Cost-Effective Suppression and Eradication of Invasive Predators

Abstract: Introduced predators can have pronounced effects on naïve prey species; thus, predator control is often essential for conservation of threatened native species. Complete eradication of the predator, although desirable, may be elusive in budget‐limited situations, whereas predator suppression is more feasible and may still achieve conservation goals. We used a stochastic predator–prey model based on a Lotka‐Volterra system to investigate the cost‐effectiveness of predator control to achieve prey conservation. We compared five control strategies: immediate eradication, removal of a constant number of predators (fixed‐number control), removal of a constant proportion of predators (fixed‐rate control), removal of predators that exceed a predetermined threshold (upper‐trigger harvest), and removal of predators whenever their population falls below a lower predetermined threshold (lower‐trigger harvest). We looked at the performance of these strategies when managers could always remove the full number of predators targeted by each strategy, subject to budget availability. Under this assumption immediate eradication reduced the threat to the prey population the most. We then examined the effect of reduced management success in meeting removal targets, assuming removal is more difficult at low predator densities. In this case there was a pronounced reduction in performance of the immediate eradication, fixed‐number, and lower‐trigger strategies. Although immediate eradication still yielded the highest expected minimum prey population size, upper‐trigger harvest yielded the lowest probability of prey extinction and the greatest return on investment (as measured by improvement in expected minimum population size per amount spent). Upper‐trigger harvest was relatively successful because it operated when predator density was highest, which is when predator removal targets can be more easily met and the effect of predators on the prey is most damaging. This suggests that controlling predators only when they are most abundant is the “best” strategy when financial resources are limited and eradication is unlikely.     

Restoration of Landscape Structure Altered by Fire Suppression

There is increasing interest in applying landscape ecological research to the management of wildlands, particularly regarding the negative effects of fragmentation and the benefits of corridors. Patch-producing large disturbances, such as fires and floods, produce a spatial mosaic structure in landscapes to which many species are sensitive. Management of the spatial structure of the patch mosaic has seldom been an explicit concern, however, in part because of insufficient knowledge about bow this spatial structure is affected by alterations in the disturbance regime. Yet the patch mosaic structure of many landscapes has been altered by disturbance control (such as fire suppression), and there is substantial interest in restoring natural disturbance regimes in some wildland landscapes. It has been proposed that, in landscapes subjected to decades of fire suppression, simple reinstatement of the natural fire regime may lead to adverse effects because fuel buildup during fire suppression may result in unusually large fires. It has also been proposed that the use of small prescribed fires may be an effective approach to restoration of landscapes subjected to fire suppression. Here I use a spatial GIS-based simulation model to analyze the effects of reinstating a natural fire regime in the Boundary Waters Canoe Area, Minnesota, after 82 years of fire suppression. The simulation experiment suggests that suppression can be expected to significantly alter landscape structure, but landscape structure can generally be restored within 50–75 years by reinstating the natural fire regime. Unusually large fires would probably hasten the restoration of landscape structure, while small prescribed fires will not restore the landscape but instead will produce further alteration.     

Paradigms for parasite conservation

Parasitic species, which depend directly on host species for their survival, represent a major regulatory force in ecosystems and a significant component of Earth's biodiversity. Yet the negative impacts of parasites observed at the host level have motivated a conservation paradigm of eradication, moving us farther from attainment of taxonomically unbiased conservation goals. Despite a growing body of literature highlighting the importance of parasite‐inclusive conservation, most parasite species remain understudied, underfunded, and underappreciated. We argue the protection of parasitic biodiversity requires a paradigm shift in the perception and valuation of their role as consumer species, similar to that of apex predators in the mid‐20th century. Beyond recognizing parasites as vital trophic regulators, existing tools available to conservation practitioners should explicitly account for the unique threats facing dependent species. We built upon concepts from epidemiology and economics (e.g., host‐density threshold and cost‐benefit analysis) to devise novel metrics of margin of error and minimum investment for parasite conservation. We define margin of error as the risk of accidental host extinction from misestimating equilibrium population sizes and predicted oscillations, while minimum investment represents the cost associated with conserving the additional hosts required to maintain viable parasite populations. This framework will aid in the identification of readily conserved parasites that present minimal health risks. To establish parasite conservation, we propose an extension of population viability analysis for host–parasite assemblages to assess extinction risk. In the direst cases, ex situ breeding programs for parasites should be evaluated to maximize success without undermining host protection. Though parasitic species pose a considerable conservation challenge, adaptations to conservation tools will help protect parasite biodiversity in the face of an uncertain environmental future.     

