Linking demographic and food‐web models to understand management trade‐offs

Alternatives in ecosystem‐based management often differ with respect to trade‐offs between ecosystem values. Ecosystem or food‐web models and demographic models are typically employed to evaluate alternatives, but the approaches are rarely integrated to uncover conflicts between values. We applied multistate models to a capture–recapture dataset on common guillemots Uria aalge breeding in the Baltic Sea to identify factors influencing survival. The estimated relationships were employed together with Ecopath‐with‐Ecosim food‐web model simulations to project guillemot survival under six future scenarios incorporating climate change. The scenarios were based on management alternatives for eutrophication and cod fisheries, issues considered top priority for regional management, but without known direct effects on the guillemot population. Our demographic models identified prey quantity (abundance and biomass of sprat Sprattus sprattus) as the main factor influencing guillemot survival. Most scenarios resulted in projections of increased survival, in the near (2016–2040) and distant (2060–2085) future. However, in the scenario of reduced nutrient input and precautionary cod fishing, guillemot survival was projected to be lower in both future periods due to lower sprat stocks. Matrix population models suggested a substantial decline of the guillemot population in the near future, 24% per 10 years, and a smaller reduction, 1.1% per 10 years, in the distant future. To date, many stakeholders and Baltic Sea governments have supported reduced nutrient input and precautionary cod fishing and implementation is underway. Negative effects on nonfocal species have previously not been uncovered, but our results show that the scenario is likely to negatively impact the guillemot population. Linking model results allowed identifying trade‐offs associated with management alternatives. This information is critical to thorough evaluation by decision‐makers, but not easily obtained by food‐web models or demographic models in isolation. Appropriate datasets are often available, making it feasible to apply a linked approach for better‐informed decisions in ecosystem‐based management.     

Incubation temperature impacts nestling growth and survival in an open‐cup nesting passerine

For oviparous species such as birds, conditions experienced while in the egg can have long‐lasting effects on the individual. The impact of subtle changes in incubation temperature on nestling development, however, remains poorly understood, especially for open‐cup nesting species with altricial young. To investigate how incubation temperature affects nestling development and survival in such species, we artificially incubated American robin (Turdus migratorius) eggs at 36.1°C (“Low” treatment) and 37.8°C (“High” treatment). Chicks were fostered to same‐age nests upon hatching, and we measured mass, tarsus, and wing length of experimental nestlings and one randomly selected, naturally incubated (“Natural”), foster nest‐mate on days 7 and 10 posthatch. We found significant effects of incubation temperature on incubation duration, growth, and survival, in which experimentally incubated nestlings had shorter incubation periods (10.22, 11.50, and 11.95 days for High, Low, and Natural eggs, respectively), and nestlings from the Low treatment were smaller and had reduced survival compared to High and Natural nestlings. These results highlight the importance of incubation conditions during embryonic development for incubation duration, somatic development, and survival. Moreover, these findings indicate that differences in incubation temperature within the natural range of variation can have important carryover effects on growth and survival in species with altricial young.     

Immune deployment increases larval vulnerability to predators and inhibits adult life‐history traits in a dragonfly

While deploying immune defences early in ontogeny can trade‐off with the production and maintenance of other important traits across the entire life cycle, it remains largely unexplored how features of the environment shape the magnitude or presence of these lifetime costs. Greater predation risk during the juvenile stage may particularly influence such costs by (1) magnifying the survival costs that arise from any handicap of juvenile avoidance traits and/or (2) intensifying allocation trade‐offs with important adult traits. Here, we tested for predator‐dependent costs of immune deployment within and across life stages using the dragonfly, Pachydiplax longipennis. We first examined how larval immune deployment affected two traits associated with larval vulnerability to predators: escape distance and foraging under predation risk. Larvae that were induced to mount an immune response had shorter escape distances but lower foraging activity in the presence of predator cues. We also induced immune responses in larvae and reared them through emergence in mesocosms that differed in the presence of large predatory dragonfly larvae (Aeshnidae spp.). Immune‐challenged larvae had later emergence overall and lower survival in pools with predators. Immune‐challenged males were also smaller at emergence and developed less sexually selected melanin wing coloration, but these effects were independent of predator treatment. Overall, these results highlight how mounting an immune defence early in ontogeny can have substantial ecological and physiological costs that manifest both within and across life stages.     

