Use of Empirically Derived Source-Destination Models to Map Regional Conservation Corridors

Abstract:  The ability of populations to be connected across large landscapes via dispersal is critical to long-term viability for many species. One means to mitigate population isolation is the protection of movement corridors among habitat patches. Nevertheless, the utility of small, narrow, linear features as habitat corridors has been hotly debated. Here, we argue that analysis of movement across continuously resistant landscapes allows a shift to a broader consideration of how landscape patterns influence connectivity at scales relevant to conservation. We further argue that this change in scale and definition of the connectivity problem improves one's ability to find solutions and may help resolve long-standing disputes regarding scale and definition of movement corridors and their importance to population connectivity. We used a new method that combines empirically derived landscape-resistance maps and least-cost path analysis between multiple source and destination locations to assess habitat isolation and identify corridors and barriers to organism movement. Specifically, we used a genetically based landscape resistance model for American black bears ( Ursus americanus ) to identify major movement corridors and barriers to population connectivity between Yellowstone National Park and the Canadian border. Even though western Montana and northern Idaho contain abundant public lands and the largest wilderness areas in the contiguous United States, moving from the Canadian border to Yellowstone Park along those paths indicated by modeled gene flow required bears to cross at least 6 potential barriers. Our methods are generic and can be applied to virtually any species for which reliable maps of landscape resistance can be developed.     

Developing Metapopulation Connectivity Criteria from Genetic and Habitat Data to Recover the Endangered Mexican Wolf

Restoring connectivity between fragmented populations is an important tool for alleviating genetic threats to endangered species. Yet recovery plans typically lack quantitative criteria for ensuring such population connectivity. We demonstrate how models that integrate habitat, genetic, and demographic data can be used to develop connectivity criteria for the endangered Mexican wolf (Canis lupus baileyi), which is currently being restored to the wild from a captive population descended from 7 founders. We used population viability analysis that incorporated pedigree data to evaluate the relation between connectivity and persistence for a restored Mexican wolf metapopulation of 3 populations of equal size. Decreasing dispersal rates greatly increased extinction risk for small populations (<150–200), especially as dispersal rates dropped below 0.5 genetically effective migrants per generation. We compared observed migration rates in the Northern Rocky Mountains (NRM) wolf metapopulation to 2 habitat‐based effective distance metrics, least‐cost and resistance distance. We then used effective distance between potential primary core populations in a restored Mexican wolf metapopulation to evaluate potential dispersal rates. Although potential connectivity was lower in the Mexican wolf versus the NRM wolf metapopulation, a connectivity rate of >0.5 genetically effective migrants per generation may be achievable via natural dispersal under current landscape conditions. When sufficient data are available, these methods allow planners to move beyond general aspirational connectivity goals or rules of thumb to develop objective and measurable connectivity criteria that more effectively support species recovery. The shift from simple connectivity rules of thumb to species‐specific analyses parallels the previous shift from general minimum‐viable‐population thresholds to detailed viability modeling in endangered species recovery planning. Desarrollo de Criterios de Conectividad Metapoblacional a Partir de Datos Genéticos y de Hábitat para Recuperar al Lobo Mexicano en Peligro de Extinción     

Demographic Consequences of Terrestrial Habitat Loss for Pool‐Breeding Amphibians: Predicting Extinction Risks Associated with Inadequate Size of Buffer Zones

