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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Treating gaps and biases in biodiversity data as a missing data problem

Biological reviews/Biological reviews of the Cambridge Philosophical Society, Journal Year: 2024, Volume and Issue: unknown

Published: Aug. 8, 2024

ABSTRACT Big biodiversity data sets have great potential for monitoring and research because of their large taxonomic, geographic temporal scope. Such become especially important assessing changes in species' populations distributions. Gaps the available data, spatial gaps, often mean that are not representative target population. This hinders drawing large‐scale inferences, such as about trends, may lead to misplaced conservation action. Here, we conceptualise gaps a missing problem, which provides unifying framework challenges solutions across different types sets. We characterise typical classes then use theory explore implications questions trends factors affecting occurrences/abundances. By using this framework, show bias due can arise when sampling and/or availability overlap with those species. But set per se is biased. The outcome depends on ecological question statistical approach, determine choices around sources variation taken into account. argue approaches long‐term species trend modelling susceptible since models do tend account driving missingness. To identify general review empirical studies simulation compare some most frequently employed deal including subsampling, weighting imputation. All these methods reduce but come at cost increased uncertainty parameter estimates. Weighting techniques arguably least used so far ecology both variance Regardless method, ability critically knowledge of, on, creating gaps. outline necessary considerations dealing stages collection analysis workflow.

Language: Английский

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MIAU: An analysis-ready dataset on presence-only and presence-absence data of Neotropical carnivores (Mammalia, Carnivora) from 2000 to 2021

Nature Conservation, Journal Year: 2025, Volume and Issue: 58, P. 11 - 30

Published: Jan. 20, 2025

In the last decade, databases of records species observed at same location different points in time over large spatial extents have been made available. Unfortunately, these sources are scarce regions such as Latin America. We present a dataset 60,179 point occurrences (i.e. presence-only data, PO) and 45,468 camera-trap survey presence-absence PA) for 63 carnivores Neotropical Region from 2000 to 2021. collated data various sources, including 64 newly-digitised bibliographic references. cleaned, taxonomically harmonised standardised following Darwin Core Humboldt standards them here csv files. also fit analyses by aggregating into two periods (time1: 2000–2013 time2: 2014–2021), with PO grid cell counts 100 × km PA polygons varying size, presented geopackage These can be used large-scale distribution models, calculation population trends, extinction risk educational purposes.

Language: Английский

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Differences in predictions of marine species distribution models based on expert maps and opportunistic occurrences

Conservation Biology, Journal Year: 2025, Volume and Issue: unknown

Published: March 24, 2025

Species distribution models (SDMs) are important tools for assessing biodiversity change. These require high-quality occurrence data, which not always available. Therefore, it is increasingly to determine how data choice affects predictions of species' ranges. Opportunistic records and expert maps both widely used sources species SDMs. However, unclear SDMs based on these differ in performance, particularly the marine realm. We built 233 fish from 2 families with types compared their performances potential predictions. occurrences were sourced field surveys South China Sea online repositories International Union Conservation Nature Red List database. generalized linear explore drivers differences prediction between model types. When projecting distinct regions no calibrated using opportunistic performed better than those maps, indicating transferability new environments. Differences predictor values accounted dissimilarity predictions, likely because included large areas unsuitable environmental conditions. Dissimilarity levels among differed, suggesting a taxonomic bias sources. Our findings highlight sensitivity distributional data. Although have an role modeling, we suggest researchers assess accuracy reduce commission errors knowledge target species.

Language: Английский

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A continental-wide decline of occupancy and diversity in five Neotropical carnivores

Global Ecology and Conservation, Journal Year: 2024, Volume and Issue: 55, P. e03226 - e03226

Published: Sept. 28, 2024

Language: Английский

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Reshaping biogeography: Perspectives on the past, present and future

Journal of Biogeography, Journal Year: 2023, Volume and Issue: 50(8), P. 1405 - 1408

Published: July 8, 2023

and macroecology originated in a novel top-down statistical view (Brown & Maurer, 1989), to name but few.We are an age of innovationduringwhichtherapidemergenceofnewtechniquescan provide unparalleled information from the smallest largest spatial scales, individuals communities, seconds tomillennia.Moreover,acquireddataaremorenumerousandmore accessiblethaneverbefore-evenbeyondtraditionalresearchcommunities, many cases unprecedentedly vast increasingly globalepistemiccommunities-andtheorymorerefined.