Integrating broad‐scale data to assess demographic and climatic contributions to population change in a declining songbird

Climate variation and trends affect species distribution and abundance across large spatial extents. However, most studies that predict species response to climate are implemented at small spatial scales or are based on occurrence‐environment relationships that lack mechanistic detail. Here, we develop an integrated population model (IPM) for multi‐site count and capture‐recapture data for a declining migratory songbird, Wilson's warbler (Cardellina pusilla), in three genetically distinct breeding populations in western North America. We include climate covariates of vital rates, including spring temperatures on the breeding grounds, drought on the wintering range in northwest Mexico, and wind conditions during spring migration. Spring temperatures were positively related to productivity in Sierra Nevada and Pacific Northwest genetic groups, and annual changes in productivity were important predictors of changes in growth rate in these populations. Drought condition on the wintering grounds was a strong predictor of adult survival for coastal California and Sierra Nevada populations; however, adult survival played a relatively minor role in explaining annual variation in population change. A latent parameter representing a mixture of first‐year survival and immigration was the largest contributor to variation in population change; however, this parameter was estimated imprecisely, and its importance likely reflects, in part, differences in spatio‐temporal distribution of samples between count and capture‐recapture data sets. Our modeling approach represents a novel and flexible framework for linking broad‐scale multi‐site monitoring data sets. Our results highlight both the potential of the approach for extension to additional species and systems, as well as needs for additional data and/or model development.     

Metabolic approaches to understanding climate change impacts on seasonal host‐macroparasite dynamics

Climate change is expected to alter the dynamics of infectious diseases around the globe. Predictive models remain elusive due to the complexity of host–parasite systems and insufficient data describing how environmental conditions affect various system components. Here, we link host–macroparasite models with the Metabolic Theory of Ecology, providing a mechanistic framework that allows integrating multiple nonlinear environmental effects to estimate parasite fitness under novel conditions. The models allow determining the fundamental thermal niche of a parasite, and thus, whether climate change leads to range contraction or may permit a range expansion. Applying the models to seasonal environments, and using an arctic nematode with an endotherm host for illustration, we show that climate warming can split a continuous spring‐to‐fall transmission season into two separate transmission seasons with altered timings. Although the models are strategic and most suitable to evaluate broad‐scale patterns of climate change impacts, close correspondence between model predictions and empirical data indicates model applicability also at the species level. As the application of Metabolic Theory considerably aids the a priori estimation of model parameters, even in data‐sparse systems, we suggest that the presented approach could provide a framework for understanding and predicting climatic impacts for many host–parasite systems worldwide.     

Dampening prey cycle overrides the impact of climate change on predator population dynamics: a long‐term demographic study on tawny owls

