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  • 1
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    Online Resource
    Temporal analysis of GBIF data reveals the restructuring of communities following climate change
    Wiley ; 2023
    In:  Journal of Animal Ecology Vol. 92, No. 2 ( 2023-02), p. 391-402
    Details
    In: Journal of Animal Ecology, Wiley, Vol. 92, No. 2 ( 2023-02), p. 391-402
    Abstract: Multiple studies revealed an effect of climate change on biodiversity by investigating long‐term changes in species distributions and community composition. However, many taxa do not benefit from systematic long‐term monitoring programmes, leaving gaps in our current knowledge of climate‐induced community turnover. We used data extracted from the Global Biodiversity Information Facility to characterize community reorganization under climate change for nine animal taxonomic groups (ants, bats, bees, birds, butterflies, earthworms, frogs, rodents and salamanders), which, for most of them, had never been studied before in this regard. Using a presence‐only community temperature index (CTI), reflecting the relative proportion of warm‐ and cold‐adapted species, we tested whether and how species' assemblages were affected by climate change over the last 30 years. Across Europe and North America, we observed an average increase in CTI, consistent with a gradual species turnover driven by climate change. At the local scale, we could observe that the composition of most species assemblages changed according to temperature variations. However, this change in composition always occurred with a lag compared to climate change, suggesting that communities are experiencing a climatic debt. Results suggest that anthropization may play a role in the decoupling between the change in CTI and the change in local temperature. The results of our study highlight an overall thermophilization of assemblages as a response of temperature warming. We demonstrated that this response may exist for a large range of understudied terrestrial animals, and we introduced a framework that can be used in a broader context, opening new opportunities for global change research.
    Type of Medium: Online Resource
    ISSN: 0021-8790 , 1365-2656
    URL: Issue
    URL: Article
    DOI: 10.1111/jane.v92.2
    DOI: 10.1111/1365-2656.13854
    RVK:
    WA 15000
    Language: English
    Publisher: Wiley
    Publication Date: 2023
    detail.hit.zdb_id: 2006616-8
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  • 2
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    Conservation status assessment of banana crop wild relatives using species distribution modelling
    Wiley ; 2021
    In:  Diversity and Distributions Vol. 27, No. 4 ( 2021-04), p. 729-746
    Details
    In: Diversity and Distributions, Wiley, Vol. 27, No. 4 ( 2021-04), p. 729-746
    Abstract: Crop wild relatives (CWR) are an essential source of genetic material for the improvement of certain traits in related crop species. Despite their importance, increasing public, scientific and political support, large gaps exist in the amount of genetic material collected and conserved of many CWR. Here, we construct a dataset on the distribution of wild banana species ( Musa spp.) and assess their risk and conservation status. We deal with the following questions: (a) What areas are potentially suitable for wild banana species? (b) How much of the wild banana diversity is currently at risk or insufficiently conserved ex and in situ ? Location Native distribution area of wild banana species, ranging from the north‐eastern states of India to north‐eastern Australia. Methods We assessed the potential environmental range of wild species using a species distribution modelling approach with MaxEnt. Extinction risk was evaluated following IUCN criterion B, and the ex and in situ conservation status was assessed using an indicator for biodiversity and sustainable development targets. Results We found that 11 out of 59 assessed species can be considered as vulnerable and nine as endangered. Highest species richness was found along the border of south China and northern Vietnam, in the north‐eastern states of India and on the Malayan peninsula. Our distribution modelling approach indicates that the northern Indo‐Burmese region has the highest environmental suitability for most wild banana species and that lowland rain forests in general are highly suitable for bananas. Assessment of in and ex situ conservation status indicates that 56 out of 59 assessed species are currently insufficiently conserved ex situ and that 49 are of high priority for further conservation. Additional in situ conservation is of high priority for six species and of medium priority for 40 species. Main conclusions To date, little of the banana CWR are sufficiently conserved both in and ex situ.
