Ecology

1.Zhang, X. et al. Managing nitrogen for sustainable development. Nature 528, 51–59 (2015).ADS 
CAS 
Article 

Google Scholar 
2.Erisman, J. W. et al. Nitrogen: Too Much of a Vital Resource. WWF Science Brief (WWF Netherlands, 2015); http://www.louisbolk.org/downloads/3005.pdf3.European Union Nitrogen Expert Panel. Nitrogen Use Efficiency (NUE)—An Indicator for the Utilization of Nitrogen in Agriculture and Food Systems (Wageningen University, 2015); http://wedocs.unep.org/handle/20.500.11822/12087
Google Scholar 
4.Cassman, K. G., Dobermann, A. & Walters, D. T. Agroecosystems, nitrogen-use efficiency, and nitrogen management. Ambio 31, 132–140 (2002).Article 

Google Scholar 
5.Harmsen, K. A comparison of the isotope-dilution and the difference method for estimating fertilizer nitrogen recovery fractions in crops. I. Plant uptake and loss of nitrogen. NJAS: Wageningen J. Life Sci. 50, 321–347 (2003).CAS 

Google Scholar 
6.Krupnik, T. J., Six, J., Ladha, J. K., Paine, M. J. & van Kessel, C. An Assessment of Fertilizer Nitrogen Recovery Efficiency by Grain Crops (Island Press, 2004).7.Jin, J. Changes in the efficiency of fertiliser use in China. J. Sci. Food Agric. 92, 1006–1009 (2012).CAS 
Article 

Google Scholar 
8.Zhang, F. et al. Nutrient use efficiencies of major cereal crops in china and measures for improvement. Acta Pedol. Sin. 45, 915–924 (2008) (in Chinese with English abstract).
Google Scholar 
9.Yu, F. & Shi, W. Nitrogen use efficiencies of major grain crops in China in recent 10 years. Acta Pedol. Sin. 52, 1311–1324 (2015) (in Chinese with English abstract).
Google Scholar 
10.Ju, X. & Christie, P. Calculation of theoretical nitrogen rate for simple nitrogen recommendations in intensive cropping systems: a case study on the North China Plain. Field Crops Res. 124, 450–458 (2011).Article 

Google Scholar 
11.Zhang, C., Ju, X., Powlson, D., Oenema, O. & Smith, P. Nitrogen surplus benchmarks for controlling N pollution in the main cropping systems of China. Environ. Sci. Technol. 53, 6678–6687 (2019).ADS 
CAS 
Article 

Google Scholar 
12.Powlson, D. S. et al. Comments on ‘Synthetic nitrogen fertilizers deplete soil nitrogen: a global dilemma for sustainable cereal production,’ by R.L. Mulvaney, S.A. Khan, and T.R. Ellsworth in the Journal of Environmental Quality, 2009 38: 2295–2314. J. Environ. Qual. 39, 749–752 (2010).CAS 
Article 

Google Scholar 
13.Yan, X. et al. Fertilizer nitrogen recovery efficiencies in crop production systems of China with and without consideration of the residual effect of nitrogen. Environ. Res. Lett. 9, 095002 (2014).ADS 
CAS 
Article 

Google Scholar 
14.Smith, C. J. & Chalk, P. M. The residual value of fertiliser N in crop sequences: an appraisal of 60 years of research using 15N tracer. Field Crops Res. 217, 66–74 (2018).Article 

Google Scholar 
15.Ju, X. et al. Reducing environmental risk by improving N management in intensive Chinese agricultural systems. Proc. Natl Acad. Sci. USA 106, 3041–3046 (2009).ADS 
CAS 
Article 

Google Scholar 
16.Wang, L. et al. Plastic mulching reduces nitrogen footprint of food crops in China: a meta-analysis. Sci. Total Environ. 748, 141479 (2020).ADS 
CAS 
Article 

Google Scholar 
17.Storkey, J. et al. Grassland biodiversity bounces back from long-term nitrogen addition. Nature 528, 401–404 (2015).ADS 
CAS 
Article 

Google Scholar 
18.Sebilo, M., Mayer, B., Nicolardot, B., Pinay, G. & Mariotti, A. Long-term fate of nitrate fertilizer in agricultural soils. Proc. Natl Acad. Sci. USA 110, 18185–18189 (2013).ADS 
CAS 
Article 

Google Scholar 
19.Raun, W. R. & Johnson, G. V. Improving nitrogen use efficiency for cereal production. Agron. J. 91, 357–363 (1999).Article 

Google Scholar 
20.Yan, M., Pan, G., Lavallee, J. M. & Conant, R. T. Rethinking sources of nitrogen to cereal crops. Glob. Change Biol. 26, 191–199 (2020).ADS 
Article 

Google Scholar  More

Preserving the biodiversity of rainforests, and limiting the effects of climate change on them, are global challenges that are recognized in international policy agreements and commitments1. The Central African rainforests are the second largest area of continuous rainforest in the world, after the Amazon rainforest. They store more carbon per hectare than does the Amazon and, on average, have a higher density of large trees2 than does any other continent — a feature attributed to the effects of big herbivores, particularly elephants, on the competition between trees for light, water and space3. Human activities, notably logging and over-hunting, facilitated by an expanding road network4, pose a serious threat to Central African rainforests and their value for society5.
Read the paper: Unveiling African rainforest composition and vulnerability to global change
How important is climate change, when acting on top of these existing human-generated pressures, for the future of these rainforests? Writing in Nature, Réjou-Méchain et al.6 provide an answer, and show that expected changes in climate in the region pose serious risks to the rainforests. Some forests in locations that have so far been relatively undisturbed by humans are more vulnerable to climate change than are those in areas already affected. For those areas already affected, the lower tree diversity as a consequence of human intervention reduces the capacity of forests to respond to climate change.The authors had access to an impressive commercial forest-inventory data set from 105 logging concessions (designated areas in which commercial operators are allowed to harvest timber), across five Central African countries. Analysing the abundance distribution of 6.1 million trees across 185,665 plots, the authors generate maps of floristically unique forest types — forests characterized by distinct sets of tree species. The spatial extent of these forest types is predominantly shaped by climate gradients, with further effects arising from human-induced pressures and variation in soil type.Previous research into links between species distribution and environmental variation used approaches such as ecological niche models, which are mechanistic or correlative models that relate field observations of species with environmental variables to predict habitat suitability. But the resulting predictions of how various species will be affected by climate change have been highly uncertain. This is mainly because of sampling bias, challenges such as spatial autocorrelation (locations closer together in space tend to be more similar to each other than do locations farther apart)7, and high variation in the responses of individual species to environmental drivers of distribution, including human-induced factors.
Satellites could soon map every tree on Earth
Réjou-Méchain et al. instead applied a modelling approach called supervised component generalized linear regression, which can identify the main predictive factors from an array of possibilities. This enabled them to detect distribution patterns at the scale of species assemblages (the set of species in a community), rather than focusing on individual species, and to model species and assemblage distribution in response to predictive variables, such as those of climate and human pressures, that potentially show linear dependencies on each other (collinearity). Collinearity is a challenge in niche models, and commonly occurs between climate variables, producing results that are unreliable and difficult to interpret.By combining their approach with a method called cluster analysis, Réjou-Méchain and colleagues show that the Central African rainforests are not a single bloc of forests, but instead encompass at least ten distinct forest types. This includes climate-driven types of forest such as the Atlantic coastal evergreen forest in Gabon, which harbours tree species that prefer cool, dark areas for the dry season. Another grouping, semi-deciduous forest, is found along the northern margin of the Central African region studied, and is characterized by species that can tolerate higher rates of water loss to the atmosphere (evapotranspiration).Such spatial variability in the species composition of Central African rainforests has many implications. For example, it will affect forest vulnerability to climate change, how warming might interact with human pressures to change biodiversity, and how it might affect the potential of these forests to mitigate the rise in atmospheric carbon. Global warming is projected to result in a drier, hotter environment in Central Africa, and previous research has suggested potentially dangerous implications for the fate of the rainforests there8. They might respond to limited water availability by opening canopies and becoming more prone to fires and less carbon dense. Using climate-model projections for the year 2085, Réjou-Méchain and colleagues conclude that the current climate niches associated with the ten forest types they have identified might disappear, or move to locations that would be difficult for the forests to reach through dispersal of tree seeds (by means such as wind and animals), and would hence become inaccessible.
Prioritizing where to restore Earth’s ecosystems
What do these findings mean for the future, and how can we manage the forests to minimize the threat from climate change? To provide an answer, Réjou-Méchain et al. looked at three components that characterize the vulnerability of forest communities to warming: their sensitivity, exposure and adaptive capacity. The authors conclude that some areas are more sensitive than others, which means that the dominant tree species in some forest types will be less able to tolerate environmental change than will those in other areas — for example, species in the northern and southwestern edge of the rainforest. Some areas, particularly those in the east, are expected to be more exposed to climate change than others. And some, especially areas under pressure from human activities, have lower local biodiversity, and might thus have less capacity to adapt compared with areas of greater biodiversity.Réjou-Méchain et al. report that the areas most vulnerable to climate change and predicted to be highly vulnerable to future human-induced pressures include forests in coastal Gabon, the Democratic Republic of the Congo (Fig. 1) and the northern margin of the domain studied. This finding suggests priority regions for targeted actions to protect forests from environmental changes. One such region under human pressure is in Cameroon and contains a forest group called degraded semi-deciduous forest. Protecting this type of forest offers a fast way of generating a carbon sink that will operate over a long time frame9. This is because it features long-lived ‘pioneer’ taxa, which colonize areas after a disturbance — whether natural or human induced. Such species frequently have a high requirement for light, and in this region have the potential to reach great heights in the absence of further disturbance.