Abstract: Much of the biodiversity associated with isolated wetlands requires aquatic and terrestrial habitat to maintain viable populations. Current federal wetland regulations in the United States do not protect isolated wetlands or extend protection to surrounding terrestrial habitat. Consequently, some land managers, city planners, and policy makers at the state and local levels are making an effort to protect these wetland and neighboring upland habitats. Balancing human land‐use and habitat conservation is challenging, and well‐informed land‐use policy is hindered by a lack of knowledge of the specific risks of varying amounts of habitat loss. Using projections of wood frog (Rana sylvatica) and spotted salamander (Ambystoma maculatum) populations, we related the amount of high‐quality terrestrial habitat surrounding isolated wetlands to the decline and risk of extinction of local amphibian populations. These simulations showed that current state‐level wetland regulations protecting 30 m or less of surrounding terrestrial habitat are inadequate to support viable populations of pool‐breeding amphibians. We also found that species with different life‐history strategies responded differently to the loss and degradation of terrestrial habitat. The wood frog, with a short life span and high fecundity, was most sensitive to habitat loss and isolation, whereas the longer‐lived spotted salamander with lower fecundity was most sensitive to habitat degradation that lowered adult survival rates. Our model results demonstrate that a high probability of local amphibian population persistence requires sufficient terrestrial habitat, the maintenance of habitat quality, and connectivity among local populations. Our results emphasize the essential role of adequate terrestrial habitat to the maintenance of wetland biodiversity and ecosystem function and offer a means of quantifying the risks associated with terrestrial habitat loss and degradation.     

Modeling and Predicting Species Occurrence Using Broad-Scale Environmental Variables: an Example with Butterflies of the Great Basin

Abstract: If occurrence of individual species can be modeled as a function of easily quantified environmental variables (e.g., derived from a geographic information system [GIS]) and the predictions of these models are demonstrably successful, then the scientific foundation for management planning will be strengthened. We used Bayesian logistic regression to develop predictive models for resident butterflies in the central Great Basin of western North America. Species inventory data and values for 14 environmental variables from 49 locations (segments of canyons) in the Toquima Range ( Nevada, U.S.A.) were used to build the models. Squares of the environmental variables were also used to accommodate possibly nonmonotonic responses. We obtained statistically significant models for 36 of 56 (64%) resident species of butterflies. The models explained 8–72% of the deviance in occurrence of those species. Each of the independent variables was significant in at least one model, and squared versions of five variables contributed to models. Elevation was included in more than half of the models. Models included one to four variables; only one variable was significant in about half the models. We conducted preliminary tests of two of our models by using an existing set of data on the occurrence of butterflies in the neighboring Toiyabe Range. We compared conventional logistic classification with posterior probability distributions derived from Bayesian modeling. For the latter, we restricted our predictions to locations with a high ( 70%) probability of predicted presence or absence. We will perform further tests after conducting inventories at new locations in the Toquima Range and nearby Shoshone Mountains, for which we have computed environmental variables by using remotely acquired topographic data, digital-terrain and microclimatic models, and GIS computation.     

Effectiveness of a Regional Corridor in Connecting Two Florida Black Bear Populations

Abstract:  Corridors may mitigate the adverse effects of habitat fragmentation by restoring or maintaining connectivity between disjunct populations. The efficacy of corridors for large carnivores, however, has rarely been evaluated objectively. We used noninvasive sampling, microsatellite analysis, and population assignment tests to evaluate the effectiveness of a regional corridor in connecting two Florida black bear ( Ursus americanus floridanus ) populations (Osceola and Ocala). Bear movement was predominantly unidirectional, with a limited mixing of individuals from the two populations in one area of the corridor. We also documented bears in Osceola that were genetically assigned to Ocala and bears in Osceola that may be offspring from an Osceola-Ocala mating. Our results indicate that the Osceola-Ocala corridor is functional and provides a conduit for gene flow between these populations. Human development, however, may hinder the use of the Osceola-Ocala corridor by bears. The noninvasive sampling and genetic methods we used provide a means of evaluating corridor effectiveness that can help identify linkages necessary for maintaining metapopulation structure and population viability.     