    Type of Medium: Online Resource
    ISSN: 1366-9516 , 1472-4642
    URL: Issue
    URL: Article
    DOI: 10.1111/ddi.v27.4
    DOI: 10.1111/ddi.13233
    Language: English
    Publisher: Wiley
    Publication Date: 2021
    detail.hit.zdb_id: 2020139-4
    detail.hit.zdb_id: 1443181-6
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  • 3
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    Glacier influence on bird assemblages in habitat islands of the high Bolivian Andes
    Wiley ; 2022
    In:  Diversity and Distributions Vol. 28, No. 2 ( 2022-02), p. 242-256
    Details
    In: Diversity and Distributions, Wiley, Vol. 28, No. 2 ( 2022-02), p. 242-256
    Abstract: Climate projections for the upcoming decades predict a significant loss of ice mass particularly critical for glaciers in tropical mountains. In the dry landscapes of the southern Andes (from Southern Peru to Chile), this global trend has strong ecological impacts on high‐altitude wetlands that support a unique avifauna for feeding, roosting and nesting. As glacier runoffs are expected to affect the area and the quality of wetland habitats, these changes may potentially affect bird communities. To address this issue, we studied the structural and functional diversity of bird assemblages in glacier‐fed high‐altitude wetlands ( 〉 4500 m). Location Five valleys of the Cordillera Real, Bolivia. Methods We surveyed bird communities during dry, wet and intermediate seasons in 40 wetlands (total of 27,720 observations of birds and habitats from 540 transects) showing different degrees of dependence on glacial meltwater. We examined the potential effect of glacier retreat on bird communities through changes in wetland area and environmental quality and heterogeneity. Results We found strong relationship between wetland area and taxonomic and functional diversity, but not on phylogenetic diversity. Generalized additive models revealed that avian diversity was influenced by wetland's productivity and elevation and maximized at intermediate levels of glacier influence. Multivariate analysis further showed that habitat productivity and humidity, both potentially influenced by future glacial retreat trends, are the main drivers of bird community composition, with the wettest habitats being crucial for aquatic birds and uncommon species. Main conclusions Glacier retreat may significantly affect bird community diversity and composition through changes in both area and quality of high‐altitude wetlands, with a particular concern for aquatic birds.
    Type of Medium: Online Resource
    ISSN: 1366-9516 , 1472-4642
    URL: Issue
    URL: Article
    DOI: 10.1111/ddi.v28.2
    DOI: 10.1111/ddi.13458
    Language: English
    Publisher: Wiley
    Publication Date: 2022
    detail.hit.zdb_id: 2020139-4
    detail.hit.zdb_id: 1443181-6
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  • 4
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    Environmental DNA metabarcoding as a tool for biodiversity assessment and monitoring: reconstructing established fish communities of north‐temperate lakes and rivers
    Wiley ; 2021
    In:  Diversity and Distributions Vol. 27, No. 10 ( 2021-10), p. 1966-1980
    Details
    In: Diversity and Distributions, Wiley, Vol. 27, No. 10 ( 2021-10), p. 1966-1980
    Abstract: To evaluate the ability of precipitation‐based environmental DNA (eDNA) sample collection and mitochondrial 12S metabarcoding sequencing to reconstruct well‐studied fish communities in lakes and rivers. Specific objectives were to 1) determine correlations between eDNA species detections and known community composition based on conventional field sampling, 2) compare efficiency of eDNA to detect fish biodiversity among systems with variable morphologies and trophic states, and 3) determine if species habitat preferences predict eDNA detection. Location Upper Great Lakes Region, North America. Methods Fish community composition was estimated for seven lakes and two Mississippi River navigation pools using sequence data from the mitochondrial 12S gene amplified from 10 to 50 water samples per waterbody collected in 50‐mL centrifuge tubes at a single time point. Environmental DNA (eDNA) was concentrated without filtration by centrifuging samples to reduce per‐sample handling time. Taxonomic detections from eDNA were compared to established community monitoring databases containing up to 40 years of sampling and a detailed habitat/substrate preference matrix to identify patterns of bias. Results Mitochondrial 12S gene metabarcoding detected 15%–47% of the known species at each waterbody and 30%–76% of known genera. Non‐metric multidimensional scaling (NMDS) assessment of the community structure indicated that eDNA‐detected communities grouped in a similar pattern as known communities. Discriminant analysis of principal components indicated that there was a high degree of overlap in habitat/substrate preference of eDNA‐detected and eDNA‐undetected species suggesting limited habitat bias for eDNA sampling. Main conclusions Large numbers of small volume samples sequenced at the mitochondrial 12S gene can describe the coarse community structure of freshwater systems. However, additional conventional sampling and environmental DNA sampling may be necessary for a complete diversity census.
