Transient population dynamics in periodic matrix models: methodology and effects of cyclic permutations

Many biological populations are subject to periodically changing environments such as years with or without fire, or rotation of crop types. The dynamics and management options for such populations are frequently investigated using periodic matrix models. However the analysis is usually limited to long-term results (asymptotic population growth rate and its sensitivity to perturbations of vital rates). In non-periodic matrix models it has been shown that long-term results may be misleading as populations are rarely in their stable structure. We therefore develop methods to analyze transient dynamics of periodic matrix models. In particular, we show how to calculate the effects of perturbations on population size within and at the end of environmental cycles. Using a model of a weed population subject to a crop rotation, we show that different cyclic permutations produce different patterns of sensitivity of population size and different population sizes. By examining how the starting environment interacts with the initial conditions, we explain how different patterns arise. Such understanding is critical to developing effective management and monitoring strategies for populations subject to periodically recurring environments.     

Reliability of Conservation Actions Based on Elasticity Analysis of Matrix Models

Abstract: Matrix population models have entered the mainstream of conservation biology, with analysis of proportional sensitivities (elasticity analysis) of demographic rates becoming important components of conservation decision making. We identify areas where management applications using elasticity analysis potentially conflict with the mathematical basis of the technique, and we use a hypothetical example and three real data sets (Prairie Chicken [   Tympanuchus cupido ], desert tortoise [ Gopherus agassizii ], and killer whale [ Orcinus orca ]) to evaluate the extent to which conservation recommendations based on elasticities might be misleading. First, changes in one demographic rate can change the qualitative ranking of the elasticity values calculated from a population matrix, a result that dampens enthusiasm for ranking conservation actions based solely on which rates have the highest elasticity values. Second, although elasticities often provide accurate predictions of future changes in population growth rate under management perturbations that are large or that affect more than one rate concurrently, concordance frequently fails when different rates vary by different amounts. In particular, when vital rates change to their high or low values observed in nature, predictions of future growth rate based on elasticities of a mean matrix can be misleading, even predicting population increase when the population growth rate actually declines following a perturbation. Elasticity measures will continue to be useful tools for applied ecologists, but they should be interpreted with considerable care. We suggest that studies using analytical elasticity analysis explicitly consider the range of variation possible for different rates and that simulation methods are a useful tool to this end.     

Effect of stage-specific vital rates on population growth rates and effective population sizes in an endangered iteroparous plant

Effective population size (N(e)) determines the strength of genetic drift and can influence the level of genetic diversity a population can maintain. Assessing how changes in demographic rates associated with environmental variables and management actions affect N(e) thus can be crucial to the conservation of endangered species. Calculation of N(e) through demographic models makes it possible to use elasticity analyses to study this issue. The elasticity of N(e) to a given vital rate is the proportional change in N(e) associated with a proportional increase in that vital rate. In addition, demographic models can be used to study N(e) and population growth rate (λ) simultaneously. Simultaneous examination is important because some vital rates differ diametrically in their associations with λ and N(e). For example, in some cases increasing these vital rates increases λ and decreases N(e). We used elasticity analysis to study the effect of stage-specific survival and flowering rates on N(e), annual effective population size (N(a)), and λ in seven populations of the endangered plant Austrian dragonhead (Dracocephalum austriacum). In populations with λ ≥ 1, the elasticities of N(e) and N(a) were similar to those of λ. Survival rates of adults were associated with greater elasticities than survival rates of juveniles, flowering rates, or fecundity. In populations with λ < 1, N(e) and N(a) exhibited greater elasticities to juvenile than to adult vital rates. These patterns are similar to those observed in other species with similar life histories. We did not observe contrasting effects of any vital rate on λ and N(e); thus, management actions that increase the λ of populations of Austrian dragonhead will not increase genetic drift. Our results show that elasticity analyses of N(e) and N(a) can complement elasticity analysis of λ. Moreover, such analyses do not require more data than standard matrix models of population dynamics.     

