Ecography最新文献

{"title":"Idiosyncratic spatial scaling of biodiversity–disease relationships","authors":"Neil A. Gilbert, Graziella V. DiRenzo, Elise F. Zipkin","doi":"10.1111/ecog.07541","DOIUrl":"https://doi.org/10.1111/ecog.07541","url":null,"abstract":"High host biodiversity is hypothesized to dilute the risk of vector-borne diseases if many host species are ‘dead ends' that cannot effectively transmit the disease and low-diversity areas tend to be dominated by competent host species. However, many studies on biodiversity–disease relationships characterize host biodiversity at single, local spatial scales, which complicates efforts to forecast disease risk if associations between host biodiversity and disease change with spatial scale. Here, our objective is to evaluate the spatial scaling of relationships between host biodiversity and <i>Borrelia</i> (the bacterial taxon which causes Lyme disease) infection prevalence in small mammals. We compared the associations between infection prevalence and small mammal host diversity for local communities (individual plots) and metacommunities (multiple plots aggregated within a landscape) sampled by the National Ecological Observatory Network (NEON), an emerging continental-scale environmental monitoring program with a hierarchical sampling design. We applied a multispecies, spatially-stratified capture–recapture model to a trapping dataset to estimate five small mammal biodiversity metrics, which we used to predict infection status for a subset of trapped individuals. We found that relationships between <i>Borrelia</i> infection prevalence and biodiversity did indeed vary when biodiversity was quantified at different spatial scales but that these scaling behaviors were idiosyncratic among the five biodiversity metrics. For example, species richness of local communities showed a negative (dilution) effect on infection prevalence, while species richness of the small mammal metacommunity showed a positive (amplification) effect on infection prevalence. Our modeling approach can inform future analyses as data from similar monitoring programs accumulate and become increasingly available through time. Our results indicate that a focus on single spatial scales when assessing the influence of biodiversity on disease risk provides an incomplete picture of the complexity of disease dynamics in ecosystems.","PeriodicalId":51026,"journal":{"name":"Ecography","volume":"1 1","pages":""},"PeriodicalIF":5.9,"publicationDate":"2025-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143375373","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"GEE-PICX: generating cloud-free Sentinel-2 and Landsat image composites and spectral indices for custom areas and time frames – a Google Earth Engine web application","authors":"Luisa Pflumm, Hyeonmin Kang, Andreas Wilting, Jürgen Niedballa","doi":"10.1111/ecog.07385","DOIUrl":"https://doi.org/10.1111/ecog.07385","url":null,"abstract":"Earth observation satellites are collecting vast amounts of free and openly accessible data with immense potential to support environmental, economic, and social fields. As the availability of remotely sensed data increases, so do the methods for accessing and processing it. Many solutions exist for creating cloud-free image composites from often cloudy satellite data, but these typically require coding skills or in-depth training in remote-sensing techniques. This technical barrier prevents many researchers and practitioners from utilising available satellite data. The few user-friendly solutions that exist often have limitations in terms of data export size and quality assessment capabilities. We developed GEE-PICX, a web application with an intuitive graphical user interface on the cloud computing platform Google Earth Engine. This tool addresses the aforementioned challenges by creating cloud-free, analysis-ready image composites for user-defined areas and time periods. It utilises Sentinel-2 and Landsat 5, 7, 8, and 9 images and offers global coverage. Users can aggregate image composites annually or seasonally, with data availability starting from 1984 (the launch of Landsat 5). The workflow automatically filters all available satellite data according to user input, removing clouds, cloud shadows, and snow. It provides spectral band information, calculates various thematic spectral indices (including vegetation, burn, built-up area, bare soil, snow, moisture, and water indices), and includes a quality assessment band indicating the number of valid scenes per pixel. GEE-PICX offers a customizable tool for creating custom data products from freely accessible satellite data, catering to researchers with limited remote sensing experience. It provides extensive temporal and global spatial coverage, with server-side processing eliminating hardware constraints. The tool facilitates easy export of time series as ready-to-use rasters with numerous spectral indices, supporting environmental programmes and biodiversity research across various disciplines.","PeriodicalId":51026,"journal":{"name":"Ecography","volume":"143 1","pages":""},"PeriodicalIF":5.9,"publicationDate":"2025-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143375370","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Norwegian lemmings, Lemmus lemmus: a case for a strong herbivore–plant interaction","authors":"Lauri Oksanen, Katariina E. M. Vuorinen, Kukka Kyrö, Aurelia