Evaluating the importance of demographic connectivity in a marine metapopulation

Recently researchers have gone to great lengths to measure marine metapopulation connectivity via tagging, genetic, and trace-elemental fingerprinting studies. These empirical estimates of larval dispersal are key to assessing the significance of metapopulation connectivity within a demographic context, but the life-history data required to do this are rarely available. To evaluate the demographic consequences of connectivity we constructed seasonal, size-structured metapopulation matrix models for two species of mytilid mussel in San Diego County, California, USA. The self-recruitment and larval exchange terms were produced from a time series of realized connectivities derived from trace-elemental fingerprinting of larval shells during spring and fall from 2003 to 2008. Both species exhibited a strong seasonal pattern of southward movement of recruits in spring and northward movement in fall. Growth and mortality terms were estimated using mark-recapture data from representative sites for each species and subpopulation, and literature estimates of juvenile mortality. Fecundity terms were estimated using county-wide settlement data from 2006-2008; these data reveal peak reproduction and recruitment in fall for Mytilus californianus, and spring for M. galloprovincialis. Elasticity and life-stage simulation analyses were employed to identify the season- and subpopulation-specific vital rates and connectivity terms to which the metapopulation growth rate (lambda) was most sensitive. For both species, metapopulation growth was most sensitive to proportional changes in adult fecundity, survival and growth of juvenile stages, and population connectivity, in order of importance, but relatively insensitive to adult growth or survival. The metapopulation concept was deemed appropriate for both Mytilus species as exchange between the subpopulations was necessary for subpopulation persistence. However, highest metapopulation growth occurred in years when a greater proportion of recruits was retained within the predominant source subpopulation. Despite differences in habitat and planktonic duration, both species exhibited similar overall metapopulation dynamics with respect to key life stages and processes. However, different peak reproductive periods in an environment of seasonal current reversals led to different regional (subpopulation) contributions to metapopulation maintenance; this result emphasizes the importance of connectivity analysis for spatial management of coastal resources.     

Cost‐Effectiveness of Translocation Options for a Threatened Waterbird

Abstract: Reintroduction of captive‐reared animals has become increasingly popular in recent decades as a conservation technique, but little is known of how demographic factors affect the success of reintroductions. We believe whether the increase in population persistence associated with reintroduction is sufficient to warrant the cost of rearing and relocating individuals should be considered as well. We examined the trade‐off between population persistence and financial cost of a reintroduction program for Crested Coots (Fulica cristata). This species was nearly extirpated from southern Europe due to unsustainable levels of hunting and reduction in amount and quality of habitat. We used a stochastic, stage‐based, single‐sex, metapopulation model with site‐specific parameters to examine the demographic effects of releasing juveniles or adults in each population for a range of durations. We parameterized the model with data from an unsuccessful reintroduction program in which juvenile captive‐bred Crested Coots were released between 2000 and 2009. Using economic data from the captive‐breeding program, we also determined whether the strategy that maximized abundance coincided with the least expensive strategy. Releasing adults resulted in slightly larger final abundance than the release of nonreproductive juveniles. Both strategies were equally poor in achieving a viable metapopulation, but releasing adults was 2–4 times more expensive than releasing juveniles. To obtain a metapopulation that would be viable for 30 years, fecundity in the wild would need to increase to the values observed in captivity and juvenile survival would need to increase to almost unity. We suggest that the most likely way to increase these vital rates is by increasing habitat quality at release sites.     

Quantifying the importance of patch-specific changes in habitat to metapopulation viability of an endangered songbird

