Outstanding Challenges in the Transferability of Ecological Models

Trends in Ecology & Evolution, Journal Year: 2018, Volume and Issue: 33(10), P. 790 - 802

Published: Aug. 28, 2018

Predictive models are central to many scientific disciplines and vital for informing management in a rapidly changing world. However, limited understanding of the accuracy precision transferred novel conditions (their 'transferability') undermines confidence their predictions. Here, 50 experts identified priority knowledge gaps which, if filled, will most improve model transfers. These summarized into six technical fundamental challenges, which underlie combined need intensify research on determinants ecological predictability, including species traits data quality, develop best practices transferring models. Of high importance is identification widely applicable set transferability metrics, with appropriate tools quantify sources impacts prediction uncertainty under conditions.

Language: Английский

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Iterative near-term ecological forecasting: Needs, opportunities, and challenges

Proceedings of the National Academy of Sciences, Journal Year: 2018, Volume and Issue: 115(7), P. 1424 - 1432

Published: Jan. 30, 2018

Two foundational questions about sustainability are “How ecosystems and the services they provide going to change in future?” do human decisions affect these trajectories?” Answering requires an ability forecast ecological processes. Unfortunately, most forecasts focus on centennial-scale climate responses, therefore neither meeting needs of near-term (daily decadal) environmental decision-making nor allowing comparison specific, quantitative predictions new observational data, one strongest tests scientific theory. Near-term opportunity iteratively cycle between performing analyses updating light evidence. This iterative process gaining feedback, building experience, correcting models methods is critical for improving forecasts. Iterative, forecasting will accelerate research, make it more relevant society, inform sustainable under high uncertainty adaptive management. Here, we identify immediate societal needs, opportunities, challenges forecasting. Over past decade, data volume, variety, accessibility have greatly increased, but remain interoperability, latency, quantification. Similarly, ecologists made considerable advances applying computational, informatic, statistical methods, opportunities exist forecast-specific theory, cyberinfrastructure. Effective also require changes training, culture, institutions. The need start now; time making ecology predictive here, learning by doing fastest route drive science forward.

Language: Английский

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A comprehensive evaluation of predictive performance of 33 species distribution models at species and community levels

Ecological Monographs, Journal Year: 2019, Volume and Issue: 89(3)

Published: May 2, 2019

Abstract A large array of species distribution model ( SDM ) approaches has been developed for explaining and predicting the occurrences individual or assemblages. Given wealth existing models, it is unclear which models perform best interpolation extrapolation data sets, particularly when one concerned with We compared predictive performance 33 variants 15 widely applied recently emerged s in context multispecies data, including both joint that multiple together, stacked each individually combining predictions afterward. offer a comprehensive evaluation these by examining their withheld empirical validation different sizes representing five taxonomic groups, prediction tasks related to extrapolation. measure 12 measures accuracy, discrimination power, calibration, precision predictions, biological levels occurrence, richness, community composition. Our results show variation among performance, especially communities comprising many are rare. The do not reveal any major trade‐offs performance; same performed generally well terms discrimination, species, In contrast, gave most precise were calibrated, suggesting poorly performing can make overconfident predictions. However, none all tasks. As general strategy, we therefore propose researchers fit small set showing complementary then apply cross‐validation procedure involving separate establish performs goal study.

Language: Английский

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Machine-learning phase prediction of high-entropy alloys

Acta Materialia, Journal Year: 2019, Volume and Issue: 169, P. 225 - 236

Published: March 15, 2019

Language: Английский

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A practical guide to selecting models for exploration, inference, and prediction in ecology

Ecology, Journal Year: 2021, Volume and Issue: 102(6)

Published: March 12, 2021

Abstract Selecting among competing statistical models is a core challenge in science. However, the many possible approaches and techniques for model selection, conflicting recommendations their use, can be confusing. We contend that much confusion surrounding selection results from failing to first clearly specify purpose of analysis. argue there are three distinct goals modeling ecology: data exploration, inference, prediction. Once goal articulated, an appropriate procedure easier identify. review highlight strengths weaknesses relative each goals. then present examples prediction using time series butterfly population counts. These show how approach flows naturally goal, leading different selected purposes, even with exactly same set. This illustrates best practices ecologists should serve as reminder recipes cannot substitute critical thinking or use independent test hypotheses validate predictions.

