. Eggert (ed. Wotzka, H.-P.) 271–289 (Francke, 2006).Saulieu, G. D. et al. Archaeological evidence for population rise and collapse between ~2500 and ~500 cal. yr BP in Western Central Africa. Afr. Archéol. Arts 17, 11–32 (2021).
Google Scholar 
Sachse, D. et al. Molecular paleohydrology: interpreting the hydrogen-isotopic composition of lipid biomarkers from photosynthesizing organisms. Annu. Rev. Earth Planet. Sci. 40, 221–249 (2012).Article 
ADS 
CAS 

Google Scholar 
Collins, J. A. et al. Estimating the hydrogen isotopic composition of past precipitation using leaf-waxes from western Africa. Quat. Sci. Rev. 65, 88–101 (2013).Article 
ADS 

Google Scholar 
Schefuß, E., Schouten, S. & Schneider, R. R. Climatic controls on central African hydrology during the past 20,000 years. Nature 437, 1003–1006 (2005).Article 
ADS 
PubMed 

Google Scholar 
Kelly, T. J. et al. The vegetation history of an Amazonian domed peatland. Palaeogeogr. Palaeoclimatol. Palaeoecol. 468, 129–141 (2017).Article 

Google Scholar 
Swindles, G. T. et al. Ecosystem state shifts during long-term development of an Amazonian peatland. Global Change Biol. 24, 738–757 (2018).Article 
ADS 

Google Scholar 
Dommain, R., Couwenberg, J. & Joosten, H. Development and carbon sequestration of tropical peat domes in south-east Asia: links to post-glacial sea-level changes and Holocene climate variability. Quat. Sci. Rev. 30, 999–1010 (2011).Article 
ADS 

Google Scholar 
Lottes, A. L. & Ziegler, A. M. World peat occurrence and the seasonality of climate and vegetation. Palaeogeogr. Palaeoclimatol. Palaeoecol. 106, 23–37 (1994).Article 

Google Scholar 
Moutsamboté, J. M. Ecological, Phytogeographic and Phytosociological Study of Northern Congo (Plateaus, Bowls, Likouala and Sangha). PhD thesis, Univ. Marien Ngouabi (2012).Dingman, S. L. Fluvial Hydrology (W. H. Freeman, 1984).Swindles, G. T., Morris, P. J., Baird, A. J., Blaauw, M. & Plunkett, G. Ecohydrological feedbacks confound peat-based climate reconstructions. Geophys. Res. Lett. 39, L11401 (2012).Article 
ADS 

Google Scholar 
Morris, P. J., Baird, A. J., Young, D. M. & Swindles, G. T. Untangling climate signals from autogenic changes in long-term peatland development. Geophys. Res. Lett. 42, 10,788–10,797 (2015).Article 

Google Scholar 
Young, D. M., Baird, A. J., Morris, P. J. & Holden, J. Simulating the long-term impacts of drainage and restoration on the ecohydrology of peatlands. Water Resour. Res. 53, 6510–6522 (2017).Article 
ADS 

Google Scholar 
Weldeab, S., Lea, D. W., Schneider, R. R. & Andersen, N. Centennial scale climate instabilities in a wet early Holocene West African monsoon. Geophys. Res. Lett. 34, L24702 (2007).Article 
ADS 

Google Scholar 
Collins, J. A. et al. Rapid termination of the African Humid Period triggered by northern high-latitude cooling. Nat. Commun. 8, 1372 (2017).Article 
ADS 
PubMed 
PubMed Central 

Google Scholar 
Garcin, Y. et al. Early anthropogenic impact on Western Central African rainforests 2,600 y ago. Proc. Natl. Acad. Sci. USA 115, 3261–3266 (2018).Article 
ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Vincens, A. et al. Changement majeur de la végétation du lac Sinnda (vallée du Niari, Sud-Congo) consécutif à l’assèchement climatique holocène supérieur: apport de la palynologie. C. R. Acad. Sci. Paris Sér. II 318, 1521–1526 (1994).
Google Scholar 
Elenga, H. et al. Diagramme pollinique holocène du lac Kitina (Congo): mise en évidence de changements paléobotaniques et paléoclimatiques dans le massif forestier du Mayombe. C. R. Acad. Sci. Paris Sér. II 323, 403–410 (1996).CAS 

Google Scholar 
Ngomanda, A., Neumann, K., Schweizer, A. & Maley, J. Seasonality change and the third millennium BP rainforest crisis in southern Cameroon (Central Africa). Quat. Res. 71, 307–318 (2009).Article 

Google Scholar 
Maley, J. et al. Late Holocene forest contraction and fragmentation in central Africa. Quat. Res. 89, 43–59 (2018).Article 