    Type of Medium: Online Resource
    ISSN: 1366-9516 , 1472-4642
    URL: Issue
    URL: Article
    DOI: 10.1111/ddi.v27.10
    DOI: 10.1111/ddi.13253
    Language: English
    Publisher: Wiley
    Publication Date: 2021
    detail.hit.zdb_id: 2020139-4
    detail.hit.zdb_id: 1443181-6
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  • 5
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    Where will species on the move go? Insights from climate connectivity modelling across European terrestrial habitats
    Elsevier BV ; 2022
    In:  Journal for Nature Conservation Vol. 66 ( 2022-04), p. 126139-
    Details
    In: Journal for Nature Conservation, Elsevier BV, Vol. 66 ( 2022-04), p. 126139-
    Type of Medium: Online Resource
    ISSN: 1617-1381
    URL: Article
    DOI: 10.1016/j.jnc.2022.126139
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2022
    detail.hit.zdb_id: 2077553-2
    detail.hit.zdb_id: 2087786-9
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  • 6
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    Host plant density and patch isolation drive occupancy and abundance at a butterfly's northern range margin
    Wiley ; 2017
    In:  Ecology and Evolution Vol. 7, No. 1 ( 2017-01), p. 331-345
    Details
    In: Ecology and Evolution, Wiley, Vol. 7, No. 1 ( 2017-01), p. 331-345
    Abstract: Marginal populations are usually small, fragmented, and vulnerable to extinction, which makes them particularly interesting from a conservation point of view. They are also the starting point of range shifts that result from climate change, through a process involving colonization of newly suitable sites at the cool margin of species distributions. Hence, understanding the processes that drive demography and distribution at high‐latitude populations is essential to forecast the response of species to global changes. We investigated the relative importance of solar irradiance (as a proxy for microclimate), habitat quality, and connectivity on occupancy, abundance, and population stability at the northern range margin of the Oberthür's grizzled skipper butterfly Pyrgus armoricanus . For this purpose, butterfly abundance was surveyed in a habitat network consisting of 50 habitat patches over 12 years. We found that occupancy and abundance (average and variability) were mostly influenced by the density of host plants and the spatial isolation of patches, while solar irradiance and grazing frequency had only an effect on patch occupancy. Knowing that the distribution of host plants extends further north, we hypothesize that the actual variable limiting the northern distribution of P. armoricanus might be its dispersal capacity that prevents it from reaching more northern habitat patches. The persistence of this metapopulation in the face of global changes will thus be fundamentally linked to the maintenance of an efficient network of habitats.
    Type of Medium: Online Resource
    ISSN: 2045-7758 , 2045-7758
    URL: Issue
    URL: Article
    DOI: 10.1002/ece3.2017.7.issue-1
    DOI: 10.1002/ece3.2597
    Language: English
    Publisher: Wiley
    Publication Date: 2017
    detail.hit.zdb_id: 2635675-2
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  • 7
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    Paintings predict the distribution of species, or the challenge of selecting environmental predictors and evaluation statistics
    Wiley ; 2018
    In:  Global Ecology and Biogeography Vol. 27, No. 2 ( 2018-02), p. 245-256
    Details
    In: Global Ecology and Biogeography, Wiley, Vol. 27, No. 2 ( 2018-02), p. 245-256
    Abstract: Species distribution modelling, a family of statistical methods that predicts species distributions from a set of occurrences and environmental predictors, is now routinely applied in many macroecological studies. However, the reliability of evaluation metrics usually employed to validate these models remains questioned. Moreover, the emergence of online databases of environmental variables with global coverage, especially climatic, has favoured the use of the same set of standard predictors. Unfortunately, the selection of variables is too rarely based on a careful examination of the species' ecology. In this context, our aim was to highlight the importance of selecting ad hoc variables in species distribution models, and to assess the ability of classical evaluation statistics to identify models with no biological realism. Innovation First, we reviewed the current practices in the field of species distribution modelling in terms of variable selection and model evaluation. Then, we computed distribution models of 509 European species using pseudo‐predictors derived from paintings or using a real set of climatic and topographic predictors. We calculated model performance based on the area under the receiver operating curve (AUC) and true skill statistics (TSS), partitioning occurrences into training and test data with different levels of spatial independence. Most models computed from pseudo‐predictors were classified as good and sometimes were even better evaluated than models computed using real environmental variables. However, on average they were better discriminated when the partitioning of occurrences allowed testing for model transferability. Main conclusions These findings confirm the crucial importance of variable selection and the inability of current evaluation metrics to assess the biological significance of distribution models. We recommend that researchers carefully select variables according to the species' ecology and evaluate models only according to their capacity to be transfered in distant areas. Nevertheless, statistics of model evaluations must still be interpreted with great caution.