Mäkynen, Johan Olofsson, Lise Ruffino, Maria Tuomi, Tarja Oksanen","doi":"10.1111/ecog.07297","DOIUrl":"https://doi.org/10.1111/ecog.07297","url":null,"abstract":"In his classical contributions, Olavi Kalela proposed that, due to the low primary productivity of the tundra, Norwegian lemmings are locked in a strong interaction with their winter forage plants. Proposedly, Norwegian lemmings respond to the threat of critical resource depletion by conducting long-range migrations at their population peaks. A tacit premise of this conjecture is that predation pressure on the Fennoscandian tundra is too weak to prevent runaway increases of lemming populations, creating violent boom–crash dynamics. Our results on the dynamics of Norwegian lemmings on the Finnmarksvidda tundra during 1977–2017 are in line with the predictions of Kalela's hypothesis. In contrast to the Siberian and North American tundra, densities of avian predators in our study area have been low even during lemming years, and efficient ones have been lacking from lemming habitats. Lemmings have thus increased unhinged in peak summers and crashed to densities below the trappability threshold during post-peak winters. Each lemming crash has been accompanied by massive habitat destruction. Indications of predator activity have been concentrated to productive shrublands, where lemmings have never reached high densities. Young lemmings have responded to high densities by becoming extremely mobile: they have been trapped in large numbers on islands, including a small island in the middle of Iešjávri, a 10 × 8 km tundra lake. Many lemmings have been seen swimming across the lake, and many drowned lemmings have been observed. The dynamics and behavior of Norwegian lemmings recorded by us differ radically from those of other <i>Lemmus</i> spp., indicating that cycles generated by lemming–vegetation interactions have two alternative states – one with and the other without intense summer predation. We propose that the cycles of Norwegian lemmings shifted to the latter state during their unique evolutionary history, when they survived the Last Glacial Maximum in a tiny refugium archipelago.","PeriodicalId":51026,"journal":{"name":"Ecography","volume":"13 1","pages":""},"PeriodicalIF":5.9,"publicationDate":"2025-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143375374","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"‘Euclimatch': an R package for climate matching with Euclidean distance metrics","authors":"Justin A. G. Hubbard, D. Andrew R. Drake, Nicholas E. Mandrak","doi":"10.1111/ecog.07614","DOIUrl":"https://doi.org/10.1111/ecog.07614","url":null,"abstract":"Climate matching, a tool for predicting non-native species survival in target (recipient) regions, is commonly used in invasive species frameworks such as horizon scanning and screening-level risk assessment protocols. Screening-level risk assessments often require the analysis of many species with limited resources, and climate matching can be advantageous to identify a reduced number of species for more detailed analyses. Additionally, risk screening may require examination of non-native species' source pools where species occurrence records are not used in model training data. In these instances, climate matching is an effective method for assessing the survival of non-native species or their source pools in a target region and has practical advantages over species distribution models. We introduce the R package ‘Euclimatch' for quantitative climate matching with the Euclidean distance algorithm Climatch. The package provides tools for creating a streamlined data-agnostic climate-matching workflow. First, climate data are extracted for species occurrence records or regions. Second, climate match is modelled between two regions as a similarity score per grid cell or summarized across a target region. Third, visualizations of the climate match model outputs are created. We demonstrate the use of the ‘Euclimatch' package with the climate match of two popular aquarium trade species and a region-to-region analysis. We also demonstrate differences in results between Euclidean distance metric standardization methods when incorporating climate-change projections. The scale of each example is global, under historical and projected climates. ‘Euclimatch' provides a scripting interface for Euclidean climate matching for the screening assessment of non-native species or regions under any climatic conditions. ‘Euclimatch' can be downloaded from the comprehensive R archive network (CRAN).","PeriodicalId":51026,"journal":{"name":"Ecography","volume":"16 1","pages":""},"PeriodicalIF":5.9,"publicationDate":"2025-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143375375","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Emerging horizons in predictive biogeography","authors":"Christine N. Meynard,&nbsp;Sydne Record,&nbsp;Nuria Galiana,&nbsp;Dominique Gravel,&nbsp;Miguel B. Araújo","doi":"10.1111/ecog.07910","DOIUrl":"10.1111/ecog.07910","url":null,"abstract":"&lt;p&gt;The notion that different branches of biological sciences – including ecology, macroecology, and biogeography – should adopt a predictive focus rather than merely aiming to describe and understand the natural world has gained traction over the past decades (Peters &lt;span&gt;1991&lt;/span&gt;, Shrader-Frechette and McCoy &lt;span&gt;1993&lt;/span&gt;). This trend has been enabled both by technological advancement leading to new predictive frameworks, and by the pressing societal demands to anticipate and mitigate the effects of global change on biodiversity and the associated ecosystem services.