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.     

Using Modeling to Improve Monitoring of Structured Populations: Are We Collecting the Right Data?

Abstract:  Population monitoring is central to most demographic studies and conservation efforts, but it may not always be directed at the most appropriate life stage. We used stochastic simulation modeling to evaluate the effectiveness of a monitoring program for a well-studied population of Eastern Imperial Eagles ( Aquila heliaca ) in Kazakhstan. Specifically, we asked whether the most appropriate data were being collected to understand system state and population dynamics. Our models were parameterized with data collected over the course of 25 years of study of this population. We used the models to conduct simulation experiments to evaluate relationships between monitored or potentially monitored parameters and the demographic variables of interest—population size ( N ) and population growth (λ). Static analyses showed that traditional territory-based monitoring was a poor indicator of eagle population size and growth and that monitoring survivorship would provide more information about these parameters. Nevertheless, these same traditionally monitored territory-based parameters had greater power to detect long-term changes in population size than did survivorship or population structure. Regardless of the taxa considered, threats can have immediate impacts on population size and growth or longer-term impacts on population dynamics. Prudently designed monitoring programs for any species will detect the demographic effects of both types of threats.     

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.     

Invasion, Disturbance, and Competition: Modeling the Fate of Coastal Plant Populations

Abstract:  Wetland habitats are besieged by biotic and abiotic disturbances such as invasive species, hurricanes, habitat fragmentation, and salinization. Predicting how these factors will alter local population dynamics and community structure is a monumental challenge. By examining ecologically similar congeners, such as Iris hexagona and I. pseudacorus (which reproduce clonally and sexually and tolerate a wide range of environmental conditions), one can identify life-history traits that are most influential to population growth and viability. We combined empirical data and stage-structured matrix models to investigate the demographic responses of native ( I. hexagona ) and invasive ( I. pseudacorus ) plant populations to hurricanes and salinity stress in freshwater and brackish wetlands. In our models I. hexagona and I. pseudacorus responded differently to salinity stress, and species coexistence was rare. In 82% of computer simulations of freshwater marsh, invasive iris populations excluded the native species within 50 years, whereas native populations excluded the invasive species in 99% of the simulations in brackish marsh. The occurrence of hurricanes allowed the species to coexist, and species persistence was determined by the length of time it took the ecosystem to recover. Rapid recovery (2 years) favored the invasive species, whereas gradual recovery (30 years) favored the native species. Little is known about the effects of hurricanes on competitive interactions between native and invasive plant species in marsh ecosystems. Our models contribute new insight into the relationship between environmental disturbance and invasion and demonstrate how influential abiotic factors such as climate change will be in determining interspecific interactions.     

Relating chronic toxicity responses to population-level effects: A comparison of population-level parameters for three salmon species as a function of low-level toxicity

Standard laboratory toxicity tests assess the physiological responses of individual organisms to exposure to toxic substances under controlled conditions. Time and space restrictions often prevent the assessment of population-level responses to a toxic substance. Contaminants can affect various biological functions (e.g. growth, fecundity or behavior), which may alter different demographic traits, leading to population-level impacts. In this study, immune suppression, reproductive dysfunction and somatic growth impairment were examined using life history matrix models for coho salmon (Oncorhynchus kisutch), sockeye salmon (Oncorhynchus nerka) and chinook salmon (Oncorhynchus tshawytscha). Our intent was to gauge the relative magnitude of response to toxic effects among species and between life history stages, not provide a specific estimate of population growth rate or abundance. Effects due to immune suppression were modeled as reductions in age-specific survival. Toxic impacts on reproductive function were modeled as a 10% reduction in reproductive contribution for all reproductively mature age groups. Model runs that examined the effect of somatic growth reduction on population parameters incorporated both survival and reproductive impacts. All impacts were modeled as 10% reductions in the affected population demographic parameters. First-year survival and reproductive impacts produced similar population growth rates (λ), but resulted in different sensitivity and stable age distributions. Modeled somatic growth reduction produced additive effects on survival and reproduction. Toxic stressors producing similar changes in λ did not necessarily produce similar changes in the age distributions. Sensitivity and elasticity analyses demonstrated that changes to the first-year survival rate produced the greatest per-unit effect on λ for each species. Alteration in abundance of mature females also strongly influenced λ. Differences observed between species showed that the number of reproductive ages and time to reproductive maturity were important components for population-level responses. These results emphasize the importance of linking toxicity responses at low concentrations to the demographic traits they affect, and help to highlight the toxicity tests that are more suitable for assessing impacts on the focal species. Additionally, life history modeling is a useful tool for developing testable hypotheses regarding impacts on specific populations as well as for conducting comparisons between populations.     

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.     

