Metapopulation Viability Analysis Research Articles

Using meta-population models to guide conservation action

Biodiversity conservation is limited by resources, data, and time for execution. To maximize efficacy, it is best if conservation plans are strategically evaluated for cost, feasibility, and likely impact prior to implementation. We present a framework to systematically examine the likely impact of proposed conservation plans for threatened taxa. As a case study of this framework we use the national Action Plan for Seabird Conservation in New Zealand and 27 threatened seabirds identified for conservation interventions. To evaluate impact, we applied a recently developed seabird meta-population viability analysis model (seabird mPVA) that employs the most current population and adjustable demographic data to assess threatened seabird viability at a global scale under various management scenarios. This publicly available, web-based tool is intended to meet the needs of threatened seabird managers at the initial phase of conservation planning. We used the seabird mPVA to model population trends and potential seabird viability gains from conservation actions that include: bycatch mitigation, invasive species removal, and seabird translocation prescribed in the action plan for individual species. Our model’s ranking of New Zealand seabirds by current quasi-extinction vulnerability roughly correlated with the seabirds’ IUCN Red List status and New Zealand Threat Classification System. We found modeled conservation impact of proposed actions and assigned priority to be generally positively correlated, but variable in magnitude. If all prescribed conservations actions were implemented, our model predicted significant mitigation of quasi-extinction risk for nine species (Antipodean Albatross, Auckland Island Shag, Black-fronted Tern, Fairy Tern, Rough-faced Shag, Northern Royal Albatross, Pitt Island Shag, Stewart Island Shag, Yellow-eyed Penguin). This approach, and our model, can be adapted to other taxonomic groups to provide a consistent framing for the prioritization of species for conservation investment and predictions about the benefits of specific conservation actions for those species.

Integrating Genetics and Metapopulation Viability Analysis to Inform Translocation Efforts for the Last Northern Leopard Frog Population in Washington State, USA

Population genetic and population viability analyses are powerful instruments that can be used to evaluate the status o populations of conservation concern. However, these two methods are rarely integrated. To better understand the status of the last know Northern Leopard Frog (Lithobates pipiens) population in Washington state, USA, and investigate the potential for translocation efforts we analyzed 96 genetic samples from 2004 and 294 genetic samples from 2014 by using seven microsatellite loci and integrate population genetic data with population viability models. Partitioning of genetic diversity indicated the presence of thre subpopulations in the area, aligning with Washington Department of Fish and Wildlife subunit designation within the watershed. I both years, heterozygosity and average number of alleles per locus were low for all subpopulations (0.20–0.36 and 1.86–2.50, respectively) Point estimates of gene flow out of two of the three subpopulations decreased from 2004 to 2014 based on G″ST (a measure of geneti differentiation) and migration estimates from BayesAss. Summed effective population size for the entire area by using tempora estimates was estimated to be small, with large amounts of uncertainty (sum of 98.4 individuals, 95% confidence interval: 15.6–infinit individuals). Population viability models using genetic estimates of number of adults and migration rates suggest that adults may be th optimal life history stage for successful direct translocation; however, because only metamorphs can be routinely collected, translocatio with head-starting was modeled and active management strategies may be necessary to establish new populations.

A Statistical Forecasting Approach to Metapopulation Viability Analysis

Conservation efforts are aided by reliable forecasts of extinction risk, under future environmental conditions and management actions. We conducted a statistical metapopulation viability analysis for the federally threatened Chiricahua leopard frog, propagating relevant sources of uncertainty. Our results suggested that without management intervention, extinction risk could be as high as 37% by year 2066. However, pond restoration reduced the upper limit on extinction risk to as low as 2%. Our approach allows management decisions to be made with a more complete understanding of the uncertainty around the intended effect of each management decision. These photographs illustrate the article “A statistical forecasting approach to metapopulation viability analysis” by Paige E. Howell, Blake R. Hossack, Erin Muths, Brent H. Sigafus, Ann Chenevert-Steffler, and Richard B. Chandler published in Ecological Applications. https://doi.org/10.1002/eap.2038

A statistical forecasting approach to metapopulation viability analysis.

