Jan O. Engler

Mapping Species Distributions with MAXENT Using a Geographically Biased Sample of Presence Data: A Performance Assessment of Methods for Correcting Sampling Bias

MAXENT is now a common species distribution modeling (SDM) tool used by conservation practitioners for predicting the distribution of a species from a set of records and environmental predictors. However, datasets of species occurrence used to train the model are often biased in the geographical space because of unequal sampling effort across the study area. This bias may be a source of strong inaccuracy in the resulting model and could lead to incorrect predictions. Although a number of sampling bias correction methods have been proposed, there is no consensual guideline to account for it. We compared here the performance of five methods of bias correction on three datasets of species occurrence: one “virtual” derived from a land cover map, and two actual datasets for a turtle (Chrysemys picta) and a salamander (Plethodon cylindraceus). We subjected these datasets to four types of sampling biases corresponding to potential types of empirical biases. We applied five correction methods to the biased samples and compared the outputs of distribution models to unbiased datasets to assess the overall correction performance of each method. The results revealed that the ability of methods to correct the initial sampling bias varied greatly depending on bias type, bias intensity and species. However, the simple systematic sampling of records consistently ranked among the best performing across the range of conditions tested, whereas other methods performed more poorly in most cases. The strong effect of initial conditions on correction performance highlights the need for further research to develop a step-by-step guideline to account for sampling bias. However, this method seems to be the most efficient in correcting sampling bias and should be advised in most cases.

Evolutionary History of Wild Barley (Hordeum vulgare subsp. spontaneum) Analyzed Using Multilocus Sequence Data and Paleodistribution Modeling

Studies of Hordeum vulgare subsp. spontaneum, the wild progenitor of cultivated barley, have mostly relied on materials collected decades ago and maintained since then ex situ in germplasm repositories. We analyzed spatial genetic variation in wild barley populations collected rather recently, exploring sequence variations at seven single-copy nuclear loci, and inferred the relationships among these populations and toward the genepool of the crop. The wild barley collection covers the whole natural distribution area from the Mediterranean to Middle Asia. In contrast to earlier studies, Bayesian assignment analyses revealed three population clusters, in the Levant, Turkey, and east of Turkey, respectively. Genetic diversity was exceptionally high in the Levant, while eastern populations were depleted of private alleles. Species distribution modeling based on climate parameters and extant occurrence points of the taxon inferred suitable habitat conditions during the ice-age, particularly in the Levant and Turkey. Together with the ecologically wide range of habitats, they might contribute to structured but long-term stable populations in this region and their high genetic diversity. For recently collected individuals, Bayesian assignment to geographic clusters was generally unambiguous, but materials from genebanks often showed accessions that were not placed according to their assumed geographic origin or showed traces of introgression from cultivated barley. We assign this to gene flow among accessions during ex situ maintenance. Evolutionary studies based on such materials might therefore result in wrong conclusions regarding the history of the species or the origin and mode of domestication of the crop, depending on the accessions included.

Evaluating the Significance of Paleophylogeographic Species Distribution Models in Reconstructing Quaternary Range-Shifts of Nearctic Chelonians

The climatic cycles of the Quaternary, during which global mean annual temperatures have regularly changed by 5–10°C, provide a special opportunity for studying the rate, magnitude, and effects of geographic responses to changing climates. During the Quaternary, high- and mid-latitude species were extirpated from regions that were covered by ice or otherwise became unsuitable, persisting in refugial retreats where the environment was compatible with their tolerances. In this study we combine modern geographic range data, phylogeny, Pleistocene paleoclimatic models, and isotopic records of changes in global mean annual temperature, to produce a temporally continuous model of geographic changes in potential habitat for 59 species of North American turtles over the past 320 Ka (three full glacial-interglacial cycles). These paleophylogeographic models indicate the areas where past climates were compatible with the modern ranges of the species and serve as hypotheses for how their geographic ranges would have changed in response to Quaternary climate cycles. We test these hypotheses against physiological, genetic, taxonomic and fossil evidence, and we then use them to measure the effects of Quaternary climate cycles on species distributions. Patterns of range expansion, contraction, and fragmentation in the models are strongly congruent with (i) phylogeographic differentiation; (ii) morphological variation; (iii) physiological tolerances; and (iv) intraspecific genetic variability. Modern species with significant interspecific differentiation have geographic ranges that strongly fluctuated and repeatedly fragmented throughout the Quaternary. Modern species with low genetic diversity have geographic distributions that were highly variable and at times exceedingly small in the past. Our results reveal the potential for paleophylogeographic models to (i) reconstruct past geographic range modifications, (ii) identify geographic processes that result in genetic bottlenecks; and (iii) predict threats due to anthropogenic climate change in the future.