Predicting the dynamics of animal populations with different life histories requires careful understanding of demographic responses to multifaceted aspects of global changes, such as climate and trophic interactions. Continent‐scale dampening of vole population cycles, keystone herbivores in many ecosystems, has been recently documented across Europe. However, its impact on guilds of vole‐eating predators remains unknown. To quantify this impact, we used a 27‐year study of an avian predator (tawny owl) and its main prey (field vole) collected in Kielder Forest (UK) where vole dynamics shifted from a high‐ to a low‐amplitude fluctuation regime in the mid‐1990s. We measured the functional responses of four demographic rates to changes in prey dynamics and winter climate, characterized by wintertime North Atlantic Oscillation (wNAO). First‐year and adult survival were positively affected by vole density in autumn but relatively insensitive to wNAO. The probability of breeding and number of fledglings were higher in years with high spring vole densities and negative wNAO (i.e. colder and drier winters). These functional responses were incorporated into a stochastic population model. The size of the predator population was projected under scenarios combining prey dynamics and winter climate to test whether climate buffers or alternatively magnifies the impact of changes in prey dynamics. We found the observed dampening vole cycles, characterized by low spring densities, drastically reduced the breeding probability of predators. Our results illustrate that (i) change in trophic interactions can override direct climate change effect; and (ii) the demographic resilience entailed by longevity and the occurrence of a floater stage may be insufficient to buffer hypothesized environmental changes. Ultimately, dampened prey cycles would drive our owl local population towards extinction, with winter climate regimes only altering persistence time. These results suggest that other vole‐eating predators are likely to be threatened by dampening vole cycles throughout Europe.     

Food quality effects on instar‐specific life histories of a holometabolous insect

1. It is a long‐standing challenge to understand how changes in food resources impact consumer life history traits and, in turn, impact how organisms interact with their environment. To characterize food quality effects on life history, most studies follow organisms throughout their life cycle and quantify major life events, such as age at maturity or fecundity. From these studies, we know that food quality generally impacts body size, juvenile development, and life span. Importantly, throughout juvenile development, many organisms develop through several stages of growth that can have different interactions with their environment. For example, some parasitoids typically attack larger instars, whereas larval insect predators typically attack smaller instars. Interestingly, most studies lump all juvenile stages together, which ignores these ecological changes over juvenile development.
2. We combine a cross‐sectional experimental approach with a stage‐structured population model to estimate instar‐specific vital rates in the bean weevil, Callosobruchus maculatus across a food quality gradient. We characterize food quality effects on the bean weevil's life history traits throughout its juvenile ontogeny to test how food quality impacts instar‐specific vital rates.
3. Vital rates differed across food quality treatments within each instar; however, their effect differed with instar. Weevils consuming low‐quality food spent 38%, 37%, and 18% more time, and were 34%, 53%, and 63% smaller than weevils consuming high‐quality food in the second, third, and fourth instars, respectively. Overall, our results show that consuming poor food quality means slower growth, but that food quality effects on vital rates, growth and development are not equal across instars. Differences in life history traits over juvenile ontogeny in response to food quality may impact how organisms interact with their environment, including how susceptible they are to predation, parasitism, and their competitive ability.

     

Reconstructing shifts in vital rates driven by long‐term environmental change: a new demographic method based on readily available data

Frequently, vital rates are driven by directional, long‐term environmental changes. Many of these are of great importance, such as land degradation, climate change, and succession. Traditional demographic methods assume a constant or stationary environment, and thus are inappropriate to analyze populations subject to these changes. They also require repeat surveys of the individuals as change unfolds. Methods for reconstructing such lengthy processes are needed. We present a model that, based on a time series of population size structures and densities, reconstructs the impact of directional environmental changes on vital rates. The model uses integral projection models and maximum likelihood to identify the rates that best reconstructs the time series. The procedure was validated with artificial and real data. The former involved simulated species with widely different demographic behaviors. The latter used a chronosequence of populations of an endangered cactus subject to increasing anthropogenic disturbance. In our simulations, the vital rates and their change were always reconstructed accurately. Nevertheless, the model frequently produced alternative results. The use of coarse knowledge of the species' biology (whether vital rates increase or decrease with size or their plausible values) allowed the correct rates to be identified with a 90% success rate. With real data, the model correctly reconstructed the effects of disturbance on vital rates. These effects were previously known from two populations for which demographic data were available. Our procedure seems robust, as the data violated several of the model's assumptions. Thus, time series of size structures and densities contain the necessary information to reconstruct changing vital rates. However, additional biological knowledge may be required to provide reliable results. Because time series of size structures and densities are available for many species or can be rapidly generated, our model can contribute to understand populations that face highly pressing environmental problems.     

