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The viability of populations can be quantified with several measures, such as the probability of extinction, the mean time to extinction, or the population size. While conservation management decisions can be based on these measures, it has not yet been explored systematically if different viability measures rank species and scenarios similarly and if one viability measure can be converted into another to compare studies. To address this challenge, we conducted a quantitative comparison of eight viability measures based on the simulated population dynamics of more than 4500 virtual species. We compared (a) the ranking of scenarios based on different viability measures, (b) assessed direct correlations between the measures, and (c) explored if parameters in the simulation models can alter the relationship between pairs of viability measures. We found that viability measures ranked species similarly. Despite this, direct correlations between the different measures were often weak and could not be generalized. This can be explained by the loss of information due to the aggregation of raw data into a single number, the effect of model parameters on the relationship between viability measures, and because distributions, such as the probability of extinction over time, cannot be ranked objectively. Similar scenario rankings by different viability measures show that the choice of the viability metric does in many cases not alter which population is regarded more viable or which management option is the best. However, the more two scenarios or populations differ, the more likely it becomes that different measures produce different rankings. We thus recommend that PVA studies publish raw simulation data, which not only describes all risks and opportunities to the reader but also facilitates meta‐analyses of PVA studies. Population viability was ranked similarly in a quantitative comparison of eight measures of population viability derived from simulated population dynamics of more than 4500 virtual species. However, direct correlations between measures were weak and could not be generalized. We thus recommend that population‐viability analyses publish raw simulation data to support robust comparisons of population viabilities.

The decline in amphibian populations is one of the starkest examples of the biodiversity crisis. For stream breeding amphibians, alterations to natural flow regimes by dams, water diversions, and climate change have been implicated in declines and extirpations. Identifying drivers of amphibian declines requires long time series of abundance data because amphibian populations can exhibit high natural variability. Multiple population viability analysis (MPVA) models integrate abundance data and share information from different populations to estimate how environmental factors influence population growth. Flow alteration has been linked to declines and extirpations in the Foothill Yellow‐legged Frog (Rana boylii), a stream breeding amphibian native to California and Oregon. To date, no study has jointly analyzed abundance data from populations throughout the range of R. boylii in an MPVA model. We compiled time series of egg mass counts (an index of adult female abundance) from R. boylii populations in 36 focal streams and fit an MPVA model to quantify how streamflow metrics, stream temperature, and surrounding land cover affect population growth. We found population growth was positively related to stream temperature and was higher in the years following a wet year with high total annual streamflow. Density dependence was weakest (i.e., carrying capacity was highest) for streams with high seasonality of streamflow and intermediate rates of change in streamflow during spring. Our results highlight how altered streamflow can further increase the risk of decline for R. boylii populations. Managing stream conditions to better match natural flow and thermal regimes would benefit the conservation of R. boylii populations.

Using the VORTEX v. 10. 5.0.0, population viability analysis (PVA) was performed for Yangtze finless porpoise (YFP, Neophocaena asiaeorientalis) in the highest density section between Hukou and Meilong section (HMS) of the Yangtze River. Baseline model showed that this population was in a relatively vulnerability state; the deterministic growth rate (Det-r) was −0.0230; the stochastic growth rate (Stoch-r) was −0.0385; the probability of extinction (PE) was 0.5690; the mean population size of extant populations (N-extant) was 22; the genetic diversity (GD) was 0.7698. Under the general protection model, the Det-r was 0.0015, and the Stoch-r was −0.0092; Under the medium protection model, the Det-r was 0.0219, and the Stoch-r was 0.0144; Under the optimal protection model, the Det-r was 0.0383, and the Stoch-r was 0.0357. Sensitivity analysis found that adult females breeding rate, sex ratio at birth, and mortality rate of juvenile YFP were sensitive to maintaining population stability. The PVA showed that the conservation of YFP population in HMS depends on: neutralization of all threats affecting YFP population in the HMS; maintenance and, whenever possible, enhancement of the functional connectivity of the waterbody, increasing the food resources of YFP and reducing the risk of injury to YFP caused by human.

The decline and extinction of native plant species is a global conservation crisis, and there is a need for rapid prioritization of our conservation efforts. In the USA, the two main systems used to identify at-risk species, Threatened and Endangered (T&E) status and conservation status ranks by NatureServe (G- and S-ranks), are categorical and typically assessed with large-scale criteria, thus are not ideal to aid practitioners in developing priorities at smaller scales. Our goal was to develop a continuous risk assignment for plant species using monitoring data collected at a smaller scale so that limited conservation resources can be better prioritized among at-risk species. To do this, we modified a count-based population viability analysis to produce two regional, species-level viability metrics: a regional growth rate and a regional 50-y probability of extinction. Our validation exercises confirmed these metrics could reliability place 24 rare forb species along a continuous scale of viability. We identified nine species (37.5% of those analyzed) in need of conservation effort in northern Illinois. The challenges we faced developing these metrics and our solutions are discussed more generally to improve rare plant species monitoring practices. Overall, this method is an innovative expansion of the use of population size monitoring data to inform conservation beyond the population.

