Homogenization of dispersal ability across bird species in response to landscape change

Human land use is known to homogenize biotic communities, increasing similarity in their genetic, taxonomic and functional diversity. Explanations have focused almost exclusively on human‐mediated extinction and range expansion. However, homogenization could also be produced by land use driving selection for similar traits across species. We propose a novel hypothesis to explain how human land use homogenizes dispersal ability across species. With habitat loss and increasing human land use intensities there should be larger increases in the costs of dispersal for dispersive than sedentary species, because dispersive species interact with non‐habitat more frequently. In contrast, the benefits of dispersal should increase more for sedentary than dispersive species, because sedentary species are at greater risk from inbreeding depression, predation and competition associated with habitat loss. Therefore we predict that sedentary species become more dispersive in a human‐altered landscape, and dispersive species more sedentary. We tested this prediction using wing pointedness to estimate the initial dispersal ability and change in dispersal ability for 21 North American passerines over the 20th century. More pointed wings are associated with stronger dispersal ability. Thus our prediction would be supported by a negative cross‐species relationship between these two measurements. We found a strong, negative relationship, as predicted. This resulted in declines in the variability in wing pointedness among species over time. Although other things can cause wing shape to change, including changes in habitat availability, none of these explained the observed relationship. Our result provides the first evidence that human landscape alteration is homogenizing bird communities, driving selection for intermediate dispersal ability across species. It also implies that more dispersive species are more at‐risk from human landscape use because, when rates of landscape alteration are faster than a species’ ability to adapt to that change, the costs of dispersal increase more for dispersive than sedentary species.     

Evolutionary responses of dispersal distance to landscape structure and habitat loss

It is generally well understood that some ecological factors select for increased and others for decreased dispersal. However, it has remained difficult to assess how the evolutionary dynamics are influenced by the spatio-temporal structure of the environment. We address this question with an individual-based model that enables habitat structure to be controlled through variables such as patch size, patch turnover rate, and patch quality. Increasing patch size at the expense of patch density can select for more or less dispersal, depending on the initial configuration. In landscapes consisting of high-quality and long-lived habitat patches, patch degradation selects for increased dispersal, yet patch loss may select for reduced dispersal. These trends do not depend on the component of life-history that is affected by habitat quality or the component of life-history through which density-dependence operates. Our results are based on a mathematical method that enables derivation of both the evolutionary stable strategy and the stationary genotype distribution that evolves in a polymorphic population. The two approaches generally lead to similar predictions. However, the evolutionary stable strategy assumes that the ecological and evolutionary time scales can be separated, and we find that violation of this assumption can critically alter the evolutionary outcome.     

A model-based framework for assessing the vulnerability of low dispersal vertebrates to landscape fragmentation under environmental change

Environmental changes are driving rapid geographic shifts of suitable environmental conditions for species. These might survive by tracking those shifts, however successful responses will depend on the spatial distribution of suitable habitats (current and future) and on their connectivity. Most herptiles (i.e., amphibians and reptiles) have low dispersal abilities, and therefore herptiles are among the most vulnerable groups to environmental changes. Here we assessed the vulnerability of herptile species to future climate and land use changes in fragmented landscapes. We developed and tested a methodological approach combining the strengths of Species Distribution Models (SDMs) and of functional connectivity analysis. First, using SDMs we forecasted current and future distributions of potential suitable areas as well as range dynamics for four herptile species in Portugal. SDM forecasts for 2050 were obtained under two contrasting emission scenarios, translated into moderate (low-emissions scenario) or large (high-emissions scenario) changes in climate and land use conditions. Then, we calculated and analysed functional connectivity from areas projected to lose environmental suitability towards areas keeping suitable conditions. Landscape matrix resistance and barrier effects of the national motorway network were incorporated as the main sources of fragmentation. Potential suitable area was projected to decrease under future conditions for most test species, with the high-emissions scenario amplifying the losses or gains. Spatiotemporal patterns of connectivity between potentially suitable areas signalled the most important locations for maintaining linkages and migration corridors, as well as potential conflicts due to overlaps with the current motorway network. By integrating SDM projections with functional connectivity analysis, we were able to assess and map the vulnerability of distinct herptile species to isolation or extinction under environmental change scenarios. Our framework provides valuable information, with fairly low data requirements, for optimizing biodiversity management and mitigation efforts, aiming to reduce the complex and often synergistic negative impacts of multiple environmental change drivers. Implications for conservation planning and management are discussed from a global change adaptation perspective.     