Language: Английский

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Responses of ant communities to disturbance: Five principles for understanding the disturbance dynamics of a globally dominant faunal group

Journal of Animal Ecology, Journal Year: 2018, Volume and Issue: 88(3), P. 350 - 362

Published: Oct. 3, 2018

Abstract Ecological disturbance is fundamental to the dynamics of biological communities, yet a conceptual framework for understanding responses faunal communities remains elusive. Here, I propose five principles ants—a globally dominant group that widely used as bioindicators in land management, which appear have wide applicability other taxa. These are follows: (1) The most important effects habitat on ants typically indirect, through its structure, microclimate, resource availability and competitive interactions; (2) openness key driver variation ant communities; (3) species large degree determined by their openness; (4) same will different habitats, because impacts (5) community vary according functional composition biogeographical history relation openness. illustrate these using results primarily from studies fire, agent globally, provide common currency comparative analysis. argue many also apply groups so can be considered general ecological “laws.” As case ants, fundamentally related openness, it it.

Language: Английский

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Mutualistic networks: moving closer to a predictive theory

Ecology Letters, Journal Year: 2019, Volume and Issue: 22(9), P. 1517 - 1534

Published: June 26, 2019

Abstract Plant–animal mutualistic networks sustain terrestrial biodiversity and human food security. Global environmental changes threaten these networks, underscoring the urgency for developing a predictive theory on how respond to perturbations. Here, I synthesise theoretical advances towards predicting network structure, dynamics, interaction strengths responses find that mathematical models incorporating biological mechanisms of interactions provide better predictions dynamics. Those include trait matching, adaptive foraging, dynamic consumption production both resources services provided by mutualisms. Models species traits predict potential structure (fundamental niche), while based dynamics abundances, rewards, foraging preferences reproductive can extremely realised structures may successfully From theoretician's standpoint, model development must more realistically represent empirical data strengths, population vary with perturbations from global change. an empiricist's needs make specific be tested observation or experiments. Developing using short‐term allows longer term community As become available, rigorous tests will improve.

Language: Английский

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Conceptual and methodological advances in habitat‐selection modeling: guidelines for ecology and evolution

Ecological Applications, Journal Year: 2021, Volume and Issue: 32(1)

Published: Oct. 9, 2021

Abstract Habitat selection is a fundamental animal behavior that shapes wide range of ecological processes, including movement, nutrient transfer, trophic dynamics and population distribution. Although habitat has been focus studies for decades, technological, conceptual methodological advances over the last 20 yr have led to surge in addressing this process. Despite substantial literature focused on quantifying habitat‐selection patterns animals, there marked lack guidance best analytical practices. The foundations most commonly applied modeling frameworks can be confusing even those well versed their application. Furthermore, yet synthesis made yr. Therefore, need both current state knowledge selection, seeking study Here, we provide an approachable overview analyses (HSAs) conducted using functions, which are by far framework understanding This review purposefully non‐technical without heavy mathematical statistical notation, confuse many practitioners. We offer history HSAs, describing tortuous path our understanding. Through overview, also aim address areas greatest confusion literature. synthesize outlining exciting field modeling, discussing evolutionary inference contemporary techniques. paper clarity navigating complex HSAs while acting as reference practices guide

Language: Английский

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Prediction in ecology: a first‐principles framework

Ecological Applications, Journal Year: 2017, Volume and Issue: 27(7), P. 2048 - 2060

Published: June 24, 2017

Abstract Quantitative predictions are ubiquitous in ecology, yet there is limited discussion on the nature of prediction this field. Herein I derive a general quantitative framework for analyzing and partitioning sources uncertainty that control predictability. The implications assessed conceptually linked to classic questions such as relative importance endogenous (density‐dependent) vs. exogenous factors, stability drift, spatial scaling processes. used make number novel reframe approaches experimental design, model selection, hypothesis testing. Next, application uncertainties illustrated using short‐term forecast net ecosystem exchange. Finally, advocate new comparative approach studying predictability across different ecological systems processes lay out hypotheses about what limits how these should scale space time.

Language: Английский

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Parasite vulnerability to climate change: an evidence-based functional trait approach

Royal Society Open Science, Journal Year: 2017, Volume and Issue: 4(1), P. 160535 - 160535

Published: Jan. 1, 2017

Despite the number of virulent pathogens that are projected to benefit from global change and spread in next century, we suggest a combination coextinction risk climate sensitivity could make parasites at least as extinction prone any other trophic group. However, existing interdisciplinary toolbox for identifying species threatened by is inadequate or inappropriate when considering conservation targets. A functional trait approach can be used connect parasites' ecological role their disappearance, but this complicated taxonomic diversity many parasite clades. Here, propose biological traits may render particularly vulnerable (including high host specificity, complex life cycles narrow climatic tolerance), identify critical gaps our knowledge biology ecology. By doing so, provide criteria triage efforts.

Language: Английский

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