    Type of Medium: Online Resource
    ISSN: 1466-822X , 1466-8238
    URL: Issue
    URL: Article
    DOI: 10.1111/geb.2018.27.issue-2
    DOI: 10.1111/geb.12684
    Language: English
    Publisher: Wiley
    Publication Date: 2018
    detail.hit.zdb_id: 1479787-2
    detail.hit.zdb_id: 2021283-5
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  • 8
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    Communities in infrastructure habitats are species rich but only partly support species associated with semi‐natural grasslands
    Wiley ; 2023
    In:  Journal of Applied Ecology Vol. 60, No. 5 ( 2023-05), p. 837-848
    Details
    In: Journal of Applied Ecology, Wiley, Vol. 60, No. 5 ( 2023-05), p. 837-848
    Abstract: Biodiversity linked to traditionally managed semi‐natural grasslands is declining, despite conservation efforts. At the same time, the area of novel grassland habitats along linear infrastructure, such as road verges and power line corridors, is increasing and in some regions surpass the area of semi‐natural grasslands. An open question is to what extent these novel grasslands can complement or even replace traditionally managed grasslands as habitat for grassland species. We compared the alpha (species richness) and beta (abundance‐based dissimilarities) diversity of plants, bumblebees and butterflies among semi‐natural pastures, verges of small and big roads, power line corridors and uncultivated field borders nested within 32 landscapes (2 × 2 km squares). Landscapes had either high or low road density and were with or without power line corridors. Across landscapes there was also a gradient in the area of semi‐natural pastures. Alpha diversity of all three species groups was as high in power line corridors and verges of small roads as in semi‐natural pastures, regardless of landscape composition. Although all habitat types shared a large proportion of species, community composition differed among habitats for all three species groups. The beta diversity of plants and butterflies was driven primarily by the replacement of species (turnover), while the beta diversity of bumblebees was driven by a rarer occurrence of certain species in road verges (nestedness). This means that linear infrastructure habitats cannot fully replace the role of semi‐natural grasslands for plant and pollinator diversity. The area of road verges, power line corridors and semi‐natural pastures in the landscape influenced community composition of plants and butterflies, but not the similarity in community composition among habitats within landscapes. Policy implications . Although novel grasslands along linear infrastructures have high numbers of grassland species, they only support a part of the biodiversity found in traditionally managed semi‐natural grasslands. Therefore, protecting and restoring semi‐natural grasslands should continue to be a priority for the conservation of grassland biodiversity. However, especially in landscapes where the area of semi‐natural grasslands is low, road verges and power line corridors can be important habitats for a number of grassland plants and insects and should be managed to promote biodiversity.