Patterns of Genetic Diversity in Remaining Giant Panda Populations

Abstract: The giant panda ( Ailuropoda melanoleuca ) is among the more familiar symbols of species conservation. The protection of giant panda populations has been aided recently by the establishment of more and better-managed reserves in existing panda habitat located in six mountain ranges in western China. These remaining populations are becoming increasingly isolated from one another, however, leading to the concern that historic patterns of gene flow will be disrupted and that reduced population sizes will lead to diminished genetic variability. We analyzed four categories of molecular genetic markers (mtDNA restriction-fragment-length polymorphisms [RFLP], mtDNA control region sequences, nuclear multilocus DNA fingerprints, and microsatellite size variation) in giant pandas from three mountain populations (Qionglai, Minshan, and Qinling) to assess current levels of genetic diversity and to detect evidence of historic population subdivisions. The three populations had moderate levels of genetic diversity compared with similarly studied carnivores for all four gene measures, with a slight but consistent reduction in variability apparent in the smaller Qinling population. That population also showed significant differentiation consistent with its isolation since historic times. From a strictly genetic perspective, the giant panda species and the three populations look promising insofar as they have retained a large amount of genetic diversity in each population, although evidence of recent population reduction—likely from habitat loss—is apparent. Ecological management to increase habitat, population expansion, and gene flow would seem an effective strategy to stabilize the decline of this endangered species.     

Bayesian Small Area Models for Assessing Wildlife Conservation Risk in Patchy Populations

Abstract:  Species conservation risk assessments require accurate, probabilistic, and biologically meaningful maps of population distribution. In patchy populations, the reasons for discontinuities are not often well understood. We tested a novel approach to habitat modeling in which methods of small area estimation were used within a hierarchical Bayesian framework. Amphibian occurrence was modeled with logistic regression that included third-order drainages as hierarchical effects to account for patchy populations. Models including the random drainage effects adequately represented species occurrences in patchy populations of 4 amphibian species in the Oregon Coast Range (U.S.A.). Amphibian surveys from other locations within the same drainage were used to calibrate local drainage-scale effects. Cross-validation showed that prediction errors for calibrated models were 77% to 86% lower than comparable regionally constructed models, depending on species. When calibration data were unavailable, small area and regional models performed similarly, although poorly. Small area estimation models complement wildlife ecology and habitat studies, and can help managers develop a regional picture of the conservation status for relatively rare species.     

Genetic population structure of the seagrass Thalassodendron ciliatum in sandy and rocky habitats in southern Mozambique

The genetic diversity of the dioecious seagrass Thalassodendron ciliatum in six populations in southern Mozambique was studied by means of random amplified polymorphic DNA (RAPD). Samples were taken from sandy and rocky habitats over a span of 880 km. Analysis of molecular variance (AMOVA) showed that most of the genetic variability (71.6% of total genetic variation) was observed within populations. There were also significant genetic differences among populations within each habitat (sandy and rocky). We did not find any significant overall genetic difference between sandy versus rocky populations, indicating that the morphological differences between plants from these two habitats are not maintained by reproductive isolation. There was no significant correlation between geographical and genetic distance, which is discussed in the light of current patterns along the coast. All sampled populations consisted of several genetically distinct individuals, indicating that sexual reproduction is widespread.     

Implications of Macroalgal Isolation by Distance for Networks of Marine Protected Areas

The global extent of macroalgal forests is declining, greatly affecting marine biodiversity at broad scales through the effects macroalgae have on ecosystem processes, habitat provision, and food web support. Networks of marine protected areas comprise one potential tool that may safeguard gene flow among macroalgal populations in the face of increasing population fragmentation caused by pollution, habitat modification, climate change, algal harvesting, trophic cascades, and other anthropogenic stressors. Optimal design of protected area networks requires knowledge of effective dispersal distances for a range of macroalgae. We conducted a global meta‐analysis based on data in the published literature to determine the generality of relation between genetic differentiation and geographic distance among macroalgal populations. We also examined whether spatial genetic variation differed significantly with respect to higher taxon, life history, and habitat characteristics. We found clear evidence of population isolation by distance across a multitude of macroalgal species. Genetic and geographic distance were positively correlated across 49 studies; a modal distance of 50–100 km maintained F_ST < 0.2. This relation was consistent for all algal divisions, life cycles, habitats, and molecular marker classes investigated. Incorporating knowledge of the spatial scales of gene flow into the design of marine protected area networks will help moderate anthropogenic increases in population isolation and inbreeding and contribute to the resilience of macroalgal forests. Implicaciones del Aislamiento por Distancia de Macroalgas para Redes de Áreas Marinas Protegidas     

