Threats to Neglected Biodiversity: Conservation Success Requires More Than Charisma

Our planet is home to an incredible array of species; however, relatively few studies have compared how anthropogenic threats impact taxonomic groups over time. Our objective was to identify temporal trends in threats facing the four most speciose phyla protected by the United States Endangered Species Act: angiosperms, arthropods, chordates, and mollusks. We determined presence or absence of threats for each species in these phyla by reviewing Final Rule listing decisions. For each phylum, we evaluated whether there was a linear, quadratic, or pseudo-threshold association between year of listing and the presence of 24 anthropogenic threats. We identified temporal trends for 80% of the 96 threat-phylum combinations. We classified threats as topmost (probability of being included in a species' listing decision peaking at ≥ 0.81) and escalating (probability of being included in a listing decision increasing by ≥ 0.81 between a species' first and most recent years of listing). Angiosperms, arthropods, and mollusks each had more topmost and escalating threats than chordates. Percentages of topmost threats were 42.9% (N = 21) for mollusks, 36.4% (N = 22) for angiosperms, and 33.3% (N = 21) for arthropods. Percentages of escalating threats were 22.7% (N = 22) for angiosperms and 14.3% (N = 21) for arthropods and mollusks. In contrast, percentages of topmost and escalating threats were only 4.2% (N = 24) for chordates, this one threat being climate change. Our research suggests potential conservation successes; some overutilization and pollution threats showed only gradually increasing or declining trends for certain phyla. We identified authorized take impacting angiosperms as the sole threat-phylum combination for which the threat had been consistently decreasing since the phylum's first year of listing. Conversely, species interactions, environmental stochasticity, and demographic stochasticity threats have seen drastic increases across all phyla; we suggest conservation efforts focus on these areas of increasing concern. We also recommend that resources be allocated to phyla with numerous topmost and escalating threats, not just to chordates.

The Last Two Remaining Populations of the Critically Endangered Estuarine Pipefish Are Inbred and Not Genetically Distinct

The critically endangered estuarine pipefish, Syngnathus watermeyeri, is one of Africa’s rarest fish species and currently faces a significant risk of extinction. A combination of anthropogenic and natural factors threaten submerged macrophyte beds in the two South African estuaries (Bushmans and Kariega) in which the species’ only two known remaining populations reside. Here, we genotyped 34 pipefish from both populations using genome-wide data to determine whether the two estuaries harbour distinct genetic diversity, such that translocating individuals between them might improve the genetic health of both. Our results show that both populations are highly inbred, and no statistically significant genetic structure was found between them. Moreover, individuals both within and between estuaries were very closely related to each other. These results indicate that the remaining populations of the estuarine pipefish suffer from the adverse genetic effects of small population sizes. Even though recent surveys have estimated population sizes in the order of thousands of individuals, these may fluctuate considerably. Although the translocation of genetically similar individuals between habitats will not increase local genetic diversity, the creation of additional populations across the species’ historical range may be a suitable conservation strategy to prevent further loss of genetic diversity, and to minimise the overall extinction risk posed by environmental stochasticity.

Switching costs in stochastic environments drive the emergence of matching behaviour in animal decision-making through the promotion of reward learning strategies

A principle of choice in animal decision-making named probability matching (PM) has long been detected in animals, and can arise from different decision-making strategies. Little is known about how environmental stochasticity may influence the switching time of these different decision-making strategies. Here we address this problem using a combination of behavioral and theoretical approaches, and show, that although a simple Win-Stay-Loss-Shift (WSLS) strategy can generate PM in binary-choice tasks theoretically, budgerigars (Melopsittacus undulates) actually apply a range of sub-tactics more often when they are expected to make more accurate decisions. Surprisingly, budgerigars did not get more rewards than would be predicted when adopting a WSLS strategy, and their decisions also exhibited PM. Instead, budgerigars followed a learning strategy based on reward history, which potentially benefits individuals indirectly from paying lower switching costs. Furthermore, our data suggest that more stochastic environments may promote reward learning through significantly less switching. We suggest that switching costs driven by the stochasticity of an environmental niche can potentially represent an important selection pressure associated with decision-making that may play a key role in driving the evolution of complex cognition in animals.

Harvesting can stabilize population fluctuations and buffer the impacts of extreme climatic events

Harvesting can magnify the destabilizing effects of environmental perturbations on population dynamics and, thereby, increase extinction risk. However, population-dynamic theory predicts that impacts of harvesting depend on the type and strength of density-dependent regulation. Here, we used logistic population growth models and an empirical reindeer case study to show that low to moderate harvesting can actually buffer populations against environmental perturbations. This occurs because of density-dependent environmental stochasticity, where negative environmental impacts on vital rates are amplified at high population density due to intraspecific resource competition. Simulations from our population models show that even low levels of harvesting may prevent overabundance, thereby dampening population fluctuations and reducing the risk of population collapse and quasi-extinction following environmental perturbations. Thus, depending on the species’ life history and the strength of density-dependent environmental drivers, low to moderate harvesting can improve population resistance to increased climate variability and extreme weather expected under global warming.

