Metamodels for transdisciplinary analysis of wildlife population dynamics

Is resilience a unifying concept for the biological sciences?

There is increasing interest in applying resilience concepts at different scales of biological organization to address major interdisciplinary challenges from cancer to climate change. It is unclear, however, whether resilience can be a unifying concept consistently applied across the breadth of the biological sciences, or whether there is limited capacity for integration. In this review, we draw on literature from molecular biology to community ecology to ascertain commonalities and shortcomings in how resilience is measured and interpreted. Resilience is studied at all levels of biological organization, although the term is often not used. There is a suite of resilience mechanisms conserved across biological scales, and there are tradeoffs that affect resilience. Resilience is conceptually useful to help diverse researchers think about how biological systems respond to perturbations, but we need a richer lexicon to describe the diversity of perturbations, and we lack widely applicable metrics of resilience.

Sustained reduction in numbers of Australian fur seal pups: Implications for future population monitoring

Fur seal populations in the Southern Hemisphere were plundered in the late 1700s and early 1800s to provide fur for a clothing industry. Millions of seals were killed resulting in potentially major ecosystem changes across the Southern Hemisphere, the consequences of which are unknown today. Following more than a century of population suppression, partly through on-going harvesting, many of the fur seal populations started to recover in the late 1900s. Australian fur seals (Arctocephalus pusillus doriferus), one of the most geographically constrained fur seal species, followed this trend. From the 1940s to 1986, pup production remained at approximately 10,000 per year, then significant growth commenced. By 2007, live pup abundance had recovered to approximately 21,400 per year and recovery was expected to continue However, a species-wide survey in 2013 recorded a 20% decline, to approximately 16,500 live pups. It was not known if this decline was due to 2013 being a poor breeding year or a true population reduction. Here we report the results of a population-wide survey conducted in 2017 and annual monitoring at the most productive colony, Seal Rocks, Victoria that recorded a large decline in live pup abundance (-28%). Sustained lower pup numbers at Seal Rocks from annual counts between 2012–2017 (mean = 2908 ± 372 SD), as well as the population-wide estimate of 16,903 live pups in 2017, suggest that the pup numbers for the total population have remained at the lower level observed in 2013 and that the 5-yearly census results are not anomalies or representative of poor breeding seasons. Potential reasons for the decline, which did not occur range-wide but predominantly in the most populated and long-standing breeding sites, are discussed. To enhance adaptive management of this species, methods for future monitoring of the population are also presented. Australian fur seals occupy several distinct regions influenced by different currents and upwellings: range-wide pup abundance monitoring enables comparisons of ecosystem status across these regions. Forces driving change in Australian fur seal pup numbers are likely to play across other marine ecosystems, particularly in the Southern Hemisphere where most fur seals live.

A New Approach to Evaluate and Reduce Uncertainty of Model-Based Biodiversity Projections for Conservation Policy Formulation

Biodiversity projections with uncertainty estimates under different climate, land-use, and policy scenarios are essential to setting and achieving international targets to mitigate biodiversity loss. Evaluating and improving biodiversity predictions to better inform policy decisions remains a central conservation goal and challenge. A comprehensive strategy to evaluate and reduce uncertainty of model outputs against observed measurements and multiple models would help to produce more robust biodiversity predictions. We propose an approach that integrates biodiversity models and emerging remote sensing and in-situ data streams to evaluate and reduce uncertainty with the goal of improving policy-relevant biodiversity predictions. In this article, we describe a multivariate approach to directly and indirectly evaluate and constrain model uncertainty, demonstrate a proof of concept of this approach, embed the concept within the broader context of model evaluation and scenario analysis for conservation policy, and highlight lessons from other modeling communities.

An Expanded Framework for Community Viability Analysis

Community viability analysis (CVA) has been put forth as an analogue for population viability analysis (PVA), an accepted conservation tool for evaluating species-specific threat and management scenarios. The original proposal recommended that CVAs examine resistance-based questions. PVAs, however, are broadly applicable to multiple types of viability questions, suggesting that the original CVA definition may be too narrow. In the present article, we advance an expanded framework in which CVA includes any analysis assessing the status, threats, or management options of an ecological community. We discuss viability questions that can be investigated with CVA. We group those inquiries into categories of resistance, resilience, and persistence, and provide case studies for each. Finally, we broadly present the steps in a CVA.

