Summary
Forests encompass enormous biodiversity and provide a wealth of ecosystem services responsible for the health, well-being, and livelihoods of humans worldwide. As the climate changes, trees are expected to experience unique climate conditions far exceeding their native ranges—a situation compounded by the proliferation of non-native species worldwide. Yet there remain few approaches for reliably projecting how forests will change over the coming century, in part because current models struggle to predict how groups of species will respond. The goal of this project is to overcome these limitations by pioneering a fundamentally new modelling approach to forecasting how communities—rather than single species—will respond to the twin threats of climate change and invasive species. To do this, the proposed work will incorporate a functional and abiotic backbone into a theoretical model of community-level coexistence, overcoming the key limitation of traditional species distribution models. By applying this model to high-resolution forest inventory data, we will quantify how species' traits interact with abiotic conditions, management history, and disturbance regimes to govern the composition and resilience of forests across North America. As a result, this approach will allow us to identify: (1) how functional traits shape forest community composition, (2) how abiotic conditions affect these relationships, (3) how management history, disturbance, and extreme events mediate co-occurrence, (4) how forest communities will change over the coming decades, (5) how native and non-native species' ranges will respond, and (6) the cascading effects on biodiversity and ecosystem function. By providing robust projections of forest change across North America, these results will directly inform management efforts to foster resilient forests, while also pioneering a new generation of models for understanding how ecosystems will respond to environmental change.
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More information & hyperlinks
| Web resources: | https://cordis.europa.eu/project/id/101164911 |
| Start date: | 01-01-2025 |
| End date: | 31-12-2029 |
| Total budget - Public funding: | 1 498 147,50 Euro - 1 498 147,00 Euro |
Cordis data
Original description
Forests encompass enormous biodiversity and provide a wealth of ecosystem services responsible for the health, well-being, and livelihoods of humans worldwide. As the climate changes, trees are expected to experience unique climate conditions far exceeding their native ranges—a situation compounded by the proliferation of non-native species worldwide. Yet there remain few approaches for reliably projecting how forests will change over the coming century, in part because current models struggle to predict how groups of species will respond. The goal of this project is to overcome these limitations by pioneering a fundamentally new modelling approach to forecasting how communities—rather than single species—will respond to the twin threats of climate change and invasive species. To do this, the proposed work will incorporate a functional and abiotic backbone into a theoretical model of community-level coexistence, overcoming the key limitation of traditional species distribution models. By applying this model to high-resolution forest inventory data, we will quantify how species' traits interact with abiotic conditions, management history, and disturbance regimes to govern the composition and resilience of forests across North America. As a result, this approach will allow us to identify: (1) how functional traits shape forest community composition, (2) how abiotic conditions affect these relationships, (3) how management history, disturbance, and extreme events mediate co-occurrence, (4) how forest communities will change over the coming decades, (5) how native and non-native species' ranges will respond, and (6) the cascading effects on biodiversity and ecosystem function. By providing robust projections of forest change across North America, these results will directly inform management efforts to foster resilient forests, while also pioneering a new generation of models for understanding how ecosystems will respond to environmental change.Status
SIGNEDCall topic
ERC-2024-STGUpdate Date
24-11-2024
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