A growing number of programs seek to facilitate species conservation using incentive-based mechanisms. Recently, a market-based incentive program for the federally endangered Golden-cheeked Warbler (Dendroica chrysoparia) was implemented on a trial basis at Fort Hood, an Army training post in Texas, USA. Under this program, recovery credits accumulated by Fort Hood through contracts with private landowners are used to offset unintentional loss of breeding habitat of Golden-cheeked Warblers within the installation. Critical to successful implementation of such programs is the ability to value, in terms of changes to overall species viability, both habitat loss and habitat restoration or protection. In this study, we sought to answer two fundamental questions: Given the same amount of change in breeding habitat, does the change in some patches have a greater effect on metapopulation persistence than others? And if so, can characteristics of a patch (e.g., size or spatial location) be used to predict how the metapopulation will respond to these changes? To answer these questions, we describe an approach for using sensitivity analysis of a metapopulation projection model to predict how changes to specific habitat patches would affect species viability. We used a stochastic, discrete-time projection model based on stage-specific estimates of survival and fecundity, as well as various assumptions about dispersal among populations. To assess a particular patch's leverage, we quantified how much metapopulation viability was expected to change in response to changing the size of that patch. We then related original patch size and distance from the largest patch to each patch's leverage to determine if general patch characteristics could be used to develop guidelines for valuing changes to patches within a metapopulation. We found that both the characteristic that best predicted patch leverage and the magnitude of the relationship changed under different model scenarios. Thus, we were unable to find a consistent set of relationships, and therefore we emphasize the dangers in relying on general guidelines to assess patch value. Instead, we provide an approach that can be used to quantitatively evaluate patch value and identify critical needs for future research.     

Populations in small, ephemeral habitat patches may drive dynamics in a Daphnia magna metapopulation

Migration is the key process to understand the dynamics and persistence of a metapopulation. Many metapopulation models assume a positive correlation between habitat patch size or stability and the number of emigrants. However, few empirical data exist, and habitat patch size and habitat stability may affect dispersal differently than they affect local persistence. Here, we studied the production of the migration stage (i.e., resting eggs called ephippia) of the cladoceran Daphnia magna in a metapopulation consisting of 530 rock pool habitat patches over 25 years. Earlier, the functioning of this metapopulation was explained with a Levins-type metapopulation model or with a mainland-island metapopulation model, based on local extinction and colonization data or time series data, respectively. We used pool volume, hydroperiod length, and number of desiccation events to calculate per-pool production of ephippia (i.e., migration stages). We estimated that populations in small and ephemeral habitat patches produced more than half of the 250 000 to 1 million ephippia that were produced in the metapopulation as a whole per year between 1982 and 2006. Furthermore, these small populations contributed approximately 90% of the ephippia exposed during desiccation events, while the contribution of the long-lived populations in large pools was minimal. We term this an "inverse mainland-island" type metapopulation and propose that populations in small, ephemeral habitat patches may also be the driving force for metapopulation dynamics in other systems.     

Integrating Landscape and Metapopulation Modeling Approaches: Viability of the Sharp-Tailed Grouse in a Dynamic Landscape

Abstract:  The lack of management experience at the landscape scale and the limited feasibility of experiments at this scale have increased the use of scenario modeling to analyze the effects of different management actions on focal species. However, current modeling approaches are poorly suited for the analysis of viability in dynamic landscapes. Demographic (e.g., metapopulation) models of species living in these landscapes do not incorporate the variability in spatial patterns of early successional habitats, and landscape models have not been linked to population viability models. We link a landscape model to a metapopulation model and demonstrate the use of this model by analyzing the effect of forest management options on the viability of the Sharp-tailed Grouse (  Tympanuchus phasianellus ) in the Pine Barrens region of northwestern Wisconsin (U.S.A.). This approach allows viability analysis based on landscape dynamics brought about by processes such as succession, disturbances, and silviculture. The landscape component of the model (LANDIS) predicts forest landscape dynamics in the form of a time series of raster maps. We combined these maps into a time series of patch structures, which formed the dynamic spatial structure of the metapopulation component (RAMAS). Our results showed that the viability of Sharp-tailed Grouse was sensitive to landscape dynamics and demographic variables such as fecundity and mortality. Ignoring the landscape dynamics gave overly optimistic results, and results based only on landscape dynamics (ignoring demography) lead to a different ranking of the management options than the ranking based on the more realistic model incorporating both landscape and demographic dynamics. Thus, models of species in dynamic landscapes must consider habitat and population dynamics simultaneously.     

