Integrating food webs in species distribution models can improve ecological niche estimation and predictions

Ecography, Год журнала: 2025, Номер unknown

Опубликована: Янв. 14, 2025

Biotic interactions play a fundamental role in shaping multitrophic species communities, yet incorporating these into distribution models (SDMs) remains challenging. With the growing availability of interaction networks, it is now feasible to integrate SDMs for more comprehensive predictions. Here, we propose novel framework that combines trophic networks with Bayesian structural equation models, enabling each be modeled based on its predators or prey alongside environmental factors. This addresses issues multicollinearity and error propagation, making possible predict distributions unobserved locations under future conditions, even when predator are unknown. We tested validated our realistic simulated communities spanning different theoretical ecological setups. scenarios. Our approach significantly improved estimation both potential realized niches compared single SDMs, mean performance gains 8% 6%, respectively. These improvements were especially notable strongly regulated by biotic factors, thereby enhancing model predictive accuracy. supports integration various SDM extensions, such as occupancy integrated offering flexibility adaptability developments. While not universal solution consistently outperforms provides valuable new tool modeling community known assumed.

Язык: Английский

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Optimizing ecological security patterns in a megacity by enhancing urban-rural connectivity: Insights from Wuhan, China

Applied Geography, Год журнала: 2025, Номер 176, С. 103535 - 103535

Опубликована: Фев. 1, 2025

Язык: Английский

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Promoting ecological restoration of deeply urbanized hilly areas: A multi-scale ecological networks approach

Ecological Indicators, Год журнала: 2023, Номер 154, С. 110655 - 110655

Опубликована: Июль 17, 2023

With the deep expansion of urbanization, contradictions between human beings and natural environment in hilly areas have shown characteristics multi-scale complexity. The traditional construction ecological network rarely focused on relationship elements at different scales, which made it difficult to systematically solve problems. To address gap, this paper proposed a novel framework construct networks based discussion problems space scales. Firstly, one most deeply urbanized area China (Changsha- Zhuzhou- Xiangtan urban agglomeration, CZXUA) was chosen as study area. By constructing evaluation system patches importance (EPI) after conducting Morphological Spatial Pattern Analysis (MSPA), identification method sources optimized Then, spatial principal component analysis (SPCA) used sort out resistance factors surfaces constructed accordingly. Furthermore, from CZXUA central were cooperatively through Least-cost path (LCP), circuit theory, hierarchical transmission scale nesting. Finally, overall security pattern development metropolitan green open area, well applied territorial planning spacial results up for deficiency single-scale neglecting important details local areas, provided feasible restoration plan decision makers practitioners. This can contribute cross-scale ecosystem biodiversity conservation hills.

Язык: Английский

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A Critical Evaluation of Network Approaches for Studying Species Interactions

Annual Review of Ecology Evolution and Systematics, Год журнала: 2024, Номер 55(1), С. 65 - 88

Опубликована: Июль 26, 2024

Ecological networks of species interactions are popular and provide powerful analytical tools for understanding variation in community structure ecosystem functioning. However, network analyses commonly used metrics such as nestedness connectance have also attracted criticism. One major concern is that observed patterns misinterpreted niche properties specialization, whereas they may instead merely reflect sampling, abundance, and/or diversity. As a result, studies potentially draw flawed conclusions about ecological function, stability, or coextinction risks. We highlight potential biases analyzing interpreting species-interaction review the solutions available to overcome them, among which we particularly recommend use null models account abundances. show why considering across important their consequences. Network can advance knowledge on principles but only when judiciously applied.

Язык: Английский

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EuPPollNet: A European Database of Plant‐Pollinator Networks

Global Ecology and Biogeography, Год журнала: 2025, Номер 34(2)

Опубликована: Фев. 1, 2025

ABSTRACT Motivation Pollinators play a crucial role in maintaining Earth's terrestrial biodiversity. However, rapid human‐induced environmental changes are compromising the long‐term persistence of plant‐pollinator interactions. Unfortunately, we lack robust, generalisable data capturing how communities structured across space and time. Here, present EuPPollNet (European Plant‐Pollinator Networks) database, fully open European‐level database containing harmonised taxonomic on interactions referenced both time, along with other ecological variables interest. In addition, evaluate sampling coverage EuPPollNet, summarise key structural properties networks. We believe will stimulate research to address gaps guide future efforts conservation planning. Main Types Variables Included contains 1,162,109 between plants pollinators from 1864 distinct networks, which belong 52 different studies distributed 23 European countries. Information about methodology, habitat type, biogeographic region additional rank information (i.e. order, family, genus species) is also provided. Spatial Location Grain The 1214 locations 13 natural anthropogenic habitats that fall 7 regions. All records geo‐referenced presented World Geodetic System 1984 (WGS84). Time Period Species interaction was collected 2004 2021. Major Taxa Level Measurement at species level for 94% records, including total 1411 plant 2223 pollinator species. includes 6% flowering plants, 34% bees, 26% butterflies 33% syrphid level. Software Format built R stored ‘.rds’ ‘.csv’ formats. Its construction reproducible can be accessed at: https://doi.org/10.5281/zenodo.14747448 .