Longevity can buffer plant and animal populations against changing climatic variability

Both means and year-to-year variances of climate variables such as temperature and precipitation are predicted to change. However, the potential impact of changing climatic variability on the fate of populations has been largely unexamined. We analyzed multiyear demographic data for 36 plant and animal species with a broad range of life histories and types of environment to ask how sensitive their long-term stochastic population growth rates are likely to be to changes in the means and standard deviations of vital rates (survival, reproduction, growth) in response to changing climate. We quantified responsiveness using elasticities of the long-term population growth rate predicted by stochastic projection matrix models. Short-lived species (insects and annual plants and algae) are predicted to be more strongly (and negatively) affected by increasing vital rate variability relative to longer-lived species (perennial plants, birds, ungulates). Taxonomic affiliation has little power to explain sensitivity to increasing variability once longevity has been taken into account. Our results highlight the potential vulnerability of short-lived species to an increasingly variable climate, but also suggest that problems associated with short-lived undesirable species (agricultural pests, disease vectors, invasive weedy plants) may be exacerbated in regions where climate variability decreases.     

Hierarchical demographic approaches for assessing invasion dynamics of non-indigenous species: An example using northern snakehead (Channa argus)

Models of species’ demographic features are commonly used to understand population dynamics and inform management tactics. Hierarchical demographic models are ideal for the assessment of non-indigenous species because our knowledge of non-indigenous populations is usually limited, data on demographic traits often come from a species’ native range, these traits vary among populations, and traits are likely to vary considerably over time as species adapt to new environments. Hierarchical models readily incorporate this spatiotemporal variation in species’ demographic traits by representing demographic parameters as multi-level hierarchies. As is done for traditional non-hierarchical matrix models, sensitivity and elasticity analyses are used to evaluate the contributions of different life stages and parameters to estimates of population growth rate. We applied a hierarchical model to northern snakehead (Channa argus), a fish currently invading the eastern United States. We used a Monte Carlo approach to simulate uncertainties in the sensitivity and elasticity analyses and to project future population persistence under selected management tactics. We gathered key biological information on northern snakehead natural mortality, maturity and recruitment in its native Asian environment. We compared the model performance with and without hierarchy of parameters. Our results suggest that ignoring the hierarchy of parameters in demographic models may result in poor estimates of population size and growth and may lead to erroneous management advice. In our case, the hierarchy used multi-level distributions to simulate the heterogeneity of demographic parameters across different locations or situations. The probability that the northern snakehead population will increase and harm the native fauna is considerable. Our elasticity and prognostic analyses showed that intensive control efforts immediately prior to spawning and/or juvenile-dispersal periods would be more effective (and probably require less effort) than year-round control efforts. Our study demonstrates the importance of considering the hierarchy of parameters in estimating population growth rate and evaluating different management strategies for non-indigenous invasive species.     

Testing sustainability by prospective and retrospective demographic analyses: evaluation for palm leaf harvest.

Harvesting nontimber forest products (NTFPs) is a major economic activity in tropical forests. As many NTFPs are overexploited, sustainability analyses are required to set harvest guidelines. Here we introduce and apply a new approach to evaluating sustainability, which combines prospective (elasticity) and retrospective (Life Table Response Experiments [LTRE]) demographic analyses of matrix population models. We relate the elasticity of vital rates (representing their importance for population growth rate, lamda) to their contribution to harvest-induced change in lamda ("LTRE contribution"). When high-elasticity vital rates have a low LTRE contribution, exploitation is potentially sustainable as negative effects for population growth are buffered. If the reverse is found, there is little scope for sustainability because crucial vital rates are affected. Our approach is less sensitive to chance fluctuations than the commonly used sustainability criterion of lamda = 1.0, as it does not depend on the absolute value of lamda. We applied this analysis to Geonoma deversa, a clustered forest understory palm. We studied three experimentally defoliated and control populations in a Bolivian rainforest during two years. Cutting all leaves of large ramets did not change mortality but strongly affected growth and reproduction. In spite of severe changes in some vital rates, population growth rate was not significantly reduced after defoliation. A literature review revealed that six other understory palms species responded very similarly to defoliation. The combination of LTRE contributions and elasticity analyses showed that low-elasticity vital rates were mainly responsible for the defoliation-induced change in lamda for Geonoma deversa. For two other understory palms (Astrocaryum mexicanum and Chamaedorea radicalis) new demographic analyses yielded very similar results. For Geonoma, the LTRE contribution-elasticity relation strongly changed when we mimicked harvest damage. Adding 5% mortality to defoliated palms caused stronger change in lamda, mainly due to changes in a high-elasticity vital rate (survival). Therefore, harvest practices that involve stem killing are clearly unsustainable. Our results show that commercial leaf cutting in Geonoma deversa is potentially sustainable, and that this is likely the case for understory palms in general. Our approach to evaluating harvest sustainability can be applied to other NTFPs.     