Simple rules for ranking and optimally managing metapopulations

We present two ‘rules of thumb’ for metapopulation management. The first identifies an explicit formula for the persistence time of the population, and thus enables the population manager to form a priority species ranking by identifying those species most at risk of extinction. The second identifies an optimal management strategy that gives direction on how to alter the colonisation rate (creation or improvement of habitat corridors) and local extinction rate (restoring habitat quality or expanding habitat) in order to maximise the persistence time under a budgetary constraint. We employ a simple stochastic version of Levins (1969) metapopulation model, which is first calibrated to a more realistic spatial model. Our rules are tested on computer-generated patch networks and a model for malleefowl (Leipoa ocellata) in the Bakara region of South Australia.     

Simulated Responses of a Forest-Interior Bird Population to Forest Management Options in Central Hardwood Forests of the United States

I used estimates of carrying capacity, survival, fecundity, and edge effects to simulate the responses of a forest-interior bird population to selection cutting clearcutting, and no timber harvest. I also modeled population sensitivity to changes in fecundity, survival, K , and edge relationships. Because model parameters are based on scant data, results should he regarded as hypotheses to be further investigated or measures of the relative impact or sensitivity (given model assumptions). Simulated population size was greater with no timber harvest than with clearcutting and greater with clearcutting than with group selection when edge effects were included in the model. Without edge effects, population levels were only slightly lower under group selection than under no timber harvest, and greater than clearcutting. Edge effects had only a small impact on population levels under clearcutting. Clearcut size did not have much effect on population levels, but longer and shorter rotation ages resulted in higher and lower population levels, respectively. The model was very sensitive to declines in mean fecundity and survival, suggesting that factors affecting mean demographic rates could be more important than local edge effects. Some methods of timber harvest may be compatible with the conservation of forest-interior birds, but better demographic data and information on habitat suitability of selectively cut forests and young even-aged stands is needed to adequately evaluate management options.     

Minimum viable metapopulation size, extinction debt, and the conservation of a declining species.

A key question facing conservation biologists is whether declines in species' distributions are keeping pace with landscape change, or whether current distributions overestimate probabilities of future persistence. We use metapopulations of the marsh fritillary butterfly Euphydryas aurinia in the United Kingdom as a model system to test for extinction debt in a declining species. We derive parameters for a metapopulation model (incidence function model, IFM) using information from a 625-km2 landscape where habitat patch occupancy, colonization, and extinction rates for E. aurinia depend on patch connectivity, area, and quality. We then show that habitat networks in six extant metapopulations in 16-km2 squares were larger, had longer modeled persistence times (using IFM), and higher metapopulation capacity (lambdaM) than six extinct metapopulations. However, there was a > 99% chance that one or more of the six extant metapopulations would go extinct in 100 years in the absence of further habitat loss. For 11 out of 12 networks, minimum areas of habitat needed for 95% persistence of metapopulation simulations after 100 years ranged from 80 to 142 ha (approximately 5-9% of land area), depending on the spatial location of habitat. The area of habitat exceeded the estimated minimum viable metapopulation size (MVM) in only two of the six extant metapopulations, and even then by only 20%. The remaining four extant networks were expected to suffer extinction in 15-126 years. MVM was consistently estimated as approximately 5% of land area based on a sensitivity analysis of IFM parameters and was reduced only marginally (to approximately 4%) by modeling the potential impact of long-distance colonization over wider landscapes. The results suggest a widespread extinction debt among extant metapopulations of a declining species, necessitating conservation management or reserve designation even in apparent strongholds. For threatened species, metapopulation modeling is a potential means to identify landscapes near to extinction thresholds, to which conservation measures can be targeted for the best chance of success.     

Sensitivity of population viability to spatial and nonspatial parameters using GRIP.