Beyond species distribution modeling: A landscape genetics approach to investigating range shifts under future climate change

Understanding how biodiversity will respond to future climate change is a major conservation and societal challenge. Climate change is predicted to force many species to shift their ranges in pursuit of suitable conditions. This study aims to use landscape genetics, the study of the effects of environmental heterogeneity on the spatial distribution of genetic variation, as a predictive tool to assess how species will shift their ranges to track climatic changes and inform conservation measures that will facilitate movement. The approach is based on three steps: 1) using species distribution models (SDMs) to predict suitable ranges under future climate change, 2) using the landscape genetics framework to identify landscape variables that impede or facilitate movement, and 3) extrapolating the effect of landscape connectivity on range shifts in response to future climate change. I show how this approach can be implemented using the publicly available genetic dataset of the grey long-eared bat, Plecotus austriacus, in the Iberian Peninsula. Forest cover gradient was the main landscape variable affecting genetic connectivity between colonies. Forest availability is likely to limit future range shifts in response to climate change, primarily over the central plateau, but important range shift pathways have been identified along the eastern and western coasts. I provide outputs that can be directly used by conservation managers and review the viability of the approach. Using landscape genetics as a predictive tool in combination with SDMs enables the identification of potential pathways, whose loss can affect the ability of species to shift their range into future climatically suitable areas, and the appropriate conservation management measures to increase landscape connectivity and facilitate movement.     

A spatially explicit model of sex ratio evolution in response to sex-biased dispersal

Sex-biased dispersal occurs in all seed plants and many animal species. Theoretical models have shown that sex-biased dispersal can lead to evolutionarily stable biased sex ratios. Here, we use a spatially explicit chessboard model to simulate the evolution of sex ratio in response to sex-biased dispersal range and sex-biased dispersal rate. Two life cycles are represented in the model: one in which both sexes disperse before mating (DDM), the other in which males disperse before mating and mated females or zygotes disperse after mating (DMD). Model parameters include factors like dispersal rate, dispersal range, number of individuals per patch, and habitat heterogeneity.When dispersal range is sex biased, we find that, in a homogeneous environment, the sex ratio is generally biased towards the sex that disperses more widely (sex ratio range: 0.47–0.52). In a heterogeneous environment, the sex ratio is generally biased towards the more dispersive sex in good habitats, and towards the less dispersive sex in poor habitats (sex ratio range: 0–1). This is opposite to the effect of sex-biased dispersal rate, which favours the production of the more dispersive sex in poor habitats and the less dispersive sex in good habitats (sex ratio range: 0–1). To allow for a comparison with theoretical predictions, data concerning sex-biased dispersal and habitat-dependent sex ratios should thus incorporate information about the spatial scale of both dispersal and environmental heterogeneity.     

Uncertainties in the response of a forest landscape to global climatic change

Many studies have been conducted to quantify the possible ecosystem/landscape response to the anticipated global warming. However, there is a large amount of uncertainty in the future climate predictions used for these studies. Specifically, the climate predictions can be very different based on a variety of global climate models and alternative greenhouse emission scenarios. In this study, we coupled a forest landscape model, LANDIS-II, and a forest process model, PnET-II, to examine the uncertainty (that results from the uncertainty in the future climate predictions) in the forest-type composition prediction for a transitional forest landscape [the Boundary Water Canoe Area]. Using an improved global-sensitivity analysis technique [Fourier amplitude sensitivity test], we also quantified the amount of uncertainty in the forest-type composition prediction contributed by different climate variables including temperature, CO₂, precipitation and photosynthetic active radiation (PAR). The forest landscape response was simulated for the period 2000–2400 ad based on the differential responses of 13 tree species under an ensemble of 27 possible climate prediction profiles (monthly time series of climate variables). Our simulations indicate that the uncertainty in the forest-type composition becomes very high after 2200 ad , which is close to the time when the current forests are largely removed by windthrow disturbances and natural mortality. The most important source of uncertainty in the forest-type composition prediction is from the uncertainty in temperature predictions. The second most important source is PAR, the third is CO₂ and the least important is precipitation. Our results also show that if the optimum photosynthetic temperature rises due to CO₂ enrichment, the forest landscape response to climatic change measured by forest-type composition may be substantially reduced.     