Population level effects of reduced fecundity in the fish species perch (Perca fluviatilis) and the implications for environmental monitoring

A 40% reduction in relative gonad size in perch (Perca fluviatilis) has been observed over that past two decades at the Swedish national reference site Kvädöfjärden. This biomarker response could be interpreted as a reduction in fecundity and increased risk of local extinction. However, abundance estimates from the same area has not provided any evidence of a reduction in population size. In the present study, a matrix population model was developed to investigate if a reduction in fecundity can be expected to have long term effects on population viability for perch and to evaluate the probability to detect such effects through abundance estimates. The model was parameterized from 17 years of population data from Kvädöfjärden as well as from other studies on perch. The model included density dependence and environmental stochasticity. The results indicated that a reduction in fecundity that is in level with the observed reduction in relative gonad size in Kvädöfjärden will cause a substantial risk for local extinction. The risk that the population will fall below 20% of the carrying capacity within 50 years is 44% when the fecundity is reduced by 40%. However, due to variability in abundance measurements it will take some time before a reduction in gonad size leads to statistically significant effects on the population. If the fecundity is reduced by 40% successively over a 10-year period, the probability to detect this through abundance estimates within 10 years is less than 50%. The results of the present study clearly show that relevant biomarkers have an important role in environmental monitoring as early warning signals, preferably in combination with measurements at higher levels of biological organization.     

Demographic Characteristics of Extinction in a Small, Insular Population of House Sparrows in Northern Norway

Abstract:  In conservation ecology there is an urgent need for indicators that can be used to predict the risk of extinction of populations. Identifying extinction-prone populations has been difficult because few data sets on the demographic characteristics of the final stage to extinction are available and because of problems in separating out stochastic effects from changes in the expected dynamics. We documented the demographic changes that occurred during the period prior to extinction of a small island population of House Sparrows ( Passer domesticus ) after the end of permanent human settlement. A mark-recapture analysis revealed that this decline to extinction was mainly due to increased mortality after closure of the last farm that resulted in a negative long-term-specific growth rate. No change occurred in either the structural composition (breeding sex ratio and age distribution) of the population or in female recruitment. No male, however, recruits were produced on the island after the farm closure. Based on a simple, stochastic, density-dependent model we constructed a population prediction interval (PPI) to estimate the time to extinction. The 95% PPI slightly overestimated the time to extinction with large uncertainty in predictions, especially due to the influence of demographic stochasticity and parameter drift. Our results strongly emphasize the importance of access to data on temporal variation that can be used to parameterize simple population models that allow estimation of critical parameters for credible prediction of time to extinction.     

Cost analysis of composite sampling for classification

When an environmental sampling objective is to classify all the sample units as contaminated or not, composite sampling with selective retesting can substantially reduce costs by reducing the number of units that require direct analysis. The tradeoff, however, is increased complexity that has its own hidden costs. For this reason, we propose a model for assessing the relative cost, expressed as the ratio of total expected cost with compositing to total expected cost without compositing (initial exhaustive testing). Expressions are derived for the following retesting protocols: (i) exhaustive, (ii) sequential and (iii) binary split. The effects of both false positive and false negative rates are also derived and incorporated. The derived expressions of relative cost are illustrated for a range of values for various cost components that reflect typical costs incurred with hazardous waste site monitoring. Results allow those who are designing sampling plans to evaluate if any of these compositing/retesting protocols will be cost effective for particular applications.     

Use of stochastic patch occupancy models in the California red-legged frog for Bayesian inference regarding past events and future persistence

Assessing causes of population decline is critically important to management of threatened species. Stochastic patch occupancy models (SPOMs) are popular tools for examining spatial and temporal dynamics of populations when presence–absence data in multiple habitat patches are available. We developed a Bayesian Markov chain method that extends existing SPOMs by focusing on past environmental changes that may have altered occupancy patterns prior to the beginning of data collection. Using occupancy data from 3 creeks, we applied the method to assess 2 hypothesized causes of population decline—in situ die-off and residual impact of past source population loss—in the California red-legged frog. Despite having no data for the 20–30 years between the hypothetical event leading to population decline and the first data collected, we were able to discriminate among hypotheses, finding evidence that in situ die-off increased in 2 of the creeks. Although the creeks had comparable numbers of occupied segments, owing to different extinction–colonization dynamics, our model predicted an 8-fold difference in persistence probabilities of their populations to 2030. Adding a source population led to a greater predicted persistence probability than did decreasing the in situ die-off, emphasizing that reversing the deleterious impacts of a disturbance may not be the most efficient management strategy. We expect our method will be useful for studying dynamics and evaluating management strategies of many species.     