Language: Английский

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Spatio‐temporal integrated Bayesian species distribution models reveal lack of broad relationships between traits and range shifts

Global Ecology and Biogeography, Journal Year: 2024, Volume and Issue: 33(5)

Published: Feb. 26, 2024

Abstract Aim Climate change and habitat loss or degradation are some of the greatest threats that species face today, often resulting in range shifts. Species traits have been discussed as important predictors shifts, with identification general trends being great interest to conservation efforts. However, studies reviewing relationships between shifts questioned existence such generalized trends, due mixed results weak correlations, well analytical shortcomings. The aim this study was test relationship empirically, using approaches account for common sources bias when assessing trends. Location Tanzania, East Africa. Time period 1980–1999 2000–2020. Major taxa studied 57 savannah specialist birds found belonging 26 families 11 orders. Methods We applied recently developed integrated spatio‐temporal distribution models R‐INLA, combining citizen science bird Atlas data estimate ranges species, quantify predictive power traditional trait groups, exposure‐related sensitivity traits. based our on 40 years observations African savannahs, a biome has experienced increasing climatic non‐climatic pressures over recent decades. correlated patterns linear regression models. Results find indications identified by previous research, but low average explanatory from an ecological perspective, confirming lack meaningful associations. analysis finds compelling species‐specific results. Main conclusions highlight importance individual assessments while demonstrating usefulness approach analyses

Language: Английский

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Estimating species distribution from camera trap by‐catch data, using jaguarundi (Herpailurus yagouaroundi) as an example

Diversity and Distributions, Journal Year: 2024, Volume and Issue: 30(10)

Published: April 12, 2024

Abstract Aim Planning conservation action requires accurate estimates of abundance and distribution the target species. For many mammals, particularly those inhabiting tropical forests, there are insufficient data to assess their status. We present a framework for predicting species using jaguarundi ( Herpailurus yagouaroundi ), poorly known felid which basic information on is lacking. Location Mesoamerica South America. Time Period From 2003 2021. Taxa yagouaroundi. Methods combined camera‐trap from multiple sites used an occupancy modelling accounting imperfect detection identify habitat associations predict range‐wide jaguarundis. Results Our model predicted that probability positively associated with rugged terrain, herbaceous cover, human night‐time light intensity. Jaguarundi was be higher where precipitation less seasonal, at intermediate levels diurnal temperature range. camera also revealed additional detections jaguarundis beyond current International Union Conservation Nature (IUCN) range distribution, including Andean foothills Colombia Bolivia. Main Conclusion Occupancy low throughout much Amazonian lowlands, vast area centre Further work required investigate whether this represents sub‐optimal conditions Overall, we estimate crude global population 35,000 230,000 individuals, covering 4,453,406 km 2 Meso‐ America 0.5 level occupancy. allows initially detailed, well‐informed should challenged refined improved layers records detection. encourage similar studies lesser‐known pooling existing by‐catch growing bank surveys around world.

Language: Английский

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Habitat for Coilia nasus in southern Zhejiang Province, China, based on a maximum entropy model

Scientific Reports, Journal Year: 2024, Volume and Issue: 14(1)

Published: Aug. 20, 2024

As an important fishery resource and endangered species, studying the habitat of Coilia nasus (C. nasus) is highly significant. This study used survey data from southern Zhejiang coastal waters 2016 to 2020, employing a maximum entropy model (MaxEnt) map distribution C. nasus. Model performance was evaluated using two metrics: area under curve (AUC) receiver operating characteristic for training test sets true skill statistics (TSS). aimed predict explore how environmental variables influence suitability. The results indicated that models each season had strong predictive performance, with AUC values above 0.8 TSS exceeding 0.6, indicating they could accurately presence In area, primarily found in brackish or marine near bays islands. Among all factors, salinity (S) bottom temperature (BOT) highest correlations distribution, although these varied across seasons. findings this provide empirical evidence reference conservation management designation its protected areas.

Language: Английский

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Thinking beyond the closure assumption: Designing surveys for estimating biological truth with occupancy models

Methods in Ecology and Evolution, Journal Year: 2024, Volume and Issue: unknown

Published: Oct. 22, 2024

Abstract Occupancy models estimate distributions of imperfectly detected species, but violations the closure assumption can bias results. However, researchers working with mobile animals may find it impossible to eliminate such violations. Here, we tested hypothesis that occupancy fit realistic sampling data generate unbiased estimates for an itinerant Wood Thrush ( Hylocichla mustelina ) population. In 2013 and 2014, tracked movements 41 breeding males. We modelled territory shift probabilities using logistic exposure within‐territory continuous‐time stochastic process models. then constructed individual‐based model, simulated (1000 iterations) spatiotemporal locations individuals these populations 162 different point count protocols variable spatial (sampling radius placement method), temporal (survey length, between‐survey intervals number surveys) characteristics. compared true values instantaneous, daily seasonal from simulations. parameterized continuous time based on within 34 unique territories estimated a probability 0.0099 (95% CI: 0.0060, 0.0152). Simulated indicated ranged 0.18 (0.06, 1.00) 0.80 (0.71, 0.89) depending protocol increased increasing survey radius, length interval. Protocols shorter surveys were good estimators instantaneous (low mean‐squared error) poor occupancy; longer generated underestimated occupancy. Logistic regression ignored imperfect detection outperformed estimating not or For animals, sites changes in space time. Consequently, aspects have strong, predictable, effects model parameter estimates. Our results demonstrate how factors interact is critical designing produce representative biological interest researcher.

Language: Английский

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