Conservation of at-risk species is aided by reliable forecasts of the consequences of environmental change and management actions on population viability. Forecasts from conventional population viability analysis (PVA) are made using a two-step procedure in which parameters are estimated, or elicited from expert opinion, and then plugged into a stochastic population model without accounting for parameter uncertainty. Recently developed statistical PVAs differ because forecasts are made conditional on models fitted to empirical data. The statistical forecasting approach allows for uncertainty about parameters, but it has rarely been applied in metapopulation contexts where spatially explicit inference is needed about colonization and extinction dynamics and other forms of stochasticity that influence metapopulation viability. We conducted a statistical metapopulation viability analysis (MPVA) using 11yr of data on the federally threatened Chiricahua leopard frog (Lithobates chiricahuensis) to forecast responses to landscape heterogeneity, drought, environmental stochasticity, and management. We evaluated several future environmental scenarios and pond restoration options designed to reduce extinction risk. Forecasts over a 50-yr time horizon indicated that metapopulation extinction risk was <4% for all scenarios, but uncertainty was high. Without pond restoration, extinction risk is forecasted to be 3.9% (95% CI 0-37%) by year 2066. Restoring six ponds by increasing their hydroperiod reduced extinction risk to <1% and greatly reduced uncertainty (95% CI 0-2%). Our results suggest that managers can mitigate the impacts of drought and environmental stochasticity on metapopulation viability by maintaining ponds that hold water throughout the year and keeping them free of invasive predators. Our study illustrates the utility of the spatially explicit statistical forecasting approach to MPVA in conservation planning efforts.

Effects of climate change and anthropogenic modification on a disturbance‐dependent species in a large riverine system

AbstractHumans have altered nearly every natural disturbance regime on the planet through climate and land‐use change, and in many instances, these processes may have interacting effects. For example, projected shifts in temperature and precipitation will likely influence disturbance regimes already affected by anthropogenic fire suppression or river impoundments. Understanding how disturbance‐dependent species respond to complex and interacting environmental changes is important for conservation efforts. Using field‐based demographic and movement rates, we conducted a metapopulation viability analysis for piping plovers (Charadrius melodus), a threatened disturbance‐dependent species, along the Missouri and Platte rivers in the Great Plains of North America. Our aim was to better understand current and projected future metapopulation dynamics given that natural disturbances (flooding or high‐flow events) have been greatly reduced by river impoundments and that climate change could further alter the disturbance regime. Although metapopulation abundance has been substantially reduced under the current suppressed disturbance regime (high‐flow return interval ~ 20 yr), it could grow if the frequency of high‐flow events increases as predicted under likely climate change scenarios. We found that a four‐year return interval would maximize metapopulation abundance, and all subpopulations in the metapopulation would act as sources at a return interval of 15 yr or less. Regardless of disturbance frequency, the presence of even a small, stable source subpopulation buffered the metapopulation and sustained a low metapopulation extinction risk. Therefore, climate change could have positive effects in ecosystems where disturbances have been anthropogenically suppressed when climatic shifts move disturbance regimes toward more historical patterns. Furthermore, stable source populations, even if unintentionally maintained through anthropogenic activities, may be critical for the persistence of metapopulations of early‐successional species under both suppressed disturbance regimes and disturbance regimes where climate change has further altered disturbance frequency or scope.

Using Bayesian Population Viability Analysis to Define Relevant Conservation Objectives.

Adaptive management provides a useful framework for managing natural resources in the face of uncertainty. An important component of adaptive management is identifying clear, measurable conservation objectives that reflect the desired outcomes of stakeholders. A common objective is to have a sustainable population, or metapopulation, but it can be difficult to quantify a threshold above which such a population is likely to persist. We performed a Bayesian metapopulation viability analysis (BMPVA) using a dynamic occupancy model to quantify the characteristics of two wood frog (Lithobates sylvatica) metapopulations resulting in sustainable populations, and we demonstrate how the results could be used to define meaningful objectives that serve as the basis of adaptive management. We explored scenarios involving metapopulations with different numbers of patches (pools) using estimates of breeding occurrence and successful metamorphosis from two study areas to estimate the probability of quasi-extinction and calculate the proportion of vernal pools producing metamorphs. Our results suggest that ≥50 pools are required to ensure long-term persistence with approximately 16% of pools producing metamorphs in stable metapopulations. We demonstrate one way to incorporate the BMPVA results into a utility function that balances the trade-offs between ecological and financial objectives, which can be used in an adaptive management framework to make optimal, transparent decisions. Our approach provides a framework for using a standard method (i.e., PVA) and available information to inform a formal decision process to determine optimal and timely management policies.