The importance of space, time, and stochasticity to the demography and management of Alliaria petiolata

As population modeling is increasingly called upon to guide policy and management, it is important that we understand not only the central tendencies of our study systems, but the consequences of their variation in space and time as well. The invasive plant Alliaria petiolata (garlic mustard) is actively managed in the United States and is the focus of a developing biological control program. Two weevils (Coleoptera: Curculionidae: Ceutorhynchus) that reduce fecundity (C. alliariae) and rosette survival plus fecundity (C. scrobicollis) are under consideration for release pending host specificity testing. We used a demographic modeling approach to (1) quantify variability in A. petiolata growth and vital rates and (2) assess the potential for single- or multiple-agent biocontrol to suppress growth of 12 A. petiolata populations in Illinois and Michigan studied over three plant generations. We used perturbation analyses and simulation models with stochastic environments to estimate stochastic growth rates (lambda(S)) and predict the probability of successful management using either a single biocontrol agent or two agent species together. Not all populations exhibited invasive dynamics. Estimates of lambda(S) ranged from 0.78 to 2.21 across sites, while annual, deterministic growth (lambda) varied up to sevenfold within individual sites. Given our knowledge of the biocontrol agents, this analysis suggests that C. scrobicollis alone may control A. petiolata at up to 63% of our study sites where lambda >1, with the combination of both agents predicted to succeed at 88% of sites. Across sites and years, the elasticity rankings were dependent on lambda. Reductions of rosette survival, fecundity, or germination of new seeds are predicted to cause the greatest reduction of lambda in growing populations. In declining populations, transitions affecting seed bank survival have the greatest effect on lambda. This contrasts with past analyses that varied parameters individually in an otherwise constant matrix, which may yield unrealistic predictions by decoupling natural parameter covariances. Overall, comparisons of stochastic and deterministic growth rates illustrate how analyses of individual populations or years could misguide management or fail to characterize complex traits such as invasiveness that emerge as attributes of populations rather than species.     

Conserving Slow-Growing, Long-Lived Tree Species: Input from the Demography of a Rare Understory Conifer, Taxus floridana

Abstract:  Although land preservation and promotion of successful regeneration are important conservation actions, their ability to increase population growth rates of slow-growing, long-lived trees is limited. We investigated the demography of Taxus floridana Nutt., a rare understory conifer, in three populations in different ravine forests spanning its entire geographic range along the Apalachicola River Bluffs in northern Florida (U.S.A.). We examined spatial and temporal patterns in demographic parameters and projected population growth rates by using four years of data on the recruitment and survival of seedlings and established stems, and on diameter growth from cross-sections of dead stems. All populations experienced a roughly 10-fold increase in seedling recruitment in 1996 compared with other years. The fates of seedlings and stems between 8 and 16 mm differed among populations. The fates of stems in two other size classes (the 2- to 4-mm class and the 4- to 8-mm class) differed among both populations and years. Individual stems in all populations exhibited similarly slow growth rates. Stochastic matrix models projected declines in all populations. Stochastic matrix analysis revealed the high elasticity of a measure of stochastic population growth rate to perturbations in the stasis of large reproductive stems for all populations. Additional analyses also indicated that occasional episodes of high recruitment do not greatly affect population growth rates. Conservation efforts directed at long-lived, slow-growing rare plants like Taxus floridana should both protect established reproductive individuals and further enhance survival of individuals in other life-history stages, such as juveniles, that often do not appear to contribute greatly to population growth rates.     

Robustness in life history of the brown seaweed Ascophyllum nodosum (Fucales, Phaeophyceae) across large scales: effects of spatially and temporally induced variability on population growth