Species distribution models contribute to determine the effect of climate and interspecific interactions in moving hybrid zones

Climate is a major factor delimiting species’ distributions. However, biotic interactions may also be prominent in shaping geographical ranges, especially for parapatric species forming hybrid zones. Determining the relative effect of each factor and their interaction of the contact zone location has been difficult due to the lack of broad scale environmental data. Recent developments in species distribution modelling (SDM) now allow disentangling the relative contributions of climate and species’ interactions in hybrid zones and their responses to future climate change. We investigated the moving hybrid zone between the breeding ranges of two parapatric passerines in Europe. We conducted SDMs representing the climatic conditions during the breeding season. Our results show a large mismatch between the realized and potential distributions of the two species, suggesting that interspecific interactions, not climate, account for the present location of the contact zone. The SDM scenarios show that the southerly distributed species, Hippolais polyglotta, might lose large parts of its southern distribution under climate change, but a similar gain of novel habitat along the hybrid zone seems unlikely, because interactions with the other species (H. icterina) constrain its range expansion. Thus, whenever biotic interactions limit range expansion, species may become ‘trapped’ if range loss due to climate change is faster than the movement of the contact zone. An increasing number of moving hybrid zones are being reported, but the proximate causes of movement often remain unclear. In a global context of climate change, we call for more interest in their interactions with climate change.

Predicting the potential distribution of the invasive Common Waxbill Estrilda astrild (Passeriformes: Estrildidae)

Human transport and commerce have led to an increased spread of non-indigenous species. Alien invasive species can have major impacts on many aspects of ecological systems. Therefore, the ability to predict regions potentially suitable for alien species, which are hence at high risk, has become a core task for successful management. The Common Waxbill Estrilda astrild is a widespread African species, which has been successfully introduced to many parts of the world. Herein, we used MAXENT software, a machine-learning algorithm, to assess its current potential distribution based on species records compiled from various sources. Models were trained separately with records from the species’ native range and from both invaded and native ranges. Subsequently, the models were projected onto different future climate change scenarios. They successfully identified the species known range as well as some regions that seem climatically well suited, where the Common Waxbill is not yet recorded. Assuming future conditions, the models suggest poleward range shifts. However, its potential distribution pattern within its tropical native and invasive ranges appears to be more complex. Although the results of both separate analyses showed general similarities, many differences have become obvious. Niche overlap analysis shows that the invasive range includes only a small fraction of the ecological space that can be found in the native range. Thus, we tentatively prefer the model based on native locations only, but in particular, we highlight the importance of the selection process of species records for modelling invasive species.ZusammenfassungWeltweiter Handel und Mobilität haben zu einer zunehmenden Ausbreitung nicht-heimischer Arten geführt. Invasive Arten können großen Einfluss auf zahlreiche Aspekte ökosystemarer Zusammenhänge haben. Deshalb ist die Fähigkeit, Regionen vorherzusagen, die für solche Arten potentiell geeignet und daher möglicherweise bedroht sind, eine Kernaufgabe erfolgreichen Managements. Der Wellenastrild Estrilda astrild ist eine weit verbreitete afrikanische Art, die erfolgreich in viele Gebiete der Welt eingeführt wurde. Mit Hilfe der Software MAXENT, einem Algorithmus, der auf maschinellem Lernen basiert, haben wir seine gegenwärtige, potentielle Verbreitung basierend auf Fundpunkten aus verschiedenen Quellen modelliert. Die Modelle wurden sowohl mit Nachweisen aus dem heimischen als auch dem invasiven und heimischen Verbreitungsgebiet gemeinsam trainiert. Nachfolgend wurden beide auf unterschiedliche zukünftige Klimawandelszenarien projiziert. Die Modelle identifizierten erfolgreich sowohl das bekannte Verbreitungsgebiet der Art, als auch Gebiete, die klimatisch gut geeignet erscheinen, in denen der Wellenastrild aber noch nicht nachgewiesen wurde. Unter zukünftigen Bedingungen legen die Modelle eine polwärts gerichtete Verschiebung der Verbreitungsgebiete nahe, obwohl die Muster der potentiellen Verbreitung innerhalb der Tropen des heimischen und invasiven Areals komplexer erscheinen. Trotz allgemeiner Übereinstimmung zwischen beiden Analysen wurden einige Unterschiede auffällig. Eine Analyse des Überlappungsbereiches der Nischen ergab, dass invasive Fundpunkte innerhalb des ökologischen Raumes liegen, der durch die Fundpunkte aus dem natürlichen Verbreitungsgebiet aufgespannt wird. Wir tendieren daher vorsichtig zu dem Modell basierend auf der natürlichen Verbreitung, unterstreichen aber vor allem die Bedeutung des Auswahlprozesses der Fundorte für Modellierungen invasiver Arten.

