The biogeographic affinity of a lineage leaves imprint on its niche, and influences its distribution under biotic interchange between landmasses. Since the beginning of the Quaternary, North America (a remnant of Laurasia) and South America (a remnant of Gondwana) have been united, and triggered the Great American Biotic Interchange. Based on existing knowledge, we expect more Laurasian lineages to occur at higher latitudes, in colder or drier areas; and more Gondwanan lineages to reside at lower latitudes, in hotter and wetter areas of the Americas. Moreover, the tropical niche conservatism (TNC) hypothesis states that the tropical flora be most ancient. If so, then both younger Laurasian and Gondwanan lineages would occur in regions at colder and higher latitudes. Here, we examine the latitudinal patterns of species richness and mean family age of Laurasian and Gondwanan angiosperm tree lineages in 422 forest plots distributed across the Americas, and investigate the underlying continent and climatic drivers. We found opposite latitudinal and climatic patterns for species richness of Laurasian and Gondwanan lineages, the former declined towards lower latitudes and hotter climates, whereas the latter declined towards higher latitudes and colder climates. In particular, more pronounced climatic patterns for species richness of Laurasian and Gondwanan lineages were observed in North and South America, respectively. In addition, the mean family age of Laurasian lineages declined towards higher latitudes and colder climates, and for Gondwanan lineages it also decreased towards higher latitudes in South America, hence supporting the TNC hypothesis. We suggest Laurasian and Gondwanan angiosperm tree lineages in forests of the Americas exhibit diverged climate niche preferences, perhaps partly due to diversification of the former in extratropical climates in recent geological times.
{"title":"Latitudinal patterns and climatic drivers of Laurasian and Gondwanan angiosperm tree distributions in forests of the Americas","authors":"Yi Jin, Hong Qian","doi":"10.1111/ecog.07687","DOIUrl":"https://doi.org/10.1111/ecog.07687","url":null,"abstract":"The biogeographic affinity of a lineage leaves imprint on its niche, and influences its distribution under biotic interchange between landmasses. Since the beginning of the Quaternary, North America (a remnant of Laurasia) and South America (a remnant of Gondwana) have been united, and triggered the Great American Biotic Interchange. Based on existing knowledge, we expect more Laurasian lineages to occur at higher latitudes, in colder or drier areas; and more Gondwanan lineages to reside at lower latitudes, in hotter and wetter areas of the Americas. Moreover, the tropical niche conservatism (TNC) hypothesis states that the tropical flora be most ancient. If so, then both younger Laurasian and Gondwanan lineages would occur in regions at colder and higher latitudes. Here, we examine the latitudinal patterns of species richness and mean family age of Laurasian and Gondwanan angiosperm tree lineages in 422 forest plots distributed across the Americas, and investigate the underlying continent and climatic drivers. We found opposite latitudinal and climatic patterns for species richness of Laurasian and Gondwanan lineages, the former declined towards lower latitudes and hotter climates, whereas the latter declined towards higher latitudes and colder climates. In particular, more pronounced climatic patterns for species richness of Laurasian and Gondwanan lineages were observed in North and South America, respectively. In addition, the mean family age of Laurasian lineages declined towards higher latitudes and colder climates, and for Gondwanan lineages it also decreased towards higher latitudes in South America, hence supporting the TNC hypothesis. We suggest Laurasian and Gondwanan angiosperm tree lineages in forests of the Americas exhibit diverged climate niche preferences, perhaps partly due to diversification of the former in extratropical climates in recent geological times.","PeriodicalId":51026,"journal":{"name":"Ecography","volume":"29 1","pages":""},"PeriodicalIF":5.9,"publicationDate":"2025-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143451894","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}
Toni Lyn Morelli, Michael T. Hallworth, Timothy Duclos, Adam Ells, Steven D. Faccio, Jane R. Foster, Kent P. McFarland, Keith Nislow, Joel Ralston, Mary Ratnaswamy, William V. Deluca, Alexej P. K. Siren
A primary prediction of climate change ecology is that species will track their climate niche poleward and upslope. However, studies have shown species responding in surprising ways. In this study, we aim to understand the impact of global change on species ranges by considering both climate and habitat changes. Using occupancy analysis of acoustic survey data in the mountains of the northeastern United States, we tested specific predictions of range responses to warming (shifting upslope), precipitation change (shifting downslope), and forest composition change (shifting downslope). We found that American red squirrels Tamiasciurus hudsonicus, key nodes in northern North American food webs, are not tracking increasing temperatures upslope, despite substantial warming in recent decades. Structural equation modeling indicates that red squirrel abundance is primarily influenced by red-spruce forest cover, which has shifted downslope with recovery from historical logging and acid deposition. Accounting for the multiple dimensions of global change will enable better predictions and more effective conservation strategies.