&lt;/p&gt;&lt;p&gt;An early example of this trend is the work by Sánchez-Cordero et al. (&lt;span&gt;2004&lt;/span&gt;) who contributed a chapter on predictive biogeography for conservation applications in a seminal volume on biogeography (Lomolino and Heaney &lt;span&gt;2004&lt;/span&gt;). While the authors did not explicitly define the term &lt;i&gt;predictive biogeography&lt;/i&gt;, their discussion emphasized how developments in statistical ecology and mapping had allowed the description of species distributions at large spatial scales. Similarly, Thuiller et al. (&lt;span&gt;2006&lt;/span&gt;) employed the concept of &lt;i&gt;predictive biogeography&lt;/i&gt; in the restricted context of describing the use of stacked species distribution models (SDMs) in predicting plant richness in South Africa.&lt;/p&gt;&lt;p&gt;Dawson et al. (&lt;span&gt;2011&lt;/span&gt;) subsequently highlighted SDMs as the most widely used predictive method in biogeography, but also called attention on the importance of establishing broader frameworks to anticipate changes in biodiversity, from species to ecosystems, in response to climate change. There are other biogeographic patterns that are widely used in a predictive context. Most notably, the species area relationships (SARs), which have also been important to understand and predict species extinctions (Drakare et al. &lt;span&gt;2006&lt;/span&gt;) driven by anthropogenic habitat fragmentation for example. However, the widespread use of SDMs, along with the fact that they remain the method of choice at large scales in ecology, has been repeatedly highlighted (Bellard et al. &lt;span&gt;2012&lt;/span&gt;, Araújo et al. &lt;span&gt;2019&lt;/span&gt;, Zurell et al. &lt;span&gt;2020&lt;/span&gt;, Soley-Guardia et al. &lt;span&gt;2024&lt;/span&gt;). Mapping biodiversity remains an essential component of large-scale spatial conservation planning (Margules et al. &lt;span&gt;2002&lt;/span&gt;). It is critical not only for delineating species conservation statuses, trends, and management strategies on regional to global scales, but also for interpreting the geological, historical, and anthropogenic causes and consequences for biodiversity distribution (Whittaker et al. &lt;span&gt;2005&lt;/span&gt;). Therefore, describing and modelling species distributions will probably remain an essential component of predictive biogeography.&lt;/p&gt;&lt;p&gt;However, many studies emphasize the need to move beyond individual species distributions to encompass a broader range of spatio-temporal issues at the interface between biodiversity sciences and s","PeriodicalId":51026,"journal":{"name":"Ecography","volume":"2025 3","pages":""},"PeriodicalIF":5.4,"publicationDate":"2025-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/ecog.07910","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143375372","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Use and misuse of trait imputation in ecology: the problem of using out‐of‐context imputed values","authors":"Lucas Damián Gorné, Jesús Aguirre-Gutiérrez, Fernanda C. Souza, Nathan G. Swenson, Nathan Jared Boardman Kraft, Beatriz Schwantes Marimon, Timothy R. Baker, Renato A. Ferreira de Lima, Emilio Vilanova, Esteban Álvarez-Dávila, Abel Monteagudo Mendoza, Gerardo Rafael Flores Llampazo, Rubens Manoel dos Santos, Gerhard Boenisch, Alejandro Araujo-Murakami, Gonzalo Rivas-Torres, Hirma Ramírez-Angulo, Nayane Cristina dos Santos Prestes, Paulo S. Morandi, Sabina Cerruto Ribeiro, Wesley Jonatar A. da Cruz, Mathias Disney, Anthony Di Fiore, Ben Hur Marimon-Junior, Ted R. Feldpausch, Yadvinder Malhi, Oliver L. Phillips, David Galbraith, Sandra Díaz","doi":"10.1111/ecog.07520","DOIUrl":"https://doi.org/10.1111/ecog.07520","url":null,"abstract":"Despite the progress in the measurement and accessibility of plant trait information, acquiring sufficiently complete data from enough species to answer broad‐scale questions in plant functional ecology and biogeography remains challenging. A common way to overcome this challenge is by imputation, or ‘gap‐filling' of trait values. This has proven appropriate when focusing on the overall patterns emerging from the database being imputed. However, some applications force the imputation procedure out of its original scope, using imputed values independently from the imputation context, and specific trait values for a given species are used as input for computing new variables. We tested the performance of three widely used imputation methods (Bayesian hierarchical probabilistic matrix factorization, multiple imputation by chained equations with predictive mean matching, and Rphylopars) on a database of tropical tree and shrub traits. By applying a leave‐one‐out procedure, we assessed the accuracy and precision of the imputed values and found that out‐of‐context use of imputed values may bias the estimation of different variables. We also found that low redundancy (i.e. low predictability of a new value on the basis of existing values) in the dataset, not uncommon for empirical datasets, is likely the main cause of low accuracy and precision in the imputed values. We therefore suggest the use of a leave‐one‐out procedure