Evidence of Local Adaptation in the Demographic Response of American Ginseng to Interannual Temperature Variation

Abstract: Bioclimatic envelope models of species’ responses to climate change are used to predict how species will respond to increasing temperatures. These models are frequently based on the assumption that the northern and southern boundaries of a species’ range define its thermal niche. However, this assumption may be violated if populations are adapted to local temperature regimes and have evolved population‐specific thermal optima. Considering the prevalence of local adaptation, the assumption of a species‐wide thermal optimum may be violated for many species. We used spatially and temporally extensive demographic data for American ginseng (Panax quinquefolius L.) to examine range‐wide variation in response of population growth rate (λ) to climatic factors. Our results suggest adaptation to local temperature, but not precipitation. For each population, λ was maximized when annual temperatures were similar to site‐specific, long‐term mean temperatures. Populations from disparate climatic zones responded differently to temperature variation, and there was a linear relation between population‐level thermal optima and the 30‐year mean temperature at each site. For species that are locally adapted to temperature, bioclimatic envelope models may underestimate the extent to which increasing temperatures will decrease population growth rate. Because any directional change from long‐term mean temperatures will decrease population growth rates, all populations throughout a species’ range will be adversely affected by temperature increase, not just populations at southern and low‐elevation boundaries. Additionally, when a species’ local thermal niche is narrower than its range‐wide thermal niche, a smaller temperature increase than would be predicted by bioclimatic envelope approaches may be sufficient to decrease 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.     

Environment-specific elasticity and sensitivity analysis of the stochastic growth rate

For matrix population models, analyses of how sensitive the population growth rate is to changes in vital rates (i.e. perturbations) are important for studies of life history evolution as well as for management and conservation of threatened species. There are two types of sensitivity analyses corresponding to absolute (sensitivity) or relative (elasticity) changes in the vital rates and both types can be applied to both deterministic and stochastic matrix population models. To date, most empirical studies of elasticity and sensitivity of the stochastic growth rate have examined the response to perturbations in the vital rates in a complete set of possible environments. However, it is often of interest to examine the response to perturbations occurring in only a subset of the possible environments. This has been done for periodic time-varying models elsewhere, but here we describe a recently published method for calculating the environment-specific sensitivity and elasticity of the stochastic growth rate and apply this method to data. These environment-specific perturbation analyses provide a logical way of dividing the sensitivity and elasticity among the environments. They give important insight into the selection regime in different environments and can provide valuable information for making management decisions and management evaluations in stochastic environments.     

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.     

Uncertainty analysis of transient population dynamics

Two types of demographic analyses, perturbation analysis and uncertainty analysis, can be conducted to gain insights about matrix population models and guide population management. Perturbation analysis studies how the perturbation of demographic parameters (survival, growth, and reproduction parameters) may affect the population projection, while uncertainty analysis evaluates how much uncertainty there is in population dynamic predictions and where the uncertainty comes from. Previously, both perturbation analysis and uncertainty analysis were conducted on the long-term population growth rate. However, the population may not reach its equilibrium state, especially when there is management by harvesting or hunting. Recently, there has been an increased interest in short-term transient dynamics, which can differ from asymptotic long-term dynamics. There are currently techniques to conduct perturbation analyses of short-term transient dynamics, but no techniques have been proposed for uncertainty analysis of such dynamics. In this study, we introduced an uncertainty analysis technique, the general Fourier Amplitude Sensitivity Test (FAST), to study uncertainties in transient population dynamics. The general FAST is able to identify the amount of uncertainty in transient dynamics and contributions by different demographic parameters. We applied the general FAST to a mountain goat (Oreamnos americanus) matrix population model to give a clear illustration of how uncertainty analysis can be conducted for transient dynamics arising from matrix population models.     

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.     

Local population dynamics of an invasive tree species with a complex life-history cycle: A stochastic matrix model

Biological invasions are widely accepted as having a major impact on ecosystem functioning worldwide, giving urgency to a better understanding of the factors that control their spread. Modelling tools have been developed for this purpose but are often discrete-space, discrete-time spatial-mechanistic models that adopt a computer simulation approach and resist mathematical analysis. We constructed a simple demographic matrix model to explore the local population dynamics of an invasive species with a complex life history and whose invasive success depends on resource availability, which occurs stochastically. As a case study we focused on the American black cherry (Prunus serotina Ehrh.), a gap-dependent tree able both to constitute a long-living seedling bank under unfavourable light conditions and to resprout vigorously once cut-down, which is invading European temperate forests. The model used was a stage-classified matrix population model (i.e., Lefkovitch matrix), integrating environmental stochasticity. Stochastic matrix projection analysis was combined with elasticity analysis and stochastic simulations to search for the species’ ‘Achille heel’. As expected, the population growth rate (i.e., Lyapunov exponent), which measures the risk of P. serotina invasion at the stand scale, increased with light frequency. There was a critical value above which the population of P. serotina explodes and below which it locally goes extinct. The resprouting capacity usually speed up the invasion but appeared to play a minor role. The mean duration of stand invasion was measured and important life stage transitions that mostly contribute to the local stochastic growth rate were identified. Some relevant management implications are discussed and the interest of such models for the understanding of demographic characteristics of invasive species is stressed.     