{"title":"Does habitat or climate change drive species range shifts?","authors":"Toni Lyn Morelli, Michael T. Hallworth, Timothy Duclos, Adam Ells, Steven D. Faccio, Jane R. Foster, Kent P. McFarland, Keith Nislow, Joel Ralston, Mary Ratnaswamy, William V. Deluca, Alexej P. K. Siren","doi":"10.1111/ecog.07560","DOIUrl":"https://doi.org/10.1111/ecog.07560","url":null,"abstract":"A primary prediction of climate change ecology is that species will track their climate niche poleward and upslope. However, studies have shown species responding in surprising ways. In this study, we aim to understand the impact of global change on species ranges by considering both climate and habitat changes. Using occupancy analysis of acoustic survey data in the mountains of the northeastern United States, we tested specific predictions of range responses to warming (shifting upslope), precipitation change (shifting downslope), and forest composition change (shifting downslope). We found that American red squirrels <i>Tamiasciurus hudsonicus</i>, key nodes in northern North American food webs, are not tracking increasing temperatures upslope, despite substantial warming in recent decades. Structural equation modeling indicates that red squirrel abundance is primarily influenced by red-spruce forest cover, which has shifted downslope with recovery from historical logging and acid deposition. Accounting for the multiple dimensions of global change will enable better predictions and more effective conservation strategies.","PeriodicalId":51026,"journal":{"name":"Ecography","volume":"12 1","pages":""},"PeriodicalIF":5.9,"publicationDate":"2025-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143427298","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}
Michal Horsák, Veronika Horsáková, Peter Samaš, Jan Divíšek, Brian Coles, Jeffrey C. Nekola
The biota of North Atlantic islands evokes intriguing questions on its evolution, colonisation routes, and an equilibrium between dispersal limitation and climatic/habitat constraints. While good data on non‐marine snails exist for most of the islands, the data for Greenland were observed mainly between 1850 and 1900. The recorded species have been described as Greenland endemics, but this conclusion has never been fully questioned based on evidence. It can be assumed that these passively dispersing invertebrates are in fact of North American origin, due to the shortest distance to the mainland across the Davis Strait. To answer these questions, we collected the snail fauna at 72 sites of five locations across west Greenland. Our sampling revealed a very species‐poor fauna, consisting of two aquatic and four terrestrial snail species. Based on mitochondrial and nuclear DNA sequences, the phylogenetic reconstruction and haplotype analysis showed that these taxa are either North American (all aquatic) or European (all terrestrial) in origin. None of them appeared to be endemic to Greenland and they were not even genetically distinct from the mainland populations. At both the macro and habitat scale, the Greenland snail fauna was found to be only a small fraction of the mainland species pool based on climate mapping and analysis of habitat requirements. While it appears to be limited mainly by dispersal, a detailed analysis of bird migration routes and intensity could not explain a puzzling difference in the biogeographical origin of the aquatic and terrestrial components. Terrestrial snails mimic the pattern seen in non‐flying beetles, while the aquatic that of some flying insects. The results are a strong reminder that simple linear distance does not make a barrier, and that the barrier permeability can differ even within a group sharing the same dispersal mode and potential.