Population viability analysis (PVA) has been an important tool for evaluating species extinction risk and alternative management strategies, but there is little information on how well PVA predicts population trajectories following changes in management actions. We tested previously published predictions from a stage-structured PVA of Peregrine Falcons ( Falco peregrinus ) in California, USA (Wootton and Bell 1992), against population trajectories following the 1992 termination of statewide, active management (population supplementation of captive-reared young). In the absence of extensive post-management monitoring, we developed surrogate estimates of breeding population size by calibrating several citizen science data sets (Christmas Bird Count, CBC; and North American Breeding Bird Survey, BBS) to intensive population surveys taken primarily during the active management period. CBC abundance data standardized by observer effort exhibited a strong relationship to intensive survey data ( r 2 = 0.971), indicated significantly reduced annual population growth rates after management was terminated (λ = 0.023 ± 0.013 SE) than when supplementation occurred (λ = 0.089 ± 0.023 SE), and demonstrated an increasing population as predicted by the PVA. The population trajectory fell within the 95% CI of stochastic simulations of the model either with or without density dependence and assuming either measurement error or process error, but models with process error were most strongly supported by the data. These results indicate that PVA can quantitatively anticipate population trajectories following changes in management, highlight the importance of post-management monitoring of species of concern, and illustrate the benefits of using management changes as large-scale experiments to more rigorously test PVA.

Biometricians have made great strides in the generation of reliable estimates of demographic rates and their uncertainties from imperfect field data, but these estimates are rarely used to produce detailed predictions of the dynamics or future viability of at-risk populations. Conversely, population viability analysis (PVA) modelers have increased the sophistication and complexity of their approaches, but most do not adequately address parameter and model uncertainties in viability assessments or include important ecological drivers. Merging the advances in these two fields could enable more defensible predictions of extinction risk and better evaluations of management options, but only if clear and interpretable PVA results can be distilled from these complex analyses and outputs. Here, we provide guidance on how to successfully conduct such a combined analysis, using the example of the endangered island fox (Urocyon littoralis), endemic to the Channel Islands of California, USA. This more rigorous demographic PVA was built by forming a close marriage between the statistical models used to estimate parameters from raw data and the details of the subsequent PVA simulation models. In particular, the use of mark—recapture analyses and other likelihood and information-theoretic methods allowed us to carefully incorporate parameter and model uncertainty, the effects of ecological drivers, density dependence, and other complexities into our PVA. Island fox populations show effects of density dependence, predation, and El Niño events, as well as substantial unexplained temporal variation in survival rates. Accounting not only for these sources of variability, but also for uncertainty in the models and parameters used to estimate their strengths, proved important in assessing fox viability with different starting population sizes and predation levels. While incorporating ecological drivers into PVA assessments can help to predict realistic dynamics, we also show that unexplained process variance has important effects even in our extremely well-studied system, and therefore must not be ignored in PVAs. Overall, the treatment of causal factors and uncertainties in parameter values and model structures need not result in unwieldy models or highly complex predictions, and we emphasize that future PVAs can and should include these effects when suitable data are available to support their analysis.

Supplementation programs based on captive breeding and rearing are increasingly being used in recovery planning for endangered or threatened salmonid populations. However, it is largely unknown if increased abundance from these programs can offset deleterious genetic changes from the captive environment and lead to viable populations in the wild. In this paper, we developed a life-history-based population viability analysis that explicitly incorporates declines in fitness attributable to captive breeding and rearing using the breeder's equation as part of the projection model. Using endangered inner Bay of Fundy Atlantic salmon as a case study (a population assemblage for which supplementation is a major component for the recovery plan), we evaluated how genetic changes influence abundance trajectories and extinction risk. Based on the population projections, continual supplementation enables the population to build from critically low abundance levels, even under high rates of fitness loss. However, beyond 4-6 generations, loss of fitness (>15%%) outweighs any increase in abundance and causes the population projection to start to decline. For the majority of the scenarios, abundances were predicted to increase and remain in excess of the current population size for 10 to upward of 30 years, albeit at progressively lower population-level fitness as compared to current values. Although the captive breeding and rearing program does prevent extinction in the short term in this case study, associated fitness costs limit the population's overall probability of recovery, as well as increase the length of time to recovery. Under the assumption of interbreeding between wild and captive-reared individuals, declines greater than 10%% in relative fitness at a population level are sufficient to counter abundance increases resulting from supplementation. Although extinction risk over the short term can be reduced by increasing the proportion of the population that is reared in captivity, this comes at a cost to the probability of recovery for the population over the longer term, particularly as environmental conditions change. Generalizing from this case study, the useful duration of supplementation programs may be limited to short-term population increase (i.e., to prevent extinction) and may not be a workable strategy for longer term recovery planning.

