Targeted gene flow and rapid adaptation in an endangered marsupial

Targeted gene flow is an emerging conservation strategy. It involves translocating individuals with favorable genes to areas where they will have a conservation benefit. The applications for targeted gene flow are wide-ranging but include preadapting native species to the arrival of invasive species. The endangered carnivorous marsupial, the northern quoll (Dasyurus hallucatus), has declined rapidly since the introduction of the cane toad (Rhinella marina), which fatally poisons quolls that attack them. There are, however, a few remaining toad-invaded quoll populations in which the quolls survive because they know not to eat cane toads. It is this toad-smart behavior we hope to promote through targeted gene flow. For targeted gene flow to be feasible, however, toad-smart behavior must have a genetic basis. To assess this, we used a common garden experiment, comparing offspring from toad-exposed and toad-naïve parents raised in identical environments, to determine whether toad-smart behavior is heritable. Offspring from toad-exposed populations were substantially less likely to eat toads than those with toad-naïve parents. Hybrid offspring showed similar responses to quolls with 2 toad-exposed parents, indicating the trait may be dominant. Together, these results suggest a heritable trait and rapid adaptive response in a small number of toad-exposed populations. Although questions remain about outbreeding depression, our results are encouraging for targeted gene flow. It should be possible to introduce toad-smart behavior into soon to be affected quoll populations.     

Effects of learning and adaptation on population viability

Cultural adaptation is one means by which conservationists may help populations adapt to threats. A learned behavior may protect an individual from a threat, and the behavior can be transmitted horizontally (within generations) and vertically (between generations), rapidly conferring population-level protection. Although possible in theory, it remains unclear whether such manipulations work in a conservation setting; what conditions are required for them to work; and how they might affect the evolutionary process. We examined models in which a population can adapt through both genetic and cultural mechanisms. Our work was motivated by the invasion of highly toxic cane toads (Rhinella marina) across northern Australia and the resultant declines of endangered northern quolls (Dasyurus hallucatus), which attack and are fatally poisoned by the toxic toads. We examined whether a novel management strategy in which wild quolls are trained to avoid toads can reduce extinction probability. We used a simulation model tailored to quoll life history. Within simulations, individuals were trained and a continuous evolving trait determined innate tendency to attack toads. We applied this model in a population viability setting. The strategy reduced extinction probability only when heritability of innate aversion was low (<20%) and when trained mothers trained >70% of their young to avoid toads. When these conditions were met, genetic adaptation was slower, but rapid cultural adaptation kept the population extant while genetic adaptation was completed. To gain insight into the evolutionary dynamics (in which we saw a transitory peak in cultural adaptation over time), we also developed a simple analytical model of evolutionary dynamics. This model showed that the strength of natural selection declined as the cultural transmission rate increased and that adaptation proceeded only when the rate of cultural transmission was below a critical value determined by the relative levels of protection conferred by genetic versus cultural mechanisms. Together, our models showed that cultural adaptation can play a powerful role in preventing extinction, but that rates of cultural transmission need to be high for this to occur.     

Bibliometric investigation of the integration of animal personality in conservation contexts

Consistent individual differences in behavior, commonly termed animal personality, are a widespread phenomenon across taxa that have important consequences for fitness, natural selection, and trophic interactions. Animal personality research may prove useful in several conservation contexts, but which contexts remains to be determined. We conducted a structured literature review of 654 studies identified by combining search terms for animal personality and various conservation subfields. We scored the relevance of personality and conservation issues for each study to identify which studies meaningfully integrated the 2 fields as opposed to surface-level connections or vague allusions. We found a taxonomic bias toward mammals (29% of all studies). Very few amphibian or reptile studies applied personality research to conservation issues (6% each). Climate change (21%), invasive species (15%), and captive breeding and reintroduction (13%) were the most abundant conservation subfields that occurred in our search, though a substantial proportion of these papers weakly integrated conservation and animal personality (climate change 54%, invasive species 51%, captive breeding and reintroduction 40%). Based on our results, we recommend that researchers strive for consistent and broadly applicable terminology when describing consistent behavioral differences to minimize confusion and improve the searchability of research. We identify several gaps in the literature that appear to be promising and fruitful avenues for future research, such as disease transmission as a function of sociability or exploration as a driver of space use in protected areas. Practitioners can begin informing future conservation efforts with knowledge gained from animal personality research.     