Measuring impacts on species with models and metrics of varying ecological and computational complexity

Approaches to assess the impacts of landscape disturbance scenarios on species range from metrics based on patterns of occurrence or habitat to comprehensive models that explicitly include ecological processes. The choice of metrics and models affects how impacts are interpreted and conservation decisions. We explored the impacts of 3 realistic disturbance scenarios on 4 species with different ecological and taxonomic traits. We used progressively more complex models and metrics to evaluate relative impact and rank of scenarios on the species. Models ranged from species distribution models that relied on implicit assumptions about environmental factors and species presence to highly parameterized spatially explicit population models that explicitly included ecological processes and stochasticity. Metrics performed consistently in ranking different scenarios in order of severity primarily when variation in impact was driven by habitat amount. However, they differed in rank for cases where dispersal dynamics were critical in influencing metapopulation persistence. Impacts of scenarios on species with low dispersal ability were better characterized using models that explicitly captured these processes. Metapopulation capacity provided rank orders that most consistently correlated with those from highly parameterized and data-rich models and incorporated information about dispersal with little additional computational and data cost. Our results highlight the importance of explicitly considering species’ ecology, spatial configuration of habitat, and disturbance when choosing indicators of species persistence. We suggest using hybrid approaches that are a mixture of simple and complex models to improve multispecies assessments.     

Building a better baseline to estimate 160 years of avian population change and create historically informed conservation targets

Globally, anthropogenic land-cover change has been dramatic over the last few centuries and is frequently invoked as a major cause of wildlife population declines. Baseline data currently used to assess population trends, however, began well after major changes to the landscape. In the United States and Canada, breeding bird population trends are assessed by the North American Breeding Bird Survey, which began in the 1960s. Estimates of distribution and abundance prior to major habitat alteration would add historical perspective to contemporary trends and allow for historically based conservation targets. We used a hindcasting framework to estimate change in distribution and abundance of 7 bird species in the Willamette Valley, Oregon (United States). After reconciling classification schemes of current and 1850s reconstructed land cover, we used multiscale species distribution models and hierarchical distance sampling models to predict spatially explicit densities in the modern and historical landscapes. We estimated that since the 1850s, White-breasted Nuthatch (Sitta carolinensis) and Western Meadowlark (Sturnella neglecta) populations, 2 species sensitive to fragmentation of oak woodlands and grasslands, declined by 93% and 97%, respectively. Five other species we estimated nearly stable or increasing populations, despite steep regional declines since the 1960s. Based on these estimates, we developed historically based conservation targets for amount of habitat, population, and density for each species. Hindcasted reconstructions provide historical perspective for assessing contemporary trends and allow for historically based conservation targets that can inform current management.     

Gastrointestinal Bacterial Transmission among Humans,Mountain Gorillas,and Livestock in Bwindi Impenetrable National Park,Uganda