Weighing the relative potential impacts of climate change and land‐use change on an endangered bird

Climate change and land‐use change are projected to be the two greatest drivers of biodiversity loss over the coming century. Land‐use change has resulted in extensive habitat loss for many species. Likewise, climate change has affected many species resulting in range shifts, changes in phenology, and altered interactions. We used a spatially explicit, individual‐based model to explore the effects of land‐use change and climate change on a population of the endangered Red‐cockaded Woodpecker (RCW; Picoides borealis). We modeled the effects of land‐use change using multiple scenarios representing different spatial arrangements of new training areas for troops across Fort Benning. We used projected climate‐driven changes in habitat and changes in reproductive output to explore the potential effects of climate change. We summarized potential changes in habitat based on the output of the dynamic vegetation model LPJ‐GUESS, run for multiple climate change scenarios through the year 2100. We projected potential changes in reproduction based on an empirical relationship between spring precipitation and the mean number of successful fledglings produced per nest attempt. As modeled in our study, climate change had virtually no effect on the RCW population. Conversely, simulated effects of land‐use change resulted in the loss of up to 28 breeding pairs by 2100. However, the simulated impacts of development depended on where the development occurred and could be completely avoided if the new training areas were placed in poor‐quality habitat. Our results demonstrate the flexibility inherent in many systems that allows seemingly incompatible human land uses, such as development, and conservation actions to exist side by side.     

Effect of breeding performance on the distribution and activity budgets of a predominantly resident population of black‐browed albatrosses

Pelagic seabirds breeding at high latitudes generally split their annual cycle between reproduction, migration, and wintering. During the breeding season, they are constrained in their foraging range due to reproduction while during winter months, and they often undertake long‐distance migrations. Black‐browed albatrosses (Thalassarche melanophris) nesting in the Falkland archipelago remain within 700 km from their breeding colonies all year‐round and can therefore be considered as resident. Accordingly, at‐sea activity patterns are expected to be adjusted to the absence of migration. Likewise, breeding performance is expected to affect foraging, flying, and floating activities, as failed individuals are relieved from reproduction earlier than successful ones. Using geolocators coupled with a saltwater immersion sensor, we detailed the spatial distribution and temporal dynamics of at‐sea activity budgets of successful and failed breeding black‐browed albatrosses nesting in New Island, Falklands archipelago, over the breeding and subsequent nonbreeding season. The 90% monthly kernel distribution of failed and successful breeders suggested no spatial segregation. Both groups followed the same dynamics of foraging effort both during daylight and darkness all year, except during chick‐rearing, when successful breeders foraged more intensively. Failed and successful breeders started decreasing flying activities during daylight at the same time, 2–3 weeks after hatching period, but failed breeders reached their maximum floating activity during late chick‐rearing, 2 months before successful breeders. Moon cycle had a significant effect on activity budgets during darkness, with individuals generally more active during full moon. Our results highlight that successful breeders buffer potential reproductive costs during the nonbreeding season, and this provides a better understanding of how individuals adjust their spatial distribution and activity budgets according to their breeding performance in absence of migration.     

A Bayesian Approach to Joint Mixed‐Effects Models with a Skew‐Normal Distribution and Measurement Errors in Covariates

Summary In recent years, nonlinear mixed‐effects (NLME) models have been proposed for modeling complex longitudinal data. Covariates are usually introduced in the models to partially explain intersubject variations. However, one often assumes that both model random error and random effects are normally distributed, which may not always give reliable results if the data exhibit skewness. Moreover, some covariates such as CD4 cell count may be often measured with substantial errors. In this article, we address these issues simultaneously by jointly modeling the response and covariate processes using a Bayesian approach to NLME models with covariate measurement errors and a skew‐normal distribution. A real data example is offered to illustrate the methodologies by comparing various potential models with different distribution specifications. It is showed that the models with skew‐normality assumption may provide more reasonable results if the data exhibit skewness and the results may be important for HIV/AIDS studies in providing quantitative guidance to better understand the virologic responses to antiretroviral treatment.     