A comparison of models for predicting population persistence

We consider a range of models that may be used to predict the future persistence of populations, particularly those based on discrete-state Markov processes. While the mathematical theory of such processes is very well-developed, they may be difficult to work with when attempting to estimate parameters or expected times to extinction. Hence, we focus on diffusion and other approximations to these models, presenting new and recent developments in parameter estimation for density dependent processes, and the calculation of extinction times for processes subject to catastrophes. We illustrate these and other methods using data from simulated and real time series. We give particular attention to a procedure, due to Ross et al. [Ross, J.V., Taimre, T., Pollett, P.K. On parameter estimation in population models, Theor. Popul. Biol., in press], for estimating the parameters of the stochastic SIS logistic model, and demonstrate ways in which these parameters may be used to estimate expected extinction times. Although the stochastic SIS logistic model is strictly density dependent and allows only for birth and death events, it nonetheless may be used to predict extinction times with some accuracy even for populations that are only weakly density dependent, or that are subject to catastrophes.     

Conservation Threats Due to Human-Caused Increases in Fire Frequency in Mediterranean-Climate Ecosystems

Periodic wildfire is an important natural process in Mediterranean-climate ecosystems, but increasing fire recurrence threatens the fragile ecology of these regions. Because most fires are human-caused, we investigated how human population patterns affect fire frequency. Prior research in California suggests the relationship between population density and fire frequency is not linear. There are few human ignitions in areas with low population density, so fire frequency is low. As population density increases, human ignitions and fire frequency also increase, but beyond a density threshold, the relationship becomes negative as fuels become sparser and fire suppression resources are concentrated. We tested whether this hypothesis also applies to the other Mediterranean-climate ecosystems of the world. We used global satellite databases of population, fire activity, and land cover to evaluate the spatial relationship between humans and fire in the world's five Mediterranean-climate ecosystems. Both the mean and median population densities were consistently and substantially higher in areas with than without fire, but fire again peaked at intermediate population densities, which suggests that the spatial relationship is complex and nonlinear. Some land-cover types burned more frequently than expected, but no systematic differences were observed across the five regions. The consistent association between higher population densities and fire suggests that regardless of differences between land-cover types, natural fire regimes, or overall population, the presence of people in Mediterranean-climate regions strongly affects the frequency of fires; thus, population growth in areas now sparsely settled presents a conservation concern. Considering the sensitivity of plant species to repeated burning and the global conservation significance of Mediterranean-climate ecosystems, conservation planning needs to consider the human influence on fire frequency. Fine-scale spatial analysis of relationships between people and fire may help identify areas where increases in fire frequency will threaten ecologically valuable areas.     

Phylogenetic Comparative Methods Strengthen Evidence for Reduced Genetic Diversity among Endangered Tetrapods

Abstract: The fitness of species with little genetic diversity is expected to be affected by inbreeding and an inability to respond to environmental change. Conservation theory suggests that endangered species will generally demonstrate lower genetic diversity than taxa that are not threatened. This hypothesis has been challenged because the time frame of anthropogenic extinction may be too fast to expect genetic factors to significantly contribute. I conducted a meta‐analysis to examine how genetic diversity in 894 tetrapods correlates with extinction threat level. Because species are not evolutionarily independent, I used a phylogenetic regression framework to address this issue. Mean genetic diversity of tetrapods, as assessed by protein heterozygosity, was 29.7–31.5% lower on average in threatened species than in their nonthreatened relatives, a highly significant reduction. Within amphibians as diversity decreased extinction risk increased in phylogenetic models, but not in nonphylogenetic regressions. The effects of threatened status on diversity also remained significant after accounting for body size in mammals. These results support the hypothesis that genetic effects on population fitness are important in the extinction process.     

Directions in Conservation Biology: Comments on Caughley

The recent review by Caughley (1994) on approaches used in conservation biology suggested that there are two: the small population paradigm and the declining population paradigm. We believe that this division is overly simplistic and that it should not be perpetuated. Both the deterministic factors that reduce population size and the stochastic factors that lead to the final extinction of a small population are critical to consider in preventing extinction. Only through an overall and comprehensive effort, which we call inclusive population viability analysis, can extinction processes be understood and mitigated. In this context we discuss Caughley's comments about genetics, demography, and general population viability, with particular attention to cheetahs (Acinonyx jubatus) and Pacific salmon (Oncorhynchus sp. ) .     

