in all months, and mean precipitation increased in most months (Fig. 2a). 68Spatial variability in climatic change (Fig. 2b,c), necessitates local matching of phenological 69 and climatic datasets rather than the use of regionally-averaged climate data (e.g. Central 70England Temperatures) or large-scale climatic indicators (e.g. North Atlantic Oscillation). 71We did not make the restrictive assumption that biological events would be related to annual CSP precip varied less among trophic levels than the upper limit (Fig. 3d,f) consumers were less than those for primary consumers (Fig. 5a). This occurred because, 195averaged across species, the opposing climate responses of primary producers and secondary 196consumers are more similar in magnitude than are those for primary consumers (Fig. 3), 197 effectively "cancelling each other out". Our models suggest greater average advances for 198 crustacea, fish and insects than for other groups, such as freshwater phytoplankton, birds and 199 mammals (Fig. 5b). However, response-variation is high for crustacea (Fig. 5b). not estimated for marine plankton data (see above), and so the second-phase LME models 441 were run twice: once to examine correlations with temperature and precipitation for all but 442 the marine plankton phenological series (9,800 series), and once to examine only correlations 443 with temperature for the whole data set (10,003 series).

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With the expansion in the quantity and types of biodiversity data being collected, there is a need to find ways to combine these different sources to provide cohesive summaries of species' potential and realized distributions in space and time. Recently, model-based data integration has emerged as a means to achieve this by combining datasets in ways that retain the strengths of each. We describe a flexible approach to data integration using point process models, which provide a convenient way to translate across ecological currencies. We highlight recent examples of large-scale ecological models based on data integration and outline the conceptual and technical challenges and opportunities that arise. Species Distribution Models in EcologyLarge-scale ecological models of how species distributions and abundances vary over space and time are a critical tool in macroecology, biogeography, and conservation biology. They underpin our understanding of how biodiversity is shaped, how it is responding to anthropogenic activities, and how it might change in the future [1][2][3]. There is now a substantial literature on statistical tools for building species distribution models (SDMs) (see Glossary) and best practice in how to fit them [4][5][6][7]. SDMs also form a building block upon which more complex models, incorporating occupancy and/or abundance in space and time, can be built [8,9].

Understanding the effects of warming on greenhouse gas feedbacks to climate change represents a major global challenge. Most research has focused on direct effects of warming, without considering how concurrent changes in plant communities may alter such effects. Here, we combined vegetation manipulations with warming to investigate their interactive effects on greenhouse gas emissions from peatland. We found that although warming consistently increased respiration, the effect on net ecosystem CO2 exchange depended on vegetation composition. The greatest increase in CO2 sink strength after warming was when shrubs were present, and the greatest decrease when graminoids were present. CH4 was more strongly controlled by vegetation composition than by warming, with largest emissions from graminoid communities. Our results show that plant community composition is a significant modulator of greenhouse gas emissions and their response to warming, and suggest that vegetation change could alter peatland carbon sink strength under future climate change.

Abstract. Understanding how plant species coexist in tropical rainforests is one of the biggest challenges in community ecology. One prominent hypothesis suggests that rare species are at an advantage because trees have lower survival in areas of high conspecific density due to increased attack by natural enemies, a process known as negative density dependence (NDD). A consensus is emerging that NDD is important for plant-species coexistence in tropical forests. Most evidence comes from short-term studies, but testing the prediction that NDD decreases the spatial aggregation of tree populations provides a long-term perspective. While spatial distributions have provided only weak evidence for NDD so far, the opposing effects of environmental heterogeneity might have confounded previous analyses. Here we use a novel statistical technique to control for environmental heterogeneity while testing whether spatial aggregation decreases with tree size in four tropical forests. We provide evidence for NDD in 22% of the 139 tree species analyzed and show that environmental heterogeneity can obscure the spatial signal of NDD. Environmental heterogeneity contributed to aggregation in 84% of species. We conclude that both biotic interactions and environmental heterogeneity play crucial roles in shaping tree dynamics in tropical forests.