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Berlin Brandenburg

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  • 1
    In: Conservation Letters, July 2016, Vol.9(4), pp.281-289
    Description: International trade of species facilitates the establishment of nonnative organisms. Highlighting areas potentially suitable for invasive species (risk areas) allows for effective importation regulations to prevent the spread of and the potential damage caused by such species. Species distribution models (SDMs) are commonly used to predict risk areas but they usually disregard intraspecific differentiation and corresponding differences in climatic requirements. We used as an example of a commonly traded species and developed SDMs at the species‐ and subspecies‐level to assess the value of subspecific information for risk area predictions. We show that species‐level models are less efficient than subspecies‐based SDMs and that risk areas differ considerably between subspecies. Therefore, the invasive potential of a species can depend on the subspecies imported and the particular climatic condition of the target area. This paves the way to novel policy‐relevant guidelines to legislate for smart regulations instead of complete import interdictions.
    Keywords: Invasive Risk Assessment ; Invasive Species ; Species Distribution Model ; Species Trade Regulation ; Subspecies ; Traded Species
    ISSN: 1755-263X
    E-ISSN: 1755-263X
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  • 2
    In: Journal of Applied Ecology, April 2016, Vol.53(2), pp.501-510
    Description: The rapid expansion of systematic monitoring schemes necessitates robust methods to reliably assess species' status and trends. Insect monitoring poses a challenge where there are strong seasonal patterns, requiring repeated counts to reliably assess abundance. Butterfly monitoring schemes (BMSs) operate in an increasing number of countries with broadly the same methodology, yet they differ in their observation frequency and in the methods used to compute annual abundance indices. Using simulated and observed data, we performed an extensive comparison of two approaches used to derive abundance indices from count data collected via BMS, under a range of sampling frequencies. Linear interpolation is most commonly used to estimate abundance indices from seasonal count series. A second method, hereafter the regional generalized additive model (GAM), fits a GAM to repeated counts within sites across a climatic region. For the two methods, we estimated bias in abundance indices and the statistical power for detecting trends, given different proportions of missing counts. We also compared the accuracy of trend estimates using systematically degraded observed counts of the Gatekeeper Pyronia tithonus (Linnaeus 1767). The regional GAM method generally outperforms the linear interpolation method. When the proportion of missing counts increased beyond 50%, indices derived via the linear interpolation method showed substantially higher estimation error as well as clear biases, in comparison to the regional GAM method. The regional GAM method also showed higher power to detect trends when the proportion of missing counts was substantial. Synthesis and applications. Monitoring offers invaluable data to support conservation policy and management, but requires robust analysis approaches and guidance for new and expanding schemes. Based on our findings, we recommend the regional generalized additive model approach when conducting integrative analyses across schemes, or when analysing scheme data with reduced sampling efforts. This method enables existing schemes to be expanded or new schemes to be developed with reduced within‐year sampling frequency, as well as affording options to adapt protocols to more efficiently assess species status and trends across large geographical scales. Monitoring offers invaluable data to support conservation policy and management, but requires robust analysis approaches and guidance for new and expanding schemes. Based on our findings, we recommend the regional generalized additive model approach when conducting integrative analyses across schemes, or when analysing scheme data with reduced sampling efforts. This method enables existing schemes to be expanded or new schemes to be developed with reduced within‐year sampling frequency, as well as affording options to adapt protocols to more efficiently assess species status and trends across large geographical scales.