Carry‐over effects of multiple stressors on benthic embryos are mediated by larval exposure to elevated UVB and temperature

Damaging effects of UVB in conjunction with other stressors associated with global change are well‐established, with many studies focused on vulnerable early life stages and immediate effects (e.g., mortality, developmental abnormalities). However, for organisms with complex life cycles, experiences at one life stage can have carry‐over effects on later life stages, such that sublethal effects may mediate later vulnerability to further stress. Here, we exposed embryos in benthic egg masses of the New Zealand intertidal gastropod Siphonaria australis to treatments of either periodic stress (e.g., elevated UVB, salinity, and water temperature mimicking tidepool conditions in which egg masses are commonly found during summer) or control conditions (low UVB, ambient salinity, and water temperatures). Although there was high mortality from stressed egg masses, 24% of larvae hatched successfully. We then exposed the hatching larvae from both egg mass treatments to different combinations of water temperature (15 or 20 °C) and light (high UVB or shade) 12 h per day for 10 days. The most stressful larval conditions of 20 °C/high UVB resulted in low survival and stunted growth. Carry‐over effects on survival were apparent for shaded larvae exposed to elevated temperature, where those from stressed egg masses had 1.8× higher mortality than those from control egg masses. Shaded larvae were also larger and had longer velar cilia if they were from control egg masses, independent of larval temperature. These results demonstrate that previous experience of environmental stress can influence vulnerability of later life stages to further stress, and that focus on a single life stage will underestimate cumulative effects of agents of global change.     

Assessing climate change associated sea‐level rise impacts on sea turtle nesting beaches using drones,photogrammetry and a novel GPS system

Climate change associated sea‐level rise (SLR) is expected to have profound impacts on coastal areas, affecting many species, including sea turtles which depend on these habitats for egg incubation. Being able to accurately model beach topography using digital terrain models (DTMs) is therefore crucial to project SLR impacts and develop effective conservation strategies. Traditional survey methods are typically low‐cost with low accuracy or high‐cost with high accuracy. We present a novel combination of drone‐based photogrammetry and a low‐cost and portable real‐time kinematic (RTK) GPS to create DTMs which are highly accurate (<10 cm error) and visually realistic. This methodology is ideal for surveying coastal sites, can be broadly applied to other species and habitats, and is a relevant tool in supporting the development of Specially Protected Areas. Here, we applied this method as a case‐study to project three SLR scenarios (0.48, 0.63 and 1.20 m) and assess the future vulnerability and viability of a key nesting habitat for sympatric loggerhead (Caretta caretta) and green turtle (Chelonia mydas) at a key rookery in the Mediterranean. We combined the DTM with 5 years of nest survey data describing location and clutch depth, to identify (a) regions with highest nest densities, (b) nest elevation by species and beach, and (c) estimated proportion of nests inundated under each SLR scenario. On average, green turtles nested at higher elevations than loggerheads (1.8 m vs. 1.32 m, respectively). However, because green turtles dig deeper nests than loggerheads (0.76 m vs. 0.50 m, respectively), these were at similar risk of inundation. For a SLR of 1.2 m, we estimated a loss of 67.3% for loggerhead turtle nests and 59.1% for green turtle nests. Existing natural and artificial barriers may affect the ability of these nesting habitats to remain suitable for nesting through beach migration.     

