Monitoring,imperfect detection,and risk optimization of a Tasmanian devil insurance population

Most species are imperfectly detected during biological surveys, which creates uncertainty around their abundance or presence at a given location. Decision makers managing threatened or pest species are regularly faced with this uncertainty. Wildlife diseases can drive species to extinction; thus, managing species with disease is an important part of conservation. Devil facial tumor disease (DFTD) is one such disease that led to the listing of the Tasmanian devil (Sarcophilus harrisii) as endangered. Managers aim to maintain devils in the wild by establishing disease‐free insurance populations at isolated sites. Often a resident DFTD‐affected population must first be removed. In a successful collaboration between decision scientists and wildlife managers, we used an accessible population model to inform monitoring decisions and facilitate the establishment of an insurance population of devils on Forestier Peninsula. We used a Bayesian catch‐effort model to estimate population size of a diseased population from removal and camera trap data. We also analyzed the costs and benefits of declaring the area disease‐free prior to reintroduction and establishment of a healthy insurance population. After the monitoring session in May–June 2015, the probability that all devils had been successfully removed was close to 1, even when we accounted for a possible introduction of a devil to the site. Given this high probability and the baseline cost of declaring population absence prematurely, we found it was not cost‐effective to carry out any additional monitoring before introducing the insurance population. Considering these results within the broader context of Tasmanian devil management, managers ultimately decided to implement an additional monitoring session before the introduction. This was a conservative decision that accounted for uncertainty in model estimates and for the broader nonmonetary costs of mistakenly declaring the area disease‐free.     

Identification of policies for a sustainable legal trade in rhinoceros horn based on population projection and socioeconomic models

Between 1990 and 2007, 15 southern white (Ceratotherium simum simum) and black (Diceros bicornis) rhinoceroses on average were killed illegally every year in South Africa. Since 2007 illegal killing of southern white rhinoceros for their horn has escalated to >950 individuals/year in 2013. We conducted an ecological–economic analysis to determine whether a legal trade in southern white rhinoceros horn could facilitate rhinoceros protection. Generalized linear models were used to examine the socioeconomic drivers of poaching, based on data collected from 1990 to 2013, and to project the total number of rhinoceroses likely to be illegally killed from 2014 to 2023. Rhinoceros population dynamics were then modeled under 8 different policy scenarios that could be implemented to control poaching. We also estimated the economic costs and benefits of each scenario under enhanced enforcement only and a legal trade in rhinoceros horn and used a decision support framework to rank the scenarios with the objective of maintaining the rhinoceros population above its current size while generating profit for local stakeholders. The southern white rhinoceros population was predicted to go extinct in the wild <20 years under present management. The optimal scenario to maintain the rhinoceros population above its current size was to provide a medium increase in antipoaching effort and to increase the monetary fine on conviction. Without legalizing the trade, implementing such a scenario would require covering costs equal to approximately $147,000,000/year. With a legal trade in rhinoceros horn, the conservation enterprise could potentially make a profit of $717,000,000/year. We believe the 35‐year‐old ban on rhinoceros horn products should not be lifted unless the money generated from trade is reinvested in improved protection of the rhinoceros population. Because current protection efforts seem to be failing, it is time to evaluate, discuss, and test alternatives to the present policy.     

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.     

A review of selection‐based tests of abiotic surrogates for species representation

Because conservation planners typically lack data on where species occur, environmental surrogates—including geophysical settings and climate types—have been used to prioritize sites within a planning area. We reviewed 622 evaluations of the effectiveness of abiotic surrogates in representing species in 19 study areas. Sites selected using abiotic surrogates represented more species than an equal number of randomly selected sites in 43% of tests (55% for plants) and on average improved on random selection of sites by about 8% (21% for plants). Environmental diversity (ED) (42% median improvement on random selection) and biotically informed clusters showed promising results and merit additional testing. We suggest 4 ways to improve performance of abiotic surrogates. First, analysts should consider a broad spectrum of candidate variables to define surrogates, including rarely used variables related to geographic separation, distance from coast, hydrology, and within‐site abiotic diversity. Second, abiotic surrogates should be defined at fine thematic resolution. Third, sites (the landscape units prioritized within a planning area) should be small enough to ensure that surrogates reflect species’ environments and to produce prioritizations that match the spatial resolution of conservation decisions. Fourth, if species inventories are available for some planning units, planners should define surrogates based on the abiotic variables that most influence species turnover in the planning area. Although species inventories increase the cost of using abiotic surrogates, a modest number of inventories could provide the data needed to select variables and evaluate surrogates. Additional tests of nonclimate abiotic surrogates are needed to evaluate the utility of conserving nature's stage as a strategy for conservation planning in the face of climate change.     