Cost‐effective conservation of an endangered frog under uncertainty

How should managers choose among conservation options when resources are scarce and there is uncertainty regarding the effectiveness of actions? Well-developed tools exist for prioritizing areas for one-time and binary actions (e.g., protect vs. not protect), but methods for prioritizing incremental or ongoing actions (such as habitat creation and maintenance) remain uncommon. We devised an approach that combines metapopulation viability and cost-effectiveness analyses to select among alternative conservation actions while accounting for uncertainty. In our study, cost-effectiveness is the ratio between the benefit of an action and its economic cost, where benefit is the change in metapopulation viability. We applied the approach to the case of the endangered growling grass frog (Litoria raniformis), which is threatened by urban development. We extended a Bayesian model to predict metapopulation viability under 9 urbanization and management scenarios and incorporated the full probability distribution of possible outcomes for each scenario into the cost-effectiveness analysis. This allowed us to discern between cost-effective alternatives that were robust to uncertainty and those with a relatively high risk of failure. We found a relatively high risk of extinction following urbanization if the only action was reservation of core habitat; habitat creation actions performed better than enhancement actions; and cost-effectiveness ranking changed depending on the consideration of uncertainty. Our results suggest that creation and maintenance of wetlands dedicated to L.raniformis is the only cost-effective action likely to result in a sufficiently low risk of extinction. To our knowledge we are the first study to use Bayesian metapopulation viability analysis to explicitly incorporate parametric and demographic uncertainty into a cost-effective evaluation of conservation actions. The approach offers guidance to decision makers aiming to achieve cost-effective conservation under uncertainty.

Genetic estimation of dispersal in metapopulation viability analysis

For geographically closed populations, it has long been known that the dynamics of rare populations are affected by demographic stochasticity, and that a short string of ‘bad luck’ (of the random variable demographic outcomes in a finite population) can easily drive rare populations to extinction. The commonly taught approximation for calculating this extinction risk, PðextinctionÞ 1⁄4 ð b Þ0 (where d, b and N0 are the respective death rate, birth rate, and initial abundance), clearly shows how sensitive population fate can be to initial abundance (Gotelli, 2008). However, when populations are geographically connected to others, immigration can ‘rescue’ rare populations from becoming extinct, and the connectivity of multiple populations created by dispersal greatly bolsters the persistence probability of the overall population. As dispersal amongst fragmented habitats increases a population becomes panmictic; overall abundance is enhanced through connectivity and the impact of demographic stochasticity on extinction risk decreases. Conversely, if dispersal is completely impeded by the loss of connectivity among habitat patches, the dynamics in each local population will be more greatly affected by local abundance, birth and death (Clobert et al., 2001). Between the realms of zero and panmictic dispersal resides the concept of a metapopulation (Levins, 1969, 1970). Theoretical studies have demonstrated the positive nonlinear relationship between metapopulation viability and the rate of dispersal among the component sub-populations (Hanski, 1999). Thus, it is not surprising that Greenwald (2010) found metapopulation viability in ambystomatid salamanders to be affected by methodological approaches to estimating dispersal that produce disparate results. The genetically based approach to estimating contemporary (as opposed to historical) rates of dispersal in a metapopulation viability framework will nevertheless be of use to many. The unique viability issues that a rare or declining population faces often requires development of original population models that match the available data and knowledge. For future users of Greenwald’s approach, I suggest using a programming language to develop a population model that matches the situation (Caswell, 2001; Bolker, 2008). Use of canned software packages can produce biased predictions when the user is forced to make complex modeling assumptions about levels of density dependence, environmental stochasticity, probability density functions describing stochastic processes, mutation rates and more (Morris & Doak, 2002). Moreover, it is not universally true that population viability is insensitive to initial abundance (Greenwald, 2010). Because of demographic stochasticity, Allee effects, inbreeding depression and other factors, a small population’s risk of extinction can be highly sensitive to abundance (e.g. see the simple equation above). Thus, careful attention should be paid to both the actual and genetically effective levels of abundance that viability projections are initiated at. Nevertheless, the assumptions made in Greenwald’s (2010) models should not take away from the novel use of genetically based estimates of dispersal in a metapopulation viability analysis. In the past, many have used dispersal– distance functions to parameterize dispersal in population models. Underlying these functions is the biological assumption that a landscape is homogeneous; a single probability density function describes an individual’s random chance of moving a given distance, regardless of where it is coming from, where it is going to, and the habitat it must cross to get there (i.e. akin to the dispersion of gas molecules in a room). Dispersal–distance functions might adequately describe wind dispersal of seeds, movement of invertebrate larvae in oceans and other passive forms of dispersal. However, a single homogeneous function cannot capture the complex processes involved in the movement of a vagile animal from one location to another across a heterogeneous landscape that is reap with both costs and benefits to dispersal and philopatry. Greenwald’s (2010) use of genetic-assignment tests for estimating contemporary dispersal in and out of specific