Abstract: Habitat overlap can increase the risks of anthroponotic and zoonotic pathogen transmission between humans, livestock, and wild apes. We collected Escherichia coli bacteria from humans, livestock, and mountain gorillas (Gorilla gorilla beringei) in Bwindi Impenetrable National Park, Uganda, from May to August 2005 to examine whether habitat overlap influences rates and patterns of pathogen transmission between humans and apes and whether livestock might facilitate transmission. We genotyped 496 E. coli isolates with repetitive extragenic palindromic polymerase chain reaction fingerprinting and measured susceptibility to 11 antibiotics with the disc‐diffusion method. We conducted population genetic analyses to examine genetic differences among populations of bacteria from different hosts and locations. Gorilla populations that overlapped in their use of habitat at high rates with people and livestock harbored E. coli that were genetically similar to E. coli from those people and livestock, whereas E. coli from gorillas that did not overlap in their use of habitats with people and livestock were more distantly related to human or livestock bacteria. Thirty‐five percent of isolates from humans, 27% of isolates from livestock, and 17% of isolates from gorillas were clinically resistant to at least one antibiotic used by local people, and the proportion of individual gorillas harboring resistant isolates declined across populations in proportion to decreasing degrees of habitat overlap with humans. These patterns of genetic similarity and antibiotic resistance among E. coli from populations of apes, humans, and livestock indicate that habitat overlap between species affects the dynamics of gastrointestinal bacterial transmission, perhaps through domestic animal intermediates and the physical environment. Limiting such transmission would benefit human and domestic animal health and ape conservation.     

High levels of genetic subdivision of marine and estuarine populations of the estuarine catfishCnidoglanis macrocephalus (Plotosidae) in southwestern Australia

The cobblerCnidoglanis macrocephalus (Valenciennes) is an endemic marine and estuarine catfish from southern Australia. Conflicting views on the degree of isolation of the estuarine populations underscore general questions about genetic divergence in coastal species. Although estuaries are widely recognized as ecologically important, little work has been done on their role in favouring genetic divergence. In order to estimate the extent of genetic subdivision among nearshore marine and estuarine populations, electrophoretic variation of enzymes was examined in seven marine and six estuarine populations of cobbler from sites spanning 1500 km along the southwest Australian coastline. Among all populations, the mean standardized variance in allelic frequencies (F _ST) for six polymorphic loci was 0.277, a high value comparable to those of other shallow-water teleosts whose life-history characteristics and habitat preferences restrict their dispersal capability. The pattern of genetic identities between populations showed divergence between west and south coast sites. Within these regional groups, however, there was substantial heterogeneity, much of which was associated with estuaries. Among all six estuarine sites, the averageF _ST was 0.333, 40% higher than the value of 0.237 for the marine sites. Low estimates of the genetically effective number of migrants suggest population subdivision between marine and estuarine environments and between similar habitat types. This study indicates the importance of habitat in affecting the connectedness of populations, even in apparently open marine systems.     

Habitat selection predicts genetic relatedness in an alpine ungulate

Landscape heterogeneity plays an integral role in shaping ecological and evolutionary processes. Despite links between the two disciplines, ecologists and population geneticists have taken different approaches to evaluating habitat selection, animal movement, and gene flow across the landscape. Ecologists commonly use statistical models such as resource selection functions (RSFs) to identify habitat features disproportionately selected by animals, whereas population genetic approaches model genetic differentiation according to the distribution of habitat variables. We combined ecological and genetic approaches by using RSFs to predict genetic relatedness across a heterogeneous landscape. We constructed sex- and season-specific resistance surfaces based on RSFs estimated using data from 102 GPS (global positioning system) radio-collared mountain goats (Oreamnos americanus) in southeast Alaska, USA. Based on mountain goat ecology, we hypothesized that summer and male surfaces would be the best predictors of relatedness. All individuals were genotyped at 22 microsatellite loci, which we used to estimate genetic relatedness. Summer resistance surfaces derived from RSFs were the best predictors of genetic relatedness, and winter models the poorest. Mountain goats generally selected for areas close to escape terrain and with a high heat load (a metric related to vegetative productivity and snow depth), while avoiding valleys. Male- and female-specific surfaces were similar, except for winter, for which male habitat selection better predicted genetic relatedness. The null models of isolation-by-distance and barrier only outperformed the winter models. This study merges high-resolution individual locations through GPS telemetry and genetic data, that can be used to validate and parameterize landscape genetics models, and further elucidates the relationship between landscape heterogeneity and genetic differentiation.     

