Effects of interactions between anthropogenic stressors and recurring perturbations on ecosystem resilience and collapse

Insights into declines in ecosystem resilience and their causes and effects can inform preemptive action to avoid ecosystem collapse and loss of biodiversity, ecosystem services, and human well-being. Empirical studies of ecosystem collapse are rare and hampered by ecosystem complexity, nonlinear and lagged responses, and interactions across scales. We investigated how an anthropogenic stressor could diminish ecosystem resilience to a recurring perturbation by altering a critical ecosystem driver. We studied groundwater-dependent, peat-accumulating, fire-prone wetlands known as upland swamps in southeastern Australia. We hypothesized that underground mining (stressor) reduces resilience of these wetlands to landscape fires (perturbation) by diminishing groundwater, a key ecosystem driver. We monitored soil moisture as an indicator of ecosystem resilience during and after underground mining. After landscape fire, we compared responses of multiple state variables representing ecosystem structure, composition, and function in swamps within the mining footprint with unmined reference swamps. Soil moisture declined without recovery in swamps with mine subsidence (i.e., undermined), but was maintained in reference swamps over 8 years (effect size 1.8). Relative to burned reference swamps, burned undermined swamps showed greater loss of peat via substrate combustion; reduced cover, height, and biomass of regenerating vegetation; reduced postfire plant species richness and abundance; altered plant species composition; increased mortality rates of woody plants; reduced postfire seedling recruitment; and extirpation of a hydrophilic animal. Undermined swamps therefore showed strong symptoms of postfire ecosystem collapse, whereas reference swamps regenerated vigorously. We found that an anthropogenic stressor diminished the resilience of an ecosystem to recurring perturbations, predisposing it to collapse. Avoidance of ecosystem collapse hinges on early diagnosis of mechanisms and preventative risk reduction. It may be possible to delay or ameliorate symptoms of collapse or to restore resilience, but the latter appears unlikely in our study system due to fundamental alteration of a critical ecosystem driver. Efectos de las interacciones entre los estresantes antropogénicos y las perturbaciones recurrentes sobre la resiliencia y el colapso de los ecosistemas     

Ecological metrics of biomass removed by three methods of purse-seine fishing for tunas in the eastern tropical Pacific Ocean

An ecosystem approach to fisheries management is a widely recognized goal, but describing and measuring the effects of a fishery on an ecosystem is difficult. Ecological information on the entire catch (all animals removed, whether retained or discarded) of both species targeted by the fishery and nontarget species (i.e., bycatch) is required. We used data from the well-documented purse-seine fishery for tunas (Thunnus albacares, T. obesus, and Katsuwonus pelamis) in the eastern tropical Pacific Ocean to examine the fishery's ecological effects. Purse-seine fishing in the eastern tropical Pacific is conducted in 3 ways that differ in the amount and composition of target species and bycatch. The choice of method depends on whether the tunas are swimming alone (unassociated sets), associated with dolphins (dolphin sets), or associated with floating objects (floating-object sets). Among the fishing methods, we compared catch on the basis of weight, number of individuals, trophic level, replacement time, and diversity. Floating-object sets removed 2-3 times as much biomass as the other 2 methods, depending on how removal was measured. Results of previous studies suggest the ecological effects of floating-object sets are thousands of times greater than the effects of other methods, but these results were derived from only numbers of discarded animals. Management of the fishery has been driven to a substantial extent by a focus on reducing bycatch, although discards are currently 4.8% of total catch by weight, compared with global averages of 7.5% for tuna longline fishing and 30.0% for midwater trawling. An ecosystem approach to fisheries management requires that ecological effects of fishing on all animals removed by a fishery, not just bycatch or discarded catch, be measured with a variety of metrics.     

Economic Valuation of Subsistence Harvest of Wildlife in Madagascar

Wildlife consumption can be viewed as an ecosystem provisioning service (the production of a material good through ecological functioning) because of wildlife's ability to persist under sustainable levels of harvest. We used the case of wildlife harvest and consumption in northeastern Madagascar to identify the distribution of these services to local households and communities to further our understanding of local reliance on natural resources. We inferred these benefits from demand curves built with data on wildlife sales transactions. On average, the value of wildlife provisioning represented 57% of annual household cash income in local communities from the Makira Natural Park and Masoala National Park, and harvested areas produced an economic return of U.S.$0.42 ha^?1· year^?1. Variability in value of harvested wildlife was high among communities and households with an approximate 2 orders of magnitude difference in the proportional value of wildlife to household income. The imputed price of harvested wildlife and its consumption were strongly associated (p< 0.001), and increases in price led to reduced harvest for consumption. Heightened monitoring and enforcement of hunting could increase the costs of harvesting and thus elevate the price and reduce consumption of wildlife. Increased enforcement would therefore be beneficial to biodiversity conservation but could limit local people's food supply. Specifically, our results provide an estimate of the cost of offsetting economic losses to local populations from the enforcement of conservation policies. By explicitly estimating the welfare effects of consumed wildlife, our results may inform targeted interventions by public health and development specialists as they allocate sparse funds to support regions, households, or individuals most vulnerable to changes in access to wildlife. Valoración Económica de la Caza de Subsistencia de Vida Silvestre en Madagascar     

