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      Factors restricting the range expansion of the invasive green anole Anolis carolinensis on Okinawa Island, Japan

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          The green anole Anolis carolinensis invaded the Ogasawara Islands in Japan, drove various native species to extinction, and its distribution expanded 14 years after initial establishment. A. carolinensis invaded Okinawa Island, but it has not expanded its distribution in more than 25 years, although its density is extremely high in the southern region. To determine whether A. carolinensis has the potential to expand its distribution on Okinawa Island, we performed phylogenetic analysis of mitochondrial ND2 DNA sequences to study the origin of A. carolinensis that invaded Okinawa Island. We further used a species distribution model (MaxEnt) based on the distribution of native populations in North America to identify ecologically suitable areas on Okinawa Island. Nucleotide sequence analysis shows that the invader A. carolinensis originated in the western part of the Gulf Coast and inland areas of the United States and that a portion of the anoles on Okinawa was not introduced via the Ogasawara Islands. The MaxEnt predictions indicate that most areas in Okinawa Island are suitable for A. carolinensis. Therefore, A. carolinensis may have the potential to expand its distribution in Okinawa Island. The predictions indicate that habitat suitability is high in areas of high annual mean temperature and urbanized areas. The values of precipitation in summer in the northern region of Okinawa Island were higher compared with those of North America, which reduced the habitat suitability in Okinawa Island. Adaptation to low temperatures, an increase in the mean temperature through global warming, and an increase in open environments through land development will likely expand the distribution of A. carolinensis in Okinawa Island. Therefore, we must continue to monitor the introduced populations and be alert to the possibility that city planning that increases open environments may cause their range to expand.

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          Is my species distribution model fit for purpose? Matching data and models to applications

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            The Effects of Sampling Bias and Model Complexity on the Predictive Performance of MaxEnt Species Distribution Models

            Species distribution models (SDMs) trained on presence-only data are frequently used in ecological research and conservation planning. However, users of SDM software are faced with a variety of options, and it is not always obvious how selecting one option over another will affect model performance. Working with MaxEnt software and with tree fern presence data from New Zealand, we assessed whether (a) choosing to correct for geographical sampling bias and (b) using complex environmental response curves have strong effects on goodness of fit. SDMs were trained on tree fern data, obtained from an online biodiversity data portal, with two sources that differed in size and geographical sampling bias: a small, widely-distributed set of herbarium specimens and a large, spatially clustered set of ecological survey records. We attempted to correct for geographical sampling bias by incorporating sampling bias grids in the SDMs, created from all georeferenced vascular plants in the datasets, and explored model complexity issues by fitting a wide variety of environmental response curves (known as “feature types” in MaxEnt). In each case, goodness of fit was assessed by comparing predicted range maps with tree fern presences and absences using an independent national dataset to validate the SDMs. We found that correcting for geographical sampling bias led to major improvements in goodness of fit, but did not entirely resolve the problem: predictions made with clustered ecological data were inferior to those made with the herbarium dataset, even after sampling bias correction. We also found that the choice of feature type had negligible effects on predictive performance, indicating that simple feature types may be sufficient once sampling bias is accounted for. Our study emphasizes the importance of reducing geographical sampling bias, where possible, in datasets used to train SDMs, and the effectiveness and essentialness of sampling bias correction within MaxEnt.
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              Multiple sources, admixture, and genetic variation in introduced anolis lizard populations.

              Invasive species are classically thought to suffer from reduced within-population genetic variation compared to their native-range sources due to founder effects and population bottlenecks during introduction. Reduction in genetic variation in introduced species may limit population growth, increase the risk of extinction, and constrain adaptation, hindering the successful establishment and spread of an alien species. Results of recent empirical studies, however, show higher than expected genetic variation, rapid evolution, and multiple native-range sources in introduced populations, which challenge the classical scenario of invasive-species genetics. With mitochondrial DNA (mtDNA) sequence data, we examined the molecular genetics of 10 replicate introductions of 8 species of Anolis lizards. Eighty percent of introductions to Florida and the Dominican Republic were from multiple native-range source populations. MtDNA haplotypes restricted to different geographically distinct populations in the native range of a species commonly occurred as intrapopulation polymorphisms in introduced populations. Two-thirds of introduced populations had two or more sources, and admixture elevated genetic variation in half of the introduced populations above levels typical of native-range populations. The mean pairwise sequence divergence among haplotypes sampled within introduced populations was nearly twice that within native-range populations (2.6% vs. 1.4%). The dynamics of introductions from multiple sources and admixture explained the observed genetic contrasts between native and introduced Anolis populations better than the classical scenario for most introduced populations. Elevated genetic variation through admixture occurred regardless of the mode or circumstances of an introduction. Little insight into the number of sources or amount of genetic variation in introduced populations was gained by knowing the number of physical introductions, the size of a species' non-native range, or whether it was a deliberate or accidental introduction. We hypothesize that elevated genetic variation through admixture of multiple sources is more common in biological invasions than previously thought. We propose that introductions follow a sequential, two-step process involving a reduction in genetic variation due to founder effects and population bottlenecks followed by an increase in genetic variation if admixture of individuals from multiple native-range sources occurs.

                Author and article information

                Ecol Evol
                Ecol Evol
                Ecology and Evolution
                John Wiley and Sons Inc. (Hoboken )
                10 May 2017
                June 2017
                : 7
                : 12 ( doiID: 10.1002/ece3.2017.7.issue-12 )
                : 4357-4366
                [ 1 ] Department of Ecology and Evolutionary Biology Graduate School of Life SciencesTohoku University Sendai MiyagiJapan
                [ 2 ] Ogasawara DivisionJapan Wildlife Research Center TokyoJapan
                [ 3 ] Naha Nature Conservation OfficeMinistry of the Environment Naha OkinawaJapan
                Author notes
                [* ] Correspondence

                Masakado Kawata, Department of Ecology and Evolutionary Biology, Graduate School of Life Sciences, Tohoku University, Sendai, Miyagi, Japan.

                Email: kawata@ 123456m.tohoku.ac.jp

                © 2017 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd.

                This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

                Page count
                Figures: 5, Tables: 1, Pages: 11, Words: 7016
                Funded by: Japan Society for the Promotion of Science
                Award ID: 22657004
                Award ID: 16J40194
                Original Research
                Original Research
                Custom metadata
                June 2017
                Converter:WILEY_ML3GV2_TO_NLMPMC version:5.1.1 mode:remove_FC converted:20.06.2017

                Evolutionary Biology

                adaptation, conservation, invasion, maxent, species distribution model, time lag


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