Cautious optimism for applied conservation genetics and metapopulation viability analysis

Among conservation biologists there is little argument that habitat loss and fragmentation are the greatest threats to future biodiversity. We know from elementary population ecology that, if isolated, even large populations will ultimately be driven to extinction by demographic stochasticity, and that this will occur more rapidly for small populations in small fragments. Theory and observations also show that post-fragmentation species losses can occur slowly, sometimes requiring more than a century for the total ‘extinction debt’ to be realized (Tilman et al., 1994; Vellend et al., 2006). For long-lived animals, such as ambystomatid salamanders, isolated populations doomed to demographic irrelevance and ultimate extinction may persist for decades or longer (Greenwald, 2010). I think of the animals occupying these isolated habitats with little chance of long-term survival as ‘zombie’ populations. As imperfect as our population models are, they represent our best chance for understanding the threats to populations at risk and possibly recovering them from zombie status. Population and metapopulation viability analyses are valuable tools for illustrating, in an understandable way, the risk of extinctions, and for exploring probabilities of local and regional persistence under different scenarios (Morris & Doak, 2002; Marsh, 2008). I see the greatest value of these modeling exercises in their ability to help land managers to evaluate alternative management actions and appreciate their relative costs and likely benefits. As Greenwald (2010) shows, actions to promote connectivity can enhance population viability. Restoring connectivity to fragmented landscapes is often extremely costly (think wildlife overpasses), and avoiding fragmentation completely may be even more controversial (think not building the freeway at all). So, models evaluating the importance of habitat connectivity must be convincing to those people on the hook for making big decisions. The greatest barrier to constructing convincing models is obtaining parameter estimates in which we have confidence, which traditionally means laborand time-intensive mark–recapture studies. Fortunately, the recent work of Greenwald (2010) in addition to others indicates that molecular tools may be surprisingly robust to the challenge of more rapidly and painlessly estimating at least some demographic parameters needed for landscape-scale population modeling. As someone who has invested years in the field marking and recapturing animals, I am optimistic at the promise these methods potentially hold (Trenham et al., 2000; Trenham, Koenig & Shaffer, 2001). The ability of genetic assignment tests to accurately reveal residents and immigrants in samples could change the study of dispersal. My caution in getting too excited about the current abilities of these methods stems from my understanding of several issues that can substantially bias the results. The author addressed the issue of unsampled ‘ghost’ populations. This is a real issue for animals like ambystomatid salamanders where large fractions of the adult population commonly skip breeding and are completely undetectable, thus samples from a single year are unlikely to accurately represent the standing genetic variation present in a population. Despite these issues, one recent study is very encouraging. A detailed study with marked skinks, occupying and dispersing among patches of rocky habitat, showed that assignment tests usually recognized immigrants with high confidence. And further, using skink tissues collected over 3months, the assignment tests yielded estimates of interpatch dispersal rates essentially identical to those estimated over 7 years of mark–recapture efforts (Berry, Tocher & Sarre et al., 2004). At this point, I think there is still need for more cross validation of these methods with mark–recapture studies in other taxa and landscapes, especially if we are to use these data predicting metapopulation viability. If these methods produce robust predictions they have the potential to greatly assist conservation planners. For example, the California tiger salamander Ambystoma californiense is the species about which I know the most, and one whose management would benefit greatly from the types of genetic data and the coupled modeling approach explored