Google Scholar 
Bayon, G. et al. Intensifying weathering and land use in Iron Age Central Africa. Science 335, 1219–1222 (2012).Article 
ADS 
CAS 
PubMed 

Google Scholar 
Giresse, P., Maley, J. & Chepstow-Lusty, A. Understanding the 2500 yr BP rainforest crisis in West and Central Africa in the framework of the Late Holocene: pluridisciplinary analysis and multi-archive reconstruction. Global Planet. Change 192, 103257 (2020).Article 

Google Scholar 
Schefuß, E. et al. Hydrologic control of carbon cycling and aged carbon discharge in the Congo River basin. Nat. Geosci. 9, 687–690 (2016).Article 
ADS 

Google Scholar 
Hoyt, A. M., Chaussard, E., Seppalainen, S. S. & Harvey, C. F. Widespread subsidence and carbon emissions across Southeast Asian peatlands. Nat. Geosci. 13, 435–440 (2020).Article 
ADS 
CAS 

Google Scholar 
Deshmukh, C. S. et al. Conservation slows down emission increase from a tropical peatland in Indonesia. Nat. Geosci. 14, 484–490 (2021).Article 
ADS 
CAS 

Google Scholar 
Köhler, P., Nehrbass-Ahles, C., Schmitt, J., Stocker, T. F. & Fischer, H. A 156 kyr smoothed history of the atmospheric greenhouse gases CO2, CH4, and N2O and their radiative forcing. Earth Syst. Sci. Data 9, 363–387 (2017).Article 
ADS 

Google Scholar 
Jiang, Y. et al. Widespread increase of boreal summer dry season length over the Congo rainforest. Nat. Clim. Change 9, 617–622 (2019).Article 

Google Scholar 
Cook, K. H., Liu, Y. & Vizy, E. K. Congo Basin drying associated with poleward shifts of the African thermal lows. Clim. Dyn. 54, 863–883 (2020).Article 

Google Scholar 
Bennett, A. C. et al. Resistance of African tropical forests to an extreme climate anomaly. Proc. Natl. Acad. Sci. USA 118, e2003169118 (2021).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Sullivan, M. J. P. et al. Long-term thermal sensitivity of Earth’s tropical forests. Science 368, 869–874 (2020).Article 
ADS 
CAS 
PubMed 

Google Scholar 
García-Palacios, P. et al. Evidence for large microbial-mediated losses of soil carbon under anthropogenic warming. Nat. Rev. Earth Environ. 2, 585–585 (2021).Article 
ADS 

Google Scholar 
Cobb, A. R. et al. How temporal patterns in rainfall determine the geomorphology and carbon fluxes of tropical peatlands. Proc. Natl. Acad. Sci. USA 114, E5187–E5196 (2017).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Feng, X., Porporato, A. & Rodriguez-Iturbe, I. Changes in rainfall seasonality in the tropics. Nat. Clim. Change 3, 811–815 (2013).Article 
ADS 

Google Scholar 
Karger, D. N. et al. Climatologies at high resolution for the earth’s land surface areas. Sci. Data 4, 170122 (2017).Article 
PubMed 
PubMed Central 

Google Scholar 
Xu, J. R., Morris, P. J., Liu, J. G. & Holden, J. PEATMAP: refining estimates of global peatland distribution based on a meta-analysis. Catena 160, 134–140 (2018).Article 

Google Scholar 
Paillard, D., Labeyrie, L. & Yiou, P. Macintosh program performs time-series analysis. Eos Trans. AGU 77, 379 (1996).Article 
ADS 

Google Scholar 
Blaauw, M. & Christen, J. A. Flexible paleoclimate age–depth models using an autoregressive gamma process. Bayesian Anal. 6, 457–474 (2011).Article 
MathSciNet 
MATH 

Google Scholar 
Blaauw, M. et al. rbacon: age–depth modelling using Bayesian statistics. R package version 2.5.7 (2021); https://cran.r-project.org/web/packages/rbacon/index.html.Hogg, A. G. et al. SHCal20 Southern Hemisphere calibration, 0–55,000 years cal BP. Radiocarbon 62, 759–778 (2020).Article 
CAS 

Google Scholar 
Reimer, P. et al. The IntCal20 Northern Hemisphere radiocarbon age calibration curve (0–55 kcal BP). Radiocarbon 62, 725–757 (2020).Article 
CAS 

Google Scholar 
Reuter, H., Gensel, J., Elvert, M. & Zak, D. Evidence for preferential protein depolymerization in wetland soils in response to external nitrogen availability provided by a novel FTIR routine. Biogeosciences 17, 499–514 (2020).Article 
ADS 
CAS 