Metapopulation dynamics are influenced by spatial parameters including the amount and arrangement of suitable habitat, yet these parameters may be uncertain when deciding how to manage species or their habitats. Sensitivity analyses of population viability analysis (PVA) models can help measure relative parameter influences on predictions, identify research priorities for reducing uncertainty, and evaluate management strategies. Few spatial PVAs, however, include sensitivity analyses of both spatial and nonspatial parameters, perhaps because computationally efficient tools for such analyses are lacking or inaccessible. We developed GRIP, a program to facilitate sensitivity analysis of spatial and nonspatial input parameters for PVAs created in RAMAS Metapop, a widely applied software program. GRIP creates random sets of input files by varying parameters specified in the PVA model including vital rates and their correlations among populations, the number and configuration of populations, dispersal rates, dispersal survival, initial population abundances, carrying capacities, and the probability, intensity, and spatial extent of catastrophes, while drawing on specified parameter distributions. We evaluated GRIP's performance as a tool for sensitivity analysis of spatial PVAs and explored the consequences of varying spatial input parameters for predictions of a published PVA model of the sand lizard (Lacerta agilis). We used GRIP output to generate standardized regression coefficients (SRCs) and nonparametric correlation coefficients as indices of the relative sensitivity of predicted conservation status to input parameters. GRIP performed well; with a single analysis we were able to rank the relative influence of input parameters identified as influential by the PVA's original author, S. A. Berglind, who used three separate forms of sensitivity analysis. Our analysis, however, also underscored the value of exploring the relative influence of spatial parameters on PVA predictions; both SRCs and correlation coefficients indicated that the most influential parameters in the sand lizard model were spatial in nature. We provide annotated code so that GRIP may be modified to reflect particular species biology, customized for more complex spatial PVA models, upgraded to incorporate features added in newer versions of RAMAS Metapop, used as a template to develop similar programs, or used as it is for computationally efficient sensitivity analyses in support of conservation planning.     

Fitting probability models to population dynamics data

Methods for modeling population dynamics in probability using the generalized point process approach are developed. The life history of these populations is such that seasonal reproduction occurs during a short time. Several models are developed and analyzed. Data about two species: colonial spiders (Stegodyphus dumicola) and a migratory bird (wood thrush, Hylocichla mustelina) are used to estimate model parameters with appropriate log maximum likelihood functions. For the spiders, the model is fitted to provide evolutionary feasible colony size based on maximum likelihood estimates of fecundity and survival data. For the migratory bird species, a maximum likelihood estimates are derived for the fecundity and survival rates of young and adult birds and immigration rate. The presented approach allows computation of quantities of interest such as probability of extinction and average time to extinction.     

Spatial occurrence of a habitat-tracking saproxylic beetle inhabiting a managed forest landscape.

Because of the dynamic nature of many managed habitats, proper evaluation of conservation efforts calls for models that take into account both spatial and temporal habitat dynamics. We develop a metapopulation model for successional-type systems, in which habitat quality changes over time in a predictable fashion. The occupancy and recruitment of the predatory saproxylic (dependent on dead wood) beetle Harminius undulatus was studied in a managed boreal forest landscape, covering 24,449 ha, in central Sweden. In a first step, we analyzed the beetle's occupancy pattern in relation to stand characteristics, and the amounts of present and past habitat in the surrounding landscape. Managed forest is suitable habitat when > or =60 years old, and immediately after cutting, but not between the ages of 10 and 60 years. The observed occupancy of H. undulatus was positively correlated with the stand's age as habitat. We used a metapopulation model to predict the current probability of occurrence in each forest stand, given the spatiotemporal distribution of suitable forest stands during the last 50 years. Metapopulation parameters were estimated by matching predicted spatial distributions with observed spatial distributions. The model predicted observed spatial distributions better than a similar model that assumed constant habitat quality of each forest stand. Thus, metapopulation models for successional-type systems, such as dead wood dependent organisms in managed forest landscapes, should include habitat dynamics. An estimated 82% of the landscape-wide recruitment took place in managed stands, which covered 87% of the forest area, in comparison with 18% in unmanaged stands, which covered 13% of the forest area. Among the managed stand types, > or =60-year-old stands and 3-7-year-old clear-cuttings contributed to 79% of the total recruitment while 8-59-year-old stands only contributed 3%. The results suggest the following guidelines to improve conditions for H. undulatus and other species with similar habitat requirements: (1) the proportion of the landscape constituted by younger stands should not be allowed to grow too large, (2) the rotation period of managed stands should not be allowed to be too short, and (3) dead wood should be retained and created at final cutting.     