Lessons from 30 years of population viability analysis of wildlife populations

Population viability analysis (PVA) has been used for three decades to assess threats and evaluate conservation options for wildlife populations. What has been learned from PVA on in situ populations are valuable lessons also for assessing and managing viability and sustainability of ex situ populations. The dynamics of individual populations are unpredictable, due to limited knowledge about important factors, variability in the environment, and the probabilistic nature of demographic events. PVA considers such uncertainty within simulations that generate the distribution of likely fates for a population; management of ex situ populations should also take into consideration the uncertainty in our data and in the trajectories of populations. The processes affecting wildlife populations interact, with feedbacks often leading to amplified threats to viability; projections of ex situ populations should include such feedbacks to allow for management that foresees and responds to the cumulative and synergistic threats. PVA is useful for evaluating conservation options only if the goals for each population and measures of success are first clearly identified; similarly, for ex situ populations to contribute maximally to species conservation, the purposes for the population and definitions of sustainability in terms of acceptable risk must be documented. PVA requires a lot of data, knowledge of many processes affecting the populations, modeling expertize, and understanding of management goals and constraints. Therefore, to be useful in guiding conservation it must be a collaborative, trans-disciplinary, and social process. PVA can help integrate management of in situ and ex situ populations within comprehensive species conservation plans.

Evaluating anthropogenic threats to endangered killer whales to inform effective recovery plans

Understanding cumulative effects of multiple threats is key to guiding effective management to conserve endangered species. The critically endangered, Southern Resident killer whale population of the northeastern Pacific Ocean provides a data-rich case to explore anthropogenic threats on population viability. Primary threats include: limitation of preferred prey, Chinook salmon; anthropogenic noise and disturbance, which reduce foraging efficiency; and high levels of stored contaminants, including PCBs. We constructed a population viability analysis to explore possible demographic trajectories and the relative importance of anthropogenic stressors. The population is fragile, with no growth projected under current conditions, and decline expected if new or increased threats are imposed. Improvements in fecundity and calf survival are needed to reach a conservation objective of 2.3% annual population growth. Prey limitation is the most important factor affecting population growth. However, to meet recovery targets through prey management alone, Chinook abundance would have to be sustained near the highest levels since the 1970s. The most optimistic mitigation of noise and contaminants would make the difference between a declining and increasing population, but would be insufficient to reach recovery targets. Reducing acoustic disturbance by 50% combined with increasing Chinook by 15% would allow the population to reach 2.3% growth.

Dynamic, spatial models of parasite transmission in wildlife: Their structure, applications and remaining challenges

Individual differences in contact rate can arise from host, group and landscape heterogeneity and can result in different patterns of spatial spread for diseases in wildlife populations with concomitant implications for disease control in wildlife of conservation concern, livestock and humans. While dynamic disease models can provide a better understanding of the drivers of spatial spread, the effects of landscape heterogeneity have only been modelled in a few well-studied wildlife systems such as rabies and bovine tuberculosis. Such spatial models tend to be either purely theoretical with intrinsic limiting assumptions or individual-based models that are often highly species- and system-specific, limiting the breadth of their utility. Our goal was to review studies that have utilized dynamic, spatial models to answer questions about pathogen transmission in wildlife and identify key gaps in the literature. We begin by providing an overview of the main types of dynamic, spatial models (e.g., metapopulation, network, lattice, cellular automata, individual-based and continuous-space) and their relation to each other. We investigate different types of ecological questions that these models have been used to explore: pathogen invasion dynamics and range expansion, spatial heterogeneity and pathogen persistence, the implications of management and intervention strategies and the role of evolution in host-pathogen dynamics. We reviewed 168 studies that consider pathogen transmission in free-ranging wildlife and classify them by the model type employed, the focal host-pathogen system, and their overall research themes and motivation. We observed a significant focus on mammalian hosts, a few well-studied or purely theoretical pathogen systems, and a lack of studies occurring at the wildlife-public health or wildlife-livestock interfaces. Finally, we discuss challenges and future directions in the context of unprecedented human-mediated environmental change. Spatial models may provide new insights into understanding, for example, how global warming and habitat disturbance contribute to disease maintenance and emergence. Moving forward, better integration of dynamic, spatial disease models with approaches from movement ecology, landscape genetics/genomics and ecoimmunology may provide new avenues for investigation and aid in the control of zoonotic and emerging infectious diseases.