Emerging conservation challenges and prospects in an era of offshore hydrocarbon exploration and exploitation

Globally, extensive marine areas important for biodiversity conservation and ecosystem functioning are undergoing exploration and extraction of oil and natural gas resources. Such operations are expanding to previously inaccessible deep waters and other frontier regions, while conservation‐related legislation and planning is often lacking. Conservation challenges arising from offshore hydrocarbon development are wide‐ranging. These challenges include threats to ecosystems and marine species from oil spills, negative impacts on native biodiversity from invasive species colonizing drilling infrastructure, and increased political conflicts that can delay conservation actions. With mounting offshore operations, conservationists need to urgently consider some possible opportunities that could be leveraged for conservation. Leveraging options, as part of multi‐billion dollar marine hydrocarbon operations, include the use of facilities and costly equipment of the deep and ultra‐deep hydrocarbon industry for deep‐sea conservation research and monitoring and establishing new conservation research, practice, and monitoring funds and environmental offsetting schemes. The conservation community, including conservation scientists, should become more involved in the earliest planning and exploration phases and remain involved throughout the operations so as to influence decision making and promote continuous monitoring of biodiversity and ecosystems. A prompt response by conservation professionals to offshore oil and gas developments can mitigate impacts of future decisions and actions of the industry and governments. New environmental decision support tools can be used to explicitly incorporate the impacts of hydrocarbon operations on biodiversity into marine spatial and conservation plans and thus allow for optimum trade‐offs among multiple objectives, costs, and risks.     

Priority areas for conservation of and research focused on terrestrial vertebrates

Effective conservation policies require comprehensive knowledge of biodiversity. However, knowledge shortfalls still remain, hindering possibilities to improve decision making and built such policies. During the last 2 decades, conservationists have made great efforts to allocate resources as efficiently as possible but have rarely considered the idea that if research investments are also strategically allocated, it would likely fill knowledge gaps while simultaneously improving conservation actions. Therefore, prioritizing areas where both conservation and research actions could be conducted becomes a critical endeavor that can further maximize return on investment. We used Zonation, a conservation planning tool and geographical distributions of amphibians, birds, mammals, and reptiles to suggest and compare priority areas for conservation and research of terrestrial vertebrates worldwide. We also evaluated the degree of human disturbance in both types of priority areas by describing the value of the human footprint index within such areas. The spatial concordance between priority conservation and research areas was low: 0.36% of the world's land area. In these areas, we found it would be possible to protect almost half of the currently threatened species and to gather information on nearly 42% of data-deficient (DD) species. We also found that 6199 protected areas worldwide are located in such places, although only 35% of them have strict conservation purposes. Areas of consensus between conservation and research areas represent an opportunity for simultaneously conserving and acquiring knowledge of threatened and DD species of vertebrates. Although the picture is not the most encouraging, joint conservation and research efforts are possible and should be fostered to save vertebrate species from our own ignorance and extinction.     

Animal agency in wildlife conservation and management

Wildlife conservation and management (WCM) practices have been historically drawn from a wide variety of academic fields, yet practitioners have been slow to engage with emerging conversations about animals as complex beings, whose individuality and sociality influence their relationships with humans. We propose an explicit acknowledgement of wild, nonhuman animals as active participants in WCM. We examined 190 studies of WCM interventions and outcomes to highlight 3 common assumptions that underpin many present approaches to WCM: animal behaviors are rigid and homogeneous; wildlife exhibit idealized wild behavior and prefer pristine habitats; and human–wildlife relationships are of marginal or secondary importance relative to nonhuman interactions. We found that these management interventions insufficiently considered animal learning, decision-making, individuality, sociality, and relationships with humans and led to unanticipated detrimental outcomes. To address these shortcomings, we synthesized theoretical advances in animal behavioral sciences, animal geographies, and animal legal theory that may help conservation professionals reconceptualize animals and their relationships with humans. Based on advances in these fields, we constructed the concept of animal agency, which we define as the ability of animals to actively influence conservation and management outcomes through their adaptive, context-specific, and complex behaviors that are predicated on their sentience, individuality, lived experiences, cognition, sociality, and cultures in ways that shape and reshape shared human–wildlife cultures, spaces, and histories. Conservation practices, such as compassionate conservation, convivial conservation, and ecological justice, incorporate facets of animal agency. Animal agency can be incorporated in conservation problem-solving by assessing the ways in which agency contributes to species’ survival and by encouraging more adaptive and collaborative decision-making among human and nonhuman stakeholders.     