A temporally explicit species distribution model for a long distance avian migrant,the common cuckoo

Modelling the distribution of migratory species has rarely been extended beyond breeding and wintering ranges despite many species showing much more complex movement patterns with multiple stopovers. We aimed to create a temporally explicit species distribution model describing the full annual distribution cycle, and use it to model the complex seasonal shifts in distribution of the common cuckoo Cuculus canorus, a declining long‐distance migrant. To do this we used full‐year satellite telemetry occurrence data, with their associated temporal information, to inform a temporally explicit species distribution model using MaxEnt. The resulting full‐year distribution model was highly predictive (AUC = 0.894) and appeared to have generality at the species‐level despite being informed by data from a single breeding population. Comparison of our methodology with seasonal distribution models describing the breeding, winter and migration ranges separately showed that our full‐year method provided more general and extensive predictions and performed better when tested with an independent dataset. When species distribution models based on a single season exclude environmental conditions experienced by birds in other parts of the annual cycle they risk underestimating niche breadth and neglecting the importance of stopover habitat. Conversely, models which simply average conditions across a season may miss the significance of finer scale within‐season movements and overestimate niche breadth. In contrast, our framework for a full‐year migrant distribution model successfully captures the finer‐scale changes expected in seasonal environments and can be used to inform conservation management at every stage of migration. The full‐year model framework appears to produce temporal distribution models generalised to the species‐level from occurrence data limited to few individuals of a single population and may have particular utility when aiming to describe the distribution of species with complex migration patterns from telemetry data.     

Sexual selection predicts advancement of avian spring migration in response to climate change

Global warming has led to earlier spring arrival of migratory birds, but the extent of this advancement varies greatly among species, and it remains uncertain to what degree these changes are phenotypically plastic responses or microevolutionary adaptations to changing environmental conditions. We suggest that sexual selection could help to understand this variation, since early spring arrival of males is favoured by female choice. Climate change could weaken the strength of natural selection opposing sexual selection for early migration, which would predict greatest advancement in species with stronger female choice. We test this hypothesis comparatively by investigating the degree of long-term change in spring passage at two ringing stations in northern Europe in relation to a synthetic estimate of the strength of female choice, composed of degree of extra-pair paternity, relative testes size and degree of sexually dichromatic plumage colouration. We found that species with a stronger index of sexual selection have indeed advanced their date of spring passage to a greater extent. This relationship was stronger for the changes in the median passage date of the whole population than for changes in the timing of first-arriving individuals, suggesting that selection has not only acted on protandrous males. These results suggest that sexual selection may have an impact on the responses of organisms to climate change, and knowledge of a species' mating system might help to inform attempts at predicting these.     

Life history predicts advancement of avian spring migration in response to climate change

An increasing number of studies demonstrate that plant and animal phenologies such as the timing of bird migration have been advancing over the globe, likely as a result of climate change. Even closely related species differ in their phenological responses, and the sources of this variation are poorly established. We used a large, standardized dataset of first arrival dates (FAD) of migratory birds to test the effects of phylogenetic relationships and various life-history and ecological traits on the degree to which different species adapt to climate change by earlier migration in spring. Using the phylogenetic comparative method, we found that the advancement of FAD was greater in species with more generalized diet, shorter migration distance, more broods per year, and less extensive prebreeding molt. In turn, we found little evidence that FAD trends were influenced by competition for mating (polygamy or extra-pair paternity) and breeding opportunities (cavity nests). Our findings were robust to several potentially confounding effects. These evolutionary correlations, coupled with the low levels of phylogenetic dependence we found, indicate that avian migration phenology adapts to climate change as a species-specific response. Our results suggest that the degree of this response is fundamentally shaped by constraints and selection pressures of the species' life history, and less so by the intensity of sexual selection.     