Figure 1 | Kahuzi-Biéga National Park, Democratic Republic of the Congo. The road marks the boundary of this forest, which is one of the few remaining forest habitats for the eastern lowland gorilla (Gorilla beringei graueri). Rainforests are under threat from human-induced pressures, such as the deforestation visible outside this park. Réjou-Méchain et al.6 present maps of Central African rainforests that could aid conservation work.Credit: Adam Amir

As for elsewhere in sub-Saharan Africa, climate-change predictions for 2085 are uncertain for Central Africa. Réjou-Méchain and colleagues’ projections for the effects of human pressures for that year are probably underestimates, especially considering that road expansions are likely to continue to push the frontier of wilderness deeper into remote forest areas. Nevertheless, the research offers convincing evidence enabling land users and managers to take decisive actions. This could include efforts to protect the areas most vulnerable to climate change from human pressures, for example by setting up protection schemes, and actions that could include boosting forest connectivity in areas that have already experienced high levels of human pressure. To ensure the effectiveness of any interventions, it will be imperative to engage with local people in developing management solutions. Conservation and the sustainable management of rainforest carbon stocks have key roles in the reduction of carbon emissions.Perhaps most crucially, rainforests in Central Africa and the ecosystem services they provide are intertwined with people’s livelihoods and food security. Developing sustainable management plans that recognize the diversity of the ways in which people interact with and depend on these forests will be a huge challenge. It will require concerted cross-disciplinary and cross-sectoral efforts that move beyond national boundaries. More

1.Kazunori, M. et al. Prediction of future methane emission from irrigated rice paddies in central Thailand under different water management practices. Sci. Total Environ. 566, 641–651 (2016).
Google Scholar 
2.FAOSTAT. http://www.fao.org/statistics/zh. (2018).3.Xu, L. et al. Effects of different fertilization treatment on paddy soil nutrients in red soil hilly region. J. Nat. Resour. 27, 1890–1898 (2012) (In Chinese).
Google Scholar 
4.National Bureau of Statistics of China. China Statistical Yearbook (China Statistics Press, 2010) (In Chinese).
Google Scholar 
5.Li, H. G. et al. Past, present, and future use of phosphorus in Chinese agriculture and its influence on phosphorus losses. Ambio 44, S274–S285 (2015).PubMed 
Article 
CAS 

Google Scholar 
6.Withers, P. J. A. et al. Stewardship to tackle global phosphorus inefficiency: The case of Europe. Ambio 44(Suppl. 2), 193–206 (2015).CAS 
PubMed Central 
Article 
PubMed 

Google Scholar 
7.Huang, Q. H. et al. Effects of long-term organic amendments on soil organic carbon in a paddy field: A case study on red soil. J. Integr. Agric. 13, 570–576 (2014).Article 

Google Scholar 
8.Wang, H. et al. Effects of long-term application of organic fertilizer on improving organic matter content and retarding acidity in red soil from China. Soil Tillage Res. 195, 104382 (2019).Article 

Google Scholar 
9.Qaswar, M. et al. Yield sustainability, soil organic carbon sequestration and nutrients balance under long-term combined application of manure and inorganic fertilizers in acidic paddy soil. Soil Tillage Res. 198, 104569 (2020).Article 

Google Scholar 
10.Blake, L. et al. Phosphorus content in soil, uptake by plants and balance in three European long-term field experiments. Nutr. Cycl. Agroecosyst. 56, 263–275 (2000).Article 

Google Scholar 
11.Dawe, D., Dobermann, A., Ladha, J. K. & Zhen, Q. X. Do organic amendments improve yield trends and profitability in intensive rice systems?. Field Crop. Res. 83, 191–213 (2003).Article 

Google Scholar 
12.Nziguheba, G., Merckx, R. & Palm, C. A. Soil phosphorus dynamics and maize response to different rates of phosphorus fertilizer applied to an acrisol in Western Kenya. Plant Soil 243, 1–10 (2002).CAS 
Article 

Google Scholar 
13.Xu, M. G. et al. Effects of organic manure application with chemical fertilizers on nutrient absorption and yield of rice in hunan of Southern China. Agric. Sci. China 7, 1245–1252 (2008).Article 

Google Scholar 
14.Bi, L. et al. Long-term effects of organic amendments on the rice yields for double rice cropping systems in subtropical China. Agric. Ecosyst. Environ. 129, 534–541 (2009).Article 

Google Scholar 
15.Zhao, B. Q. et al. Long-term fertilizer experiment network in China: Crop yields and soil nutrient trends. Agron. J. 102, 216–230 (2010).CAS 
Article 

Google Scholar 
16.Gao, Y. et al. Phosphorus and carbon competitive sorption-desorption and associated non-point loss respond to natural rainfall events. J. Hydrol. 517, 447–457 (2014).ADS 
CAS 
Article 

Google Scholar 
17.Powers, S. M. et al. Long-term accumulation and transport of anthropogenic phosphorus in three river basins. Nat. Geosci. 9, 353–356 (2016).ADS 
CAS 
Article 

Google Scholar 
18.Abe, S. S. et al. Excessive application of farmyard manure reduces rice yield and enhances environmental pollution risk in paddy fields. Arch. Agron. Soil Sci. 62, 1208–1221 (2016).Article 

Google Scholar 
19.Sato, S. & Comerford, N. B. Influence of soil pH on inorganic phosphorus sorption and desorption in a humid Brazilian ultisol. Rev. Bras. Ciênc. Solo 29, 685–694 (2005).CAS 
Article 

Google Scholar 
20.Shasheen, S. & Tsadilas, C. Phosphorus sorption and availability to canola grown in an alfisol amended with various soil amendments. Commun. Soil Sci. Plan. 44, 89–103 (2013).Article 
CAS 

Google Scholar 
21.Shepherd, M. A. & Withers, P. J. Applications of poultry litter and triple superphosphate fertilizer to a sandy soil: Effects on soil phosphorus status and profile distribution. Nutr. Cycl. Agroecosyst. 54, 233–242 (1999).Article 

Google Scholar 
22.Morteza, Y., Javad, S. & Mahmood, S. S. On dealing with the pollution costs in agriculture: A case study of paddy fields. Sci. Total Environ. 556, 310–318 (2016).Article 
CAS 

Google Scholar 
23.Zhang, N.M., Li, C.X. & Li, Y.H. Accumulation and releasing risk of phosphorus in soils in Dianchi watershed. Soils 39, 665–667. (2007). (in Chinese). 24.Zhang, Z. J., Zhang, J. Y., He, R., Wang, Z. D. & Zhu, Y. M. Phosphorus interception in floodwater of paddy field during the rice-growing season in TaiHu Lake Basin. Environ. Pollut. 145, 425–433 (2007) (In Chinese).CAS 
PubMed 
Article 

Google Scholar 
25.Hua, L. et al. Risks of phosphorus runoff losses from five Chinese paddy soils under conventional management practices. Agric. Ecosyst. Environ. 245, 112–123 (2017).CAS 
Article 

Google Scholar 
26.Challinor, A. J. et al. A meta-analysis of crop yield under climate change and adaptation. Nat. Clim. Change 4, 287–291 (2014).ADS 
Article 

Google Scholar 
27.Shi, W. et al. Source-sink dynamics and proteomic reprogramming under elevated night temperature and their impact on rice yield and grain quality. New Phytol. 197, 825–837 (2013).CAS 
PubMed 
Article 

Google Scholar 
28.Andriamananjara, A. et al. Farmyard manure application in weathered upland soils of Madagascar sharply increase phosphate fertilizer use efficiency for upland rice. Field Crop. Res. 222, 94–100 (2018).Article 

Google Scholar 
29.Andriamananjara, A. et al. Farmyard manure improves phosphorus use efficiency in weathered P deficient soil. Nutr. Cycl. Agroecosyst. 115, 407–425 (2019).CAS 
Article 

Google Scholar 
30.Seufert, V., Ramankutty, N. & Foley, J. A. Comparing the yields of organic and conventional agriculture. Nature 485, 229-U113 (2012).ADS 
CAS 
PubMed 
Article 

Google Scholar 
31.Xin, X. et al. Yield, phosphorus use efficiency and balance response to substituting long-term chemical fertilizer use with organic manure in a wheat-maize system. Field Crop. Res. 208, 27–33 (2017).Article 

Google Scholar 
32.Aggarwal, R. K. & Power, J. F. Use of crop residue and manure to conserve water and enhance nutrient availability and pearl millet yields in an arid tropical region. Soil Tillage Res. 41, 43–51 (1997).Article 

Google Scholar 
33.Rehman, A., Ullah, A., Nadeem, F. & Farooq, M. Sustainable nutrient management. In Innovations in Sustainable Agriculture 167–211 (Springer, 2019).34.Whalen, J. K., Chang, C., Clayton, G. W. & Carefoot, J. P. Cattle manure amendments can increase the pH of acid soils. Soil Sci. Soc. Am. J. 64, 962–966 (2000).ADS 
CAS 
Article 

Google Scholar 
35.Mowrer, J., Endale, D. M., Schomberg, H. H., Norris, S. E. & Woodroof, R. H. Liming potential of poultry litter in a long-term tillage comparison study. Soil Tillage Res. 196, 104446 (2020).Article 

Google Scholar 
36.Miller, J., Beasley, B., Drury, C., Larney, F. & Hao, X. Y. Influence of long-term application of composted or stockpiled feedlot manure with straw or wood chips on soil cation exchange capacity. Compos. Sci. Util. 24, 54–60 (2016).CAS 
Article 

Google Scholar 
37.Liang, Y. et al. Organic manure stimulates biological activity and barley growth in soil subject to secondary salinization. Soil Biol. Biochem. 37, 1185–1195 (2005).CAS 
Article 

Google Scholar 
38.Güsewell, S. N:P ratios in terrestrial plants: Variation and functional significance. New Phytol. 164, 243–266 (2004).Article 

Google Scholar 
39.Khan, F. et al. Effect of different levels of nitrogen and phosphorus on the phenology and yield of maize varieties. Am. J. Plant Sci. 5, 2582–2590 (2014).CAS 
Article 

Google Scholar 
40.Luo, X. et al. Nitrogen: Phosphorous supply ratio and allometry in five alpine plant species. Ecol. Evol. 6, 8881–8892 (2016).PubMed 
PubMed Central 
Article 

Google Scholar 
41.Güsewell, S. Responses of wetland graminoids to the relative supply of nitrogen and phosphorus. Plant Ecol. 176, 35–55 (2005).Article 