Effects of site-selection bias on estimates of biodiversity change

Estimates of biodiversity change are essential for the management and conservation of ecosystems. Accurate estimates rely on selecting representative sites, but monitoring often focuses on sites of special interest. How such site-selection biases influence estimates of biodiversity change is largely unknown. Site-selection bias potentially occurs across four major sources of biodiversity data, decreasing in likelihood from citizen science, museums, national park monitoring, and academic research. We defined site-selection bias as a preference for sites that are either densely populated (i.e., abundance bias) or species rich (i.e., richness bias). We simulated biodiversity change in a virtual landscape and tracked the observed biodiversity at a sampled site. The site was selected either randomly or with a site-selection bias. We used a simple spatially resolved, individual-based model to predict the movement or dispersal of individuals in and out of the chosen sampling site. Site-selection bias exaggerated estimates of biodiversity loss in sites selected with a bias by on average 300–400% compared with randomly selected sites. Based on our simulations, site-selection bias resulted in positive trends being estimated as negative trends: richness increase was estimated as 0.1 in randomly selected sites, whereas sites selected with a bias showed a richness change of −0.1 to −0.2 on average. Thus, site-selection bias may falsely indicate decreases in biodiversity. We varied sampling design and characteristics of the species and found that site-selection biases were strongest in short time series, for small grains, organisms with low dispersal ability, large regional species pools, and strong spatial aggregation. Based on these findings, to minimize site-selection bias, we recommend use of systematic site-selection schemes; maximizing sampling area; calculating biodiversity measures cumulatively across plots; and use of biodiversity measures that are less sensitive to rare species, such as the effective number of species. Awareness of the potential impact of site-selection bias is needed for biodiversity monitoring, the design of new studies on biodiversity change, and the interpretation of existing data.     

Identifying robust strategies for assisted migration in a competitive stochastic metacommunity

Assisted migration (AM) is the translocation of species beyond their historical range to locations that are expected to be more suitable under future climate change. However, a relocated population may fail to establish in its donor community if there is high uncertainty in decision-making, climate, and interactions with the recipient ecological community. To quantify the benefit to persistence and risk of establishment failure of AM under different management scenarios (e.g., choosing target species, proportion of population to relocate, and optimal location to relocate), we built a stochastic metacommunity model to simulate several species reproducing, dispersing, and competing on a temperature gradient as temperature increases over time. Without AM, the species were vulnerable to climate change when they had low population sizes, short dispersal, and strong poleward competition. When relocating species that exemplified these traits, AM increased the long-term persistence of the species most when relocating a fraction of the donor population, even if the remaining population was very small or rapidly declining. This suggests that leaving behind a fraction of the population could be a robust approach, allowing managers to repeat AM in case they move the species to the wrong place and at the wrong time, especially when it is difficult to identify a species’ optimal climate. We found that AM most benefitted species with low dispersal ability and least benefited species with narrow thermal tolerances, for which AM increased extinction risk on average. Although relocation did not affect the persistence of nontarget species in our simple competitive model, researchers will need to consider a more complete set of community interactions to comprehensively understand invasion potential.     

Effects of flow regimes altered by dams on survival, population declines, and range-wide losses of California river-breeding frogs

Widespread alteration of natural hydrologic patterns by large dams combined with peak demands for power and water delivery during summer months have resulted in frequent aseasonal flow pulses in rivers of western North America. Native species in these ecosystems have evolved with predictable annual flood-drought cycles; thus, their likelihood of persistence may decrease in response to disruption of the seasonal synchrony between stable low-flow conditions and reproduction. We evaluated whether altered flow regimes affected 2 native frogs in California and Oregon (U.S.A.) at 4 spatial and temporal extents. We examined changes in species distribution over approximately 50 years, current population density in 11 regulated and 16 unregulated rivers, temporal trends in abundance among populations occupying rivers with different hydrologic histories, and within-year patterns of survival relative to seasonal hydrology. The foothill yellow-legged frog (Rana boylii), which breeds only in flowing water, is more likely to be absent downstream of large dams than in free-flowing rivers, and breeding populations are on average 5 times smaller in regulated rivers than in unregulated rivers. Time series data (range = 8 - 19 years) from 5 populations of yellow-legged frogs and 2 populations of California red-legged frogs (R. draytonii) across a gradient of natural to highly artificial timing and magnitude of flooding indicate that variability of flows in spring and summer is strongly correlated with high mortality of early life stages and subsequent decreases in densities of adult females. Flow management that better mimics natural flow timing is likely to promote persistence of these species and others with similar phenology.