Coding for Life: Designing a Platform for Projecting and Protecting Global Biodiversity

Urban, Mark C.; Travis, Justin; Zurell, Damaris; Thompson, Patrick L.; Synes, Nicholas W.; Scarpa, Alice; Peres‐Neto, Pedro R.; Malchow, Anne-Kathleeen; James, Patrick M. A.; Gravel, Dominique; Meester, Luc De; Brown, Calum; Bocedi, Greta; Albert, Cécile H.; Gonzalez, Andrew; Hendry, Andrew P.

doi:10.1093/biosci/biab099

Cited by 37 publications

(49 citation statements)

References 77 publications

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“…Other findings relate to further necessary development. This model, and land use models in general, will have greater utility as they become more closely aligned with biodiversity outcomes, in particular by more fully assessing the role of land management and climate in driving either declines or recovery in terrestrial biodiversity (Leclère et al., 2020; Rounsevell et al., 2018; Urban et al., 2021). More realistic assessment of land‐based climate change mitigation is also a priority (Estoque et al., 2020).…”

Section: Discussionmentioning

confidence: 99%

Agent‐Based Modeling of Alternative Futures in the British Land Use System

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Section: Discussionmentioning

confidence: 99%

Agent‐Based Modeling of Alternative Futures in the British Land Use System

et al. 2022

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“…Though we have not found studies to have tackled it through mechanistic approaches, this seems achievable as mechanistic land-use models that consider climate input have been already coupled with mechanistic biodiversity models (see Synes et al 2019combining RangeShifter, Bocedi et al, 2014, with CRAFTY, Murray-Rust et al, 2014a. Furthermore, an avenue to explore such indirect effects at regional level is becoming more feasible as mechanistic land-use models that incorporate climate scenarios are being applied to larger extents (Brown et al 2021).…”

Section: Integrating Climate-driven Land-use Change Into Biodiversity...mentioning

confidence: 99%

“…3). This would account for emergent interactions between both systems, something that has been recently called for (Urban et al, 2021). Therefore, the current knowledge of land-use effects is in fact mostly based on the unidirectional effect from land use on biodiversity.…”

Section: Integrating Climate-driven Land-use Change Into Biodiversity...mentioning

confidence: 99%

“…Data harmonization and standard formats should be also strived across biodiversity models. This means to implement models that consider input and generate output matching current trends in empirical biodiversity assessments to follow the Essential Biodiversity Variables (EBVs) framework (Pereira et al, 2013;Urban et al, 2021). This should promote a better integration across models and data-model integration.…”

Section: Directions To Modelling Developmentsmentioning

confidence: 99%

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The road to integrate climate change effects on land-use change in regional biodiversity models

Cabral

Mendoza‐Ponce

Silva

et al. 2022

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1. Current modelling approaches to predict spatially explicit biodiversity responses to climate change mainly focus on the direct effects of climate on species. Integration of spatiotemporal land-cover scenarios is still limited. Current approaches either regard land cover as constant boundary conditions, or rely on general, typically globally defined land-use scenarios. This is problematic as it disregards the complex synergistic effects of climate and land use on biodiversity at the regional scale, as biophysical, economic, and social issues important for regional land-use decisions are also affected by climate change. To realistically predict climate impacts on biodiversity, it is therefore necessary to consider both, the direct effect of climate change on biodiversity, and its indirect effect on biodiversity via land-use change. 2. In this review and perspective paper, we outline how biodiversity models could be better integrated with regional, climate-driven land-use models. We provide an overview of empirical and modelling approaches to both land-use (LU) and biodiversity (BD) change, focusing on how integration has been attempted. We then analyse how LU and BD model properties, such as scales, inputs, and outputs, can be matched and identify potential integration challenges and opportunities. 3. We found LU integration in BD models has been frequently attempted. By contrast, integrating the role of BD in models of LU decisions is largely lacking. As a result, bi-directional effects remain largely understudied. Only few integrated LU-BD socio-ecological models have assessed climate change effects on LU and no study has yet investigated the relative contribution of direct vs. indirect effects of climate change on BD. 4. There is a large potential for model integration given the overlap on spatial scales, although challenges remain with respect to spatial scale, temporal dynamics, investigation of indirect effects, and bi-directionality, including feeding back to climate models. Efforts to better understand human decisions, eco-evolutionary dynamics, connection between terrestrial and aquatic systems, and format standardization of modelling outputs and empirical data should improve future models. Integrating biodiversity feedbacks into land-use and climate models requires modelling innovations, but should be feasible.

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“…These range dynamics result from an interplay of key ecological processes such as local population dynamics and dispersal, which are widely considered to be influenced by the environment [6, 7]. An improved, model-based understanding of how climate affects range and population dynamics through these key processes is needed to better explain and predict the observed responses [8, 9]. Such insights can further form a quantitative, science-guided basis for deriving effective conservation measures to mitigate biodiversity loss [10].…”

Section: Introductionmentioning

confidence: 99%

Demography-environment relationships improve mechanistic understanding of range dynamics under climate change

Malchow

Härtig

Reeg

et al. 2022

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Species responses to climate change are widely detected as range and abundance changes. To better explain and predict them, we need a mechanistic understanding of how the underlying demographic processes are shaped by climatic conditions. We built spatially-explicit, process-based models for eight Swiss breeding bird populations. They jointly consider dispersal, population dynamics and the climate-dependence of three demographic processes - juvenile survival, adult survival and fecundity. The models were calibrated to two-decade abundance time-series in a Bayesian framework. We assessed goodness-of-fit and discriminatory power of the models with different metrics, indicating fair to excellent model fit. The most influential climatic predictors for population performance were the mean breeding-season temperature and the total winter precipitation. Maps of overall growth rate highlighted demographically suitable areas. Further, benefits from contemporary climate change were detected for typical mountain birds, whereas lowland birds were adversely affected. Embedding generic process-based models in a solid statistical framework improves our mechanistic understanding of range dynamics and allows disentangling the underlying abiotic and biotic processes. For future research, we advocate a stronger integration of experimental and empirical measurements and more detailed predictors in order to generate precise insights into the processes by which climate affects populations.

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Coding for Life: Designing a Platform for Projecting and Protecting Global Biodiversity

Cited by 37 publications

References 77 publications

Agent‐Based Modeling of Alternative Futures in the British Land Use System

Agent‐Based Modeling of Alternative Futures in the British Land Use System

The road to integrate climate change effects on land-use change in regional biodiversity models

Demography-environment relationships improve mechanistic understanding of range dynamics under climate change

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