Google Scholar 
42.Hu, B. et al. Nitrate-NRT1.1B-SPX4 cascade integrates nitrogen and phosphorus signalling networks in plants. Nat. Plants 5, 401–413 (2019).CAS 
PubMed 
Article 

Google Scholar 
43.Zhang, W. F. et al. Efficiency, economics, and environmental implications of phosphorus resource use and the fertilizer industry in China. Nutr. Cycl. Agroecosyst. 80, 131–144 (2008).Article 

Google Scholar 
44.Andriamananjara, A. et al. Land management modifies the temperature sensitivity of soil organic carbon, nitrogen and phosphorus dynamics in a Ferralsol. Appl. Soil Ecol. 138, 112–122 (2019).Article 

Google Scholar 
45.Nziguheba, G., Merckx, R., Palm, C. A. & Rao, M. R. Organic residues affect phosphorus availability and maize yields in a Nitisol of Western Kenya. Biol. Fertil. Soils 32, 328–339 (2000).CAS 
Article 

Google Scholar 
46.Peretyazhko, T. & Sposito, G. Iron(III) reduction and phosphorous solubilization in humid tropical forest soils. Geochim. Cosmochim. Acta 69, 3643–3652 (2005).ADS 
CAS 
Article 

Google Scholar 
47.Wright, A. L. Soil phosphorus stocks and distribution in chemical fractions for long-term sugarcane, pasture, turfgrass, and forest systems in Florida. Nutr. Cycl. Agroecosyst. 83, 223–231 (2009).CAS 
Article 

Google Scholar 
48.Zhong, X. et al. The evaluation of phosphorus leaching risk of 23 Chinese soils I. Leaching criterion. Acta Ecol. Sin. 24, 2275–2280 (2004).
Google Scholar 
49.Wang, S. et al. Phosphorus loss potential and phosphatase activity under phosphorus fertilization in long-term paddy wetland agroecosystems. Soil Sei. Soc. Am. J. 6, 161–167 (2012).Article 
CAS 

Google Scholar 
50.Haynes, R. J. & Mokolobate, M. S. Amelioration of Al toxicity and P deficiency in acid soils by additions of organic residues: A critical review of the phenomenon and the mechanisms involved. Nutr. Cycl. Agroecosyst. 59, 47–63 (2001).CAS 
Article 

Google Scholar 
51.Ayaga, G., Todd, A. & Brookes, P. C. Enhanced biological cycling of phosphorus increases its availability to crops in low-input sub-Saharan farming systems. Soil Biol. Biochem. 38, 81–90 (2006).CAS 
Article 

Google Scholar 
52.Nie, J., Zhou, J., Wang, H., Chen, X. & Du, C. Effect of long-term rice straw return on soil glomalin, carbon and nitrogen. Pedosphere 17, 295–302 (2007).CAS 
Article 

Google Scholar 
53.Yu, Y. et al. Responses of paddy soil bacterial community assembly to different long-term fertilizations in southeast China. Sci. Total Environ. 656, 625–633 (2019).ADS 
CAS 
PubMed 
Article 

Google Scholar 
54.Murphy, J. & Riley, J. P. A modified single solution method for the determination of phosphate in natural waters. Anal. Chim. A. 27, 31–36 (1962).CAS 
Article 

Google Scholar 
55.Kitson, R. E. & Mellon, M. G. Colorimetric determination of phosphorus as molybdivanadophosporic acid. Ind. Eng. Chem. Anal. Ed. 16, 379–383 (1944).CAS 
Article 

Google Scholar 
56.Soon, Y. K. & Kalra, Y. P. A comparison of plant tissue digestion methods for nitrogen and phosphorus analyses. Can. J. Soil Sci. 75, 243–245 (1995).CAS 
Article 

Google Scholar  More

1.Réale, D., Dingemanse, N. J., Kazem, A. J. N. & Wright, J. Evolutionary and ecological approaches to the study of personality. Philos. Trans. R. Soc. B. 365, 3937–3946 (2010).Article 

Google Scholar 
2.Dingemanse, N. J. & Wright, J. Criteria for acceptable studies of animal personality and behavioural syndromes. Ethology 126, 865–869 (2020).Article 

Google Scholar 
3.Wilson, D. S. Adaptive individual differences within single populations. Philos. Trans. R. Soc. B. 353, 199–205 (1998).Article 

Google Scholar 
4.Van Oers, K., De Jong, G., Van Noordwijk, A. J., Kempenaers, B. & Drent, P. J. Contribution of genetics to the study of animal personalities: A review of case studies. Behaviour 142, 1185–1206 (2005).Article 

Google Scholar 
5.Dochtermann, N. A., Schwab, T. & Sih, A. The contribution of additive genetic variation to personality variation: Heritability of personality. Proc. R. Soc. B. 282, 20142201 (2015).PubMed 
Article 
PubMed Central 

Google Scholar 
6.Dochtermann, N. A., Schwab, T., Berdal, M. A., Dalos, J. & Royauté, R. The heritability of behavior: A meta-analysis. J. Hered. 110, 403–410 (2019).PubMed 
Article 
PubMed Central 

Google Scholar 
7.Smith, B. R. & Blumstein, D. T. Fitness consequences of personality: A meta-analysis. Behav. Ecol. 19, 448–455 (2008).Article 

Google Scholar 
8.Moiron, M., Laskowski, K. L. & Niemelä, P. T. Individual differences in behaviour explain variation in survival: a meta-analysis. Ecol. Lett. 23, 399–408 (2020).PubMed 
Article 
PubMed Central 

Google Scholar 
9.Dingemanse, N. J. & Wolf, M. Recent models for adaptive personality differences: A review. Philos. Trans. R. Soc. B. 365, 3947–3958 (2010).Article 

Google Scholar 
10.Dingemanse, N. J. & Réale, D. What is the evidence that natural selection maintains variation in animal personalities? In Animal Personalities: Behavior, Physiology, and Evolution (eds Carere, C. & Maestripieri, D.) 201–220 (Chicago University Press, 2013).
Google Scholar 
11.Oers, K. V. & Mueller, J. C. Evolutionary genomics of animal personality. Philos. Trans. R. Soc. B. 365, 3991–4000 (2010).Article 

Google Scholar 
12.Laine, V. N. & van Oers, K. The quantitative and molecular genetics of individual differences in animal personality. In Personality in Nonhuman Animals (eds Vonk, J. et al.) 55–72 (Springer, 2017).
Google Scholar 
13.Bubac, C. M., Miller, J. M. & Coltman, D. W. The genetic basis of animal behavioural diversity in natural populations. Mol. Ecol. 29, 1957–1971 (2020).PubMed 
Article 
PubMed Central 

Google Scholar 
14.Dingemanse, N. J., Kazem, A. J. N., Réale, D. & Wright, J. Behavioural reaction norms: Animal personality meets individual plasticity. Trends Ecol. Evol. 25, 81–89 (2010).PubMed 
Article 
PubMed Central 

Google Scholar 
15.Brommer, J. E. & Class, B. The importance of genotype-by-age interactions for the development of repeatable behavior and correlated behaviors over lifetime. Front. Zool. 12, S2 (2015).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
16.Nussey, D. H., Wilson, A. J. & Brommer, J. E. The evolutionary ecology of individual phenotypic plasticity in wild populations. J. Evol. Biol. 20, 831–844 (2007).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
17.Scheiner, S. M. Genetics and evolution of phenotypic plasticity. Annu. Rev. Ecol. Syst. 24, 35–68 (1993).Article 

Google Scholar 
18.Gienapp, P., Laine, V. N., Mateman, A. C., van Oers, K. & Visser, M. E. Environment-dependent genotype-phenotype associations in avian breeding time. Front. Genet. 8, 1–9 (2017).Article 
CAS 

Google Scholar 
19.Korsten, P. et al. Association between DRD4 gene polymorphism and personality variation in great tits: A test across four wild populations. Mol. Ecol. 19, 832–843 (2010).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
20.Mueller, J. C. et al. Haplotype structure, adaptive history and associations with exploratory behaviour of the DRD4 gene region in four great tit (Parus major) populations. Mol. Ecol. 22, 2797–2809 (2013).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
21.Riyahi, S., Sánchez-Delgado, M., Calafell, F., Monk, D. & Senar, J. C. Combined epigenetic and intraspecific variation of the DRD4 and SERT genes influence novelty seeking behavior in great tit Parus major. Epigenetics 10, 516–525 (2015).PubMed 
PubMed Central 
Article 

Google Scholar 
22.Mueller, J. C., Partecke, J., Hatchwell, B. J., Gaston, K. J. & Evans, K. L. Candidate gene polymorphisms for behavioural adaptations during urbanization in blackbirds. Mol. Ecol. 22, 3629–3637 (2013).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
23.Holtmann, B. et al. Population differentiation and behavioural association of the two ‘personality’ genes DRD4 and SERT in dunnocks (Prunella modularis). Mol. Ecol. 25, 706–722 (2016).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
24.Class, B. & Brommer, J. E. Senescence of personality in a wild bird. Behav. Ecol. Sociobiol. 70, 733–744 (2016).Article 

Google Scholar 
25.Class, B., Brommer, J. E. & van Oers, K. Exploratory behavior undergoes genotype–age interactions in a wild bird. Ecol. Evol. 9, 8987–8994 (2019).PubMed 
PubMed Central 
Article 

Google Scholar 
26.Savitz, J. B. & Ramesar, R. S. Genetic variants implicated in personality: A review of the more promising candidates. Am. J. Med. Genet. Neuropsychiatr. Genet. 131B, 20–32 (2004).Article 

Google Scholar 
27.Craig, I. W. & Halton, K. E. Genetics of human aggressive behaviour. Hum. Genet. 126, 101–113 (2009).PubMed 
Article 
PubMed Central 

Google Scholar 
28.Miller-Butterworth, C. M., Kaplan, J. R., Barmada, M. M., Manuck, S. B. & Ferrell, R. E. The serotonin transporter: Sequence variation in Macaca fascicularis and its relationship to dominance. Behav. Genet. 37, 678–696 (2007).PubMed 
Article 
PubMed Central 