Understanding the demography and function of biotope-forming seaweed species is of great importance for the conservation of the target species itself, as well as its associated organisms. The brown seaweed Ascophyllum nodosum is fundamental for the functioning of coastal marine ecosystems in the North Atlantic. In this study, we use a data-based size-classified matrix model to investigate the temporal and spatial variability in demography, and the environment-specific stochastic sensitivity and elasticity, of two A. nodosum populations, one in western Sweden and one on the Isle of Man in the Irish Sea. A significant difference between the two populations was that the Swedish population had comparably low and more variable stochastic population growth rate (λ _s). This pattern was partly explained by the relatively high and varying mortality rates during extreme ice-years in Sweden, and by the lower survival of small individuals during all years. There were also fewer large individuals in Sweden due to lower transitions to the larger size-classes and higher probability of shrinkage. Sensitivities were analogous in the two populations, and showed a high selection pressure for increased individual growth. Elasticities were also similar, with the exception that survival of the smallest individuals (i.e., transition a _1,1), had a higher elasticity on the Isle of Man. Overall, the stochastic growth rate (λ _s) was most sensitive to proportional changes in loop- (i.e., survival within size-class) and, to some extent, growth-transitions in both study areas. These results show that structurally and demographically diverging A. nodosum populations may be similarly sensitive to changes in vital rates. This, in turn, indicates a plastic life history of A. nodosum that may cope with large environmental variability. The results further suggest that environmental change affecting the survival or growth of the larger, reproductive A. nodosum individuals could have severe and regional effects on the abundance and biomass of this species, with potential negative effects on the biodiversity of the associated communities.     

Invasion dynamics of the varnish clam (Nuttallia obscurata): a matrix demographic modeling approach

Marine invaders have become a significant threat to native biodiversity and ecosystem function. In this study, the invasion of the varnish clam (Nuttallia obscurata) in British Columbia, Canada, is investigated using a matrix modeling approach to identify the life history characteristics most crucial for population growth and to investigate population differences. Mark-recapture analyses and field collections from 2003 to 2004 were used to determine individual growth, survival rates, and fecundity for two sites. A multi-state matrix model was used to determine population growth rates and to conduct sensitivity and elasticity analyses. A life table response experiment was also used to determine what life history stage contributed most to observed differences in population growth rates. Population survey data were used in conjunction with the matrix model to determine plausible recruitment levels and to investigate recruitment scenarios. Both populations are currently declining but are likely sustainable because of the pulsed nature of large recruitment events. Survival of larger clams (>40 mm) is the most important for population growth based on elasticity and sensitivity analyses. Adult survival also had the largest influence on observed differences between site-specific population growth rates. The two populations studied differed in recruitment dynamics; one experiencing annual recruitment with higher post-settlement mortality and the other, episodic recruitment and lower post-settlement mortality. The most influential factor for the successful invasion of the varnish clam appears to be survival of the larger size classes. Therefore, any process that decreases adult survival (e.g., predation, commercial harvest) will have the greatest impact on population growth.     

Predicting [corrected] extinction risk in spite of predator-prey oscillations.

Most population viability analyses (PVA) assume that the effects of species interactions are subsumed by population-level parameters. We examine how robust five commonly used PVA models are to violations of this assumption. We develop a stochastic, stage-structured predator-prey model and simulate prey population vital rates and abundance. We then use simulated data to parameterize and estimate risk for three demographic models (static projection matrix, stochastic projection matrix, stochastic vital rate matrix) and two time series models (diffusion approximation [DA], corrupted diffusion approximation [CDA]). Model bias is measured as the absolute deviation between estimated and observed quasi-extinction risk. Our results highlight three generalities about the application of single-species models to multi-species conservation problems. First, our collective model results suggest that most single-species PVA models overestimate extinction risk when species interactions cause periodic variation in abundance. Second, the DA model produces the most (conservatively) biased risk forecasts. Finally, the CDA model is the most robust PVA to population cycles caused by species interactions. CDA models produce virtually unbiased and relatively precise risk estimates even when populations cycle strongly. High performance of simple time series models like the CDA owes to their ability to effectively partition stochastic and deterministic sources of variation in population abundance.     

Climate change threatens polar bear populations: a stochastic demographic analysis