Google Scholar 
Kuhry, P. & Vitt, D. H. Fossil carbon/nitrogen ratios as a measure of peat decomposition. Ecology 77, 271–275 (1996).Article 

Google Scholar 
Hornibrook, E. R. C., Longstaffe, F. J. & Fyfe, W. S. Evolution of stable carbon isotope compositions for methane and carbon dioxide in freshwater wetlands and other anaerobic environments. Geochim. Cosmochim. Acta 64, 1013–1027 (2000).Article 
ADS 
CAS 

Google Scholar 
Broder, T., Blodau, C., Biester, H. & Knorr, K. H. Peat decomposition records in three pristine ombrotrophic bogs in southern Patagonia. Biogeosciences 9, 1479–1491 (2012).Article 
ADS 
CAS 

Google Scholar 
Biester, H., Knorr, K. H., Schellekens, J., Basler, A. & Hermanns, Y. M. Comparison of different methods to determine the degree of peat decomposition in peat bogs. Biogeosciences 11, 2691–2707 (2014).Article 
ADS 
CAS 

Google Scholar 
Leifeld, J., Klein, K. & Wüst-Galley, C. Soil organic matter stoichiometry as indicator for peatland degradation. Sci. Rep. 10, 7634 (2020).Article 
ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Hodgkins, S. B. et al. Tropical peatland carbon storage linked to global latitudinal trends in peat recalcitrance. Nat. Commun. 9, 3640 (2018).Article 
ADS 
PubMed 
PubMed Central 

Google Scholar 
Chimner, R. A. & Ewel, K. C. A tropical freshwater wetland: II. Production, decomposition, and peat formation. Wetlands Ecol. Manage. 13, 671–684 (2005).Article 

Google Scholar 
Lafargue, E., Marquis, F. & Pillot, D. Rock-Eval 6 applications in hydrocarbon exploration, production, and soil contamination studies. Oil Gas Sci. Technol. 53, 421–437 (1998).CAS 

Google Scholar 
Behar, F., Beaumont, V. & Penteado, H. L. D. Rock-Eval 6 technology: performances and developments. Oil Gas Sci. Technol. 56, 111–134 (2001).Article 
CAS 

Google Scholar 
Disnar, J. R., Guillet, B., Keravis, D., Di-Giovanni, C. & Sebag, D. Soil organic matter (SOM) characterization by Rock-Eval pyrolysis: scope and limitations. Org. Geochem. 34, 327–343 (2003).Article 
CAS 

Google Scholar 
Marzi, R., Torkelson, B. E. & Olson, R. K. A revised carbon preference index. Org. Geochem. 20, 1303–1306 (1993).Article 
CAS 

Google Scholar 
Eglinton, G. & Hamilton, R. J. Leaf epicuticular waxes. Science 156, 1322–1334 (1967).Article 
ADS 
CAS 
PubMed 

Google Scholar 
Sauer, P. E., Eglinton, T. I., Hayes, J. M., Schimmelmann, A. & Sessions, A. L. Compound-specific D/H ratios of lipid biomarkers from sediments as a proxy for environmental and climatic conditions. Geochim. Cosmochim. Acta 65, 213–222 (2001).Article 
ADS 
CAS 

Google Scholar 
Waelbroeck, C. et al. Sea-level and deep water temperature changes derived from benthic foraminifera isotopic records. Quat. Sci. Rev. 21, 295–305 (2002).Article 
ADS 

Google Scholar 
Han, J. & Calvin, M. Hydrocarbon distribution of algae and bacteria, and microbiological activity in sediments. Proc. Natl. Acad. Sci. U.S.A. 64, 436–443 (1969).Article 
ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Nakagawa, T. et al. Dense-media separation as a more efficient pollen extraction method for use with organic sediment/deposit samples: comparison with the conventional method. Boreas 27, 15–24 (1998).Article 

Google Scholar 
Stone, B. C. A synopsis of the African Species of Pandanus. Ann. Missouri Bot. Gard. 60, 260–272 (1973).Article 

Google Scholar 
African Plant Database (version 3.4.0) (Conservatoire et Jardin Botaniques de la Ville de Genève and South African National Biodiversity Institute, accessed January 2022); http://africanplantdatabase.ch.Polhill, R. M., Nordal, I., Kativu, S. & Poulsen, A. D. Flora of Tropical East Africa 1st edn (CRC Press, 1997).Hawthorne, D. et al. Global Modern Charcoal Dataset (GMCD): a tool for exploring proxy-fire linkages and spatial patterns of biomass burning. Quat. Int. 488, 3–17 (2018).Article 