Demographic Forecasting in Koala Conservation

Abstract: The koala currently needs conservation intervention. There is clear evidence of decline in many populations, but the existence of other stable or expanding populations offers the possibility of a variety of creative solutions to their conservation problems. The 1998 National Koala Conservation Strategy emphasizes the need to obtain demographic information and to use this information to assess management options for koalas. We need accurate diagnoses of the status of koala populations and forecasts of their demographic future with and without particular management actions. In a qualitative fashion, this process has been undertaken many times on a local and national scale. Quantitative demographic forecasting tools are increasingly available, and koala management could benefit from their application both at the scale of individual populations and more broadly. There is already a considerable body of suitable data on the dispersal, effects of normal and catastrophic environmental variation on reproduction and survival, and on the effects of habitat change. Demographic forecasting, however, is hampered because the full suite of information is rarely available from a single population. In two Queensland populations, retrospective population viability analyses provided forecasts that were in agreement with observed population trends. Work is needed to determine whether data from one population can be applied to other populations. Models can then be developed to make projections at a multipopulation level on the basis of local population dynamics and dispersal. Certain koala populations, because of their long history of study, offer the opportunity to test demographic models retrospectively. These tests will not only aid in fine-tuning the models for koala biology and data but will also assist with the more general process of validating the models.     

Translating habitat class to land cover to map area of habitat of terrestrial vertebrates

Area of habitat (AOH) is defined as the “habitat available to a species, that is, habitat within its range” and is calculated by subtracting areas of unsuitable land cover and elevation from the range. The International Union for the Conservation of Nature (IUCN) Habitats Classification Scheme provides information on species habitat associations, and typically unvalidated expert opinion is used to match habitat to land-cover classes, which generates a source of uncertainty in AOH maps. We developed a data-driven method to translate IUCN habitat classes to land cover based on point locality data for 6986 species of terrestrial mammals, birds, amphibians, and reptiles. We extracted the land-cover class at each point locality and matched it to the IUCN habitat class or classes assigned to each species occurring there. Then, we modeled each land-cover class as a function of IUCN habitat with (SSG, using) logistic regression models. The resulting odds ratios were used to assess the strength of the association between each habitat and land-cover class. We then compared the performance of our data-driven model with those from a published translation table based on expert knowledge. We calculated the association between habitat classes and land-cover classes as a continuous variable, but to map AOH as binary presence or absence, it was necessary to apply a threshold of association. This threshold can be chosen by the user according to the required balance between omission and commission errors. Some habitats (e.g., forest and desert) were assigned to land-cover classes with more confidence than others (e.g., wetlands and artificial). The data-driven translation model and expert knowledge performed equally well, but the model provided greater standardization, objectivity, and repeatability. Furthermore, our approach allowed greater flexibility in the use of the results and uncertainty to be quantified. Our model can be modified for regional examinations and different taxonomic groups.     

Conservation of Fragmented Populations

In this paper we argue that landscape spatial structure is of central importance in understanding the effects of fragmentation on population survival. Landscape spatial structure is the spatial relationships among habitat patches and the matrix in which they are embedded. Many general models of subdivided populations make the assumptions that (1) all habitat patches are equivalent in size and quality and (2) all local populations (in the patches) are equally accessible by dispersers. Models that gloss over spatial details of landscape structure can be useful for theoretical developments but will almost always be misleading when applied to real-world conservation problems. We show that local extinctions of fragmented populations are common. From this it follows that recolonization of local extinctions is critical for regional survival of fragmented populations. The probability of recolonization depends on (1) spatial relationships among landscape elements used by the population, including habitat patches for breeding and elements of the inter-patch matrix through which dispersers move, (2) dispersal characteristics of the organism of interest, and (3) temporal changes in the landscape structure. For endangered species, which are typically restricted in their dispersal range and in the kinds of habitat through which they can disperse, these factors are of primary importance and must be explicitly considered in management decisions.     