Interspecific Patterns of Genetic Diversity in Birds: Correlations with Extinction Risk

Abstract:  Birds are frequently used as indicators of ecosystem health and are the most comprehensively studied class in the animal kingdom. Nevertheless, a comprehensive, interspecific assessment of the correlates of avian genetic diversity is lacking, even though indices of genetic diversity are of considerable interest in the conservation of threatened species. We used published data on variation at microsatellite loci from 194 bird species to examine correlates of diversity, particularly with respect to conservation status and population size. We found a significant decline in mean heterozygosity with increasing extinction risk, and showed, by excluding species whose heterozygosity values were calculated with heterospecific primers, that this relationship was not dependent on ascertainment bias. Results of subsequent regression analyses suggested that smaller population sizes of threatened species were largely responsible for this relationship. Thus, bird species at risk of extinction are relatively depauperate in terms of neutral genetic diversity, which is expected to make population recovery more difficult if it reflects adaptive genetic variation. Conservation policy will need to minimize further loss of diversity if the chances of saving threatened species are to be maximized.     

Population feedback after successful invasion leads to ecological suicide in seasonal environments

For most consumer species, winter represents a period of harsh food conditions in addition to the physiological strain that results from the low ambient temperatures. In size-structured populations, larger-bodied individuals do better during winter as they have larger energy reserves to buffer starvation periods. In contrast, smaller-bodied individuals do better under growing conditions, as they have lower maintenance costs. We study how the interplay between size-dependent life-history processes and seasonal changes in temperature and food availability shape the long-term dynamics of a size-structured consumer population and its unstructured resource. We show that the size dependence of maintenance requirements translates into a minimum body size that is needed for surviving starvation when consumers can adapt only to a limited extent to the low food densities in winter. This size threshold can lead to population extinction because adult individuals suffer only a little during winter and hence produce large numbers of offspring. Due to population feedback on the resource and intense intra-cohort competition, newborn consumers then fail to reach the size threshold for survival. Under these conditions, small numbers of individuals can survive, increase in density, and build up a population, which will subsequently go extinct due to its feedback on the resource. High juvenile mortality may prevent this ecological suicide from occurring, as it releases resource competition among newborns and speeds up their growth. In size-structured populations, annual fluctuations in temperature and food availability may thus lead to a conflict between individual fitness and population persistence.     

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.     

Conservation Genetics of Potentially Endangered Mutualisms: Reduced Levels of Genetic Variation in Specialist versus Generalist Bees

Abstract:  Oligolectic bees collect pollen from one or a few closely related species of plants, whereas polylectic bees visit a variety of flowers for pollen. Because of their more restricted range of host plants, it maybe expected that specialists exist in smaller, more isolated populations, with lower effective population sizes than generalists. Consequently, we hypothesized that oligolectic bees have reduced levels of genetic variation relative to related polylectic species. To test this hypothesis, we used five phylogenetically independent pairs of species in which one member was oligolectic and the other was polylectic. We assayed genetic variation in our species pairs at an average of 32 allozyme loci. Within each species pair, the oligolectic member had fewer polymorphic loci, lower average allelic richness, and lower average expected heterozygosity than its polylectic relative. Averaged over all species pairs, this corresponds to a 21% reduction in allelic richness, a 72% reduction in the proportion of polymorphic loci, and an 83% reduction in expected heterozygosity in specialists compared with generalists. Our data support the hypothesis of reduced effective population size in oligolectic bees and suggest that they may be more prone to extinction as a result. We suggest that in instances in which bee specialists are involved in mutually codependent relationships with their floral hosts, these mutualisms may be endangered for genetic and ecological reasons.     