to test the quality of the imputed values before any out‐of‐context application of the imputed values, and make practical recommendations to avoid the misuse of imputation procedures. Furthermore, we recommend not publishing gap‐filled datasets, publishing instead only the empirical data, together with the imputation method applied and the corresponding script to reproduce the imputation. This will help avoid the spread of imputed data, whose accuracy, precision, and source are difficult to assess and track, into the public domain.","PeriodicalId":51026,"journal":{"name":"Ecography","volume":"4 1","pages":""},"PeriodicalIF":5.9,"publicationDate":"2025-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143083419","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A pattern-oriented simulation for forecasting species spread through time and space: a case study on an ecosystem engineer on the move","authors":"Rahil J. Amin, Jessie C. Buettel, Matthew W. Fielding, Peter M. Vaughan, Barry W. Brook","doi":"10.1111/ecog.07597","DOIUrl":"https://doi.org/10.1111/ecog.07597","url":null,"abstract":"Modelling the spread of introduced ecosystem engineers is a conservation priority due to their potential to cause irreversible ecosystem-level changes. While existing models predict potential distributions and spread capacities, new approaches that simulate the trajectory of a species' spread over time are needed. We developed novel simulations that predict spatial and temporal spread, capturing both continuous diffusion-dispersal and occasional long-distance leaps. We focused on the introduced population of superb lyrebird <i>Menura novaehollandiae</i> in Tasmania, Australia. Initially introduced as an insurance population, lyrebirds have become novel bioturbators, spreading across key natural areas and becoming ‘unwanted but challenging to eradicate'. Using multi-scale ecological data, our research 1) identified broad and fine-scale correlates of lyrebird occupation and 2) developed a spread simulation guided by a pattern-oriented framework. This occurrence-based modelling framework is useful when demographic data are scarce. We found that the cool, wet forests of western Tasmania with open understoreys offer well-connected habitats for lyrebird foraging and nesting. By 2023, lyrebirds had reached quasi-equilibrium within a core range in southern Tasmania and were expanding northwest, with the frontier reaching the western coast. Our model forecasts that by 2085, lyrebirds will have spread widely across suitable regions of western Tasmania. By pinpointing current and future areas of lyrebird occupation, we provide land managers with targeted locations for monitoring the effects of their expansion. Further, our area of applicability (AOA) analysis identified regions where environmental variables deviate from the training data, guiding future data collection to improve model certainty. Our findings offer an evidence-based approach for future monitoring and provide a framework for understanding the dynamics of other range-expanding species with invasive potential.","PeriodicalId":51026,"journal":{"name":"Ecography","volume":"36 1","pages":""},"PeriodicalIF":5.9,"publicationDate":"2025-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143083575","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assembly processes inferred from eDNA surveys of a pond metacommunity are consistent with known species ecologies","authors":"Wang Cai, Maximilian Pichler, Jeremy Biggs, Pascale Nicolet, Naomi Ewald, Richard A. Griffiths, Alex Bush, Mathew A. Leibold, Florian Hartig, Douglas W. Yu","doi":"10.1111/ecog.07461","DOIUrl":"https://doi.org/10.1111/ecog.07461","url":null,"abstract":"Technological advances are enabling ecologists to conduct large-scale and structured community surveys. However, it is unclear how best to extract information from these novel community data. We metabarcoded 48 vertebrate species from their eDNA in 320 ponds across England and applied the ‘internal structure' approach, which uses joint species distribution models (JSDMs) to explain compositions as the result of four metacommunity processes: environmental filtering, dispersal, species interactions, and stochasticity. We confirm that environmental filtering plays an important role in community assembly, and find that species' estimated environmental preferences are consistent with known ecologies. We also detect negative biotic covariances between fish and amphibians after controlling for divergent environmental preferences, consistent with predator–prey interactions (likely mediated by predator avoidance behaviour), and we detect high spatial autocorrelation for the palmate newt, consistent with its hypothesised relict distribution. Promisingly, ecologically and spatially distinctive sites are better explained by their environmental covariates and geographic locations, respectively, revealing sites where environmental filtering and dispersal limitation act more strongly. These results are consistent with the recent proposal that applying JSDMs to species distribution patterns can help reveal the relative importance of environmental filtering, dispersal limitation, and biotic interaction processes for individual sites and species. Our results also highlight the value of the modern interpretation of metacommunity ecology, which embraces the fact that assembly processes differ among species