Google Scholar 
29.Jannini, E. A., Burri, A., Jern, P. & Novelli, G. Genetics of human sexual behavior: Where we are, where we are going. Sex. Med. Rev. 3, 65–77 (2015).PubMed 
Article 
PubMed Central 

Google Scholar 
30.Timm, K., Van Oers, K. & Tilgar, V. SERT gene polymorphisms are associated with risk-taking behaviour and breeding parameters in wild great tits. J. Exp. Biol. 221, jeb171595 (2018).PubMed 
Article 
PubMed Central 

Google Scholar 
31.Timm, K., Koosa, K. & Tilgar, V. The serotonin transporter gene could play a role in anti-predator behaviour in a forest passerine. J. Ethol. 37, 221–227 (2019).Article 

Google Scholar 
32.Edwards, H. A., Hajduk, G. K., Durieux, G., Burke, T. & Dugdale, H. L. No association between personality and candidate gene polymorphisms in a wild bird population. PLoS ONE 10, 1–13 (2015).
Google Scholar 
33.Van Dongen, W. F. D., Robinson, R. W., Weston, M. A., Mulder, R. A. & Guay, P. J. Variation at the DRD4 locus is associated with wariness and local site selection in urban black swans. BMC Evol. Biol. 15, 1–11 (2015).Article 

Google Scholar 
34.Sibley, C. G. Behavioral mimicry in the titmice (Paridae) and certain other birds. Wilson Bull. 67, 128–132 (1955).
Google Scholar 
35.Thys, B. et al. The female perspective of personality in a wild songbird: Repeatable aggressiveness relates to exploration behaviour. Sci. Rep. 7, 1–10 (2017).CAS 
Article 

Google Scholar 
36.Thys, B., Lambreghts, Y., Pinxten, R. & Eens, M. Nest defence behavioural reaction norms: Testing life-history and parental investment theory predictions. R. Soc. Open Sci. 6, 182180 (2019).PubMed 
PubMed Central 
Article 
ADS 

Google Scholar 
37.Thys, B., Pinxten, R. & Eens, M. Long-term repeatability and age-related plasticity of female behaviour in a free-living passerine. Anim. Behav. 172, 45–54 (2021).Article 

Google Scholar 
38.Grunst, A. S. et al. Variation in personality traits across a metal pollution gradient in a free-living songbird. Sci. Total Environ. 630, 668–678 (2018).CAS 
PubMed 
Article 
ADS 
PubMed Central 

Google Scholar 
39.Graffelman, J. Exploring diallelic genetic markers: The HardyWeinberg package. J. Stat. Softw. 64, 1–23 (2015).Article 

Google Scholar 
40.Solé, X., Guinó, E., Valls, J., Iniesta, R. & Moreno, V. SNPStats: A web tool for the analysis of association studies. Bioinformatics 22, 1928–1929 (2006).PubMed 
Article 
CAS 
PubMed Central 

Google Scholar 
41.Benjamini, Y. & Hocherg, Y. Controlling the false discovery rate: A practical and powerful approach to multiple testing. J. R. Stat. Soc. Ser. B 57, 289–300 (1995).MathSciNet 
MATH 

Google Scholar 
42.Therneau, T. coxme: Mixed effects Cox models. R package version 2.2-16. https://CRAN.R-project.org/package=coxme (2020).43.Balding, D. J. A tutorial on statistical methods for population association studies. Nat. Rev. Genet. 7, 781–791 (2006).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
44.van de Pol, M. & Wright, J. A simple method for distinguishing within- versus between-subject effects using mixed models. Anim. Behav. 77, 753–758 (2009).Article 

Google Scholar 
45.Araya-Ajoy, Y. G., Mathot, K. J. & Dingemanse, N. J. An approach to estimate short-term, long-term and reaction norm repeatability. Methods Ecol. Evol. 6, 1462–1473 (2015).Article 

Google Scholar 
46.Sinnwell, J., Therneau, T. & Schaid, D. The kinship 2 R Package for Pedigree Data. Hum. Hered. 78, 91–93 (2014).PubMed 
PubMed Central 
Article 

Google Scholar 
47.Wilson, A. J. et al. An ecologist’s guide to the animal model. J. Anim. Ecol. 79, 13–26 (2010).PubMed 
Article 
PubMed Central 

Google Scholar 
48.Nakagawa, S. & Schielzeth, H. A general and simple method for obtaining R2 from generalized linear mixed-effects models. Methods Ecol. Evol. 4, 133–142 (2013).Article 

Google Scholar 
49.Deans, C. & Maggert, K. A. What do you mean, “Epigenetic”?. Genetics 199, 887–896 (2015).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
50.Hirschhorn, J. N., Lohmueller, K., Byrne, E. & Hirschhorn, K. A comprehensive review of genetic association studies. Genet. Med. 4, 45–61 (2002).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
51.Hedrick, P. W. Genetic polymorphism in heterogeneous environments: The age of genomics. Annu. Rev. Ecol. Evol. Syst. 37, 67–93 (2006).Article 

Google Scholar 
52.Krams, I. et al. Hissing calls improve survival in incubating female great tits (Parus major). Acta Ethol. 17, 83–88 (2014).Article 

Google Scholar 
53.Munafò, M. R., Yalcin, B., Willis-Owen, S. A. & Flint, J. Association of the dopamine D4 receptor (DRD4) gene and approach-related personality traits: Meta-analysis and new data. Biol. Psychiatry 63, 197–206 (2008).PubMed 
Article 
CAS 
PubMed Central 

Google Scholar 
54.Chamary, J. V., Parmley, J. L. & Hurst, L. D. Hearing silence: Non-neutral evolution at synonymous sites in mammals. Nat. Rev. Genet. 7, 98–108 (2006).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
55.Sauna, Z. E. & Kimchi-Sarfaty, C. Understanding the contribution of synonymous mutations to human disease. Nat. Rev. Genet. 12, 683–691 (2011).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
56.Pastinen, T. Genome-wide allele-specific analysis: Insights into regulatory variation. Nat. Rev. Genet. 11, 533–538 (2010).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
57.Vergnes, M., Depaulis, A. & Boehrer, A. Parachlorophenylalanine-induced serotonin depletion increases offensive but not defensive aggression in male rats. Physiol. Behav. 36, 653–658 (1986).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
58.Lesch, K. P. & Merschdorf, U. Impulsivity, aggression, and serotonin: A molecular psychobiological perspective. Behav. Sci. Law 18, 581–604 (2000).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
59.Seo, D., Patrick, C. J. & Kennealy, P. J. Role of serotonin and dopamine system interactions in the neurobiology of impulsive aggression and its comorbidity with other clinical disorders. Aggress. Violent Behav. 13, 383–395 (2008).PubMed 
PubMed Central 
Article 

Google Scholar 
60.Thys, B., Eens, M., Pinxten, R. & Iserbyt, A. Pathways linking female personality with reproductive success are trait- and year-specific. Behav. Ecol. 32, 114–123 (2020).Article 

Google Scholar  More

1.Gardner, T. A., Côté, I. M., Gill, J. A., Grant, A. & Watkinson, A. R. Hurricanes and caribbean coral reefs: impacts, recovery patterns, and role in long-term decline. Ecology 86, 174–184 (2005).Article 

Google Scholar 
2.Harvell, D. et al. Coral disease, environmental drivers, and the balance between coral and microbial associates. Oceanography 20, 172–195 (2007).Article 

Google Scholar 
3.Silverman, J., Lazar, B., Cao, L., Caldeira, K. & Erez, J. Coral reefs may start dissolving when atmospheric CO2 doubles. Geophys. Res. Lett. 36, 1–5 (2009).Article 

Google Scholar 
4.Jackson, J., Donovan, M., Cramer, K. & Lam, W. Status and Trends of Caribbean Coral Reefs 1970–2012 (2012).5.IPCC. Climate Change 2014 Synthesis Report. IPCC Fifth Assessment Report 151 (2014).6.Zaneveld, J. R. et al. Overfishing and nutrient pollution interact with temperature to disrupt coral reefs down to microbial scales. Nat. Commun. 7, 1–12 (2016).Article 

Google Scholar 
7.Bruno, J. F., Petes, L. E., Drew Harvell, C. & Hettinger, A. Nutrient enrichment can increase the severity of coral diseases. Ecol. Lett. 6, 1056–1061 (2003).Article 

Google Scholar 
8.Danovaro, R. et al. Sunscreens cause coral bleaching by promoting viral infections. Environ. Health Perspect. 116, 441–447 (2008).CAS 
Article 

Google Scholar 
9.Díaz, M. & Madin, J. Macroecological relationships between coral species’ traits and disease potential. Coral Reefs 30, 73–84 (2011).ADS 
Article 

Google Scholar 
10.Bruno, J. F. The coral disease triangle. Nat. Clim. Chang. 5, 302–303 (2015).ADS 
Article 

Google Scholar 
11.Muller, E. M. et al. Low pH reduces the virulence of black band disease on Orbicella faveolata. PLoS ONE 12, e0178869 (2017).Article 

Google Scholar 
12.Thurber, R. V., Payet, J. P., Thurber, A. R. & Correa, A. M. S. Virus-host interactions and their roles in coral reef health and disease. Nat. Rev. Microbiol. 15, 205–216 (2017).CAS 
Article 

Google Scholar 
13.Pollock, F. J., Morris, P. J., Willis, B. L. & Bourne, D. G. The urgent need for robust coral disease diagnostics. PLoS Pathog. 7 (2011).14.Beeden, R., Maynard, J. A., Marshall, P. A., Heron, S. F. & Willis, B. L. A framework for responding to coral disease outbreaks that facilitates adaptive management. Environ. Manag. 49, 1–13 (2012).ADS 
Article 

Google Scholar 
15.Walton, C. J., Hayes, N. K. & Gilliam, D. S. Impacts of a regional, multi-year, multi-species coral disease outbreak in Southeast Florida. Front. Mar. Sci. 5 (2018).16.Harvell, C. D. et al. Emerging marine diseases: Climate links and anthropogenic factors. Manter Lab. 580 (1999).17.Wilkinson, C. Status of Coral Reefs of the World: 2008. (2008).18.Ruiz-Moreno, D. et al. Global coral disease prevalence associated with sea temperature anomalies and local factors. Dis. Aquat. Organ. 100, 249–261 (2012).Article 