Improving supplementary feeding in species conservation

Supplementary feeding is often a knee‐jerk reaction to population declines, and its application is not critically evaluated, leading to polarized views among managers on its usefulness. Here, we advocate a more strategic approach to supplementary feeding so that the choice to use it is clearly justified over, or in combination with, other management actions and the predicted consequences are then critically assessed following implementation. We propose combining methods from a set of specialist disciplines that will allow critical evaluation of the need, benefit, and risks of food supplementation. Through the use of nutritional ecology, population ecology, and structured decision making, conservation managers can make better choices about what and how to feed by estimating consequences on population recovery across a range of possible actions. This structured approach also informs targeted monitoring and more clearly allows supplementary feeding to be integrated in recovery plans and reduces the risk of inefficient decisions. In New Zealand, managers of the endangered Hihi (Notiomystis cincta) often rely on supplementary feeding to support reintroduced populations. On Kapiti island the reintroduced Hihi population has responded well to food supplementation, but the logistics of providing an increasing demand recently outstretched management capacity. To decide whether and how the feeding regime should be revised, managers used a structured decision making approach informed by population responses to alternative feeding regimes. The decision was made to reduce the spatial distribution of feeders and invest saved time in increasing volume of food delivered into a smaller core area. The approach used allowed a transparent and defendable management decision in regard to supplementary feeding, reflecting the multiple objectives of managers and their priorities.     

Reconstructibility of Density Dependence and the Conservative Assessment of Extinction Risks

Abstract: The probability of extinction is sensitive to the presence and character of density dependence controlling the dynamics of a population. This means that our capacity to estimate a population's risks of extinction under varying environmental conditions or competing management regimes is linked to our ability to reconstruct from data the density-dependence relationships governing the natural dynamics, especially when data do not reveal a trend of population growth or decline. In an example using Gadus morhua , we show that even 10- or 20-year data sets are too short to make precise estimates of these risks. We also observe, however, that under moderate or weak density dependence, the computed risks are lower than when density dependence is not included in the model. We propose, therefore, that when available data sets are insufficient for reconstructing reliable measurements of density dependence, conservative estimates of extinction probabilities can be made from models that simply omit density dependence.     

Incorporating evolutionary processes into population viability models

We examined how ecological and evolutionary (eco‐evo) processes in population dynamics could be better integrated into population viability analysis (PVA). Complementary advances in computation and population genomics can be combined into an eco‐evo PVA to offer powerful new approaches to understand the influence of evolutionary processes on population persistence. We developed the mechanistic basis of an eco‐evo PVA using individual‐based models with individual‐level genotype tracking and dynamic genotype–phenotype mapping to model emergent population‐level effects, such as local adaptation and genetic rescue. We then outline how genomics can allow or improve parameter estimation for PVA models by providing genotypic information at large numbers of loci for neutral and functional genome regions. As climate change and other threatening processes increase in rate and scale, eco‐evo PVAs will become essential research tools to evaluate the effects of adaptive potential, evolutionary rescue, and locally adapted traits on persistence.     

Parental investment decision rules and the Concorde fallacy

Summary Investment theory states that animals should base their parental investment decisions on expected benefits, and not on whether or not past investment will be wasted. Otherwise, they would comnit the Concorde fallacy. If reproduction has a cost, however, then past investment and expected benefits are necessarily confounded. Assuming a cost of reproduction, animals will be selected to maximize their remaining lifetime reproductive success, subject to a tradeoff between present and future reproduction (Williams' principle). We extend Williams' principle and develop an experimental design that would allow past investment and expected benefits to be varied independently. This design illustrates the importance of the value of the brood relative to the value of future reproduction.     

Spatial uncertainty analysis of population models

This paper describes an approach for conducting spatial uncertainty analysis of spatial population models, and illustrates the ecological consequences of spatial uncertainty for landscapes with different properties. Spatial population models typically simulate birth, death, and migration on an input map that describes habitat. Typically, only a single “reference” map is available, but we can imagine that a collection of other, slightly different, maps could be drawn to represent a particular species’ habitat. As a first approximation, our approach assumes that spatial uncertainty (i.e., the variation among values assigned to a location by such a collection of maps) is constrained by characteristics of the reference map, regardless of how the map was produced. Our approach produces lower levels of uncertainty than alternative methods used in landscape ecology because we condition our alternative landscapes on local properties of the reference map. Simulated spatial uncertainty was higher near the borders of patches. Consequently, average uncertainty was highest for reference maps with equal proportions of suitable and unsuitable habitat, and no spatial autocorrelation. We used two population viability models to evaluate the ecological consequences of spatial uncertainty for landscapes with different properties. Spatial uncertainty produced larger variation among predictions of a spatially explicit model than those of a spatially implicit model. Spatially explicit model predictions of final female population size varied most among landscapes with enough clustered habitat to allow persistence. In contrast, predictions of population growth rate varied most among landscapes with only enough clustered habitat to support a small population, i.e., near a spatially mediated extinction threshold. We conclude that spatial uncertainty has the greatest effect on persistence when the amount and arrangement of suitable habitat are such that habitat capacity is near the minimum required for persistence.