Effective Population Size in Red-Cockaded Woodpeckers: Population and Model Differences

Loss of genetic variability in isolated populations is an important issue for conservation biology. Most studies involve only a single population of a given species and a single method of estimating rate of loss. Here we present analyses for three different Red-cockaded Woodpecker ( Picoides borealis ) populations from different geographic regions. We compare two different models for estimating the expected rate of loss of genetic variability, and test their sensitivity to model parameters. We found that the simpler model (Reed et al. 1988) consistently estimated a greater rate of loss of genetic variability from a population than did the Emigh and Pollak (1979) model. The ratio of effective population size (which describes the expected rate of loss of genetic variability) to breeder population size varied widely among Red-cockaded Woodpecker populations due to geographic variation in demography. For this species, estimates of effective size were extremely sensitive to survival parameters, but not to the probability of breeding or reproductive success. Sensitivity was sufficient that error in estimating survival rates in the field could easily mask true population differences in effective size. Our results indicate that accurate and precise demographic data are prerequisites to determining effective population size for this species using genetic models, and that a single estimate of rate of loss of genetic variability is not valid across populations.     

Climate influences the demography of three dominant sagebrush steppe plants

Climate change could alter the population growth of dominant species, leading to profound effects on community structure and ecosystem dynamics. Understanding the links between historical variation in climate and population vital rates (survival, growth, recruitment) is one way to predict the impact of future climate change. Using a unique, long-term data set from eastern Idaho, USA, we parameterized integral projection models (IPMs) for Pseudoroegneria spicata, Hesperostipa comata, and Artemisia tripartita to identify the demographic rates and climate variables most important for population growth. We described survival, growth, and recruitment as a function of genet size using mixed-effect regression models that incorporated climate variables. Elasticites for the survival + growth portion of the kernel were larger than the recruitment portion for all three species, with survival + growth accounting for 87-95% of the total elasticity. The genet sizes with the highest elasticity values in each species were very close to the genet size threshold where survival approached 100%. We found strong effects of climate on the population growth rate of two of our three species. In H. comata, a 1% decrease in previous year's precipitation would lead to a 0.6% decrease in population growth. In A. tripartita, a 1% increase in summer temperature would result in a 1.3% increase in population growth. In both H. comata and A. tripartita, climate influenced population growth by affecting genet growth more than survival or recruitment. Late-winter snow was the most important climate variable for P. spicata, but its effect on population growth was smaller than the climate effects we found in H. comata or A. tripartita. For all three species, demographic responses lagged climate by at least one year. Our analysis indicates that understanding climate effects on genet growth may be crucial for anticipating future changes in the structure and function of sagebrush steppe vegetation.     

A Behaviorally Explicit Demographic Model Integrating Habitat Selection and Population Dynamics in California Sea Lions

Abstract: Although there has been a call for the integration of behavioral ecology and conservation biology, there are few tools currently available to achieve this integration. Explicitly including information about behavioral strategies in population viability analyses may enhance the ability of conservation biologists to understand and estimate patterns of extinction risk. Nevertheless, most behavioral‐based PVA approaches require detailed individual‐based data that are rarely available for imperiled species. We present a mechanistic approach that incorporates spatial and demographic consequences of behavioral strategies into population models used for conservation. We developed a stage‐structured matrix model that includes the costs and benefits of movement associated with 2 habitat‐selection strategies (philopatry and direct assessment). Using a life table for California sea lions (Zalophus californianus), we explored the sensitivity of model predictions to the inclusion of these behavioral parameters. Including behavioral information dramatically changed predicted population sizes, model dynamics, and the expected distribution of individuals among sites. Estimated population sizes projected in 100 years diverged up to 1 order of magnitude among scenarios that assumed different movement behavior. Scenarios also exhibited different model dynamics that ranged from stable equilibria to cycles or extinction. These results suggest that inclusion of behavioral data in viability models may improve estimates of extinction risk for imperiled species. Our approach provides a simple method for incorporating spatial and demographic consequences of behavioral strategies into population models and may be easily extended to other species and behaviors to understand the mechanisms of population dynamics for imperiled populations.     