A graph-based approach to investigating the influence of the landscape on population spread processes

Modelling of landscape connectivity is a key point in the study of the movement of populations within a given landscape. For studies focused on the preservation of biodiversity, graph-based methods provide an interesting framework to investigate the landscape influence on population spread processes. Such an approach is described here, based on the mapping of landscape categories in habitat patches, including a diachronic data set describing the population spread within the habitat patches. A minimum planar graph was built by computing spatial distances between all pairs of neighbouring patches. From this structure, two types of analysis are proposed: one focused on the links of the graph and consists in correlating spatial distances and gap indicators computed from the diachronic data. The other was based on the correlations between population data and connectivity metrics at the patch level. As an example, this approach was applied to the spread of the fossorial water vole on the Jura plateau (France), with annual population data covering eleven years from 1989 to 2000. Link analysis allowed to find an optimal set of resistance values used in the least-cost distances computations, and thus to build a relevant graph. From this graph, patch analysis displayed a cyclic correlation between a metric based on potential dispersal flux and the population density, outlining the strong role of landscape connectivity in the population spread. The present study clearly shows that landscape modelling and graph-based approach can produce parameters which are consistent with field observations and thus pave the way to simulating the effect of landscape modification on population dynamics.     

Dynamic larval dispersal can mediate the response of marine metapopulations to multiple climate change impacts

Climate change is having multiple impacts on marine species characterized by sedentary adult and pelagic larval phases, from increasing adult mortality to changes in larval duration and ocean currents. Recent studies have shown impacts of climate change on species persistence through direct effects on individual survival and development, but few have considered the indirect effects mediated by ocean currents and species traits such as pelagic larval duration. We used a density-dependent and stochastic metapopulation model to predict how changes in adult mortality and dynamic connectivity can affect marine metapopulation stability. We analyzed our model with connectivity data simulated from a biophysical ocean model of the northeast Pacific coast forced under current (1998–2007) and future (2068–2077) climate scenarios in combination with scenarios of increasing adult mortality and decreasing larval duration. Our results predict that changes of ocean currents and larval duration mediated by climate change interact in complex and opposing directions to shape local mortality and metapopulation connectivity with synergistic effects on regional metapopulation stability: while species with short larval duration are most sensitive to temperature-driven reduction in larval duration, the response of species with longer larval duration are mostly mediated by changes in both the mean and variance of larval connectivity driven by ocean currents. Our results emphasize the importance of considering the spatiotemporal structure of connectivity in order to predict how the multiple effects of climate change will impact marine populations.     

Contribution of different dispersal sources to the metabolic response of lake bacterioplankton following a salinity change

Dispersal can modify how bacterial community composition (BCC) changes in response to environmental perturbations, yet knowledge about the functional consequences of dispersal is limited. Here we hypothesized that changes in bacterial community production in response to a salinity disturbance depend on the possibility to recruit cells from different dispersal sources. To investigate this, we conducted an in situ mesocosm experiment where bacterial communities of an oligotrophic lake were exposed to different salinities (0, 18, 36 psu) for 2 weeks and subjected to dispersal of cells originating from sediments, air (mesocosms open to air deposition), both or none. BCC was determined using 454 pyrosequencing of the 16S rRNA gene and bacterial production was measured by ³H leucine uptake. Bacterial production differed significantly among salinity treatments and dispersal treatments, being highest at high salinity. These changes were associated with changes in BCC and it was found that the identity of the main functional contributors differed at different salinities. Our results further showed that after a salinity perturbation, the response of bacterial communities depended on the recruitment of taxa, including marine representatives (e.g., Alphaproteobacteria Loktanella, Erythrobacter and the Gammaproteobacterium Rheiheimera) from dispersal sources, in which atmospheric deposition appeared to play a major role.     