Consequences of ignoring dispersal variation in network models for landscape connectivity

Habitat loss and fragmentation can negatively influence population persistence and biodiversity, but the effects can be mitigated if species successfully disperse between isolated habitat patches. Network models are the primary tool for quantifying landscape connectivity, yet in practice, an overly simplistic view of species dispersal is applied. These models often ignore individual variation in dispersal ability under the assumption that all individuals move the same fixed distance with equal probability. We developed a modeling approach to address this problem. We incorporated dispersal kernels into network models to determine how individual variation in dispersal alters understanding of landscape-level connectivity and implemented our approach on a fragmented grassland landscape in Minnesota. Ignoring dispersal variation consistently overestimated a population's robustness to local extinctions and underestimated its robustness to local habitat loss. Furthermore, a simplified view of dispersal underestimated the amount of habitat substructure for small populations but overestimated habitat substructure for large populations. Our results demonstrate that considering biologically realistic dispersal alters understanding of landscape connectivity in ecological theory and conservation practice.     

Are existing vegetation maps adequate to predict bird distributions?

Bird species are selective on the vegetation types in which they are found but predictive models of bird distribution based on variables derived from land-use/land-cover maps tend to have limited success. It has been suggested that accuracy of existing maps used to derive predictors is in part responsible for the limited success of bird distribution models. In two areas of 4900 km² of Western Andalusia, Spain, we compared the predictive ability of bird distribution models derived from two existing general-purpose land-use/land-cover maps, which differ in their resolution and accuracy: a coarse scale vegetation map of Europe, the CORINE land-cover map, and a detailed regional map, the 1995 land-use/land-cover map of Andalusia from the SINAMBA (Consejerı́a de Medio Ambiente, Junta de Andalucı́a). We compared the bird distribution models derived from these general-purpose vegetation maps with models derived from two more accurate structural vegetation maps built considering directly variables that influence bird habitat selection, one built from satellite images for this study and another obtained by improving the resolution and accuracy of the SINAMBA map with satellite data. We sampled the presence/absence of bird species at 857 points using 15-min point surveys. Predictive models for 54 bird species were built with generalised additive models (GAMs), using as potential predictors the same set of landscape and vegetation structure variables measured on each map. We compared for each bird species the predictive accuracy of the best model derived from each map. Vegetation structure measured at bird sample points was used as ground-truth for comparing the accuracy of vegetation maps. Although maps differed in their resolution and accuracy, the results show that all of them produced similarly accurate bird distribution models, with a mixed map produced with both thematic and satellite information being the best. The models derived from the more accurate vegetation structure maps obtained from satellite data were not more accurate than those derived directly from the SINAMBA or CORINE maps. Our results suggest that some general-purpose land-use/land-cover maps are accurate enough to derive bird distribution models. There is a certain limit to improve vegetation maps above which there is no effect in their power to predict bird distribution.     

Unraveling the complexities of variation in female mate preference for vertical bars in the swordtail, Xiphophorus cortezi

Investigations into the nature of mate choice suggest that variation in female mate preferences is often context dependent, varying in response to genetic and environmental influences on female condition as well as to external environmental stimuli. Determining whether variation in female mate preference is adaptive requires understanding the variables involved that produce this variation and how they interact. Comparative, multivariate studies of wild-caught adult females can be used as initial assessments of variation in female mate preferences, providing valuable insights into the parameters that influence female preferences under natural conditions. We examined variation in female preferences for the pigment pattern vertical bars across five populations of the swordtail, Xiphophorus cortezi. The populations we examined are genetically differentiated and varied in the frequency of males and females with bars. We also considered a variable indicative of within-individual variation (size, as influenced by age) and a variable that varies across individuals (genotype for vertical bars: barred or barless). Using Akaike information criterion, all candidate models explaining variation in strength of preference included female bar state, female size, and population. We suggest that a combination of genetic (bar state) and environmental (female size) conditions influenced how they responded to experience with both male phenotypes in X. cortezi. Future studies should examine the possibility that barred and barless females respond differently over an environmental gradient.