Douglas‐fir plantations in Europe: a retrospective test of assisted migration to address climate change

We evaluate genetic test plantations of North American Douglas‐fir provenances in Europe to quantify how tree populations respond when subjected to climate regime shifts, and we examined whether bioclimate envelope models developed for North America to guide assisted migration under climate change can retrospectively predict the success of these provenance transfers to Europe. The meta‐analysis is based on long‐term growth data of 2800 provenances transferred to 120 European test sites. The model was generally well suited to predict the best performing provenances along north–south gradients in Western Europe, but failed to predict superior performance of coastal North American populations under continental climate conditions in Eastern Europe. However, model projections appear appropriate when considering additional information regarding adaptation of Douglas‐fir provenances to withstand frost and drought, even though the model partially fails in a validation against growth traits alone. We conclude by applying the partially validated model to climate change scenarios for Europe, demonstrating that climate trends observed over the last three decades warrant changes to current use of Douglas‐fir provenances in plantation forestry throughout Western and Central Europe.     

Spatiotemporally explicit demographic modelling supports a joint effect of historical barriers to dispersal and contemporary landscape composition on structuring genomic variation in a red‐listed grasshopper

Inferring the processes underlying spatial patterns of genomic variation is fundamental to understand how organisms interact with landscape heterogeneity and to identify the factors determining species distributional shifts. Here, we use genomic data (restriction site‐associated DNA sequencing) to test biologically informed models representing historical and contemporary demographic scenarios of population connectivity for the Iberian cross‐backed grasshopper Dociostaurus hispanicus, a species with a narrow distribution that currently forms highly fragmented populations. All models incorporated biological aspects of the focal taxon that could hypothetically impact its geographical patterns of genomic variation, including (a) spatial configuration of impassable barriers to dispersal defined by topographic landscapes not occupied by the species; (b) distributional shifts resulting from the interaction between the species bioclimatic envelope and Pleistocene glacial cycles; and (c) contemporary distribution of suitable habitats after extensive land clearing for agriculture. Spatiotemporally explicit simulations under different scenarios considering these aspects and statistical evaluation of competing models within an Approximate Bayesian Computation framework supported spatial configuration of topographic barriers to dispersal and human‐driven habitat fragmentation as the main factors explaining the geographical distribution of genomic variation in the species, with no apparent impact of hypothetical distributional shifts linked to Pleistocene climatic oscillations. Collectively, this study supports that both historical (i.e., topographic barriers) and contemporary (i.e., anthropogenic habitat fragmentation) aspects of landscape composition have shaped major axes of genomic variation in the studied species and emphasizes the potential of model‐based approaches to gain insights into the temporal scale at which different processes impact the demography of natural populations.     

Multi‐model comparison highlights consistency in predicted effect of warming on a semi‐arid shrub

A number of modeling approaches have been developed to predict the impacts of climate change on species distributions, performance, and abundance. The stronger the agreement from models that represent different processes and are based on distinct and independent sources of information, the greater the confidence we can have in their predictions. Evaluating the level of confidence is particularly important when predictions are used to guide conservation or restoration decisions. We used a multi‐model approach to predict climate change impacts on big sagebrush (Artemisia tridentata), the dominant plant species on roughly 43 million hectares in the western United States and a key resource for many endemic wildlife species. To evaluate the climate sensitivity of A. tridentata, we developed four predictive models, two based on empirically derived spatial and temporal relationships, and two that applied mechanistic approaches to simulate sagebrush recruitment and growth. This approach enabled us to produce an aggregate index of climate change vulnerability and uncertainty based on the level of agreement between models. Despite large differences in model structure, predictions of sagebrush response to climate change were largely consistent. Performance, as measured by change in cover, growth, or recruitment, was predicted to decrease at the warmest sites, but increase throughout the cooler portions of sagebrush's range. A sensitivity analysis indicated that sagebrush performance responds more strongly to changes in temperature than precipitation. Most of the uncertainty in model predictions reflected variation among the ecological models, raising questions about the reliability of forecasts based on a single modeling approach. Our results highlight the value of a multi‐model approach in forecasting climate change impacts and uncertainties and should help land managers to maximize the value of conservation investments.     