    Type of Medium: Online Resource
    ISSN: 0021-8901 , 1365-2664
    URL: Issue
    URL: Article
    DOI: 10.1111/jpe.v60.5
    DOI: 10.1111/1365-2664.14378
    Language: English
    Publisher: Wiley
    Publication Date: 2023
    detail.hit.zdb_id: 2020408-5
    detail.hit.zdb_id: 410405-5
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  • 9
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    Balancing transferability and complexity of species distribution models for rare species conservation
    Wiley ; 2021
    In:  Diversity and Distributions Vol. 27, No. 1 ( 2021-01), p. 95-108
    Details
    In: Diversity and Distributions, Wiley, Vol. 27, No. 1 ( 2021-01), p. 95-108
    Abstract: Species distribution models (SDMs) are valuable for rare species conservation and are commonly used to extrapolate predictions of habitat suitability geographically to regions where species occurrence is unknown (i.e., transferability). Spatially structured cross‐validation can be used to infer transferability, yet, few studies have evaluated how delineation of cross‐validation folds affects model complexity and predictions. We developed SDMs using multiple cross‐validation approaches to understand the implications for predicting habitat suitability for northern Idaho ground squirrels, a rare, federally threatened species that has been extensively surveyed in regions where known populations occur, resulting in 〉 8000 presence locations. Location Idaho, USA. Methods We delineated cross‐validation folds by mimicking the manner in which predictions would be geographically extrapolated or by using existing dispersal barriers. We varied the distance between, number, and directionality of folds. We conducted a grid search on statistical regularization parameters to optimize model complexity, covering a range of values exceeding that typically implemented. For each cross‐validation approach, we selected optimal regularization and model complexity based on out‐of‐sample predictive ability. Results Delineation of cross‐validation folds substantially affected resulting model complexity and extrapolated predictions. All cross‐validation approaches resulted in models with apparently high out‐of‐sample predictive ability, yet optimal model complexity varied substantially among the approaches. Regularization demonstrated a noisy relationship between model complexity and prediction, where local optima in predictive performance were common at small values. Main conclusion Subtle modelling decisions can have large consequences for predictions of habitat suitability and transferability of SDMs. When transferability is the goal, cross‐validation approaches should be considered carefully and mimic the manner in which spatial extrapolation will occur, else overly complex models with inflated assessments of predictive accuracy may result. Further, spatially structured cross‐validation may not guard against over‐parameterization, and assessing a broader range of regularization parameters may be necessary to optimize model complexity for transferability.
    Type of Medium: Online Resource
    ISSN: 1366-9516 , 1472-4642
    URL: Issue
    URL: Article
    DOI: 10.1111/ddi.v27.1
    DOI: 10.1111/ddi.13174
    Language: English
    Publisher: Wiley
    Publication Date: 2021
    detail.hit.zdb_id: 2020139-4
    detail.hit.zdb_id: 1443181-6
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  • 10
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    Analytical guidelines to increase the value of community science data: An example using eBird data to estimate species distributions
    Wiley ; 2021
    In:  Diversity and Distributions Vol. 27, No. 7 ( 2021-07), p. 1265-1277
    Details
    In: Diversity and Distributions, Wiley, Vol. 27, No. 7 ( 2021-07), p. 1265-1277
    Abstract: Ecological data collected by the general public are valuable for addressing a wide range of ecological research and conservation planning, and there has been a rapid increase in the scope and volume of data available. However, data from eBird or other large‐scale projects with volunteer observers typically present several challenges that can impede robust ecological inferences. These challenges include spatial bias, variation in effort and species reporting bias. Innovation We use the example of estimating species distributions with data from eBird, a community science or citizen science (CS) project. We estimate two widely used metrics of species distributions: encounter rate and occupancy probability. For each metric, we critically assess the impact of data processing steps that either degrade or refine the data used in the analyses. CS data density varies widely across the globe, so we also test whether differences in model performance are robust to sample size. Main conclusions Model performance improved when data processing and analytical methods addressed the challenges arising from CS data; however, the degree of improvement varied with species and data density. The largest gains we observed in model performance were achieved with 1) the use of complete checklists (where observers report all the species they detect and identify, allowing non‐detections to be inferred) and 2) the use of covariates describing variation in effort and detectability for each checklist. Occupancy models were more robust to a lack of complete checklists. Improvements in model performance with data refinement were more evident with larger sample sizes. In general, we found that the value of each refinement varied by situation and we encourage researchers to assess the benefits in other scenarios. These approaches will enable researchers to more effectively harness the vast ecological knowledge that exists within CS data for conservation and basic research.
    Type of Medium: Online Resource
    ISSN: 1366-9516 , 1472-4642
    URL: Issue
    URL: Article
    DOI: 10.1111/ddi.v27.7
    DOI: 10.1111/ddi.13271
    Language: English
    Publisher: Wiley
    Publication Date: 2021
    detail.hit.zdb_id: 2020139-4
    detail.hit.zdb_id: 1443181-6
    SSG: 12
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