Google Scholar 
19.Bruckner, A. W. Proceedings of the Caribbean Acropora Workshop: Potential Application of the U.S. Endangered Species Act as a Conservation Strategy. in Proceedings of the Caribbean Acropora Workshop 199 (2003).20.Casas, V. et al. Widespread association of a Rickettsiales-like bacterium with reef-building corals. Environ. Microbiol. 6, 1137–1148 (2004).Article 

Google Scholar 
21.Aronson, R. B. & Precht, W. F. White-band disease and the changing face of Caribbean coral reefs. Hydrobiologia 460, 25–38 (2001).Article 

Google Scholar 
22.Gladfelter, W. B. White-band disease in Acropora palmata: Implications for the structure and growth of shallow reefs. Bull. Mar. Sci. 32, 639–643 (1982).
Google Scholar 
23.Richardson, L. L. Coral diseases: What is really known?. TREE 13, 438–443 (1998).CAS 
PubMed 

Google Scholar 
24.Richardson, L. L. et al. Florida’s mystery coral-killer identified. Sci. Corresp. 392, 557–558 (1998).CAS 

Google Scholar 
25.Richardson, L. & Voss, J. Changes in a coral population on reefs of the northern Florida Keys following a coral disease epizootic. Mar. Ecol. Prog. Ser. 297, 147–156 (2005).ADS 
Article 

Google Scholar 
26.Berkelmans, R., De’ath, G., Kininmonth, S. & Skirving, W. J. A comparison of the 1998 and 2002 coral bleaching events on the Great Barrier Reef: Spatial correlation, patterns, and predictions. Coral Reefs 23, 74–83 (2004).Article 

Google Scholar 
27.Burge, C. A. et al. Climate change influences on marine infectious diseases: Implications for management and society. Ann. Rev. Mar. Sci. 6, 249–277 (2014).Article 

Google Scholar 
28.Maynard, J. et al. Projections of climate conditions that increase coral disease susceptibility and pathogen abundance and virulence. Nat. Clim. Chang. 5, 688–694 (2015).ADS 
Article 

Google Scholar 
29.Roth, L., Kramer, P. R., Doyle, E. & and O’Sullivan, C. Caribbean SCTLD Dashboard. ArcGIS Online (2020). https://www.agrra.org/coral-disease-outbreak/.30.Alvarez-Filip, L., Estrada-Saldívar, N., Pérez-Cervantes, E., Molina-Hernández, A. & González-Barrios, F. J. A rapid spread of the stony coral tissue loss disease outbreak in the Mexican Caribbean. PeerJ https://doi.org/10.7717/peerj.8069 (2019).Article 
PubMed 
PubMed Central 

Google Scholar 
31.Muller, E. M., Sartor, C., Alcaraz, N. I. & van Woesik, R. Spatial epidemiology of the stony-coral-tissue-loss disease in Florida. Front. Mar. Sci. 7, 163 (2020).Article 

Google Scholar 
32.Aeby, G. S. et al. Pathogenesis of a tissue loss disease affecting multiple species of corals along the florida reef tract. Front. Mar. Sci. 6, 1–18 (2019).ADS 
Article 

Google Scholar 
33.Weil, E. & Rogers, C. S. Coral reef diseases in the Atlantic-Caribbean. In Coral Reefs: An Ecosystem in Transition (eds Dubinsky, Z. & Stambler, N.) 465–491 (Springer, 2011). https://doi.org/10.1007/978-94-007-0114-4.
Google Scholar 
34.Rippe, J. P., Kriefall, N. G., Davies, S. W. & Castillo, K. D. Differential disease incidence and mortality of inner and outer reef corals of the upper Florida Keys in association with a white syndrome outbreak. Bull. Mar. Sci. 95, 305–316 (2019).Article 

Google Scholar 
35.Neely, K. Ex-Situ Disease Treatment Trials. 1–3 (2018). https://floridadep.gov/sites/default/files/Ex-Situ-Disease-Treatment-Trials.pdf.36.Neely, K. Ex Situ Disease Treatment Trials Final Report. 1–3 (2019). Available at: https://floridadep.gov/sites/default/files/DEPLabTrialsFINALReport2019.01508comp_0.pdf.37.Miller, C. V., May, L. A., Moffitt, Z. J. & Woodley, C. M. Exploratory Treatments for Stony Coral Tissue Loss Disease: Pillar Coral (Dendrogyra cylindrus). (2020). https://doi.org/10.7289/V5/TM-NOS-NCCOS-24538.Favero, M., Balut, K., Levine, M. & Circle, M. Amoxicillin Trihydrate Stability in Correlation with Coral Ointment Batch #18006-B and Simulated Seawater. 1–9 (2019). https://floridadep.gov/sites/default/files/AmoxicillinStabilityinBothSeawaterBatch18006-B_FINAL_508C_0.pdf.39.Aeby, G. S. et al. First record of black band disease in the Hawaiian archipelago: Response, outbreak status, virulence, and a method of treatment. PLoS ONE 10, 1–17 (2015).Article 

Google Scholar 
40.Walker, B. K. & Brunelle, A. Southeast Florida large ( >2 meter) diseased coral colony intervention summary report. 1–164 (2018). https://floridadep.gov/sites/default/files/Large-Coral-Disease-Intervention-Summary-Report.pdf.41.Combs, I. Characterizing the Impacts of Scleractinian Tissue Loss Disease Outbreak on Corals in Southeast Florida. (2019).42.Combs, I. R., Studivan, M. S., Eckert, R. J. & Voss, J. D. Quantifying impacts of stony coral tissue loss disease on corals in Southeast Florida through surveys and 3D photogrammetry. PLoS One (In the press).43.Voss, J. D., Shilling, E. N. & Combs, I. R. Intervention and fate tracking for corals affected by stony coral tissue loss disease in the northern Florida Reef Tract. 1–23 (2019). Available at: https://floridadep.gov/sites/default/files/VossSEFLDiseaseReport2018_FINAL_508compliant.pdf.44.Veron, J. E. N. Corals of the World. (2000).45.NOAA. Stony Coral Tissue Loss Disease Case Definition. Florida Keys National Marine Sanctuary (2018).46.Banks, K. W. et al. The Reef Tract of Continental Southeast Florida (Miami-Dade, Broward and Palm Beach Counties, USA). in Coral Reefs of the USA 175–220 (2008).47.González-Barrios, F. J. & Álvarez-Filip, L. A framework for measuring coral species-specific contribution to reef functioning in the Caribbean. Ecol. Indic. 95, 877–886 (2018).Article 

Google Scholar 
48.R Core Team. R: A language and environment for statistical computing. (2020).49.Wickham, H. Package ‘ggplot2’: Create Elegant Data Visualizations Using the Grammar of Graphics. 277 (2020).50.Hope, R. M. Package ‘ Rmisc ’: Ryan Miscellaneous. (2016).51.Kassambara, A. Package ‘ rstatix ’: Pipe-Friendly Framework for Basic Statistical Tests. (2020).52.Derek, O., Wheeler, P. & Dinno, A. Package ‘ FSA ’: Simple Fisheries Stock Assessment Methods. (2020).53.Sweet, M. J., Croquer, A. & Bythell, J. C. Experimental antibiotic treatment identifies potential pathogens of white band disease in the endangered Caribbean coral Acropora cervicornis. Proc. R. Soc. B Biol. Sci. 281, 20140094–20140094 (2014).CAS 
Article 

Google Scholar 
54.Neely, K. L., Macaulay, K. A., Hower, E. K. & Dobler, M. A. Effectiveness of topical antibiotics in treating corals affected by Stony Coral Tissue Loss Disease. PeerJ 8, e9289 (2020).Article 

Google Scholar 
55.Voss, J. D., Mills, D. K., Myers, J. L., Remily, E. R. & Richardson, L. L. Black band disease microbial community variation on corals in three regions of the wider Caribbean. Microb. Ecol. 54, 730–739 (2007).CAS 
Article 

Google Scholar 
56.Sekar, R., Kaczmarsky, L. & Richardson, L. Microbial community composition of black band disease on the coral host Siderastrea siderea from three regions of the wider Caribbean. Mar. Ecol. Prog. Ser. 362, 85–98 (2008).ADS 
CAS 
Article 

Google Scholar 
57.Sato, Y., Willis, B. L. & Bourne, D. G. Successional changes in bacterial communities during the development of black band disease on the reef coral, Montipora hispida. ISME J. 4, 203–214 (2010).Article 

Google Scholar 
58.Miller, A. W. & Richardson, L. L. A meta-analysis of 16S rRNA gene clone libraries from the polymicrobial black band disease of corals. FEMS Microbiol. Ecol. 75, 231–241 (2010).Article 

Google Scholar 
59.Hudson, H. First Aid for Massive Corals Infected With Black Band Disease, Phormidium corallyticum: An Underwater Aspirator and Post-Treatment Sealant to Curtail Reinfection. In AAUS 20th Symposium Proceedings 2000 (2000).60.Randall, C. J. et al. Testing methods to mitigate Caribbean yellow-band disease on Orbicella faveolata. PeerJ 2018, 1–20 (2018).
Google Scholar 
61.Walker, B. K. & Pitts, K. SE FL Reef-building-coral Response to Amoxicillin Intervention and Broader-scale Coral Disease Intervention. 1–17 (2019). https://floridadep.gov/sites/default/files/WalkerMCAVDiseaseExperimentSummaryReportJune2019_final_14Aug2019.pdf.62.Neely, K. Florida Keys Coral Disease Strike Team: FY 2019/2020 Final Report. 1–17 (2020). Available at: https://floridadep.gov/sites/default/files/FloridaKeysCoralDiseaseStrikeTeam_FY19-20FinalReport.pdf.63.Paterson, I. K., Hoyle, A., Ochoa, G., Baker-Austin, C. & Taylor, N. G. H. Optimising antibiotic usage to treat bacterial infections. Sci. Rep. 6, 1–10 (2016).Article 