Using historical dip net data to infer absence of flatwoods salamanders in stochastic environments

Local extinction and undetected presence are two very different biological phenomena, but they can be challenging to differentiate. Stochastic environments hamper the development of standardized monitoring schemes for wildlife, and make it more challenging to plan and evaluate the success of conservation efforts. To avoid reintroductions of species at risk that could jeopardize extant populations, managers attempting translocation events require a higher level of confidence that a failure to confirm presence represents a true absence. For many pond breeding amphibians, monitoring of the breeding population occurs indirectly through larval surveys. Larval development and successful recruitment only occurs after a sequence of appropriate environmental conditions, thus it is possible for a breeding population of adults to exist at a site but for detectability of the species to be functionally zero. We investigate how annual variability in detection influences long-term monitoring efforts of Reticulated Flatwoods Salamanders (Ambystoma bishopi) breeding in 29 wetlands in Florida. Using 8 years of historic dip net data, we simulate plausible monitoring scenarios that incorporate environmental stochasticity into estimates of detection probability. We found that annual variation in environmental conditions precluded a high degree of certainty in predicting site status for low-intensity monitoring schemes. Uncertainty was partly alleviated by increasing survey effort, but even at the highest level of sampling intensity assessed, multiple years of monitoring are required to confidently determine presence/absence at a site. Combined with assessments of habitat quality and landscape connectivity, our results can be used to identify sites suitable for reintroduction efforts. Our methodologies can be generally applied to increase the effectiveness of surveys for diverse organisms for which annual variability in detectability is known.

Generalized Counting Processes in a Stochastic Environment

This paper addresses the generalization of counting processes through the age formalism of Lévy Walks. Simple counting processes are introduced and their properties are analyzed: Poisson processes or fractional Poisson processes can be recovered as particular cases. The stationarity assumption in the renewal mechanism characterizing simple counting processes can be modified in different ways, leading to the definition of generalized counting processes. In the case that the transition mechanism of a counting process depends on the environmental conditions—i.e., the parameters describing the occurrence of new events are themselves stochastic processes—the counting processes is said to be influenced by environmental stochasticity. The properties of this class of processes are analyzed, providing several examples and applications and showing the occurrence of new phenomena related to the modulation of the long-term scaling exponent by environmental noise.

Tipping Cascades in a Multi-patch System with Noise and Spatial Coupling

Forecasting tipping points in spatially extended systems is a key area of interest to ecologists. A slowly declining spatially distributed population is an important example of an ecological system that could exhibit a cascade of tipping points. Here, we develop a spatial two-patch model with environmental stochasticity that is slowly forced through population collapse, in the presence of changing environmental conditions. We begin with a basic spatial model, then introduce a fast–slow version of the model using geometric singular perturbation theory, followed by the inclusion of stochasticity. Using the spectral density of the fluctuating subpopulation in each patch, we derive analytic expressions for candidate indicators of population extinction and evaluate their performance through a simulation study. We find that coupling and spatial heterogeneity decrease the magnitude of the proposed indicators in coupled populations relative to isolated populations. Moreover, the degree of coupling dictates the trends in summary statistics. We conclude that this theory may be applied to other contexts, including the control of invasive species.

Multi-species prey dynamics influence local survival in resident and wintering generalist predators

Stochasticity in food availability influences vital rates such as survival and fertility. Life-history theory predicts that in long-lived organisms, survival should be buffered against environmental stochasticity showing little temporal variability. Furthermore, to optimize survival prospects, many animal species perform migrations to wintering areas where food availability is larger. Species with large latitudinal distribution ranges may show populations that migrate and others that are resident, and they may co-occur in winter. One example of these species is the predatory raptor buzzard Buteo buteo. Here, we test whether temporal variability in the density of five small mammal species of prey inhabiting different habitats (shrubland and forests) influences local annual survival of buzzards in a wintering area depending on their age and residency status (residents versus wintering individuals). We found that prey density explained a considerable amount of annual changes in local survival, which was higher for older and resident birds. This difference in local survival likely corresponded to philopatry to the wintering area, which was larger for residents and increased when prey density was larger. The total density of prey inhabiting open shrublands was the variable explaining more variance in temporal variability of local survival, even though the study area is mostly occupied by woodlands. Temporal population dynamics of the different small mammals inhabiting shrublands were not synchronous, which suggests that buzzards preyed opportunistically on the most abundant prey each winter. Generalist predation may buffer the impact of resource unpredictability for pulsed and asynchronous prey dynamics, typical of small mammals in winter.

Long-Term Conservation Effects of Protected Areas in Stochastic Population Dynamics

Terrestrial and marine protected areas are essential tools in mitigating anthropogenic impacts and promoting population persistence and resource sustainability. Adequately implemented protected areas (PAs) aim to promote conservation by increasing population size and reducing its variability. To resolve how these effects depend on PA features, I develop and analyze new models of stochastic processes that encompass the fluctuations generated by demographic or environmental stochasticity in PAs management. The stochastic model is built upon individual processes. In the model, density-independent mortality, migration between PAs and non-PAs, organism preference for PAs, and size characterize the features of the PA. The effect of PAs size is also examined. The long-term conservation effects are quantified using the coefficient of variation (CV) of population size in PAs, where a lower CV indicates higher robustness in stochastic variations. The results from this study demonstrate that sufficiently reduced density-independent mortality in PAs and high site preference for PAs and immigration rate into PAs are likely to decrease the CV. However, different types of stochasticity induce rather different consequences: under demographic stochasticity, the CV is always reduced because PAs increase the population size therein, but an increased population size by PAs does not always decrease the CV under environmental stochasticity. The deterministic dynamics of the model are investigated, facilitating effective management decisions.