Effects of the spatial pattern of disturbance on the patch-occupancy dynamics of juniper–pine open woodland

Typically, studies of the disturbance effect on metapopulation dynamics are limited to understanding the effect of habitat loss although, recently, the spatial pattern of the disturbance has been shown to influence dynamics. In this study, we used a stochastic patch-dynamic model to investigate the effects of spatial disturbance patterns on the persistence of an open woodland community of Juniperus spp. and Pinus spp. First, we estimated patch-occupancy dynamics by using the coefficients that best predicted the occupancy observed in 1998 based on occupancy data from 1957. Next, we evaluated the effects of the rate and pattern of the disturbance on the extinction probability. In modeling the disturbance, we considered (1) the degree of disturbance produced by scenarios of complete destruction or degradation (with the potential for recolonization), (2) the overall rate of disturbance, and (3) the spatial autocorrelation of habitat destruction. Twenty 40-year simulations predicted a 25% increase in the number of patches, and when 50% of the habitat was removed, the impact was more pronounced after complete destruction than it was after degradation of the area. Predictions based on scenarios of complete destruction, including random, contiguous, Brownian, and autoregressive noise, demonstrated that the impact of disturbance depends upon the spatial structure of the disturbance regimen. The autocorrelated structure of the disturbance regimen had the greatest impact on patch persistence. Patch-occupancy was higher after 20 40-year simulations when habitat loss was randomly distributed than when it followed an autocorrelated patch destruction, which was simulated using autoregressive noise to produce 50% habitat destruction. In addition, while habitat loss was negatively linearly correlated with patch persistence when habitat destruction was randomly distributed, a dramatic transition shift occurred when habitat destruction was simulated following an autoregressive spatial distribution after a certain threshold of habitat destruction (40% of the actual open woodland habitat). Our study suggests that the spatial patterns of the disturbance should be considered when predicting the consequences of fragmentation and improving management strategies.     

Extinction Debts and Risks Faced by Abundant Species

A recent model indicating that good competitiors and abundant species face the greatest risk of extinction from habitat destruction is critically examined. The conclusions drawn from the model are shown to rely on a number of assumptions regarding the mechanism of species coexistence, the relationship between abundance and competitive ability, and spatial characteristics of habitat destruction. The generality of these assumptions is questioned. Of particular concern are the assumptions that good competitors are poor dispersers, and that good competitors are the most abundant species. Furthermore, we suggest that the spatial scale of metapopulation dynamics in the model may not be appropriate for representing impacts of habitat destrustion. Empirical evidence is discussed indicating the limited applicability of the model for describing effects of habitat destruction on risks of species extinctions. Examples from a number of fragmented systems demonstrate that poor competitors and rare species are vulnerable to habitat destruction.     

Metapopulation Extinction Risk under Spatially Autocorrelated Disturbance

Abstract:  Recent extinction models generally show that spatial aggregation of habitat reduces overall extinction risk because sites emptied by local extinction are more rapidly recolonized. We extended such an investigation to include spatial structure in the disturbance regime. A spatially explicit metapopulation model was developed with a wide range of dispersal distances. The degree of aggregation of both habitat and disturbance pattern could be varied from a random distribution, through the intermediate case of a fractal distribution, all the way to complete aggregation (single block). Increasing spatial aggregation of disturbance generally increased extinction risk. The relative risk faced by populations in different landscapes varied greatly, depending on the disturbance regime. With random disturbance, the spatial aggregation of habitat reduced extinction risk, as in earlier studies. Where disturbance was spatially autocorrelated, however, this advantage was eliminated or reversed because populations in aggregated habitats are at risk of mass extinction from coarse-scale disturbance events. The effects of spatial patterns on extinction risk tended to be reduced by long-distance dispersal. Given the high levels of spatial correlation in natural and anthropogenic disturbance processes, population vulnerability may be greatly underestimated both by classical (nonspatial) models and by those that consider spatial structure in habitat alone.     