Effects of rarity form on species’ responses to land use

Anthropogenic land-use change causes substantial changes in local and global biodiversity. Rare and common species can differ in sensitivity to land-use change; rare species are expected to be affected more negatively. Rarity may be defined in terms of geographic range size, population density, or breadth of habitat requirements. How these 3 forms of rarity interact in determining global responses to land use is yet to be assessed. Using global data representing 912 vertebrate species, we tested for differences in responses to land use of species characterized by different types of rarity. Land-use responses were fitted using generalized linear mixed-effects models, allowing responses to vary among groups of species with different forms of rarity. Species considered rare with respect to all 3 forms of rarity showed particularly strong declines in disturbed land uses (>40% of species and 30% of individuals in the most disturbed land uses). In contrast, species common both geographically and numerically and with broad habitat requirements showed strong increases (up to 90% increase in species and 40% in abundance in some land uses). Our results suggest that efforts to understand the vulnerability of species to environmental changes should account for different types of rarity where possible. Our results also have potentially important implications for ecosystem functioning, given that rare species may play unique roles within ecosystems.     

Minimizing species extinctions through strategic planning for conservation fencing

Conservation fences are an increasingly common management action, particularly for species threatened by invasive predators. However, unlike many conservation actions, fence networks are expanding in an unsystematic manner, generally as a reaction to local funding opportunities or threats. We conducted a gap analysis of Australia's large predator‐exclusion fence network by examining translocation of Australian mammals relative to their extinction risk. To address gaps identified in species representation, we devised a systematic prioritization method for expanding the conservation fence network that explicitly incorporated population viability analysis and minimized expected species’ extinctions. The approach was applied to New South Wales, Australia, where the state government intends to expand the existing conservation fence network. Existing protection of species in fenced areas was highly uneven; 67% of predator‐sensitive species were unrepresented in the fence network. Our systematic prioritization yielded substantial efficiencies in that it reduced expected number of species extinctions up to 17 times more effectively than ad hoc approaches. The outcome illustrates the importance of governance in coordinating management action when multiple projects have similar objectives and rely on systematic methods rather than expanding networks opportunistically.     

Rapid declines of large mammal populations after the collapse of the Soviet Union

Anecdotal evidence suggests that socioeconomic shocks strongly affect wildlife populations, but quantitative evidence is sparse. The collapse of socialism in Russia in 1991 caused a major socioeconomic shock, including a sharp increase in poverty. We analyzed population trends of 8 large mammals in Russia from 1981 to 2010 (i.e., before and after the collapse). We hypothesized that the collapse would first cause population declines, primarily due to overexploitation, and then population increases due to adaptation of wildlife to new environments following the collapse. The long‐term Database of the Russian Federal Agency of Game Mammal Monitoring, consisting of up to 50,000 transects that are monitored annually, provided an exceptional data set for investigating these population trends. Three species showed strong declines in population growth rates in the decade following the collapse, while grey wolf (Canis lupus) increased by more than 150%. After 2000 some trends reversed. For example, roe deer (Capreolus spp.) abundance in 2010 was the highest of any period in our study. Likely reasons for the population declines in the 1990s include poaching and the erosion of wildlife protection enforcement. The rapid increase of the grey wolf populations is likely due to the cessation of governmental population control. In general, the widespread declines in wildlife populations after the collapse of the Soviet Union highlight the magnitude of the effects that socioeconomic shocks can have on wildlife populations and the possible need for special conservation efforts during such times. Declinación Rápida de las Poblaciones de Mamíferos Mayores después del Colapso de la Unión Soviética     

Effects of Multiple Levels of Social Organization on Survival and Abundance

Abstract: Identifying how social organization shapes individual behavior, survival, and fecundity of animals that live in groups can inform conservation efforts and improve forecasts of population abundance, even when the mechanism responsible for group‐level differences is unknown. We constructed a hierarchical Bayesian model to quantify the relative variability in survival rates among different levels of social organization (matrilines and pods) of an endangered population of killer whales (Orcinus orca). Individual killer whales often participate in group activities such as prey sharing and cooperative hunting. The estimated age‐specific survival probabilities and survivorship curves differed considerably among pods and to a lesser extent among matrilines (within pods). Across all pods, males had lower life expectancy than females. Differences in survival between pods may be caused by a combination of factors that vary across the population's range, including reduced prey availability, contaminants in prey, and human activity. Our modeling approach could be applied to demographic rates for other species and for parameters other than survival, including reproduction, prey selection, movement, and detection probabilities.     