Species-level persistence probabilities for recovery and conservation status assessment

Recovery planning for species listed under the U.S. Endangered Species Act has been hampered by a lack of consistency and transparency, which can be improved by implementing a standardized approach for evaluating species status and developing measurable recovery criteria. However, managers lack an assessment method that integrates threat abatement and can be used when demographic data are limited. To help meet these needs, we demonstrated an approach for evaluating species status based on habitat configuration data. We applied 3 established persistence measures (patch occupancy, metapopulation capacity, and proportion of population lost) to compare 2 conservation strategies (critical habitat designated by the U.S. Fish and Wildlife Service and the Forest Service's Carbonate Habitat Management Strategy) and 2 threat scenarios (maximum limestone mining, removal of all habitat in areas with mining claims; minimum mining, removal of habitat only in areas with existing operations and high-quality ore) against a baseline of existing habitat for 3 federally listed plant species. Protecting all area within the designated critical habitat maintained a similar level (83.9-99.9%) of species persistence as the baseline, whereas maximum mining greatly reduced persistence (0.51-38.4% maintained). The 3 persistence measures provided complementary insights reflecting different aspects of habitat availability (total area, number of patches, patch size, and connectivity). These measures can be used to link recovery criteria developed following the 3 R principles (representation, redundancy, and resilience) to the resulting improvements in species viability. By focusing on amount and distribution of habitat, our method provides a means of assessing the status of data-poor species to inform decision making under the Endangered Species Act.

The sociality-health-fitness nexus: synthesis, conclusions and future directions

This theme issue has highlighted the links between sociality, health and fitness in a broad range of organisms, and with approaches that include field and captive studies of animals, comparative and meta-analyses, theoretical modelling and clinical and psychological studies of humans. In this concluding chapter, we synthesize the results of these diverse studies into some of the key concepts discussed in this issue, focusing on risks of infectious disease through social contact, the effects of competition in groups on susceptibility to disease, and the integration of sociality into research on life-history trade-offs. Interestingly, the studies in this issue both support pre-existing hypotheses, and in other ways challenge those hypotheses. We focus on unexpected results, including a lack of association between ectoparasites and fitness and weak results from a meta-analysis of the links between dominance rank and immune function, and place these results in a broader context. We also review relevant topics that were not covered fully in this theme issue, including self-medication and sickness behaviours, society-level defences against infectious disease, sexual selection, evolutionary medicine, implications for conservation biology and selective pressures on parasite traits. We conclude by identifying general open questions to stimulate and guide future research on the links between sociality, health and fitness.

Yellow fever impact on brown howler monkeys (Alouatta guariba clamitans) in Argentina: a metamodelling approach based on population viability analysis and epidemiological dynamics

In South America, yellow fever (YF) is an established infectious disease that has been identified outside of its traditional endemic areas, affecting human and nonhuman primate (NHP) populations. In the epidemics that occurred in Argentina between 2007-2009, several outbreaks affecting humans and howler monkeys (Alouatta spp) were reported, highlighting the importance of this disease in the context of conservation medicine and public health policies. Considering the lack of information about YF dynamics in New World NHP, our main goal was to apply modelling tools to better understand YF transmission dynamics among endangered brown howler monkey (Alouatta guariba clamitans) populations in northeastern Argentina. Two complementary modelling tools were used to evaluate brown howler population dynamics in the presence of the disease: Vortex, a stochastic demographic simulation model, and Outbreak, a stochastic disease epidemiology simulation. The baseline model of YF disease epidemiology predicted a very high probability of population decline over the next 100 years. We believe the modelling approach discussed here is a reasonable description of the disease and its effects on the howler monkey population and can be useful to support evidence-based decision-making to guide actions at a regional level.

Timing and severity of immunizing diseases in rabbits is controlled by seasonal matching of host and pathogen dynamics

Infectious diseases can exert a strong influence on the dynamics of host populations, but it remains unclear why such disease-mediated control only occurs under particular environmental conditions. We used 16 years of detailed field data on invasive European rabbits (Oryctolagus cuniculus) in Australia, linked to individual-based stochastic models and Bayesian approximations, to test whether (i) mortality associated with rabbit haemorrhagic disease (RHD) is driven primarily by seasonal matches/mismatches between demographic rates and epidemiological dynamics and (ii) delayed infection (arising from insusceptibility and maternal antibodies in juveniles) are important factors in determining disease severity and local population persistence of rabbits. We found that both the timing of reproduction and exposure to viruses drove recurrent seasonal epidemics of RHD. Protection conferred by insusceptibility and maternal antibodies controlled seasonal disease outbreaks by delaying infection; this could have also allowed escape from disease. The persistence of local populations was a stochastic outcome of recovery rates from both RHD and myxomatosis. If susceptibility to RHD is delayed, myxomatosis will have a pronounced effect on population extirpation when the two viruses coexist. This has important implications for wildlife management, because it is likely that such seasonal interplay and disease dynamics has a strong effect on long-term population viability for many species.

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.