Google Scholar 
Stevenson, J. & Haberle, S. Macro Charcoal Analysis: A Modified Technique Used by the Department of Archaeology and Natural History. Palaeoworks Technical Paper No. 5 (PalaeoWorks, Department of Archaeology and Natural History, Research School of Pacific and Asian Studies, Australian National University, 2005).Tierney, J. E., Pausata, F. S. R. & deMenocal, P. B. Rainfall regimes of the Green Sahara. Sci. Adv. 3, e1601503 (2017).Article 
ADS 
PubMed 
PubMed Central 

Google Scholar 
Shanahan, T. M. et al. The time-transgressive termination of the African Humid Period. Nat. Geosci. 8, 140–144 (2015).Article 
ADS 
CAS 

Google Scholar 
Ladd, S. N. et al. Leaf wax hydrogen isotopes as a hydroclimate proxy in the Tropical Pacific. J. Geophys. Res. 126, e2020JG005891 (2021).
Google Scholar 
Dansgaard, W. Stable isotopes in precipitation. Tellus 16, 436–468 (1964).Article 
ADS 

Google Scholar 
Munksgaard, N. C. et al. Data Descriptor: daily observations of stable isotope ratios of rainfall in the tropics. Sci. Rep. 9, 14419 (2019).Article 
ADS 
PubMed 
PubMed Central 

Google Scholar 
Aggarwal, P. K. et al. Proportions of convective and stratiform precipitation revealed in water isotope ratios. Nat. Geosci. 9, 624–629 (2016).Article 
CAS 

Google Scholar 
Zwart, C. et al. The isotopic signature of monsoon conditions, cloud modes, and rainfall type. Hydrol. Processes 32, 2296–2303 (2018).Article 
ADS 

Google Scholar 
Jackson, B., Nicholson, S. E. & Klotter, D. Mesoscale convective systems over Western Equatorial Africa and their relationship to large-scale circulation. Mon. Weather Rev. 137, 1272–1294 (2009).Article 
ADS 

Google Scholar 
Sorí, R., Nieto, R., Vicente-Serrano, S. M., Drumond, A. & Gimeno, L. A Lagrangian perspective of the hydrological cycle in the Congo River basin. Earth Syst. Dynam. 8, 653–675 (2017).Article 
ADS 

Google Scholar 
International Atomic Energy Agency–World Meteorological Organization Global Network of Isotopes in Precipitation: The GNIP Database (accessed May 2020); https://nucleus.iaea.org/wiser/index.aspx.Sachse, D., Dawson, T. E. & Kahmen, A. Seasonal variation of leaf wax n-alkane production and δ2H values from the evergreen oak tree, Quercus agrifolia. Isotopes Environ. Health Stud. 51, 124–142 (2015).Article 
CAS 
PubMed 

Google Scholar 
Huang, X., Zhao, B., Wang, K., Hu, Y. & Meyers, P. A. Seasonal variations of leaf wax n-alkane molecular composition and δD values in two subtropical deciduous tree species: results from a three-year monitoring program in central China. Org. Geochem. 118, 15–26 (2018).Article 
CAS 

Google Scholar 
Botev, Z. I., Grotowski, J. F. & Kroese, D. P. Kernel density estimation via diffusion. Ann. Stat. 38, 2916–2957 (2010).Article 
MathSciNet 
MATH 

Google Scholar 
Albrecht, R., Sebag, D. & Verrecchia, E. Organic matter decomposition: bridging the gap between Rock-Eval pyrolysis and chemical characterization (CPMAS 13C NMR). Biogeochemistry 122, 101–111 (2015).Article 
CAS 

Google Scholar 
Matteodo, M. et al. Decoupling of topsoil and subsoil controls on organic matter dynamics in the Swiss Alps. Geoderma 330, 41–51 (2018).Article 
ADS 
CAS 

Google Scholar 
Malou, O. P. et al. The Rock-Eval® signature of soil organic carbon in arenosols of the Senegalese groundnut basin. How do agricultural practices matter? Agr. Ecosyst. Environ. 301, 107030 (2020).Article 
CAS 

Google Scholar 
Thoumazeau, A. et al. A new in-field indicator to assess the impact of land management on soil carbon dynamics. Geoderma 375, 114496 (2020).Article 
ADS 
CAS 

Google Scholar 
Cranwell, P. A. Diagenesis of free and bound lipids in terrestrial detritus deposited in a lacustrine sediment. Org. Geochem. 3, 79–89 (1981).Article 
CAS 