Site‐Occupancy Distribution Modeling to Correct Population‐Trend Estimates Derived from Opportunistic Observations

Abstract: Species’ assessments must frequently be derived from opportunistic observations made by volunteers (i.e., citizen scientists). Interpretation of the resulting data to estimate population trends is plagued with problems, including teasing apart genuine population trends from variations in observation effort. We devised a way to correct for annual variation in effort when estimating trends in occupancy (species distribution) from faunal or floral databases of opportunistic observations. First, for all surveyed sites, detection histories (i.e., strings of detection–nondetection records) are generated. Within‐season replicate surveys provide information on the detectability of an occupied site. Detectability directly represents observation effort; hence, estimating detectablity means correcting for observation effort. Second, site‐occupancy models are applied directly to the detection‐history data set (i.e., without aggregation by site and year) to estimate detectability and species distribution (occupancy, i.e., the true proportion of sites where a species occurs). Site‐occupancy models also provide unbiased estimators of components of distributional change (i.e., colonization and extinction rates). We illustrate our method with data from a large citizen‐science project in Switzerland in which field ornithologists record opportunistic observations. We analyzed data collected on four species: the widespread Kingfisher (Alcedo atthis) and Sparrowhawk (Accipiter nisus) and the scarce Rock Thrush (Monticola saxatilis) and Wallcreeper (Tichodroma muraria). Our method requires that all observed species are recorded. Detectability was <1 and varied over the years. Simulations suggested some robustness, but we advocate recording complete species lists (checklists), rather than recording individual records of single species. The representation of observation effort with its effect on detectability provides a solution to the problem of differences in effort encountered when extracting trend information from haphazard observations. We expect our method is widely applicable for global biodiversity monitoring and modeling of species distributions.     

Male Mutation Bias and Possible Long‐Term Effects of Human Activities

Abstract: The ability of a population to adapt to changing environments depends critically on the amount and kind of genetic variability it possesses. Mutations are an important source of new genetic variability and may lead to new adaptations, especially if the population size is large. Mutation rates are extremely variable between and within species, and males usually have higher mutation rates as a result of elevated rates of male germ cell division. This male bias affects the overall mutation rate. We examined the factors that influence male mutation bias, and focused on the effects of classical life‐history parameters, such as the average age at reproduction and elevated rates of sperm production in response to sexual selection and sperm competition. We argue that human‐induced changes in age at reproduction or in sexual selection will affect male mutation biases and hence overall mutation rates. Depending on the effective population size, these changes are likely to influence the long‐term persistence of a population.     

Ability of Matrix Models to Explain the Past and Predict the Future of Plant Populations

Uncertainty associated with ecological forecasts has long been recognized, but forecast accuracy is rarely quantified. We evaluated how well data on 82 populations of 20 species of plants spanning 3 continents explained and predicted plant population dynamics. We parameterized stage‐based matrix models with demographic data from individually marked plants and determined how well these models forecast population sizes observed at least 5 years into the future. Simple demographic models forecasted population dynamics poorly; only 40% of observed population sizes fell within our forecasts’ 95% confidence limits. However, these models explained population dynamics during the years in which data were collected; observed changes in population size during the data‐collection period were strongly positively correlated with population growth rate. Thus, these models are at least a sound way to quantify population status. Poor forecasts were not associated with the number of individual plants or years of data. We tested whether vital rates were density dependent and found both positive and negative density dependence. However, density dependence was not associated with forecast error. Forecast error was significantly associated with environmental differences between the data collection and forecast periods. To forecast population fates, more detailed models, such as those that project how environments are likely to change and how these changes will affect population dynamics, may be needed. Such detailed models are not always feasible. Thus, it may be wiser to make risk‐averse decisions than to expect precise forecasts from models. Habilidad de los Modelos Matriciales para Explicar el Pasado y Predecir el Futuro de las Poblaciones de Plantas