Язык: Английский

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How to measure response diversity

Methods in Ecology and Evolution, Год журнала: 2023, Номер 14(5), С. 1150 - 1167

Опубликована: Март 21, 2023

Abstract The insurance effect of biodiversity—that diversity stabilises aggregate ecosystem properties—is mechanistically underlain by inter‐ and intraspecific trait variation in organismal responses to the environment. This variation, termed response , is therefore a potentially critical determinant ecological stability. However, has yet be widely quantified, possibly due difficulties its measurement. Even when it been measured, approaches have varied. Here, we review methods for measuring from them distil methodological framework quantifying experimental and/or observational data, which can practically applied laboratory field settings across range taxa. Previous empirical studies on most commonly invoke traits as proxies aimed at capturing species' Our approach, based environment‐dependent any biotic or abiotic environmental variable, conceptually simple robust form response, including nonlinear responses. Given derivation data responses, this approach should more directly reflect than trait‐based dominant literature. By even subtle environment dependencies diversity, hope will motivate tests diversity–stability relationship new perspective, provide an mapping, monitoring conserving dimension biodiversity.

Язык: Английский

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Identifying and optimizing ecological spatial patterns based on the bird distribution in the Yellow River Basin, China

Journal of Environmental Management, Год журнала: 2023, Номер 348, С. 119293 - 119293

Опубликована: Окт. 10, 2023

Язык: Английский

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Quantitative Representativeness and Constituency of the Long-Term Agroecosystem Research Network and Analysis of Complementarity with Existing Ecological Networks

Environmental Management, Год журнала: 2023, Номер 72(4), С. 705 - 726

Опубликована: Июнь 16, 2023

Abstract Studies conducted at sites across ecological research networks usually strive to scale their results larger areas, trying reach conclusions that are valid throughout enclosing regions. Network representativeness and constituency can show how well conditions sampling locations represent also found elsewhere be used help scale-up over Multivariate statistical methods have been design select optimize regional representation, thereby maximizing the value of datasets research. However, in created from already established sites, an immediate challenge is understand existing range environments whole area interest. We performed analysis USDA Long-Term Agroecosystem Research (LTAR) all agricultural working lands within conterminous United States (CONUS). Our 18 LTAR based on 15 climatic edaphic characteristics, produced maps constituency. Representativeness was quantified through exhaustive pairwise Euclidean distance calculation multivariate space, between experiments each site every 1 km cell CONUS. perspective CONUS locations, but we considered site. For site, identified region best represented by particular site—its constituency—as set grid environmental drivers shows combination characteristics location sites’ environments, while which closest match for location. good most croplands higher than grazinglands, probably because more specific criteria. Constituencies resemble ecoregions “centered” those sites. Constituency prioritize experimental or even identify extents likely included when generalizing knowledge regions Sites with a large generalist smaller areas specialized combinations. These “specialist” representatives smaller, unusual areas. The potential sharing complementary Ecological (LTER) National Observatory (NEON) boost explored. network would benefit borrowing several NEON Sevilleta LTER Later additions must include such specialist targeted unique missing environments. While this exhaustively principal related production lands, did not consider focal agronomic systems under study, socio-economic context.

Язык: Английский

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Heterogeneous dispersal networks to improve biodiversity science

Trends in Ecology & Evolution, Год журнала: 2023, Номер 39(3), С. 229 - 238

Опубликована: Окт. 25, 2023

Язык: Английский

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Mutualistic interactions shape global spatial congruence and climatic niche evolution in Neotropical mimetic butterflies

Ecology Letters, Год журнала: 2023, Номер 26(6), С. 843 - 857

Опубликована: Март 17, 2023

Abstract Understanding the mechanisms underlying species distributions and coexistence is both a priority challenge for biodiversity hotspots such as Neotropics. Here, we highlight that Müllerian mimicry, where defended prey display similar warning signals, key to maintenance of in c. 400 Neotropical butterfly tribe Ithomiini (Nymphalidae: Danainae). We show mimicry drives large‐scale spatial association among phenotypically species, providing new empirical evidence validity Müller's model at macroecological scale. Additionally, mimetic interactions drive evolutionary convergence climatic niche, thereby strengthening co‐occurrence co‐mimetic species. This study provides insights into importance mutualistic shaping niche evolution assemblages large scales. Critically, context climate change, our results vulnerability extinction cascades adaptively assembled communities tied by positive interactions.

Язык: Английский

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