Using experimental reintroductions to resolve the roles of habitat quality and metapopulation dynamics on patch occupancy in fragmented landscapes

Declines of species in fragmented landscapes can potentially be reversed either by restoring connectivity or restoring local habitat quality. Models fitted to snapshot occupancy data can be used to predict the effectiveness of these actions. However, such inferences can be misleading if the reliability of the habitat and landscape metrics used is unknown. The only way to unambiguously resolve the roles of habitat quality and metapopulation dynamics is to conduct experimental reintroductions to unoccupied patches so that habitat quality can be measured directly from data on vital rates. We, therefore, conducted a 15-year study that involved reintroducing a threatened New Zealand bird to unoccupied forest fragments to obtain reliable data on their habitat quality and reassess initial inferences made by modeling occupancy against habitat and landscape metrics. Although reproductive rates were similar among fragments, subtle differences in adult survival rates resulted in λ (finite rate of increase) estimations of <0.9 for 9 of the 12 fragments that were previously unoccupied. This was the case for only 1 of 14 naturally occupied fragments. This variation in λ largely explained the original occupancy pattern, reversing our original conclusion from occupancy modeling that this occupancy pattern was isolation driven and suggesting that it would be detrimental to increase connectivity without improving local habitat quality. These results illustrate that inferences from snapshot occupancy should be treated with caution and subjected to testing through experimental reintroductions in selected model systems.     

Linking life history to landscape for threatened species conservation in a multiuse region

Landscape-scale conservation that considers metapopulation dynamics will be essential for preventing declines of species facing multiple threats to their survival. Toward this end, we developed a novel approach that combines occurrence records, spatial–environmental data, and genetic information to model habitat, connectivity, and patterns of genetic structure and link spatial attributes to underlying ecological mechanisms. Using the threatened northern quoll (Dasyurus hallucatus) as a case study, we applied this approach to address the need for conservation decision-making tools that promote resilient metapopulations of this threatened species in the Pilbara, Western Australia, a multiuse landscape that is a hotspot for biodiversity and mining. Habitat and connectivity were predicted by different landscape characteristics. Whereas habitat suitability was overwhelmingly driven by terrain ruggedness, dispersal was facilitated by proximity to watercourses. Although there is limited evidence for major physical barriers in the Pilbara, areas with high silt and clay content (i.e., alluvial and hardpan plains) showed high resistance to dispersal. Climate subtlety shaped distributions and patterns of genetic turnover, suggesting the potential for local adaptation. By understanding these spatial–environmental associations and linking them to life-history and metapopulation dynamics, we highlight opportunities to provide targeted species management. To support this, we have created habitat, connectivity, and genetic uniqueness maps for conservation decision-making in the region. These tools have the potential to provide a more holistic approach to conservation in multiuse landscapes globally.     

Integrating the Metapopulation and Habitat Paradigms for Understanding Broad-Scale Declines of Species

Abstract:  Caughley (1994) argued that researchers working on threatened populations tended to follow the "small population paradigm" or the "declining population paradigm," and that greater integration of these paradigms was needed. Here I suggest that two related paradigms exist at the broader spatial scale, namely the metapopulation paradigm and habitat paradigm, and that these two paradigms also need to be integrated if we are to provide sound management advice. This integration is not trivial, and I outline five problems that need to be addressed: (1) habitat variables may not measure habitat quality, so site-specific data on vital rates are needed to resolve the effects of habitat quality and metapopulation dynamics; (2) measurements of vital rates may be confounded by movements; (3) vital rates may be density dependent; (4) vital rates may be affected by genotype; and (5) vital rates cannot be measured in unoccupied patches. I reviewed papers published in Conservation Biology from 1994 to 2003 and found 41 studies that analyzed data from 10 or more sites to understand the factors limiting species' distributions. Five of the analyses presented were purely within the metapopulation paradigm, 14 were purely within the habitat paradigm, 17 involved elements of both paradigms, and 7 were theoretically ambiguous (2 papers presented 2 distinct analyses and were counted twice). This suggests that many researchers appreciate the need to integrate the paradigms. Only one study, however, used data on vital rates to resolve the effects of habitat quality and metapopulation dynamics (problem 1), and this study did not address problems 2–5. I conclude that more intensive research incorporating site-specific data on vital rates and movement is needed to complement the numerous analyses of distributional data being produced.     