Google Scholar 
Ofiti, N. O. E. et al. Warming promotes loss of subsoil carbon through accelerated degradation of plant-derived organic matter. Soil Biol. Biochem. 156, 108185 (2021).Article 
CAS 

Google Scholar 
Stuiver, M. & Reimer, P. J. Extended 14C data base and revised CALIB 3.0 14C age calibration program. Radiocarbon 35, 215–230 (1993).Article 

Google Scholar  More

All the results were reported relative to the control, unless specifically stated to the contrary or for clarity.Growth of cucumber plants in response to different biofertilizersSoilThere was no significant difference in cucumber growth before microbial fertilizer was applied. However, some microbial fertilizers significantly increased cucumber height and stem diameter when they were applied within 4 weeks from when the seedlings were planted (Fig. 1a,b,e,f). In the second week, SHZ and SMF increased plant height by 11.2 and 9.5%, respectively. In the third week, S267, SBS, SBH, SM and SHZ increased plant height by 12.0, 13.8, 15.0, 20.5 and 26.9%, respectively (Fig. 1a). In the fourth and fifth weeks, some treatments significantly increased cucumber height. In the second and third weeks, S267 significantly increased stem diameter by 21.2 and 16.8% (Fig. 1b).Figure 1Effect of different biofertilizer treatments on the growth of cucumber seedlings produced in soil or substrate in a greenhouse. S267 = Trichoderma Strain 267 added to soil; SBH = Bacillus subtilis and T. harzianum biofertilizers added to soil; SBS = B. subtilis biofertilizer added to the soil; SM = Compound biofertilizer added to soil; SHZ = T. harzianum biofertilizer added to soil; SCK = Untreated soil. US267 = T.267 biofertilizer added to substrate; USBH = B. subtilis and T. harzianum biofertilizers added to substrate; USBS = B. subtilis biofertilizer added to substrate; USM = Compound biofertilizer added to substrate; USHZ = T. harzianum biofertilizer added to substrate; USCK = Untreated substrate.Full size imageOver the subsequent 5 weeks, some microbial fertilizer treatments decreased cucumber height and stem diameter (Fig. 1g,h).SubstrateThere were no significant differences in cucumber growth before microbial fertilizer microbial fertilizer was applied (Fig. 1c,d,g,h). However, within 4 weeks of applying the microbial fertilizer, each biofertilizer treatment applied significantly increased cucumber height (Fig. 1c). US267 and USHZ significantly increased cucumber height by 39.8–75.4% and 56.1–86.1%, respectively. US267, USM and USHZ significantly increased the stem diameter by 76.8–108.9%, 71.1–97.6% and 80.4–122.4%, respectively (Fig. 1d).Over the subsequent 5 weeks, US267, USM and USHZ treatments continued to significantly increase cucumber height and stem diameter (Fig. 1g,h).Changes in the taxonomic composition of soil-borne fungal pathogensSoilBiofertilizers application significantly reduced the taxonomic composition of soil-borne fungal pathogens at different times during the cucumber growth period (Tables 1 and 2). Fusarium spp. were significantly reduced (T, 63.8% reduction, P  More

Bobbink, R. et al. Ecol. Appl. 20, 30–59 (2010).Article 
PubMed 

Google Scholar 
Olff, H. & Ritchie, M. E. Trends Ecol. Evol. 13, 261–265 (1998).Article 
PubMed 

Google Scholar 
DeMalach, N., Zaady, E. & Kadmon, R. Ecol. Lett. 20, 60–69 (2017).Article 
PubMed 

Google Scholar 
Borer, E. T. et al. Nature 508, 517–520 (2014).Article 
PubMed 

Google Scholar 
Harpole, W. S. et al. Nature 537, 93–96 (2016).Article 
PubMed 

Google Scholar 
Eskelinen, A., Harpole, W. S., Jessen, M.-T., Virtanen, R. & Hautier, Y. Nature https://doi.org/10.1038/s41586-022-05383-9 (2022).Article 

Google Scholar 
Koerner, S. E. et al. Nature Ecol. Evol. 2, 1925–1932 (2018).Article 
PubMed 

Google Scholar 
Chesson, P. Annu. Rev. Ecol. Syst. 31, 343–366 (2000).Article 

Google Scholar 
Coley, P. D., Bryant, J. P. & Chapin, F. S. Science 230, 895–899 (1985).Article 
PubMed 

Google Scholar 
Hautier, Y., Niklaus, P. A. & Hector, A. Science 324, 636–638 (2009).Article 
PubMed 

Google Scholar 
Allan, E. & Crawley, M. J. Ecol. Lett. 14, 1246–1253 (2011).Article 
PubMed 

Google Scholar  More