{"title":"Dispersal rather than climate and local environment constrains non‐marine snail fauna in west Greenland","authors":"Michal Horsák, Veronika Horsáková, Peter Samaš, Jan Divíšek, Brian Coles, Jeffrey C. Nekola","doi":"10.1111/ecog.07623","DOIUrl":"https://doi.org/10.1111/ecog.07623","url":null,"abstract":"The biota of North Atlantic islands evokes intriguing questions on its evolution, colonisation routes, and an equilibrium between dispersal limitation and climatic/habitat constraints. While good data on non‐marine snails exist for most of the islands, the data for Greenland were observed mainly between 1850 and 1900. The recorded species have been described as Greenland endemics, but this conclusion has never been fully questioned based on evidence. It can be assumed that these passively dispersing invertebrates are in fact of North American origin, due to the shortest distance to the mainland across the Davis Strait. To answer these questions, we collected the snail fauna at 72 sites of five locations across west Greenland. Our sampling revealed a very species‐poor fauna, consisting of two aquatic and four terrestrial snail species. Based on mitochondrial and nuclear DNA sequences, the phylogenetic reconstruction and haplotype analysis showed that these taxa are either North American (all aquatic) or European (all terrestrial) in origin. None of them appeared to be endemic to Greenland and they were not even genetically distinct from the mainland populations. At both the macro and habitat scale, the Greenland snail fauna was found to be only a small fraction of the mainland species pool based on climate mapping and analysis of habitat requirements. While it appears to be limited mainly by dispersal, a detailed analysis of bird migration routes and intensity could not explain a puzzling difference in the biogeographical origin of the aquatic and terrestrial components. Terrestrial snails mimic the pattern seen in non‐flying beetles, while the aquatic that of some flying insects. The results are a strong reminder that simple linear distance does not make a barrier, and that the barrier permeability can differ even within a group sharing the same dispersal mode and potential.","PeriodicalId":51026,"journal":{"name":"Ecography","volume":"22 1","pages":""},"PeriodicalIF":5.9,"publicationDate":"2025-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143427174","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}
James M. R. Brock, André M. Bellvé, Bruce R. Burns
Cold tolerance strategies in plants vary from structural to biochemical permitting many plants to survive and grow on sites that experience freezing conditions intermittently. Although tree ferns occur predominantly across the tropics, they also occur in temperate zones and occasionally in areas that experience sub‐zero temperatures, and how these large ferns survive freezing conditions is unknown. Many temperate tree fern taxa are marcescent – retaining whorls of dead fronds encircling the upper trunk – or develop short or prostrate trunks, possibly to insulate against frost damage to their trunks and growing crowns. We asked the following questions: 1) do global growth patterns and traits of tree ferns respond to freezing conditions associated with latitude and elevation, 2) do growth patterns of tree ferns in New Zealand vary along a temperature‐related gradient, and 3) do marcescent tree fern skirts insulate the growing crown from sub‐zero temperatures? To establish what morphological adaptations permitted the Cyatheales to occur in biomes that experience intermittent sub‐zero temperatures and frost, we 1) reviewed the global distributions of these structural and morphological traits within the tree ferns (Cyatheales); 2) assessed the patterns of tree fern marcescence, and other traits potentially associated with cold tolerance (no trunk, prostrate, short‐trunked) of nine taxa of the Cyatheales along environmental gradients across New Zealand; and 3) conducted a field experiment to assess the thermal insulation properties of tree fern marcescent skirts. We identified significant trends among growth forms, marcescence, and environmental gradients consistent with our hypothesis that these are adaptations to tolerate cold. Our field experiments provide quantitative evidence that marcescent skirts have a strong insulating effect on tree fern trunks. The Cyatheales have evolved several strategies to protect the pith cores of their trunks from extreme cold temperatures in temperate forests allowing them to capture niche space in environments beyond the tropics.
{"title":"Marcescence and prostrate growth in tree ferns are adaptations to cold tolerance","authors":"James M. R. Brock, André M. Bellvé, Bruce R. Burns","doi":"10.1111/ecog.07362","DOIUrl":"https://doi.org/10.1111/ecog.07362","url":null,"abstract":"Cold tolerance strategies in plants vary from structural to biochemical permitting many plants to survive and grow on sites that experience freezing conditions intermittently. Although tree ferns occur predominantly across the tropics, they also occur in temperate zones and occasionally in areas that experience sub‐zero temperatures, and how these large ferns survive freezing conditions is unknown. Many temperate tree fern taxa are marcescent – retaining whorls of dead fronds encircling the upper trunk – or develop short or prostrate trunks, possibly to insulate against frost damage to their trunks and growing crowns. We asked the following questions: 1) do global growth patterns and traits of tree ferns respond to freezing conditions associated with latitude and elevation, 2) do growth patterns of tree ferns in New Zealand vary along a temperature‐related gradient, and 3) do marcescent tree fern skirts insulate the growing crown from sub‐zero temperatures? To establish what morphological adaptations permitted the Cyatheales to occur in biomes that experience intermittent sub‐zero temperatures and frost, we 1) reviewed the global distributions of these structural and morphological traits within the tree ferns (Cyatheales); 2) assessed the patterns of tree fern marcescence, and other traits potentially associated with cold tolerance (no trunk, prostrate, short‐trunked) of nine taxa of the Cyatheales along environmental gradients across New Zealand; and 3) conducted a field experiment to assess the thermal insulation properties of tree fern marcescent skirts. We identified significant trends among growth forms, marcescence, and environmental gradients consistent with our hypothesis that these are adaptations to tolerate cold. Our field experiments provide quantitative evidence that marcescent skirts have a strong insulating effect on tree fern trunks. The Cyatheales have evolved several strategies to protect the pith cores of their trunks from extreme cold temperatures in temperate forests allowing them to capture niche space in environments beyond the tropics.","PeriodicalId":51026,"journal":{"name":"Ecography","volume":"69 1","pages":""},"PeriodicalIF":5.9,"publicationDate":"2025-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143417642","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}
Neil A. Gilbert, Graziella V. DiRenzo, Elise F. Zipkin
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 Borrelia (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 Borrelia 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.