A model for behavioral regulation of metapopulation dynamics

Habitat fragmentation can decrease local population persistence by reducing connectivity, which is a function of dispersal of individuals among habitat fragments. Dispersal is often treated as diffusion in population models, even though for many species it is a result of a series of behavioral decisions. We developed a metapopulation model to explore the potential importance of dispersal behaviors in driving metapopulation dynamics. We incorporated types of behavior that affect dispersal—colonization inhibiting, colonization enhancing, extinction inhibiting, extinction enhancing, rescue enhancing, rescue inhibiting—into Levins’ (1969) metapopulation model and projected occupancy rates for a variety of parameter values. Examples from the literature of behaviors associated with each of these parameters are provided. Our model simplifies into previously published metapopulation models that incorporate only a single behavior, and we present a density-dependent rescue function that leads to multiple non-zero equilibria. We found a variety of behavioral effects on metapopulations. Rescue enhancement fills patches faster than does colonization enhancement or extinction inhibition, and declines in patch occupancy are moderate with extinction enhancement, but colonization inhibition causes metapopulation extinction. We also found that with colonization and extinction inhibitions, equilibrium patch occupancy is inversely related to patch turnover rate. With density-dependent rescue, persistence depends not only on the strength of the strong rescue effect, but also on having a sufficient initial fraction of patches occupied; the stronger the rescue effect, the lower this fraction can be. This study suggests that dispersal behavior can have strong influences on metapopulation dynamics. It confirms the importance of understanding the relationship between landscape structure and dispersal behavior in understanding population persistence.     

Dispersal depression with habitat fragmentation in the bog fritillary butterfly

Habitat fragmentation is expected to impose strong selective pressures on dispersal rates. However, evolutionary responses of dispersal are not self-evident, since various selection pressures act in opposite directions. Here we disentangled the components of dispersal behavior in a metapopulation context using the Virtual Migration model, and we linked their variation to habitat fragmentation in the specialist butterfly Proclossiana eunomia. Our study provided a nearly unique opportunity to study how habitat fragmentation modifies dispersal at the landscape scale, as opposed to microlandscapes or simulation studies. Indeed, we studied the same species in four landscapes with various habitat fragmentation levels, in which large amounts of field data were collected and analyzed using similar methodologies. We showed the existence of quantitative variations in dispersal behavior correlated with increased fragmentation. Dispersal propensity from habitat patches (for a given patch size), and mortality during dispersal (for a given patch connectivity) were lower in more fragmented landscapes. We suggest that these were the consequences of two different evolutionary responses of dispersal behavior at the individual level: (1) when fragmentation increased, the reluctance of individuals to cross habitat patch boundaries also increased; (2) when individuals dispersed, they flew straighter in the matrix, which is the best strategy to improve dispersal success. Such evolutionary responses could generate complex nonlinear patterns of dispersal changes at the metapopulation level according to habitat fragmentation. Due to the small size and increased isolation of habitat patches in fragmented landscapes, overall emigration rate and mortality during dispersal remained high. As a consequence, successful dispersal at the metapopulation scale remained limited. Therefore, to what extent the selection of individuals with a lower dispersal propensity and a higher survival during dispersal is able to limit detrimental effects of habitat fragmentation on dispersal success is unknown, and any conclusion that metapopulations would compensate for them is flawed.     

Incorporating diverse data and realistic complexity into demographic estimation procedures for sea otters.

Reliable information on historical and current population dynamics is central to understanding patterns of growth and decline in animal populations. We developed a maximum likelihood-based analysis to estimate spatial and temporal trends in age/sex-specific survival rates for the threatened southern sea otter (Enhydra lutris nereis), using annual population censuses and the age structure of salvaged carcass collections. We evaluated a wide range of possible spatial and temporal effects and used model averaging to incorporate model uncertainty into the resulting estimates of key vital rates and their variances. We compared these results to current demographic parameters estimated in a telemetry-based study conducted between 2001 and 2004. These results show that survival has decreased substantially from the early 1990s to the present and is generally lowest in the north-central portion of the population's range. The greatest temporal decrease in survival was for adult females, and variation in the survival of this age/sex class is primarily responsible for regulating population growth and driving population trends. Our results can be used to focus future research on southern sea otters by highlighting the life history stages and mortality factors most relevant to conservation. More broadly, we have illustrated how the powerful and relatively straightforward tools of information-theoretic-based model fitting can be used to sort through and parameterize quite complex demographic modeling frameworks.