The polar bear (Ursus maritimus) depends on sea ice for feeding, breeding, and movement. Significant reductions in Arctic sea ice are forecast to continue because of climate warming. We evaluated the impacts of climate change on polar bears in the southern Beaufort Sea by means of a demographic analysis, combining deterministic, stochastic, environment-dependent matrix population models with forecasts of future sea ice conditions from IPCC general circulation models (GCMs). The matrix population models classified individuals by age and breeding status; mothers and dependent cubs were treated as units. Parameter estimates were obtained from a capture-recapture study conducted from 2001 to 2006. Candidate statistical models allowed vital rates to vary with time and as functions of a sea ice covariate. Model averaging was used to produce the vital rate estimates, and a parametric bootstrap procedure was used to quantify model selection and parameter estimation uncertainty. Deterministic models projected population growth in years with more extensive ice coverage (2001-2003) and population decline in years with less ice coverage (2004-2005). LTRE (life table response experiment) analysis showed that the reduction in lambda in years with low sea ice was due primarily to reduced adult female survival, and secondarily to reduced breeding. A stochastic model with two environmental states, good and poor sea ice conditions, projected a declining stochastic growth rate, log lambdas, as the frequency of poor ice years increased. The observed frequency of poor ice years since 1979 would imply log lambdas approximately - 0.01, which agrees with available (albeit crude) observations of population size. The stochastic model was linked to a set of 10 GCMs compiled by the IPCC; the models were chosen for their ability to reproduce historical observations of sea ice and were forced with "business as usual" (A1B) greenhouse gas emissions. The resulting stochastic population projections showed drastic declines in the polar bear population by the end of the 21st century. These projections were instrumental in the decision to list the polar bear as a threatened species under the U.S. Endangered Species Act.     

Forecasting extinction risk with nonstationary matrix models.

Matrix population growth models are standard tools for forecasting population change and for managing rare species, but they are less useful for predicting extinction risk in the face of changing environmental conditions. Deterministic models provide point estimates of lambda, the finite rate of increase, as well as measures of matrix sensitivity and elasticity. Stationary matrix models can be used to estimate extinction risk in a variable environment, but they assume that the matrix elements are randomly sampled from a stationary (i.e., non-changing) distribution. Here we outline a method for using nonstationary matrix models to construct realistic forecasts of population fluctuation in changing environments. Our method requires three pieces of data: (1) field estimates of transition matrix elements, (2) experimental data on the demographic responses of populations to altered environmental conditions, and (3) forecasting data on environmental drivers. These three pieces of data are combined to generate a series of sequential transition matrices that emulate a pattern of long-term change in environmental drivers. Realistic estimates of population persistence and extinction risk can be derived from stochastic permutations of such a model. We illustrate the steps of this analysis with data from two populations of Sarracenia purpurea growing in northern New England. Sarracenia purpurea is a perennial carnivorous plant that is potentially at risk of local extinction because of increased nitrogen deposition. Long-term monitoring records or models of environmental change can be used to generate time series of driver variables under different scenarios of changing environments. Both manipulative and natural experiments can be used to construct a linking function that describes how matrix parameters change as a function of the environmental driver. This synthetic modeling approach provides quantitative estimates of extinction probability that have an explicit mechanistic basis.     

Invasion with stage-structured coupled map lattices: Application to the spread of scentless chamomile

Two fundamental aspects of invasion dynamics are population growth and population spread. These quantities have been subject of study in biological invasions and can be used to study management and control of organisms. In this paper we derive formulae to calculate wave speed and rates of spread for coupled map lattices. Coupled map lattice models are dynamical models where space and time are discrete. We also show how wave speed and rate of spread can be calculated for structured population coupled map lattices in deterministic, stochastic environments and heterogeneous landscapes. Coupled map lattices are simple mathematical models that can be easily linked to landscape data to study invading organisms control strategies.     

Demographic Viability of a Relict Population of the Critically Endangered Plant Borderea chouardii

Abstract:   In addition to human-caused changes in the environment, natural stochasticity may threaten species persistence, and its impact must be taken into account when priorities are established and management plans are designed. Borderea chouardii is a Tertiary relict at risk of extinction that occurs in only one location in the world, where the probability of human disturbance is low. Its persistence, therefore, is mainly linked to its response to natural threats such as stochasticity. Over 8 years I monitored up to 25% of this rupicolous small geophyte. The population had an unbalanced size structure and 90% failure in seed arrival at appropriate microhabitats, which suggests a problem with recruitment. I used matrix models to describe its population dynamics, conducted hand sowings, and performed stochastic simulations to investigate the effect of environmental stochasticity on population trend and viability. I modeled several scenarios to represent a variety of ecological situations, such as population reduction, episodic or persistent disease, and enhancement or decrease of recruitment. Population growth rate (λ) was never significantly different from unity over the study period. The risk of extinction was null over the next five centuries under current conditions. Increase of mortality and decrease of recruitment reduced stochastic population growth rate, but no factor except a persistent increase of 10% mortality resulted in extinction. These results are the consequence of the plant's extremely long life span (over 300 years) and low temporal variability of key vital rates. Even though hand sowing significantly increased the stochastic population growth rate, other approaches may be more important for the persistence of this species. The extremely slow capacity for recovery following disturbances renders habitat preservation essential. In addition, the founding of new populations would reduce the risk associated with habitat destruction.     