Establishing and maintaining protected areas (PAs) are key tools for biodiversity conservation. However, this approach is insufficient for many species, particularly those that are wide-ranging and sparse. The cheetah Acinonyx jubatus exemplifies such a species and faces extreme challenges to its survival. Here, we show that the global population is estimated at ∼7,100 individuals and confined to 9% of its historical distributional range. However, the majority of current range (77%) occurs outside of PAs, where the species faces multiple threats. Scenario modeling shows that, where growth rates are suppressed outside PAs, extinction rates increase rapidly as the proportion of population protected declines. Sensitivity analysis shows that growth rates within PAs have to be high if they are to compensate for declines outside. Susceptibility of cheetah to rapid decline is evidenced by recent rapid contraction in range, supporting an uplisting of the International Union for the Conservation of Nature (IUCN) Red List threat assessment to endangered. Our results are applicable to other protection-reliant species, which may be subject to systematic underestimation of threat when there is insufficient information outside PAs. Ultimately, conserving many of these species necessitates a paradigm shift in conservation toward a holistic approach that incentivizes protection and promotes sustainable human–wildlife coexistence across large multiple-use landscapes.

Extinction risk is elevated in small, isolated populations due to demographic and genetic interactions. Therefore, it is critical to model these processes realistically in population viability analyses (PVA) to inform local management and contribute to a greater understanding of mechanisms within the extinction vortex. We conducted PVA’s for two small mountain lion populations isolated by urbanization in southern California to predict population growth, extinction probability, and loss of genetic diversity with empirical data. Specifically, we (1) provide the first PVA for isolated mountain lions in the Santa Ana Mountains (SAM) that considers both demographic and genetic risk factors and (2) test the hypothesis that variation in abundance and mortality between the SAM and Santa Monica Mountains (SMM) result in differences in population growth, loss of heterozygosity, and extinction probability. Our models predicted 16–21% probability of local extinction in the SAM due purely to demographic processes over 50 yr with current low levels or no immigration. Our models also predicted that genetic diversity will further erode in the SAM such that concern regarding inbreeding depression is warranted unless gene flow is increased, and that if inbreeding depression occurs, rapid local extinction will be highly likely. Dynamics of the two populations were broadly similar, but they also exhibited differences driven by larger population size and higher mortality in the SAM. Density-independent scenarios predicted a rapidly increasing population in the SMM, whereas growth potential did not differ from a stable trend in the SAM. Demographic extinction probability and loss of heterozygosity were greater in the SMM for density-dependent scenarios without immigration. However, higher levels of immigration had stronger, positive influences on both demographic viability and retention of genetic diversity in the SMM driven by lower abundance and higher adult survival. Our results elucidate demographic and genetic threats to small populations within the extinction vortex, and how these vary relative to demographic structure. Importantly, simulating seemingly attainable increases in connectivity was sufficient to greatly reduce extinction probability. Our work highlights that conservation of large carnivores is achievable within urbanized landscapes, but requires land protection, connectivity, and strategies to promote coexistence with humans.

1. Predicting population responses to environmental conditions or management scenarios is a fundamental challenge for conservation. Proper consideration of demographic, environmental and parameter uncertainties is essential for projecting population trends and optimal conservation strategies. 2. We developed a coupled integrated population model-Bayesian population viability analysis to assess the (1) impact of demographic rates (survival, fecundity, immigration) on past population dynamics; (2) population viability 10 years into the future; and (3) efficacy of possible management strategies for the federally endangered Great Lakes piping plover Charadrius meiodus population. 3. Our model synthesizes long-term population survey, nest monitoring and mark-resight data, while accounting for multiple sources of uncertainty. We incorporated latent abundance of eastern North American merlins Falco columbarius, a primary predator of adult plovers, as a covariate on adult survival via a parallel state-space model, accounting for the influence of an imperfectly observed process (i.e. predation pressure) on population viability. 4. Mean plover abundance increased from 18 pairs in 1993 to 75 pairs in 2016, but annual population growth (λ̄t) was projected to be 0.95 (95% Cl 0.72-1.12), suggesting a potential decline to 67 pairs within 10 years. Without accounting for an expanding merlin population, we would have concluded that the plover population was projected to increase (λ̄t = 1.02; 95% Cl 0.94-1.09) to 91 pairs by 2026. We compared four conservation scenarios: (1) no proposed management; (2) increased control of chick predators (e.g. Corvidae, Laridae, mammals); (3) increased merlin control; and (4) simultaneous chick predator and merlin control. Compared to the null scenario, chick predator control reduced quasi-extinction probability from 11.9% to 8.7%, merlin control more than halved (3.5%) the probability and simultaneous control reduced quasi-extinction probability to 2.6%. 5. Synthesis and applications. Piping plover recovery actions should consider systematic predator control, rather than current ad hoc protocols, especially given the predicted increase in regional merlin abundance. This approach of combining integrated population models with Bayesian population viability analysis to identify limiting components of the population cycle and evaluate alternative management strategies for conservation decision-making shows great utility for aiding recovery of threatened populations.