Google Scholar  More

1.Roth-Schulze, A. J. et al. Functional biogeography and host specificity of bacterial communities associated with the Marine Green Alga Ulva spp. Mol. Ecol. 27, 1952–1965 (2018).PubMed 
Article 

Google Scholar 
2.Teagle, H., Hawkins, S. J., Moore, P. J. & Smale, D. A. The role of kelp species as biogenic habitat formers in coastal marine ecosystems. J. Exp. Mar. Biol. Ecol. 492, 81–98 (2017).Article 

Google Scholar 
3.Goecke, F., Labes, A., Wiese, J. & Imhoff, J. F. Chemical interactions between marine macroalgae and bacteria. Mar. Ecol. Prog. Ser. 409, 267–300 (2010).ADS 
CAS 
Article 

Google Scholar 
4.Singh, R. P. & Reddy, C. R. K. Seaweed-microbial interactions: Key functions of seaweed-associated bacteria. FEMS Microbiol. Ecol. 88, 213–230 (2014).CAS 
PubMed 
Article 

Google Scholar 
5.Ramanan, R., Kim, B. H., Cho, D. H., Oh, H. M. & Kim, H. S. Algae-bacteria interactions: Evolution, ecology and emerging applications. Biotechnol. Adv. 34, 14–29 (2016).CAS 
PubMed 
Article 

Google Scholar 
6.Ismail, A. et al. Antimicrobial activities of bacteria associated with the brown alga padina pavonica. Front. Microbiol. 7, 1–13 (2016).
Google Scholar 
7.Sañudo-Wilhelmy, S. A., Gómez-Consarnau, L., Suffridge, C. & Webb, E. A. The role of B vitamins in marine biogeochemistry. Ann. Rev. Mar. Sci. 6, 339–367 (2014).PubMed 
Article 

Google Scholar 
8.Karthick, P. & Mohanraju, R. Antimicrobial potential of epiphytic bacteria associated with seaweeds of little Andaman, India. Front. Microbiol. 9, 1–11 (2018).Article 

Google Scholar 
9.El Shafay, S. M., Ali, S. S. & El-Sheekh, M. M. Antimicrobial activity of some seaweeds species from Red sea, against multidrug resistant bacteria. Egypt. J. Aquat. Res. 42, 65–74 (2016).Article 

Google Scholar 
10.Dobretsov, S. V. & Qian, P. Y. Effect of bacteria associated with the green alga Ulva reticulata on marine micro- and macrofouling. Biofouling 18, 217–228 (2002).Article 

Google Scholar 
11.Mieszkin, S., Callow, M. E. & Callow, J. A. Interactions between microbial biofilms and marine fouling algae: A mini review. Biofouling 29, 1097–1113 (2013).CAS 
PubMed 
Article 

Google Scholar 
12.Burke, C., Thomas, T., Lewis, M., Steinberg, P. & Kjelleberg, S. Composition, uniqueness and variability of the epiphytic bacterial community of the green alga Ulva australis. ISME J. 5, 590–600 (2010).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
13.Tujula, N. A. et al. Variability and abundance of the epiphytic bacterial community associated with a green marine Ulvacean alga. ISME J. 4, 301–311 (2010).PubMed 
Article 

Google Scholar 
14.Burke, C., Steinberg, P., Rusch, D., Kjelleberg, S. & Thomas, T. Bacterial community assembly based on functional genes rather than species. Proc. Natl. Acad. Sci. 108, 14288–14293 (2011).ADS 
CAS 
PubMed 
Article 

Google Scholar 
15.Roth-Schulze, A. J., Zozaya-Valdés, E., Steinberg, P. D. & Thomas, T. Partitioning of functional and taxonomic diversity in surface-associated microbial communities. Environ. Microbiol. 18, 4391–4402 (2016).PubMed 
Article 

Google Scholar 
16.Selvarajan, R. et al. Distribution, interaction and functional profiles of epiphytic bacterial communities from the rocky intertidal seaweeds, South Africa. Sci. Rep. 9, 1–13 (2019).ADS 
Article 
CAS 

Google Scholar 
17.Aires, T., Serrão, E. A. & Engelen, A. H. Host and environmental specificity in bacterial communities associated to two highly invasive marine species (genus Asparagopsis). Front. Microbiol. 7, 1–14 (2016).Article 

Google Scholar 
18.Lachnit, T., Fischer, M., Künzel, S., Baines, J. F. & Harder, T. Compounds associated with algal surfaces mediate epiphytic colonization of the marine macroalga Fucus vesiculosus. FEMS Microbiol. Ecol. 84, 411–420 (2013).CAS 
PubMed 
Article 

Google Scholar 
19.Nylund, G. M. et al. The red alga Bonnemaisonia asparagoides regulates epiphytic bacterial abundance and community composition by chemical defence. FEMS Microbiol. Ecol. 71, 84–93 (2010).CAS 
PubMed 
Article 

Google Scholar 
20.Campbell, A. H., Marzinelli, E. M., Gelber, J. & Steinberg, P. D. Spatial variability of microbial assemblages associated with a dominant habitat-forming seaweed. Front. Microbiol. 6, 1–10 (2015).Article 

Google Scholar 
21.Munday, P. L. Competitive coexistence of coral-dwelling fishes: The lottery hypothesis revisited. Ecology 85, 623–628 (2004).Article 

Google Scholar 
22.Geange, S. W., Poulos, D. E., Stier, A. C. & McCormick, M. I. The relative influence of abundance and priority effects on colonization success in a coral-reef fish. Coral Reefs 36, 151–155 (2017).ADS 
Article 

Google Scholar 
23.Stratil, S. B., Neulinger, S. C., Knecht, H., Friedrichs, A. K. & Wahl, M. Temperature-driven shifts in the epibiotic bacterial community composition of the brown macroalga Fucus vesiculosus. Microbiologyopen 2, 338–349 (2013).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
24.Stratil, S. B., Neulinger, S. C., Knecht, H., Friedrichs, A. K. & Wahl, M. Salinity affects compositional traits of epibacterial communities on the brown macroalga Fucus vesiculosus. FEMS Microbiol. Ecol. 88, 272–279 (2014).CAS 
PubMed 
Article 

Google Scholar 
25.Zhang, Y. et al. Effect of salinity on the microbial community and performance on anaerobic digestion of marine macroalgae. J. Chem. Technol. Biotechnol. 92, 2392–2399 (2017).CAS 
Article 

Google Scholar 
26.Liao, L. & Xu, Y. Effects of nitrogen nutrients on growth and epiphytic bacterial composition in sea weed Gracilaria lemaneiformis. Fish. Sci. 28, 130–135 (2009).ADS 
CAS 

Google Scholar 
27.Zozaya-Valdés, E., Roth-Schulze, A. J. & Thomas, T. Effects of temperature stress and aquarium conditions on the red macroalga Delisea pulchra and its associated microbial community. Front. Microbiol. 7, 1–10 (2016).Article 

Google Scholar 
28.Nemergut, D. R. et al. Patterns and processes of microbial community assembly. Microbiol. Mol. Biol. Rev. 77, 342–356 (2013).PubMed 
PubMed Central 
Article 

Google Scholar 
29.Liu, X. et al. Isolation and pathogenicity identification of bacterial pathogens in bleached disease and their physiological effects on the red macroalga Gracilaria lemaneiformis. Aquat. Bot. 153, 1–7 (2019).ADS 
CAS 
Article 

Google Scholar 
30.Xie, X. et al. Large-scale seaweed cultivation diverges water and sediment microbial communities in the coast of Nan’ao Island, South China Sea. Sci. Total Environ. 598, 97–108 (2017).ADS 
CAS 
PubMed 
Article 

Google Scholar 
31.Yang, Y. et al. Cultivation of seaweed Gracilaria in Chinese coastal waters and its contribution to environmental improvements. Algal Res. 9, 236–244 (2015).Article 

Google Scholar 
32.Lindström, E. S. & Langenheder, S. Local and regional factors influencing bacterial community assembly. Environ. Microbiol. Rep. 4, 1–9 (2012).PubMed 
Article 

Google Scholar 
33.Hellweger, F. L., Van Sebille, E. & Fredrick, N. D. Biogeographic patterns in ocean microbes emerge in a neutral agent-based model. Science (80-. ). 345, 1346–1349 (2014).34.Longford, S. R. et al. Comparisons of diversity of bacterial communities associated with three sessile marine eukaryotes. Aquat. Microb. Ecol. 48, 217–229 (2007).Article 

Google Scholar 
35.Lachnit, T., Meske, D., Wahl, M., Harder, T. & Schmitz, R. Epibacterial community patterns on marine macroalgae are host-specific but temporally variable. Environ. Microbiol. 13, 655–665 (2010).PubMed 
Article 

Google Scholar 
36.Pei, P. et al. Effects of biological water purification grid on microbial community of culture environment and intestine of the shrimp Litopenaeus vannamei. Aquac. Res. 50, 1300–1312 (2019).CAS 
Article 

Google Scholar 
37.Shade, A. & Handelsman, J. Beyond the Venn diagram: The hunt for a core microbiome. Environ. Microbiol. 14, 4–12 (2012).CAS 
PubMed 
Article 

Google Scholar 
38.Spoerner, M., Wichard, T., Bachhuber, T., Stratmann, J. & Oertel, W. Growth and thallus morphogenesis of Ulva mutabilis (chlorophyta) depends on a combination of two bacterial species excreting regulatory factors. J. Phycol. 48, 1433–1447 (2012).PubMed 
Article 
PubMed Central 

Google Scholar 
39.Kessler, R. W., Weiss, A., Kuegler, S., Hermes, C. & Wichard, T. Macroalgal–bacterial interactions: Role of dimethylsulfoniopropionate in microbial gardening by Ulva (Chlorophyta). Mol. Ecol. 27, 1808–1819 (2018).CAS 
PubMed 
Article 