Comparative landscape genetics of three closely related sympatric Hesperid butterflies with diverging ecological traits.

To understand how landscape characteristics affect gene flow in species with diverging ecological traits, it is important to analyze taxonomically related sympatric species in the same landscape using identical methods. Here, we present such a comparative landscape genetic study involving three closely related Hesperid butterflies of the genus Thymelicus that represent a gradient of diverging ecological traits. We analyzed landscape effects on their gene flow by deriving inter-population connectivity estimates based on different species distribution models (SDMs), which were calculated from multiple landscape parameters. We then used SDM output maps to calculate circuit-theoretic connectivity estimates and statistically compared these estimates to actual genetic differentiation in each species. We based our inferences on two different analytical methods and two metrics of genetic differentiation. Results indicate that land use patterns influence population connectivity in the least mobile specialist T. acteon. In contrast, populations of the highly mobile generalist T. lineola were panmictic, lacking any landscape related effect on genetic differentiation. In the species with ecological traits in between those of the congeners, T. sylvestris, climate has a strong impact on inter-population connectivity. However, the relative importance of different landscape factors for connectivity varies when using different metrics of genetic differentiation in this species. Our results show that closely related species representing a gradient of ecological traits also show genetic structures and landscape genetic relationships that gradually change from a geographical macro- to micro-scale. Thus, the type and magnitude of landscape effects on gene flow can differ strongly even among closely related species inhabiting the same landscape, and depend on their relative degree of specialization. In addition, the use of different genetic differentiation metrics makes it possible to detect recent changes in the relative importance of landscape factors affecting gene flow, which likely change as a result of contemporary habitat alterations.

Missing the target? A critical view on butterfly conservation efforts on calcareous grasslands in south-western Germany

Butterflies are strongly declining on grassland habitats of Central Europe. Therefore, the success of conservation measures on high quality grassland habitats is controversially discussed. We compared the changes in butterfly diversity and community structure on six managed calcareous grasslands with eight unmanaged vineyard fallows. We obtained strong losses of species diversity and remarkable shifts of community compositions on both habitat types. However, the changes on vineyard fallows were only slightly more severe but more stochastic than on the calcareous grasslands. The shifts in community composition with respect to functional species traits were rather similar between the two different grassland types so that complex butterfly communities evolved into generalist-dominated ones. Connectivity was higher among vineyard fallows than among calcareous grasslands. Consequently, conservation measures on calcareous grasslands only partly achieved their goal to maintain the high species diversity and functional complexity still observed in the 1970s. The negative impacts of eutrophication and monotonisation of the landscape as well as climate change are affecting all habitats, independently from management concepts. Therefore, management on conservation sites can buffer against these effects, but is not sufficient for a full compensation.