A framework for considering prior information in network-based approaches to omics data analysis

For decades, molecular biologists have been uncovering the mechanics of biological systems. Efforts to bring their findings together have led to the development of multiple databases and information systems that capture and present pathway information in a computable network format. Concurrently, the advent of modern omics technologies has empowered researchers to systematically profile cellular processes across different modalities. Numerous algorithms, methodologies, and tools have been developed to use prior knowledge networks (PKNs) in the analysis of omics datasets. Interestingly, it has been repeatedly demonstrated that the source of prior knowledge can greatly impact the results of a given analysis. For these methods to be successful it is paramount that their selection of PKNs is amenable to the data type and the computational task they aim to accomplish. Here we present a five-level framework that broadly describes network models in terms of their scope, level of detail, and ability to inform causal predictions. To contextualize this framework, we review a handful of network-based omics analysis methods at each level, while also describing the computational tasks they aim to accomplish.     

Stable isotope analysis provides new information on winter habitat use of declining avian migrants that is relevant to their conservation

Winter habitat use and the magnitude of migratory connectivity are important parameters when assessing drivers of the marked declines in avian migrants. Such information is unavailable for most species. We use a stable isotope approach to assess these factors for three declining African-Eurasian migrants whose winter ecology is poorly known: wood warbler Phylloscopus sibilatrix, house martin Delichon urbicum and common swift Apus apus. Spatially segregated breeding wood warbler populations (sampled across a 800 km transect), house martins and common swifts (sampled across a 3,500 km transect) exhibited statistically identical intra-specific carbon and nitrogen isotope ratios in winter grown feathers. Such patterns are compatible with a high degree of migratory connectivity, but could arise if species use isotopically similar resources at different locations. Wood warbler carbon isotope ratios are more depleted than typical for African-Eurasian migrants and are compatible with use of moist lowland forest. The very limited variance in these ratios indicates specialisation on isotopically restricted resources, which may drive the similarity in wood warbler populations' stable isotope ratios and increase susceptibility to environmental change within its wintering grounds. House martins were previously considered to primarily use moist montane forest during the winter, but this seems unlikely given the enriched nature of their carbon isotope ratios. House martins use a narrower isotopic range of resources than the common swift, indicative of increased specialisation or a relatively limited wintering range; both factors could increase house martins' vulnerability to environmental change. The marked variance in isotope ratios within each common swift population contributes to the lack of population specific signatures and indicates that the species is less vulnerable to environmental change in sub-Saharan Africa than our other focal species. Our findings demonstrate how stable isotope research can contribute to understanding avian migrants' winter ecology and conservation status.     

A landscape for the dynamics of an immune response

Dynamic shaping of the antibody repertoire is essential for effective immunity. We describe here a novel approach for clarifying how the antibody repertoire is shaped over time for development of a specific immune response. We obtained over 500 immunoglobulin G1 clones harboring VH186.2 from the spleen, bone marrow, and microdissected individual germinal centers of (4-hydroxy-3-nitrophenyl) acetyl-immunized C57BL/6 mice at various time points postimmunization. Statistical analyses provided an index for defining clonal diversity and cluster analyses gave us a three-dimensional landscape with which clone distance was visualized with the expression level of antibodies. This landscape approach facilitated our understanding of the dynamics shaping the actual antibody repertoire, in which pre-existing naturally occurring population persisted and provided a significant impact upon the repertoire. To the established model for describing production of the antibody-forming cells, we were able to append an indispensable issue in considering the maturation of humoral immune response.     

In response to the continuum model for fauna research: a hierarchical, patch-based model of spatial landscape patterns

Models of nature are implicitly influenced by the scale of observation of the processes on which they are founded. The continuum model and the hierarchical patch-based model are two alternate approaches for the spatial modelling of fauna distribution. The continuum model aggregates continuous approximations to individual landscape characteristics, whereas the hierarchical patch-based model constructs a hierarchy in which classifications of landscape characteristics describe an interconnected series of patches. We propose the hierarchical patch-based theory for models of population distributions and landscapes in which the spatial patterns can be effectively represented by mosaics at the variety of levels within the set of individual process models. Given that observations are typically made as points or pixels, and that discrete boundaries exist in both natural and human-modified landscapes, we suggest that the hierarchical patch-based method has many applications in conservation and management.