Google Scholar 
40.Malmstrom, R. R., Kiene, R. P. & Kirchman, D. L. Identification and enumeration of bacteria assimilating dimethylsulfoniopropionate (DMSP) in the North Atlantic and Gulf of Mexico. Limnol. Oceanogr. 49, 597–606 (2004).ADS 
CAS 
Article 

Google Scholar 
41.Holmström, C., Egan, S., Franks, A., McCloy, S. & Kjelleberg, S. Antifouling activities expressed by marine surface associated Pseudoalteromonas species. FEMS Microbiol. Ecol. 41, 47–58 (2002).PubMed 
Article 

Google Scholar 
42.Holmström, C. & Kjelleberg, S. The effect of external biological factors on settlement of marine invertebrate and new antifouling technology. Biofouling 8, 147–160 (1994).Article 

Google Scholar 
43.Lachnit, T., Blümel, M., Imhoff, J. F. & Wahl, M. Specific epibacterial communities on macroalgae : Phylogeny matters more than habitat. Aquat. Biol. 5, 181–186 (2009).Article 

Google Scholar 
44.Fan, X. et al. The effect of nutrient concentrations, nutrient ratios and temperature on photosynthesis and nutrient uptake by Ulva prolifera : Implications for the explosion in green tides. J. Appl. Phycol. 26, 537–544 (2014).CAS 
Article 

Google Scholar 
45.Van Alstyne, K. L. Seawater nitrogen concentration and light independently alter performance, growth, and resource allocation in the bloom-forming seaweeds Ulva lactuca and Ulvaria obscura ( Chlorophyta ). Harmful Algae 78, 27–35 (2018).PubMed 
Article 
CAS 

Google Scholar 
46.Lachnit, T., Wahl, M. & Harder, T. Isolated thallus-associated compounds from the macroalga Fucus vesiculosus mediate bacterial surface colonization in the field similar to that on the natural alga. Biofouling 26, 247–255 (2010).CAS 
PubMed 
Article 

Google Scholar 
47.Su, H. et al. Persistence and spatial variation of antibiotic resistance genes and bacterial populations change in reared shrimp in South China. Environ. Int. 119, 327–333 (2018).CAS 
PubMed 
Article 

Google Scholar 
48.Ekwanzala, M. D., Dewar, J. B. & Momba, M. N. B. Environmental resistome risks of wastewaters and aquatic environments deciphered by shotgun metagenomic assembly. Ecotoxicol. Environ. Saf. 197, 110612 (2020).CAS 
PubMed 
Article 

Google Scholar 
49.Numberger, D. et al. Characterization of bacterial communities in wastewater with enhanced taxonomic resolution by full-length 16S rRNA sequencing. Sci. Rep. 9, 1–14 (2019).CAS 
Article 

Google Scholar 
50.Teklehaimanot, G. Z., Genthe, B., Kamika, I. & Momba, M. N. B. Prevalence of enteropathogenic bacteria in treated effluents and receiving water bodies and their potential health risks. Sci. Total Environ. 518–519, 441–449 (2015).ADS 
PubMed 
Article 
CAS 

Google Scholar 
51.Kelley, S. E. Experimental studies of the evolutionary significance of sexual reproduction. V. A field test of the sib-competition hypotheses. Evolution (N. Y). 43, 1066 (1989).52.Browne, L. & Karubian, J. Rare genotype advantage promotes survival and genetic diversity of a tropical palm. New Phytol. 218, 1658–1667 (2018).PubMed 
Article 

Google Scholar 
53.Gressler, V. et al. Lipid, fatty acid, protein, amino acid and ash contents in four Brazilian red algae species. Food Chem. 120, 585–590 (2010).CAS 
Article 

Google Scholar 
54.Gu, D. et al. Purification of R-phycoerythrin from Gracilaria lemaneiformis by centrifugal precipitation chromatography. J. Chromatogr. B Anal. Technol. Biomed. Life Sci. 1087–1088, 138–141 (2018).55.Su, Y. bin et al. Pyruvate cycle increases aminoglycoside efficacy and provides respiratory energy in bacteria. Proc. Natl. Acad. Sci. U. S. A. 115, E1578–E1587 (2018).56.Hollants, J., Leliaert, F., De Clerck, O. & Willems, A. What we can learn from sushi: A review on seaweed-bacterial associations. FEMS Microbiol. Ecol. 83, 1–16 (2013).CAS 
PubMed 
Article 

Google Scholar 
57.AQSIQ. Specifications for Oceanographic Survey. Part 4: Survey of Chemical Parameters in Sea Water. 16–26 (Standards Press of China, 2007).58.Burke, C., Kjelleberg, S. & Thomas, T. Selective extraction of bacterial DNA from the surfaces of macroalgae. Appl. Environ. Microbiol. 75, 252–256 (2009).CAS 
PubMed 
Article 

Google Scholar 
59.Xu, Y., Le, G. & Zhang, Y. Comparison with several methods to isolate epiphytic bacteria from Gracilaria lemaneiformis (Rhodophyta). Microbiol. China 34, 123–126 (2007).
Google Scholar 
60.Pei, P. et al. Analysis of the bacterial community composition of the epiphytes on diseased Gracilaria lemaneiformis using PCR-DGGE fingerprinting technology. J. Fish. Sci. China 25 (2018).61.Takahashi, S., Tomita, J., Nishioka, K., Hisada, T. & Nishijima, M. Development of a prokaryotic universal primer for simultaneous analysis of bacteria and archaea using next-generation sequencing. PLoS One 9 (2014).62.Bokulich, N. A. et al. Quality-filtering vastly improves diversity estimates from Illumina amplicon sequencing. Nat. Methods 10, 57–59 (2013).CAS 
PubMed 
Article 

Google Scholar 
63.Liu, T. et al. Joining Illumina paired-end reads for classifying phylogenetic marker sequences. BMC Bioinform. 21, 1–13 (2020).Article 

Google Scholar 
64.Edgar, R. C., Haas, B. J., Clemente, J. C., Quince, C. & Knight, R. UCHIME improves sensitivity and speed of chimera detection. Bioinformatics 27, 2194–2200 (2011).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
65.Edgar, R. C. UPARSE: Highly accurate OTU sequences from microbial amplicon reads. Nat. Methods 10, 996–998 (2013).CAS 
PubMed 
Article 

Google Scholar 
66.Cole, J. R. et al. Ribosomal database project: Data and tools for high throughput rRNA analysis. Nucleic Acids Res. 42, 633–642 (2014).Article 
CAS 

Google Scholar 
67.Quast, C. et al. The SILVA ribosomal RNA gene database project: Improved data processing and web-based tools. Nucleic Acids Res. 41, 590–596 (2013).Article 
CAS 

Google Scholar 
68.Wang, Y. et al. Comparison of the levels of bacterial diversity in freshwater, intertidal wetland, and marine sediments by using millions of illumina tags. Appl. Environ. Microbiol. 78, 8264–8271 (2012).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
69.Somerfield, P. J. Identification of the Bray-Curtis similarity index: Comment on Yoshioka (2008). Mar. Ecol. Prog. Ser. 372, 303–306 (2008).ADS 
Article 

Google Scholar 
70.Higgins, M. A., Robbins, G. A., Maas, K. R. & Binkhorst, G. K. Use of bacteria community analysis to distinguish groundwater recharge sources to shallow wells. J. Environ. Qual. 49, 1530–1540 (2020).CAS 
PubMed 
Article 

Google Scholar 
71.Yang, J., Ma, L., Jiang, H., Wu, G. & Dong, H. Salinity shapes microbial diversity and community structure in surface sediments of the Qinghai-Tibetan Lakes. Sci. Rep. 6, 6–11 (2016).ADS 
Article 
CAS 

Google Scholar 
72.Langille, M. G. I. et al. Predictive functional profiling of microbial communities using 16S rRNA marker gene sequences. Nat. Biotechnol. 31, 814–821 (2013).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar  More

1.Blackburn, T. M. et al. A proposed unified framework for biological invasions. Trends Ecol. Evol. 26, 333–339 (2011).PubMed 
Article 
PubMed Central 

Google Scholar 
2.Guisan, A. et al. Predicting species distributions for conservation decisions. Ecol. Lett. 16, 1424–1435 (2013).PubMed 
PubMed Central 
Article 

Google Scholar 
3.Richardson, D. M. Fifty Years of Invasion Ecology: The Legacy of Charles Elton. (John Wiley & Sons, 2011).4.Soberón, J. Grinnellian and Eltonian niches and geographic distributions of species. Ecol. Lett. 10, 1115–1123 (2007).PubMed 
Article 
PubMed Central 

Google Scholar 
5.Brown, J. H. Patterns, modes and extents of invasions by vertebrates. Biological Invasions: A Global Perspective. 85–110 (John Wiley & Sons, 1989).6.Holt, R. D., Barfield, M. & Gomulkiewicz, R. Theories of niche conservatism and evolution: could exotic species be potential tests. in: Species Invasions: Insights into Ecology, Evolution and Biogeography (eds. Sax, Stachowicz & Gaines) 259–290 (Sinauer Associates, Mass, 2005).7.Brown, J. H., Stevens, G. C. & Kaufman, D. M. The geographic range: size, shape, boundaries, and internal structure. Annu. Rev. Ecol. Syst. 27, 597–623 (1996).Article 

Google Scholar 
8.Sagarin, R. D., Gaines, S. D. & Gaylord, B. Moving beyond assumptions to understand abundance distributions across the ranges of species. Trends Ecol. Evol. 21, 524–530 (2006).PubMed 
Article 
PubMed Central 

Google Scholar 
9.Guisan, A., Petitpierre, B., Broennimann, O., Daehler, C. & Kueffer, C. Unifying niche shift studies: insights from biological invasions. Trends Ecol. Evol. 29, 260–269 (2014).PubMed 
Article 
PubMed Central 

Google Scholar 
10.Forsyth, D. M., Duncan, R. P., Bomford, M. & Moore, G. Climatic suitability, life-history traits, introduction effort, and the establishment and spread of introduced mammals in Australia. Conserv. Biol. 18, 557–569 (2004).Article 

