Accounting for niche truncation to improve spatial and temporal predictions of species distributions

Frontiers in Ecology and Evolution, Journal Year: 2022, Volume and Issue: 10

Published: Aug. 4, 2022

Species Distribution Models (SDMs) are essential tools for predicting climate change impact on species’ distributions and commonly employed as an informative tool which to base management conservation actions. Focusing only a part of the entire distribution species fitting SDMs is common approach. Yet, geographically restricting their range can result in considering subset ecological niche (i.e., truncation) could lead biased spatial predictions future effects, particularly if conditions belong those parts that have been excluded model fitting. The integration large-scale data encompassing whole with more regional improve but comes along challenges owing broader scale and/or lower quality usually associated these data. Here, we compare obtained from traditional SDM fitted dataset (Switzerland) methods combine European datasets several bird breeding Switzerland. Three models were fitted: based thus not accounting truncation, pooling where two merged without differences extent or resolution, downscaling hierarchical approach accounts resolution. Results show leads much larger predicted changes (either positively negatively) under than both methods. also identified different variables main drivers compared data-integration models. Differences between regarding outside existing when implied extrapolation). In conclusion, showed (i) calibrated restricted provide markedly (ii) at least partly explained by truncation. This suggests using accurate nuanced through better characterization realized niches.

Language: Английский

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Predicting climate change impacts on poikilotherms using physiologically guided species abundance models

Proceedings of the National Academy of Sciences, Journal Year: 2023, Volume and Issue: 120(15)

Published: April 3, 2023

Poikilothermic animals comprise most species on Earth and are especially sensitive to changes in environmental temperatures. Species conservation a changing climate relies upon predictions of responses future conditions, yet predicting change when temperatures exceed the bounds observed data is fraught with challenges. We present physiologically guided abundance (PGA) model that combines observations conditions laboratory-derived physiological response poikilotherms temperature predict geographical distributions change. The incorporates uncertainty thermal curves provides estimates habitat suitability extinction probability based site-specific conditions. show temperature-driven distributions, local extinction, cold, cool, warm-adapted vary substantially information incorporated. Notably, cold-adapted were predicted by PGA be extirpated 61% locations they currently inhabit, while extirpation was never correlative niche model. Failure account for species-specific constraints could lead unrealistic under warming climate, including underestimates near edges their space overoptimistic species.

Language: Английский

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Integrated community models: A framework combining multispecies data sources to estimate the status, trends and dynamics of biodiversity

Journal of Animal Ecology, Journal Year: 2023, Volume and Issue: 92(12), P. 2248 - 2262

Published: Oct. 25, 2023

Abstract Data deficiencies among rare or cryptic species preclude assessment of community‐level processes using many existing approaches, limiting our understanding the trends and stressors for large numbers species. Yet evaluating dynamics whole communities, not just common charismatic species, is critical to responses biodiversity ongoing environmental pressures. A recent surge in both public science government‐funded data collection efforts has led a wealth data. However, these programmes use wide range sampling protocols (from unstructured, opportunistic observations wildlife well‐structured, design‐based programmes) record information at variety spatiotemporal scales. As result, available vary substantially quantity content, which must be carefully reconciled meaningful ecological analysis. Hierarchical modelling, including single‐species integrated models hierarchical community models, improved ability assess predict processes. Here, we highlight emerging ‘integrated modelling’ framework that combines integration modelling improve inferences on species‐ dynamics. We illustrate with series worked examples. Our three case studies demonstrate how can used extend geographic scope when distributions richness patterns; discern population over time; estimate demographic rates growth communities sympatric implemented examples multiple software methods through R platform via packages formula‐based interfaces development custom code JAGS, NIMBLE Stan. Integrated provide an exciting approach model biological observational types sources simultaneously, thus accounting uncertainty error within unified framework. By leveraging combined benefits produce valuable about as well dynamics, allowing holistic evaluation effects global change biodiversity.

Language: Английский

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Lessons to be learned by comparing integrated fisheries stock assessment models (SAMs) with integrated population models (IPMs)

Fisheries Research, Journal Year: 2024, Volume and Issue: 272, P. 106925 - 106925

Published: Jan. 5, 2024

Integrated fisheries stock assessment models (SAMs) and integrated population (IPMs) are used in biological ecological systems to estimate abundance demographic rates. The approaches fundamentally very similar, but historically have been considered as separate endeavors, resulting a loss of shared vision, practice progress. We review the two identify similarities differences, with view identifying key lessons that would benefit more generally overarching topic ecology. present case study for each SAM (snapper from west coast New Zealand) IPM (woodchat shrikes Germany) highlight differences similarities. between SAMs IPMs appear be objectives parameter estimates required meet these objectives, size spatial scale populations, differing availability various types data. In addition, up now, typical applied aquatic habitats, while most stem terrestrial habitats. aim assess level sustainable exploitation fish so absolute or biomass must estimated, although some only relative trends. Relative is often sufficient understand dynamics inform conservation actions, which main objective IPMs. small populations concern, where uncertainty can important, conveniently implemented using Bayesian approaches. typically at moderate scales (1 104 km2), possibility collecting detailed longitudinal individual data, whereas large, economically valuable stocks large (104 106 km2) limited There sense data- (or information-) hungry than an because its goal abundance, data rates difficult obtain (often marine) applied. therefore require 'tuning' assumptions IPMs, 'data speak themselves', consequently techniques such weighting model evaluation nuanced being fit disaggregated quantify variation allow richer inference on processes. attempts example by unconditional capture-recapture

Language: Английский

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Finding the right fit: Comparative cetacean distribution models using multiple data sources and statistical approaches

Diversity and Distributions, Journal Year: 2018, Volume and Issue: 24(11), P. 1657 - 1673

Published: June 12, 2018

Abstract Aim Accurate predictions of cetacean distributions are essential to their conservation but limited by statistical challenges and a paucity data. This study aimed at comparing the capacity various algorithms deal with biases commonly found in nonsystematic surveys evaluate potential for citizen science data improve habitat modelling predictions. An endangered population humpback whales ( Megaptera novaeangliae ) breeding ground was used as case study. Location New Caledonia, Oceania. Methods Five were model preferences from 1,360 sightings collected over 14 years research surveys. Three different background sampling approaches tested when developing models 625 crowdsourced assess methods accounting spatial bias. Model evaluation conducted through cross‐validation prediction an independent satellite tracking dataset. Results Algorithms differed complexity environmental relationships modelled, ecological interpretability transferability. While parameter tuning had great effect on performances, GLM s generally low predictive performance, SVM particularly hard interpret, BRT high descriptive power showed signs overfitting. MAXENT especially GAM provided valuable trade‐off, accurate ecologically intelligible. Models that favoured cool (22–23°C) shallow waters (0–100 m deep) coastal well offshore areas. Citizen converged survey models, specifically Main conclusions Marine megafauna distribution present specific may be addressed integrative evaluation, testing appropriately tuned algorithms. Specifically, controlling overfitting is priority predicting large‐scale perspectives. appear powerful tool describe habitat.

Language: Английский

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