Integrating farming techniques in an ecological matrix model: Implementation on the primrose (Primula vulgaris)

Several studies have proven the importance of field margins in sustaining biodiversity and other work has been done on the effect of field management on field margin flora. However few models have been built to predict the effects of field management on the flora. Our project addresses this need for a model capable of predicting the effect of cropping techniques and their timing on the flora of field margins. Primula vulgaris is a biodiversity indicator, characteristic of undisturbed flora and found in field margins and woodlands: its population has been declining for several years. We created a temporal matrix model of P. vulgaris populations on field margins, taking into account the effects of field, field margin and roadside management based on literature and expert knowledge. We then analysed its sensitivity to demographic parameters by comparing lambda (growth rate) sensitivity and elasticity. We compared the management parameter effect using the relative growth rate of the population after 6 years of simulation. Sensitivity analysis to biological parameters showed the importance of adult survival and seed production and germination. Results show that P. vulgaris is particularly sensitive to broad-spectrum herbicides and that other management techniques like early mowing, scything and scrub-killer (diluted broad-spectrum herbicide or specific herbicide) are less aggressive. Our simulations show that management of cash crops in Brittany is too aggressive for P. vulgaris populations and that 4-5 years of grassland in the adjacent field are necessary to maintain populations.     

Demographic models inform selection of biocontrol agents for garlic mustard (Alliaria petiolata).

Nonindigenous invasive plants pose a major threat to natural communities worldwide. Biological control of weeds via selected introduction of their natural enemies can affect control over large spatial areas but also risk nontarget effects. To maximize effectiveness while minimizing risk, weed biocontrol programs should introduce the minimum number of host-specific natural enemies necessary to control an invasive nonindigenous plant. We used elasticity analysis of a matrix model to help inform biocontrol agent selection for garlic mustard (Alliaria petiolata (M. Bieb.) Cavara and Grande). The Eurasian biennial A. petiolata is considered one of the most problematic invaders of temperate forests in North America. Four weevil species in the genus Ceutorhynchus (Coleoptera: Curculionidae) are currently considered potential biocontrol agents. These species attack rosettes (C. scrobicollis), stems (C. roberti, C. alliariae), and seeds (C. constrictus) of A. petiolata. Elasticity analyses using A. petiolata demographic parameters from North America indicated that changes in the rosette-to-flowering-plant transition and changes in fecundity consistently had the greatest impact on population growth rate. These results suggest that attack by the rosette-feeder C. scrobicollis, which reduces overwintering survival, and seed or stem feeders that reduce seed output should be particularly effective. Model outcomes differed greatly as A. petiolata demographic parameters were varied within ranges observed in North America, indicating that successful control of A. petiolata populations may occur under some, but not all, conditions. Using these a priori analyses we predict: (1) rosette mortality and reduction of seed output will be the most important factors determining A. petiolata demography; (2) the root-crown feeder C. scrobicollis will have the most significant impact on A. petiolata demography; (3) releases of single control agents are unlikely to control A. petiolata across its full range of demographic variability; (4) combinations of agents that simultaneously reduce rosette survival and seed production will be required to suppress the most vigorous A. petiolata populations. These predictions can be tested using established long-term monitoring sites coupled with a designed release program. If demographic models can successfully predict biocontrol agent impact on invasive plant populations, a continued dialogue and collaboration between empirical and theoretical approaches may be the key to the development of successful biocontrol tactics for plant invaders in the future.     

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.     

Effects of life‐history requirements on the distribution of a threatened reptile

Survival and reproduction are the two primary life‐history traits essential for species’ persistence; however, the environmental conditions that support each of these traits may not be the same. Despite this, reproductive requirements are seldom considered when estimating species’ potential distributions. We sought to examine potentially limiting environmental factors influencing the distribution of an oviparous reptile of conservation concern with respect to the species’ survival and reproduction and to assess the implications of the species’ predicted climatic constraints on current conservation practices. We used ecological niche modeling to predict the probability of environmental suitability for the alligator snapping turtle (Macrochelys temminckii). We built an annual climate model to examine survival and a nesting climate model to examine reproduction. We combined incubation temperature requirements, products of modeled soil temperature data, and our estimated distributions to determine whether embryonic development constrained the northern distribution of the species. Low annual precipitation constrained the western distribution of alligator snapping turtles, whereas the northern distribution was constrained by thermal requirements during embryonic development. Only a portion of the geographic range predicted to have a high probability of suitability for alligator snapping turtle survival was estimated to be capable of supporting successful embryonic development. Historic occurrence records suggest adult alligator snapping turtles can survive in regions with colder climes than those associated with consistent and successful production of offspring. Estimated egg‐incubation requirements indicated that current reintroductions at the northern edge of the species’ range are within reproductively viable environmental conditions. Our results highlight the importance of considering survival and reproduction when estimating species’ ecological niches, implicating conservation plans, and benefits of incorporating physiological data when evaluating species’ distributions.