Google Scholar 
11.Bomford, M., Kraus, F., Barry, S. C. & Lawrence, E. Predicting establishment success for alien reptiles and amphibians: a role for climate matching. Biol. Invasions 11, 713–724 (2009).Article 

Google Scholar 
12.Petitpierre, B. et al. Climatic niche shifts are rare among terrestrial plant invaders. Science 335, 1344–1348 (2012).ADS 
CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
13.Liu, C., Wolter, C., Xian, W. & Jeschke, J. M. Most invasive species largely conserve their climatic niche. Proc. Natl Acad. Sci. U.S.A. 117, 23643–23651 (2020).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
14.Pearman, P. B., Guisan, A., Broennimann, O. & Randin, C. F. Niche dynamics in space and time. Trends Ecol. Evol. 23, 149–158 (2008).PubMed 
Article 
PubMed Central 

Google Scholar 
15.González-Suárez, M., Bacher, S. & Jeschke, J. M. Intraspecific trait variation is correlated with establishment success of alien mammals. Am. Nat. 185, 737–746 (2015).PubMed 
Article 
PubMed Central 

Google Scholar 
16.Redding, D. W. et al. Location-level processes drive the establishment of alien bird populations worldwide. Nature https://doi.org/10.1038/s41586-019-1292-2 (2019).17.Titeux, N. et al. The need for large-scale distribution data to estimate regional changes in species richness under future climate change. Divers. Distrib. 23, 1393–1407 (2017).Article 

Google Scholar 
18.Chevalier, M., Broennimann, O., Cornuault, J., & Guisan, A. Data integration methods to account for spatial niche truncation effects in regional projections of species distribution. Ecol. Appl. (in press).19.Blackburn, T. M. & Duncan, R. P. Determinants of establishment success in introduced birds. Nature 414, 195–197 (2001).ADS 
CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
20.Bacon, S. J., Aebi, A., Calanca, P. & Bacher, S. Quarantine arthropod invasions in Europe: the role of climate, hosts and propagule pressure. Divers. Distrib. 20, 84–94 (2014).Article 

Google Scholar 
21.Abellán, P., Tella, J. L., Carrete, M., Cardador, L. & Anadón, J. D. Climate matching drives spread rate but not establishment success in recent unintentional bird introductions. Proc. Natl Acad. Sci. 114, 9385–9390 (2017).PubMed 
Article 
CAS 
PubMed Central 

Google Scholar 
22.Long, J. L. Introduced Mammals of the World: Their History, Distribution and Influence. (CSIRO PUBLISHING, 2003).23.Pulliam, H. R. On the relationship between niche and distribution. Ecol. Lett. 3, 349–361 (2000).Article 

Google Scholar 
24.Godsoe, W., Jankowski, J., Holt, R. D. & Gravel, D. Integrating biogeography with contemporary niche theory. Trends Ecol. Evol. 32, 488–499 (2017).PubMed 
Article 
PubMed Central 

Google Scholar 
25.Sax, D. F., Early, R. & Bellemare, J. Niche syndromes, species extinction risks, and management under climate change. Trends Ecol. Evol. 28, 517–523 (2013).PubMed 
Article 
PubMed Central 

Google Scholar 
26.Csergő, A. M. et al. Less favourable climates constrain demographic strategies in plants. Ecol. Lett. 20, 969–980 (2017).PubMed 
PubMed Central 
Article 

Google Scholar 
27.Capellini, I., Baker, J., Allen, W. L., Street, S. E. & Venditti, C. The role of life history traits in mammalian invasion success. Ecol. Lett. 18, 1099–1107 (2015).PubMed 
PubMed Central 
Article 

Google Scholar 
28.Sol, D., Bacher, S., Reader, S. M., & Lefebvre, L. Brain size predicts the success of mammal species introduced into novel environments. American Naturalist 172(S1), S63–S71 (2008).Article 

Google Scholar 
29.Duncan, R. P., Blackburn, T. M., Rossinelli, S. & Bacher, S. Quantifying invasion risk: the relationship between establishment probability and founding population size. Methods Ecol. Evol. 5, 1255–1263 (2014).Article 

Google Scholar 
30.Allen, C. R. et al. Predictors of regional establishment success and spread of introduced non-indigenous vertebrates. Glob. Ecol. Biogeogr. 22, 889–899 (2013).Article 

Google Scholar 
31.Cassey, P., Delean, S., Lockwood, J. L., Sadowski, J. S. & Blackburn, T. M. Dissecting the null model for biological invasions: A meta-analysis of the propagule pressure effect. PLoS Biol. 16, e2005987 (2018).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
32.Buswell, J. M., Moles, A. T. & Hartley, S. Is rapid evolution common in introduced plant species? J. Ecol. 99, 214–224 (2011).Article 

Google Scholar 
33.Broennimann, O., Mráz, P., Petitpierre, B., Guisan, A. & Müller-Schärer, H. Contrasting spatio-temporal climatic niche dynamics during the eastern and western invasions of spotted knapweed in North America. J. Biogeogr. 41, 1126–1136 (2014).Article 

Google Scholar 
34.Shea, K. & Chesson, P. Community ecology theory as a framework for biological invasions. Trends Ecol. Evol. 17, 170–176 (2002).Article 

Google Scholar 
35.Facon, B. et al. A general eco-evolutionary framework for understanding bioinvasions. Trends Ecol. Evol. 21, 130–135 (2006).PubMed 
Article 
PubMed Central 

Google Scholar 
36.Escobar, L. E., Qiao, H., Cabello, J. & Townsend Peterson, A. Ecological niche modeling re-examined: a case study with the Darwin’s fox. Ecol. Evolut. 8, 4757–4770 (2018).Article 

Google Scholar 
37.Petitpierre, B. et al. Will climate change increase the risk of plant invasions into mountains? Ecol. Appl. 26, 530–544 (2016).PubMed 
Article 
PubMed Central 

Google Scholar 
38.Pheloung, P. C., Williams, P. A. & Halloy, S. R. A weed risk assessment model for use as a biosecurity tool evaluating plant introductions. J. Environ. Manag. 57, 239–251 (1999).Article 

Google Scholar 
39.Pluess, T. et al. Which factors affect the success or failure of eradication campaigns against alien species? PLoS One 7, e48157 (2012).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
40.Pyšek, P. et al. MAcroecological Framework for Invasive Aliens (MAFIA): disentangling large-scale context dependence in biological invasions. NeoBiota 62, 407–461 (2020).Article 

Google Scholar 
41.Lonsdale, W. M. Global patterns of plant invasions and the concept of invasibility. Ecology 80, 1522 (1999).Article 

Google Scholar 
42.Leung, B. et al. TEASIng apart alien species risk assessments: a framework for best practices. Ecol. Lett. 15, 1475–1493 (2012).PubMed 
Article 
PubMed Central 

Google Scholar 
43.Fourcade, Y. Comparing species distributions modelled from occurrence data and from expert-based range maps. Implication for predicting range shifts with climate change. Ecol. Inform. 36, 8–14 (2016).Article 

Google Scholar 
44.Hijmans, R. J., Cameron, S. E., Parra, J. L., Jones, P. G. & Jarvis, A. Very high resolution interpolated climate surfaces for global land areas. Int. J. Climatol. 25, 1965–1978 (2005).Article 

Google Scholar 
45.Zomer, R. J., Trabucco, A., Bossio, D. A. & Verchot, L. V. Climate change mitigation: A spatial analysis of global land suitability for clean development mechanism afforestation and reforestation. Agriculture. Ecosyst. Environ. 126, 67–80 (2008).Article 

Google Scholar 
46.Bellard, C. et al. Will climate change promote future invasions? Glob. Chang. Biol. 19, 3740–3748 (2013).ADS 
PubMed 
PubMed Central 
Article 

Google Scholar 
47.Broennimann, O. et al. Measuring ecological niche overlap from occurrence and spatial environmental data. Glob. Ecol. Biogeogr. 21, 481–497 (2012).Article 

Google Scholar 
48.Cola, V. D. et al. ecospat: an R package to support spatial analyses and modeling of species niches and distributions. Ecography 40, 774–787 (2017).Article 

Google Scholar 
49.Hurlbert, A. H. & Jetz, W. Species richness, hotspots, and the scale dependence of range maps in ecology and conservation. Proc. Natl Acad. Sci. U.S.A. 104, 13384–13389 (2007).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
50.Plummer, M. JAGS: a program for analysis of Bayesian graphical models using Gibbs sampling. in Proceedings of the 3rd International Workshop on Distributed Statistical Computing (DSC 2003), March 20–22, Vienna, Austria. (2003).51.R Core Team. R: a language and environment for statistical computing. (2014).52.Su, Y.-S. & Yajima, M. R2jags: a package for running jags from R. (2013).53.Gelman, A. Prior distributions for variance parameters in hierarchical models (comment on article by Browne and Draper). Bayesian Anal. 1, 515–534 (2006).MathSciNet 
MATH 

Google Scholar 
54.Little, R. & Rubin, D. Statistical Analysis with Missing Data, Second Edition. (Wiley Series in Probability and Statistics, 2002).55.Gelman, A. & Rubin, D. B. Inference from iterative simulation using multiple sequences. Stat. Sci. 7, 457–472 (1992).MATH 

Google Scholar 
56.Gelman, A., Meng, X.-L. & Stern, H. Posterior predictive assessment of model fitness via realized discrepancies. Stat. Sin. 6, 733–760 (1996).MathSciNet 
MATH 

Google Scholar 
57.Allouche, O., Tsoar, A. & Kadmon, R. Assessing the accuracy of species distribution models: prevalence, kappa and the true skill statistic (TSS). J. Appl. Ecol. 43, 1223–1232 (2006).Article 

Google Scholar 
58.Guisan, A., Thuiller, W. & Zimmermann, N. E. Habitat Suitability and Distribution Models: With Applications in R. (Cambridge University Press, 2017).59.Broennimann, O., et al. Distance to native climatic niche margins explains establishment success of alien mammals. ecospat/NMI: NMI v1.0. Zenodo. https://doi.org/10.5281/zenodo.4588999. (2021). More

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain
the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in
Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles
and JavaScript. More