Metapopulation viability analysis for amphibians

Metapopulation viability analysis for amphibians

The Viability of Metapopulations: Individual Dispersal Behaviour Matters

Metapopulation models are frequently used for analysing species–landscape interactions and their effect on structure and dynamic of populations in fragmented landscapes. They especially support a better understanding of the viability of metapopulations. In such models, the processes determining metapopulation viability are often modelled in a simple way. Animals’ dispersal between habitat fragments is mostly taken into account by using a simple dispersal function that assumes the underlying process of dispersal to be random movement. Species-specific dispersal behaviour such as a systematic search for habitat patches is likely to influence the viability of a metapopulation. Using a model for metapopulation viability analysis, we investigate whether such specific dispersal behaviour affects the predictions of ranking orders among alternative landscape configurations rated regarding their ability to carry viable metapopulations. To incorporate dispersal behaviour in the model, we use a submodel for the colonisation rates which allows different movement patterns to be considered (uncorrelated random walk, correlated random walk with various degrees of correlation, and loops). For each movement pattern, the landscape order is determined by comparing the resulting mean metapopulation lifetime Tm of different landscape configurations. Results show that landscape orders can change considerably between different movement patterns. We analyse whether and under what circumstances dispersal behaviour influences the ranking orders of landscapes. We find that the ‘competition between patches for migrants’ – i.e. the fact that dispersers immigrating into one patch are not longer available as colonisers for other patches – is an important factor driving the change in landscape ranks. The implications of our results for metapopulation modelling, planning and conservation are discussed.

Wild-captive metapopulation viability analysis

We developed an interactive management model for wild and captive populations of the ploughshare tortoise or angonoka, Geochelone yniphora. Interactive management is based on the translocation of individuals between wild and captive populations to simulate a metapopulation. Demographic parameters of one captive and two wild populations of this rare tortoise were used to conduct a metapopulation viability analysis (MVA). The effectiveness of the conservation strategy proposed for this species was then evaluated by modifying the probability of extinction and growth of the metapopulation over a fixed period of time. Several alternative scenarios of interactive management were then tested and ranked in terms of their effect on the viability of the metapopulation. The model predicted that catastrophic events such as bush fires would likely have a negative effect on the future of remaining wild populations. However, the model also predicted that the use of captive-born offspring to establish additional wild populations would decrease the risk of extinction of the metapopulation as a whole. We believe that, when supported by sound knowledge of the demographic parameters of a species, the use of MVA as part of an interactive management program can be an effective conservation tool that allows assessment of the probable response of both captive and wild populations to different management alternatives. One of the most interesting aspects of this interactive management approach is the link between in situ and ex situ conservation.

META-X: Generic Software for Metapopulation Viability Analysis

The major tools used to make population viability analyses (PVA) quantitative are stochastic models of population dynamics. Since a specially tailored model cannot be developed for every threatened population, generic models have been designed which can be parameterised and analysed by non-modellers. These generic models compromise on detail so that they can be used for a wide range of species. However, generic models have been criticised because they can be employed without the user being fully aware of the concepts, methods, potentials, and limitations of PVA. Here, we present the conception of a new generic software package for metapopulation viability analysis, META-X. This conception is based on three elements, which take into account the criticism of earlier generic PVA models: (1) comparative simulation experiments; (2) an occupancy-type model structure which ignores details of local population dynamics (these details are integrated in external submodels); and (3) a unifying currency to quantify persistence and viability, the ‘intrinsic mean time to extinction’. The rationale behind these three elements is explained and demonstrated by exemplary applications of META-X in the three fields for which META-X has been designed: teaching, risk assessment in the field, and planning. The conception of META-X is based on the notion that PVA is a tool to deal with rather than to overcome uncertainty. The purpose of PVA is to produce relative, not absolute, assessments of extinction risk which support, but do not supplant, management decisions.