    Keywords: Abundance Indices ; Butterfly Monitoring Scheme ; Butterfly Count ; Citizen Science ; Flight Period ; Insect Conservation ; Missing Data ; Pollard Walk ; Sampling Effort ; Seasonal Pattern
    ISSN: 0021-8901
    E-ISSN: 1365-2664
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  • 3
    In: Ecology and Evolution, May 2019, Vol.9(10), pp.5870-5890
    Description: The Irano‐Turanian (IT) floristic region is considered an important center of origin for many taxa. However, there is a lack of studies dealing with typical IT genera that also occur in neighboring areas. The species‐rich monocot genus Salisb. shows a center of diversity in IT region and a distribution in adjacent regions, therefore representing a good study object to investigate spatial and temporal relationships among IT region and its neighboring areas (East Asia, Euro‐Siberia, Himalaya, and Mediterranean). We aimed at (a) testing the origin of the genus and of its major lineages in the IT region, (b) reconstructing divergence times, and (c) reconstructing colonization events. To address these problems, sequences of the ribosomal DNA internal transcribed spacer (ITS) region of 418 individuals and chloroplast intergenic spacers sequences (A‐H, L‐F) of 497 individuals, representing 116 species from all sections of the genus and nearly its entire distribution area were analyzed. Divergence times were estimated under a random molecular clock based on nrITS phylogeny, which was the most complete data set regarding the representation of species and distribution areas. Ancestral distribution ranges were estimated for the nrITS data set as well as for a combined data set, revealing that most likely originated in southwestern Asia. This genus first diversified there starting in the Early Miocene. In the Middle Miocene, migrated to the Mediterranean and to East Asia, while migration into Euro‐Siberia took place in the Late Miocene. During the Pleistocene, the Arctic was colonized and the most widespread species, reached North America. The Mediterranean basin was colonized multiple times from southwestern Asia or Euro‐Siberia. Most of the currently existing species originated during the last 3 Ma. Divergence time estimation and ancestral range reconstructions were carried out for the species‐rich monocot genus (Liliaceae). Our study could demonstrate that the species‐rich Irano‐Turanian (IT) floristic region, a current centre of species diversity, is also the origin of the genus and of its major linages. Colonisation of adjacent areas started from the IT floristic region and benefit from periods of climatic changes creating dry habits. Therefore, our study supports that the IT region is an important source of taxa for adjacent areas of Euro‐Siberia.
    Keywords: Ancestral Area Reconstruction ; Biogeography ; Dated Phylogeny ; Gagea ; Irano‐Turanian Region ; Southwestern Asia
    ISSN: 2045-7758
    E-ISSN: 2045-7758
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  • 4
    In: Diversity and Distributions, July 2019, Vol.25(7), pp.1088-1100
    Description: Byline: Thomas Lecocq, Alexander Harpke, Pierre Rasmont,Oliver Schweiger, Janine Bolliger Keywords: bumblebee; climate change; evolutionary significant unit; intraspecific variability; model performance; species distribution model Abstract Aim Conventional species distribution models (SDMs) usually focus on the species level but disregard intraspecific variability. Phylogeographic structure and evolutionary significant units (ESU) have been proposed as pragmatic proxies to incorporate intraspecific differentiation in SDMs. Nevertheless, the efficiency of using these proxies in SDMs has been poorly investigated. We analysed how the projections of current and future climatically suitable areas can be affected when using ESU-based or lineage-based models compared to a species-level model. Location West-Palaearctic region. Methods As examples, we used three bumblebee species (133,787 observations). We assessed potential climatic niche differentiation between species level, lineages and ESUs, by determining the niche position and niche breadth for each classification level by outlying mean index analyses. Subsequently, we developed SDMs for each species and classification level separately using boosted regression trees prior to a comparison of their performances. Finally, we used the alternative models to project the extent of climatically suitable areas in 2070. Results We found that in spite of highly similar overall model accuracy, integrating intraspecific variability significantly increases model sensitivity (i.e., better predicting presences) while decreased model specificity (i.e., over-predicting the range). Consequently, both predictions of current and projections of future suitable conditions differed among the three approaches. Main conclusions We showed that although integrating lineage or ESU information did not improve the accuracy of conventional species-level SDMs, it led to considerably different conclusions. As SDM-based climatic risk assessments are increasingly used to help and improve conservation plans, divergences and limitations of each modelling approach should be taken into account for developing efficient biodiversity management strategies. Lineage and ESU-based SDMs offer the advantage to draw attention to species in which allopatric populations could display physiologically different responses to climate change when they lead to different results than species-based models. CAPTION(S):
    Keywords: Bumblebee ; Climate Change ; Evolutionary Significant Unit ; Intraspecific Variability ; Model Performance ; Species Distribution Model
    ISSN: 1366-9516
    E-ISSN: 1472-4642
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