Using demography and movement behavior to predict range expansion of the southern sea otter

In addition to forecasting population growth, basic demographic data combined with movement data provide a means for predicting rates of range expansion. Quantitative models of range expansion have rarely been applied to large vertebrates, although such tools could be useful for restoration and management of many threatened but recovering populations. Using the southern sea otter (Enhydra lutris nereis) as a case study, we utilized integro-difference equations in combination with a stage-structured projection matrix that incorporated spatial variation in dispersal and demography to make forecasts of population recovery and range recolonization. In addition to these basic predictions, we emphasize how to make these modeling predictions useful in a management context through the inclusion of parameter uncertainty and sensitivity analysis. Our models resulted in hind-cast (1989-2003) predictions of net population growth and range expansion that closely matched observed patterns. We next made projections of future range expansion and population growth, incorporating uncertainty in all model parameters, and explored the sensitivity of model predictions to variation in spatially explicit survival and dispersal rates. The predicted rate of southward range expansion (median = 5.2 km/yr) was sensitive to both dispersal and survival rates; elasticity analysis indicated that changes in adult survival would have the greatest potential effect on the rate of range expansion, while perturbation analysis showed that variation in subadult dispersal contributed most to variance in model predictions. Variation in survival and dispersal of females at the south end of the range contributed most of the variance in predicted southward range expansion. Our approach provides guidance for the acquisition of further data and a means of forecasting the consequence of specific management actions. Similar methods could aid in the management of other recovering populations.     

Elasticity analyses of size-based red and white abalone matrix models: management and conservation.

Prospective elasticity analyses have been used to aid in the management of fished species and the conservation of endangered species. Elasticities were examined for deterministic size-based matrix models of red abalone, Haliotis rufescens, and white abalone, H. sorenseni, to evaluate which size classes influenced population growth (lambda) the most. In the red abalone matrix, growth transitions were determined from a tag recapture study and grouped into nine size classes. In the white abalone matrix, abalone growth was determined from a laboratory study and grouped into five size classes. Survivorship was estimated from tag recapture data for red abalone using a Jolly-Seber model with size as a covariate and used for both red and white abalone. Reproduction estimates for both models used averages of the number of mature eggs produced by female red and white abalone in each size class from four-year reproduction studies. Population growth rate (lambda) was set to 1.0, and the first-year survival (larval survival through to the first size class) was estimated by iteration. Survival elasticities were higher than fecundity elasticities in both the red and white matrix models. The sizes classes with the greatest survival elasticities, and therefore the most influence on population growth in the model, were the sublegal red abalone (150-178 mm) and the largest white abalone size class (140-175 mm). For red abalone, the existing minimum legal size (178 mm) protects the size class the model suggests is critical to population growth. Implementation of education programs for novice divers coupled with renewed enforcement may serve to minimize incidental mortality of the critical size class. For white abalone, conservation efforts directed at restoring adults may have more of an impact on population growth than efforts focusing on juveniles. Our work is an example of how prospective elasticity analyses of size-structured matrix models can be used to quantitatively evaluate research priorities, fishery management strategies, and conservation options.     

Linking irreplaceable landforms in a self‐organizing landscape to sensitivity of population vital rates for an ecological specialist