and sites. We discuss how novel community data allow for several study design improvements that will strengthen the inference of metacommunity assembly processes from observational data.","PeriodicalId":51026,"journal":{"name":"Ecography","volume":"28 1","pages":""},"PeriodicalIF":5.9,"publicationDate":"2025-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143083580","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The best of two worlds: toward large-scale monitoring of biodiversity combining COI metabarcoding and optimized parataxonomic validation","authors":"Benoit Penel, Christine N. Meynard, Laure Benoit, Axel Boudonne, Anne-Laure Clamens, Laurent Soldati, Alain Migeon, Marie-Pierre Chapuis, Sylvain Piry, Gael Kergoat, Julien Haran","doi":"10.1111/ecog.07699","DOIUrl":"https://doi.org/10.1111/ecog.07699","url":null,"abstract":"In a context of unprecedented insect decline, it is critical to have reliable monitoring tools to measure species diversity and their dynamic at large-scales. High-throughput DNA-based identification methods, and particularly metabarcoding, were proposed as an effective way to reach this aim. However, these identification methods are subject to multiple technical limitations, resulting in unavoidable false-positive and false-negative species detection. Moreover, metabarcoding does not allow a reliable estimation of species abundance in a given sample, which is key to document and detect population declines or range shifts at large scales. To overcome these obstacles, we propose here a human-assisted molecular identification (HAMI) approach, a framework based on a combination of metabarcoding and image-based parataxonomic validation of outputs and recording of abundance. We assessed the advantages of using HAMI over the exclusive use of a metabarcoding approach by examining 492 mixed beetle samples from a biodiversity monitoring initiative conducted throughout France. On average, 23% of the species are missed when relying exclusively on metabarcoding, this percent being consistently higher in species-rich samples. Importantly, on average, 20% of the species identified by molecular-only approaches correspond to false positives linked to cross-sample contaminations or mis-identified barcode sequences in databases. The combination of molecular methodologies and parataxonomic validation in HAMI significantly reduces the intrinsic biases of metabarcoding and recovers reliable abundance data. This approach also enables users to engage in a virtuous circle of database improvement through the identification of specimens associated with missing or incorrectly assigned barcodes. As such, HAMI fills an important gap in the toolbox available for fast and reliable biodiversity monitoring at large scales.","PeriodicalId":51026,"journal":{"name":"Ecography","volume":"76 1","pages":""},"PeriodicalIF":5.9,"publicationDate":"2025-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143083576","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The role of climate and species interactions in determining the distribution of two elevationally segregated species of small mammals through time","authors":"Alexandra C. Coconis, Kenneth E. Nussear, Rebecca J. Rowe, Angela D. Hornsby, Marjorie D. Matocq","doi":"10.1111/ecog.07556","DOIUrl":"https://doi.org/10.1111/ecog.07556","url":null,"abstract":"The relative importance of abiotic and biotic factors in determining species distributions has long been of interest to ecologists but is often difficult to assess due to the lack of spatially and temporally robust occurrence records. Furthermore, locating places where potentially highly competitive species co-occur may be challenging but would provide critical knowledge into the effects of competition on species ranges. We built species distribution models for two closely related species of small mammals (<i>Neotoma</i>) that are largely parapatric along mountainsides throughout the Great Basin Desert, USA using extensive modern occurrence records. We hindcasted these models to the mid-Holocene to compare the response of each species to dramatic climatic change and used paleontological records to validate our models. Model results showed species co-occurrence at mid-elevations along select mountain ranges in this region. We confirmed our model results with fine-scale field surveys in a single mountain range containing one of the most extensive survey datasets across an elevational gradient in the Great Basin. We found close alignment of realized distributions to the respective abiotic species distribution model predictions, despite the presence of the congener, indicating that climate may be more influential than competition in shaping distribution at the scale of a single mountain range. Our models also predict differential species responses to historic climate change, leading to reduced probability of species interactions during warmer and dryer climatic conditions. Our results emphasize the utility of examining species distributions with regard to both abiotic variables and species interactions and at various spatial scales to make inferences about the mechanisms underlying distributional limits.","PeriodicalId":51026,"journal":{"name":"Ecography","volume":"40 1","pages":""},"PeriodicalIF":5.9,"publicationDate":"2025-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143083912","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}