{"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}
Luisa Pflumm, Hyeonmin Kang, Andreas Wilting, Jürgen Niedballa
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.
{"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}
Lauri Oksanen, Katariina E. M. Vuorinen, Kukka Kyrö, Aurelia Mäkynen, Johan Olofsson, Lise Ruffino, Maria Tuomi, Tarja Oksanen
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 Lemmus 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.
{"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}
Justin A. G. Hubbard, D. Andrew R. Drake, Nicholas E. Mandrak
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).
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Christine N. Meynard, Sydne Record, Nuria Galiana, Dominique Gravel, Miguel B. Araújo
<p>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 <span>1991</span>, Shrader-Frechette and McCoy <span>1993</span>). 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.</p> <p>An early example of this trend is the work by Sánchez-Cordero et al. (<span>2004</span>) who contributed a chapter on predictive biogeography for conservation applications in a seminal volume on biogeography (Lomolino and Heaney <span>2004</span>). While the authors did not explicitly define the term <i>predictive biogeography</i>, 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. (<span>2006</span>) employed the concept of <i>predictive biogeography</i> in the restricted context of describing the use of stacked species distribution models (SDMs) in predicting plant richness in South Africa.</p> <p>Dawson et al. (<span>2011</span>) 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. <span>2006</span>) 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. <span>2012</span>, Araújo et al. <span>2019</span>, Zurell et al. <span>2020</span>, Soley-Guardia et al. <span>2024</span>). Mapping biodiversity remains an essential component of large-scale spatial conservation planning (Margules et al. <span>2002</span>). 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. <span>2005</span>). Therefore, describing and modelling species distributions will probably remain an essential component of predictive biogeography.</p> <p>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 an
{"title":"Emerging horizons in predictive biogeography","authors":"Christine N. Meynard, Sydne Record, Nuria Galiana, Dominique Gravel, Miguel B. Araújo","doi":"10.1111/ecog.07910","DOIUrl":"https://doi.org/10.1111/ecog.07910","url":null,"abstract":"<p>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 <span>1991</span>, Shrader-Frechette and McCoy <span>1993</span>). 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.</p>\u0000<p>An early example of this trend is the work by Sánchez-Cordero et al. (<span>2004</span>) who contributed a chapter on predictive biogeography for conservation applications in a seminal volume on biogeography (Lomolino and Heaney <span>2004</span>). While the authors did not explicitly define the term <i>predictive biogeography</i>, 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. (<span>2006</span>) employed the concept of <i>predictive biogeography</i> in the restricted context of describing the use of stacked species distribution models (SDMs) in predicting plant richness in South Africa.</p>\u0000<p>Dawson et al. (<span>2011</span>) 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. <span>2006</span>) 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. <span>2012</span>, Araújo et al. <span>2019</span>, Zurell et al. <span>2020</span>, Soley-Guardia et al. <span>2024</span>). Mapping biodiversity remains an essential component of large-scale spatial conservation planning (Margules et al. <span>2002</span>). 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. <span>2005</span>). Therefore, describing and modelling species distributions will probably remain an essential component of predictive biogeography.</p>\u0000<p>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 an","PeriodicalId":51026,"journal":{"name":"Ecography","volume":"62 1","pages":""},"PeriodicalIF":5.9,"publicationDate":"2025-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","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":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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
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.
{"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}
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