Irreplaceable, self‐organizing landforms and the endemic and ecologically specialized biodiversity they support are threatened globally by anthropogenic disturbances. Although the outcome of disrupting landforms is somewhat understood, little information exists that documents population consequences of landform disturbance on endemic biodiversity. Conservation strategies for species dependent upon landforms have been difficult to devise because they require understanding complex feedbacks that create and maintain landforms and the consequences of landform configuration on demography of species. We characterized and quantified links between landform configuration and demography of an ecological specialist, the dunes sagebrush lizard (Sceloporus arenicolus), which occurs only in blowouts (i.e., wind‐blown sandy depressions) of Shinnery oak (Quercus havardii) sand‐dune landforms. We used matrix models to estimate vital rates from a multisite mark‐recapture study of 6 populations occupying landforms with different spatial configurations. Sensitivity and elasticity analyses demonstrated demographic rates among populations varied in sensitivity to different landform configurations. Specifically, significant relationships between blowout shape complexity and vital rate elasticities suggested direct links between S. arenicolus demography and amount of edge in Shinnery oak sand‐dune landforms. These landforms are irreplaceable, based on permanent transition of disturbed areas to alternative grassland ecosystem states. Additionally, complex feedbacks between wind, sand, and Shinnery oak maintain this landform, indicating restoration through land management practices is unlikely. Our findings that S. arenicolus population dynamics depended on landform configuration suggest that failure to consider processes of landform organization and their effects on species’ population dynamics may lead to incorrect inferences about threats to endemic species and ineffective habitat management for threatened or endangered species. As such, successful conservation of these systems and the biodiversity they support must be informed by research linking process‐oriented studies of self‐organized landforms with studies of movement, behavior, and demography of species that dwell in them.     

Dependence of the Endangered Black‐Capped Vireo on Sustained Cowbird Management

Conservation‐reliant species depend on active management, even after surpassing recovery goals, for protection from persistent threats. Required management may include control of another species, habitat maintenance, or artificial recruitment. Sometimes, it can be difficult to determine whether sustained management is required. We used nonspatial stochastic population projection matrix simulation and a spatially explicit population model to estimate the effects of parasitism by a brood parasite, the Brown‐headed Cowbird (Moluthrus ater), on a population of endangered Black‐capped Vireos (Vireo atricapilla). We simulated parasitism as a percentage of breeding vireo pairs experiencing decreased fecundity due to cowbirds. We estimated maximum sustainable parasitism (i.e., highest percentage of parasitized vireo breeding pairs for which population growth is ≥1) with the nonspatial model under multiple scenarios designed to assess sensitivity to assumptions about population growth rate, demographic effects of parasitism, and spatial distribution of parasitism. We then used the spatially explicit model to estimate cumulative probabilities of the population falling below the population recovery target of 1000 breeding pairs for a range of parasitism rates under multiple scenarios. We constructed our models from data on vireos collected on the Fort Hood Military Reservation, Texas (U.S.A.). Estimates of maximum sustainable parasitism rates ranged from 9–12% in scenarios with a low (6%) vireo population growth rate to 49–60% in scenarios with a high (24%) growth rate. Sustained parasitism above 45–85%, depending on the scenario, would likely result in the Fort Hood Vireo population dropping below its recovery goal within the next 25 years. These estimates suggest that vireos, although tolerant of low parasitism rates, are a conservation‐reliant species dependent on cowbird management. Dependencia de Vireo atricapilla, Especie en Peligro, hacia el Manejo Sostenido de Moluthurs ater     

A case study of bats and white‐nose syndrome demonstrating how to model population viability with evolutionary effects

Ecological factors generally affect population viability on rapid time scales. Traditional population viability analyses (PVA) therefore focus on alleviating ecological pressures, discounting potential evolutionary impacts on individual phenotypes. Recent studies of evolutionary rescue (ER) focus on cases in which severe, environmentally induced population bottlenecks trigger a rapid evolutionary response that can potentially reverse demographic threats. ER models have focused on shifting genetics and resulting population recovery, but no one has explored how to incorporate those findings into PVA. We integrated ER into PVA to identify the critical decision interval for evolutionary rescue (DIER) under which targeted conservation action should be applied to buffer populations undergoing ER against extinction from stochastic events and to determine the most appropriate vital rate to target to promote population recovery. We applied this model to little brown bats (Myotis lucifugus) affected by white‐nose syndrome (WNS), a fungal disease causing massive declines in several North American bat populations. Under the ER scenario, the model predicted that the DIER period for little brown bats was within 11 years of initial WNS emergence, after which they stabilized at a positive growth rate (λ = 1.05). By comparing our model results with population trajectories of multiple infected hibernacula across the WNS range, we concluded that ER is a potential explanation of observed little brown bat population trajectories across multiple hibernacula within the affected range. Our approach provides a tool that can be used by all managers to provide testable hypotheses regarding the occurrence of ER in declining populations, suggest empirical studies to better parameterize the population genetics and conservation‐relevant vital rates, and identify the DIER period during which management strategies will be most effective for species conservation.