Extinction in a hyperdiverse endemic Hawaiian land snail family and implications for the underestimation of invertebrate extinction

The International Union for Conservation of Nature (IUCN) Red List includes 832 species listed as extinct since 1600, a minuscule fraction of total biodiversity. This extinction rate is of the same order of magnitude as the background rate and has been used to downplay the biodiversity crisis. Invertebrates comprise 99% of biodiversity, yet the status of a negligible number has been assessed. We assessed extinction in the Hawaiian land snail family Amastridae (325 species, IUCN lists 33 as extinct). We did not use the stringent IUCN criteria, by which most invertebrates would be considered data deficient, but a more realistic approach comparing historical collections with modern surveys and expert knowledge. Of the 325 Amastridae species, 43 were originally described as fossil or subfossil and were assumed to be extinct. Of the remaining 282, we evaluated 88 as extinct and 15 as extant and determined that 179 species had insufficient evidence of extinction (though most are probably extinct). Results of statistical assessment of extinction probabilities were consistent with our expert evaluations of levels of extinction. Modeling various extinction scenarios yielded extinction rates of 0.4‐14.0% of the amastrid fauna per decade. The true rate of amastrid extinction has not been constant; generally, it has increased over time. We estimated a realistic average extinction rate as approximately 5%/decade since the first half of the nineteenth century. In general, oceanic island biotas are especially susceptible to extinction and global rate generalizations do not reflect this. Our approach could be used for other invertebrates, especially those with restricted ranges (e.g., islands), and such an approach may be the only way to evaluate invertebrates rapidly enough to keep up with ongoing extinction.     

Economic costs of achieving current conservation goals in the future as climate changes

Conservation of biologically diverse regions has thus far been accomplished largely through the establishment and maintenance of protected areas. Climate change is expected to shift climate space of many species outside existing reserve boundaries. We used climate-envelope models to examine shifts in climate space of 11 species that are representative of the Mount Hamilton Project area (MHPA) (California, U.S.A.), which includes areas within Alameda, Santa Clara, San Joaquin, Stanislaus, Merced, and San Benito counties and is in the state's Central Coast ecoregion. We used Marxan site-selection software to determine the minimum area required as climate changes to achieve a baseline conservation goal equal to 80% of existing climate space for all species in the MHPA through 2050 and 2100. Additionally, we assessed the costs associated with use of existing conservation strategies (land acquisition and management actions such as species translocation, monitoring, and captive breeding) necessary to meet current species-conservation goals as climate changes. Meeting conservation goals as climate changes through 2050 required an additional 256,000 ha (332%) of protected area, primarily to the south and west of the MHPA. Through 2050 the total cost of land acquisition and management was estimated at US$1.67-1.79 billion, or 139-149% of the cost of achieving the same conservation goals with no climate change. To maintain 80% of climate space through 2100 required nearly 380,000 additional hectares that would cost $2.46-2.62 billion, or 209-219% of the cost of achieving the same conservation goals with no climate change. Furthermore, maintaining 80% of existing climate space within California for 27% of the focal species was not possible by 2100 because climate space for these species did not exist in the state. The high costs of conserving species as the climate changes-that we found in an assessment of one conservation project-highlights the need for tools that will aid in iterative goal setting given the uncertainty of the effects of climate change and adaptive management that includes new conservation strategies and consideration of the long-term economic costs of conservation.     

Moving from trends to benchmarks by using regression tree analysis to find inbreeding thresholds in a critically endangered bird

Understanding how inbreeding affects endangered species in conservation breeding programs is essential for their recovery. The Hawaiian Crow (‘Alalā) (Corvus hawaiiensis) is one of the world's most endangered birds. It went extinct in the wild in 2002, and, until recent release efforts starting in 2016, nearly all of the population remained under human care for conservation breeding. Using pedigree inbreeding coefficients (F), we evaluated the effects of inbreeding on Hawaiian Crow offspring survival and reproductive success. We used regression tree analysis to identify the level of inbreeding (i.e., inbreeding threshold) that explains a substantial decrease in ‘Alalā offspring survival to recruitment. Similar to a previous study of inbreeding in ‘Alalā, we found that inbreeding had a negative impact on offspring survival but that parental (vs. artificial) egg incubation improved offspring survival to recruitment. Furthermore, we found that inbreeding did not substantially affect offspring reproductive success, based on the assumption that offspring that survive to adulthood breed with distantly related mates. Our novel application of regression tree analysis showed that offspring with inbreeding levels exceeding F = 0.098 were 69% less likely to survive to recruitment than more outbred offspring, providing a specific threshold value for ongoing population management. Our results emphasize the importance of assessing inbreeding depression across all life history stages, confirm the importance of prioritizing parental over artificial egg incubation in avian conservation breeding programs, and demonstrate the utility of regression tree analysis as a tool for identifying inbreeding thresholds, if present, in any pedigree-managed population.     