RANKING METAPOPULATION EXTINCTION RISK: FROM PATTERNS IN DATA TO CONSERVATION MANAGEMENT DECISIONS

Viability analyses of large metapopulations are often hampered by difficulties in the parameter estimation. This leads to high uncertainty in parameter values and model outputs and complicates the formulation of clear recommendations for conservation management. We present a comprehensive procedure that is able to process spatiotemporal patterns of metapopulation occupancy to rank management scenarios. The first step of the procedure involves the formulation of the stochastic metapopulation model and the estimation of parameter values with a Bayesian approach, using a Markov chain Monte Carlo algorithm. In the second step, the model is used to predict the effects of different management actions, taking into account the uncertainty in the parameter estimates. Finally, in the third step, decision analysis is used to evaluate and aggregate the results of the previous step into a simple rank order of management scenarios. The procedure was applied to a metapopulation of the Glanville fritillary, Melitaea cinxia. Although the amount of available occupancy data was considerable, the uncertainty in the estimated model parameter values was so large that a precise estimate of the extinction risk of the metapopulation could not be made. However, the procedure was able to produce a rank order of management scenarios that was extraordinarily robust to the uncertainty. Application of the procedure to two other case studies revealed that, even though robust rankings cannot always be obtained, the results of the procedure are helpful in assessing the degree of uncertainty in the ranking and pointing to those factors most responsible for the lack of robustness. The results of this paper demonstrate very clearly, by way of example, both the limitations and the possibilities of model-based metapopulation viability analysis.

Viability of piping plover Charadrius melodus metapopulations

The metapopulation viability analysis package, vortex, was used to examine viability and recovery objectives for piping plovers Charadrius melodus, an endangered shorebird that breeds in three distinct regions of North America. Baseline models indicate that while Atlantic Coast populations, under current management practices, are at little risk of near-term extinction, Great Plains and Great Lakes populations require 36% higher mean fecundity for a significant probability of persisting for the next 100 years. Metapopulation structure (i.e. the delineation of populations within the metapopulation) and interpopulation dispersal rates had varying effects on model results; however, spatially-structured metapopulations exhibited lower viability than that reported for single-population models. The models were most sensitive to variation in survivorship; hence, additional mortality data will improve their accuracy. With this information, such models become useful tools in identifying successful management objectives; and sensitivity analyses, even in the absence of some data, may indicate which options are likely to be most effective. Metapopulation viability models are best suited for developing conservation strategies for achieving recovery objectives based on maintaining an externally derived, target population size and structure.

Sex-biased density-dependent migration in a metapopulation of the butterfly Proclossiana eunomia

Current metapopulation models assume that migration rate remains constant from one generation to the other, leading to a constant population foundation rate. In the butterfly Proclossiana eunomia, the mating behaviour is a main factor affecting individual migration. In a field study, male harrassments induced female emigration at high male density. Simulation, ed away in search of mates at low female density. Simulations of male-female movements based on behavioural data from the field revealed that changes in mate density will induce sex-biased emigration. assessment of migration within a metapopulation in the field during 2 years supported these predictions. Such bias in migration has been reported earlier in other butterfly species with a similar mating system. Consequences of sex-biased emigration on metapopulation dynamics may be spasms in population foundation as these occur only when density oversteps a certain threshold. Patterns of colonization in a region where P. eunomia did not occur naturally correspond to this prediction. Variability in the rates of emigration and population foundation between generations may affect metapopulation viability analysis by current models. (C) Elsevier, Paris.

Metapopulation viability analysis of the greater glider Petauroides volans in a wood production area

Successful forest wildlife management is dependent on information that estimates long-term viability of populations in response to different management practices. In this paper we couple information captured in a GIS database, relationships between habitat attributes and habitat quality, and the dynamics of those habitat attributes, to assess the long-term metapopulation viability of a forest-dependent arboreal marsupial, greater glider Petauroides volans Kerr, in the Ada Forest Block in south-eastern Australia. Estimates of the size and spatial distribution of populations in remnant patches of old-growth forest, and the dynamics of key elements of that habitat, are input to ALEX, a computer package for population viability analysis. The model is used to predict the probability of persistence of P. volans within the Ada Forest Block concentrating on scenarios that assess the value of different old-growth patches and the impact of wildfire. We conclude that small patches of old-growth forest (<20 ha) make almost no contribution to the persistence of the species. In addition, control of wildfire will significantly increase the viability of the species in the remaining habitat.