Landscape genetics of a recent population extirpation in a burnet moth species

The intensification of agricultural land use over wide parts of Europe has led to the decline of semi-natural habitats, such as extensively used meadows, with those that remain often being small and isolated. These rapid changes in land use during recent decades have strongly affected populations inhabiting these ecosystems. Increasing habitat deterioration and declining permeability of the surrounding landscape matrix disrupt the gene flow within metapopulations. The burnet moth species Zygaena loti has suffered strongly from recent habitat fragmentation, as reflected by its declining abundance. We have studied its population genetic structure and found a high level of genetic diversity in some of the populations analysed, while others display low genetic diversity and a lack of heterozygosity. Zygaena loti was formerly highly abundant in meadows and along the skirts of forests. However, the species is currently restricted to isolated habitat remnants, which is reflected by the high genetic divergence among populations (FST: 0.136). Species distribution modelling as well as the spatial examination of panmictic clusters within the study area strongly support a scattered population structure for this species. We suggest that populations with a high level of genetic diversity still represent the former genetic structure of interconnected populations, while populations with low numbers of alleles, high FIS values, and a lack of heterozygosity display the negative effects of reduced interconnectivity. A continuous exchange of individuals is necessary to maintain high genetic variability. Based on these results, we draw the general conclusion that more common taxa with originally large population networks and high genetic diversity suffer stronger from sudden habitat fragmentation than highly specialised species with lower genetic diversity which have persisted in isolated patches for long periods of time.

Coupling Satellite Data with Species Distribution and Connectivity Models as a Tool for Environmental Management and Planning in Matrix-Sensitive Species.

Abstract Climate change and anthropogenic habitat fragmentation are considered major threats for global biodiversity. As a direct consequence, connectivity is increasingly disrupted in many species, which might have serious consequences that could ultimately lead to the extinction of populations. Although a large number of reserves and conservation sites are designated and protected by law, potential habitats acting as inter-population connectivity corridors are, however, mostly ignored in the common practice of environmental planning. In most cases, this is mainly caused by a lack of quantitative measures of functional connectivity available for the planning process. In this study, we highlight the use of fine-scale potential connectivity models (PCMs) derived from multispectral satellite data for the quantification of spatially explicit habitat corridors for matrix-sensitive species of conservation concern. This framework couples a species distribution model with a connectivity model in a two-step framework, where suitability maps from step 1 are transformed into maps of landscape resistance in step 2 filtered by fragmentation thresholds. We illustrate the approach using the sand lizard (Lacerta agilis L.) in the metropolitan area of Cologne, Germany, as a case study. Our model proved to be well suited to identify connected as well as completely isolated populations within the study area. Furthermore, due to its fine resolution, the PCM was also able to detect small linear structures known to be important for sand lizards’ inter-population connectivity such as railroad embankments. We discuss the applicability and possible implementation of PCMs to overcome shortcomings in the common practice of environmental impact assessments.

Quantifying apart what belongs together: A multi-state species distribution modelling framework for species using distinct habitats

Summary 1.Species distribution models (SDMs) have been used to inform scientists and conservationists about the status and change of occurrence patterns in threatened species. Many mobile species use multiple functionally distinct habitats, and cannot occupy one habitat type without the other being within a reachable distance. For such species, classical applications of SDMs might lead to erroneous representations of habitat suitability, as the complex relationships between predictors are lost when merging occurrence information across multiple habitats. To better account for the spatial arrangement of complementary—yet mandatory—habitat types, it is important to implement modeling strategies that partition occurrence information according to habitat use in a spatial context. Here, we address this issue by introducing a multi-state SDM framework. 2.The multi-state SDM framework stratifies occurrences according to the temporal or behavioral use of distinct habitat types, referred to as “states.” Multiple SDMs are then run for each state and statistical thresholds of presence are used to combine these separate predictions. To identify suitable sites that account for distance between habitats, two optional modules are proposed where the thresholded output is aggregated and filtered by minimum area size, or through moving windows across maximum reachable distances. 3.We illustrate the full use of this framework by modeling the dynamic terrestrial breeding habitat preferences of the New Zealand sea lion (NZSL; Phocarctos hookeri), using Maxent and trialing both modules to identify suitable sites for possible recolonization. 4.The Maxent predictions showed excellent performance, and the multi-state SDM framework highlighted 36 to 77 potential suitable breeding sites in the study area. 5.This framework can be applied to inform management when defining habitat suitability for species with complex changes in habitat use. It accounts for temporal and behavioral changes in distribution, maintains the individuality of each partitioned SDM, and considers distance between distinct habitat types. It also yields one final, easy-to-understand output for stakeholders and managers. This article is protected by copyright. All rights reserved.