Controlling range expansion in habitat networks by adaptively targeting source populations

Controlling the spread of invasive species, pests, and pathogens is often logistically limited to interventions that target specific locations at specific periods. However, in complex, highly connected systems, such as marine environments connected by ocean currents, populations spread dynamically in both space and time via transient connectivity links. This results in nondeterministic future distributions of species in which local populations emerge dynamically and concurrently over a large area. The challenge, therefore, is to choose intervention locations that will maximize the effectiveness of the control efforts. We propose a novel method to manage dynamic species invasions and outbreaks that identifies the intervention locations most likely to curtail population expansion by selectively targeting local populations most likely to expand their future range. Critically, at any point during the development of the invasion or outbreak, the method identifies the local intervention that maximizes the long‐term benefit across the ecosystem by restricting species’ potential to spread. In so doing, the method adaptively selects the intervention targets under dynamically changing circumstances. To illustrate the effectiveness of the method we applied it to controlling the spread of crown‐of‐thorns starfish (Acanthaster sp.) outbreaks across Australia's Great Barrier Reef. Application of our method resulted in an 18‐fold relative improvement in management outcomes compared with a random targeting of reefs in putative starfish control scenarios. Although we focused on applying the method to reducing the spread of an unwanted species, it can also be used to facilitate the spread of desirable species through connectivity networks. For example, the method could be used to select those fragments of habitat most likely to rebuild a population if they were sufficiently well protected.     

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     

Modeling outcomes of approaches to sustained human and snow leopard coexistence

The snow leopard (Uncia uncia) is in danger of extinction. Killing to protect livestock is among the primary causes of its decline. Efforts to mitigate this threat have focused on balancing the need to conserve the snow leopard with the needs of local people in snow leopard habitat, many of whom rely on raising livestock for their livelihoods. Conservation of the snow leopard has the characteristics of a public good, and outside funding is required to support conservation efforts. There are 5 commonly discussed approaches to resolving this issue: (1) direct payments for conservation, (2) investments in protection from predation, (3) damage compensation payments, (4) investments in better livestock husbandry, and (5) leases of pastureland for wild prey. After a review of these 5 conservation strategies, an economic–ecologic model, which includes the interactions between the snow leopard, its wild prey, and livestock, is used to evaluate the 2 most promising conservation strategies. The model reveals that investments in protection from predation and leases of pastureland for wild prey are effective but only in delaying the eventual extinction of the snow leopard. To preserve the snow leopard, these approaches must be applied more aggressively and new ones explored.     

A dynamic simulation model to support reduction in illegal trade within legal wildlife markets

Sustainable wildlife trade is critical for biodiversity conservation, livelihoods, and food security. Regulatory frameworks are needed to secure these diverse benefits of sustainable wildlife trade. However, regulations limiting trade can backfire, sparking illegal trade if demand is not met by legal trade alone. Assessing how regulations affect wildlife market participants’ incentives is key to controlling illegal trade. Although much research has assessed how incentives at both the harvester and consumer ends of markets are affected by regulations, little has been done to understand the incentives of traders (i.e., intermediaries). We built a dynamic simulation model to support reduction in illegal wildlife trade within legal markets by focusing on incentives traders face to trade legal or illegal products. We used an Approximate Bayesian Computation approach to infer illegal trading dynamics and parameters that might be unknown (e.g., price of illegal products). We showcased the utility of the approach with a small-scale fishery case study in Chile, where we disentangled within-year dynamics of legal and illegal trading and found that the majority (∼77%) of traded fish is illegal. We utilized the model to assess the effect of policy interventions to improve the fishery's sustainability and explore the trade-offs between ecological, economic, and social goals. Scenario simulations showed that even significant increases (over 200%) in parameters proxying for policy interventions enabled only moderate improvements in ecological and social sustainability of the fishery at substantial economic cost. These results expose how unbalanced trader incentives are toward trading illegal over legal products in this fishery. Our model provides a novel tool for promoting sustainable wildlife trade in data-limited settings, which explicitly considers traders as critical players in wildlife markets. Sustainable wildlife trade requires incentivizing legal over illegal wildlife trade and consideration of the social, ecological, and economic impacts of interventions.