Seed germination responses to seasonal temperature and drought stress are species‐specific but not related to seed size in a desert steppe: Implications for effect of climate change on community structure

Investigating how seed germination of multiple species in an ecosystem responds to environmental conditions is crucial for understanding the mechanisms for community structure and biodiversity maintenance. However, knowledge of seed germination response of species to environmental conditions is still scarce at the community level. We hypothesized that responses of seed germination to environmental conditions differ among species at the community level, and that germination response is not correlated with seed size. To test this hypothesis, we determined the response of seed germination of 20 common species in the Siziwang Desert Steppe, China, to seasonal temperature regimes (representing April, May, June, and July) and drought stress (0, ?0.003, ?0.027, ?0.155, and ?0.87 MPa). Seed germination percentage increased with increasing temperature regime, but Allium ramosum, Allium tenuissimum, Artemisia annua, Artemisia mongolica, Artemisia scoparia, Artemisia sieversiana, Bassia dasyphylla, Kochia prastrata, and Neopallasia pectinata germinated to >60% in the lowest temperature regime (April). Germination decreased with increasing water stress, but Allium ramosum, Artemisia annua, Artemisia scoparia, Bassia dasyphylla, Heteropappus altaicus, Kochia prastrata, Neopallasia pectinata, and Potentilla tanacetifolia germinated to near 60% at ?0.87 MPa. Among these eight species, germination of six was tolerant to both temperature and water stress. Mean germination percentage in the four temperature regimes and the five water potentials was not significantly correlated with seed mass or seed area, which were highly correlated. Our results suggest that the species‐specific germination responses to environmental conditions are important in structuring the desert steppe community and have implications for predicting community structure under climate change. Thus, the predicted warmer and dryer climate will favor germination of drought‐tolerant species, resulting in altered proportions of germinants of different species and subsequently change in community composition of the desert steppe.     

Logistic regression when covariates are random effects from a non‐linear mixed model

In many studies, the association of longitudinal measurements of a continuous response and a binary outcome are often of interest. A convenient framework for this type of problems is the joint model, which is formulated to investigate the association between a binary outcome and features of longitudinal measurements through a common set of latent random effects. The joint model, which is the focus of this article, is a logistic regression model with covariates defined as the individual‐specific random effects in a non‐linear mixed‐effects model (NLMEM) for the longitudinal measurements. We discuss different estimation procedures, which include two‐stage, best linear unbiased predictors, and various numerical integration techniques. The proposed methods are illustrated using a real data set where the objective is to study the association between longitudinal hormone levels and the pregnancy outcome in a group of young women. The numerical performance of the estimating methods is also evaluated by means of simulation.     

Using multiple landscape genetic approaches to test the validity of genetic clusters in a species characterized by an isolation‐by‐distance pattern

Bayesian clustering methods are typically used to identify barriers to gene flow, but they are prone to deduce artificial subdivisions in a study population characterized by an isolation‐by‐distance pattern (IbD). Here we analysed the landscape genetic structure of a population of wild boars (Sus scrofa) from south‐western Germany. Two clustering methods inferred the presence of the same genetic discontinuity. However, the population in question was characterized by a strong IbD pattern. While landscape‐resistance modelling failed to identify landscape features that influenced wild boar movement, partial Mantel tests and multiple regression of distance matrices (MRDMs) suggested that the empirically inferred clusters were separated by a genuine barrier. When simulating random lines bisecting the study area, 60% of the unique barriers represented, according to partial Mantel tests and MRDMs, significant obstacles to gene flow. By contrast, the random‐lines simulation showed that the boundaries of the inferred empirical clusters corresponded to the most important genetic discontinuity in the study area. Given the degree of habitat fragmentation separating the two empirical partitions, it is likely that the clustering programs correctly identified a barrier to gene flow. The differing results between the work published here and other studies suggest that it will be very difficult to draw general conclusions about habitat permeability in wild boar from individual studies.