Use of ambiguous detections to improve estimates from species distribution models

As large carnivores recover throughout Europe, their distribution needs to be studied to determine their conservation status and assess the potential for human-carnivore conflicts. However, efficient monitoring of many large carnivore species is challenging due to their rarity, elusive behavior, and large home ranges. Their monitoring can include opportunistic sightings from citizens in addition to designed surveys. Two types of detection errors may occur in such monitoring schemes: false negatives and false positives. False-negative detections can be accounted for in species distribution models (SDMs) that deal with imperfect detection. False-positive detections, due to species misidentification, have rarely been accounted for in SDMs. Generally, researchers use ad hoc data-filtering methods to discard ambiguous observations prior to analysis. These practices may discard valuable ecological information on the distribution of a species. We investigated the costs and benefits of including data types that may include false positives rather than discarding them for SDMs of large carnivores. We used a dynamic occupancy model that simultaneously accounts for false negatives and positives to jointly analyze data that included both unambiguous detections and ambiguous detections. We used simulations to compare the performances of our model with a model fitted on unambiguous data only. We tested the 2 models in 4 scenarios in which parameters that control false-positive detections and true detections varied. We applied our model to data from the monitoring of the Eurasian lynx (Lynx lynx) in the European Alps. The addition of ambiguous detections increased the precision of parameter estimates. For the Eurasian lynx, incorporating ambiguous detections produced more precise estimates of the ecological parameters and revealed additional occupied sites in areas where the species is likely expanding. Overall, we found that ambiguous data should be considered when studying the distribution of large carnivores through the use of dynamic occupancy models that account for misidentification.     

A Comparison of Global Conservation Prioritization Models with Spatial Spending Patterns of Conservation Nongovernmental Organizations

Abstract: In recent decades, various conservation organizations have developed models to prioritize locations for conservation. Through a survey of the spending patterns of 281 conservation nongovernmental organizations (NGOs), we examined the relation between 2 such models and spatial patterns of spending by conservation NGOs in 44 countries in sub‐Saharan Africa. We tested whether, at the country level, the proportion of a country designated as a conservation priority was correlated with where NGOs spent money. For one model (the combination of Conservation International's hotspots and High Biodiversity Wilderness Areas, which are areas of high endemism with high or low levels of vegetation loss respectively), there was no relation between the proportion of a country designated as a priority and levels of NGO spending, including by the NGO associated with the model. In the second model (Global 200), the proportion of a country designated as a priority and the amount of money spent by NGOs were significantly and positively related. Less money was spent in countries in northern and western sub‐Saharan Africa than countries in southern and eastern Africa, relative to the proportion of the country designated as a conservation priority. We suggest that on the basis of our results some NGOs consider increasing their spending on the areas designated as of conservation priority which are currently relatively underfunded, although there are economic, political, cultural, historical, biological, and practical reasons why current spending patterns may not align with priority sites.     

Assumption‐versus data‐based approaches to summarizing species’ ranges

For conservation decision making, species’ geographic distributions are mapped using various approaches. Some such efforts have downscaled versions of coarse‐resolution extent‐of‐occurrence maps to fine resolutions for conservation planning. We examined the quality of the extent‐of‐occurrence maps as range summaries and the utility of refining those maps into fine‐resolution distributional hypotheses. Extent‐of‐occurrence maps tend to be overly simple, omit many known and well‐documented populations, and likely frequently include many areas not holding populations. Refinement steps involve typological assumptions about habitat preferences and elevational ranges of species, which can introduce substantial error in estimates of species’ true areas of distribution. However, no model‐evaluation steps are taken to assess the predictive ability of these models, so model inaccuracies are not noticed. Whereas range summaries derived by these methods may be useful in coarse‐grained, global‐extent studies, their continued use in on‐the‐ground conservation applications at fine spatial resolutions is not advisable in light of reliance on assumptions, lack of real spatial resolution, and lack of testing. In contrast, data‐driven techniques that integrate primary data on biodiversity occurrence with remotely sensed data that summarize environmental dimensions (i.e., ecological niche modeling or species distribution modeling) offer data‐driven solutions based on a minimum of assumptions that can be evaluated and validated quantitatively to offer a well‐founded, widely accepted method for summarizing species’ distributional patterns for conservation applications.     

The complex relationship between personal sense of connection to animals and self‐reported proenvironmental behaviors by zoo visitors

The global biodiversity crisis requires an engaged citizenry that provides collective support for public policies and recognizes the consequences of personal consumption decisions. Understanding the factors that affect personal engagement in proenvironmental behaviors is essential for the development of actionable conservation solutions. Zoos and aquariums may be some of the only places where many people can explore their relations with wild animals and proenvironmental behaviors. Using a moderated‐mediation analysis of a survey of U.S. zoo and aquarium visitors (n = 3588), we explored the relationship between the sense of connection to animals and self‐reported engagement in proenvironmental behaviors related to climate change and how this relationship is affected by certainty that climate change is happening, level of concern about climate change, and perceptions of effectiveness in personally addressing climate change. We found a significant, directional relationship between sense of connection to animals and self‐reported proenvironmental behaviors. Political inclination within the conservative to liberal spectrum did not affect the relationship. We conclude that a personal sense of connection to animals may provide a foundation for educational and communication strategies to enhance involvement in proenvironmental actions.     

Minimum area requirements for an at‐risk butterfly based on movement and demography

Determining the minimum area required to sustain populations has a long history in theoretical and conservation biology. Correlative approaches are often used to estimate minimum area requirements (MARs) based on relationships between area and the population size required for persistence or between species’ traits and distribution patterns across landscapes. Mechanistic approaches to estimating MAR facilitate prediction across space and time but are few. We used a mechanistic MAR model to determine the critical minimum patch size (CMP) for the Baltimore checkerspot butterfly (Euphydryas phaeton), a locally abundant species in decline along its southern range, and sister to several federally listed species. Our CMP is based on principles of diffusion, where individuals in smaller patches encounter edges and leave with higher probability than those in larger patches, potentially before reproducing. We estimated a CMP for the Baltimore checkerspot of 0.7–1.5 ha, in accordance with trait‐based MAR estimates. The diffusion rate on which we based this CMP was broadly similar when estimated at the landscape scale (comparing flight path vs. capture‐mark‐recapture data), and the estimated population growth rate was consistent with observed site trends. Our mechanistic approach to estimating MAR is appropriate for species whose movement follows a correlated random walk and may be useful where landscape‐scale distributions are difficult to assess, but demographic and movement data are obtainable from a single site or the literature. Just as simple estimates of lambda are often used to assess population viability, the principles of diffusion and CMP could provide a starting place for estimating MAR for conservation.     

The Ability of Landowners and Their Cooperatives to Leverage Payments Greater Than Opportunity Costs from Conservation Contracts

In negotiations over land‐right acquisitions, landowners have an informational advantage over conservation groups because they know more about the opportunity costs of conservation measures on their sites. This advantage creates the possibility that landowners will demand payments greater than the required minimum, where this minimum required payment is known as the landowner's willingness to accept (WTA). However, in recent studies of conservation costs, researchers have assumed landowners will accept conservation with minimum payments. We investigated the ability of landowners to demand payments above their WTA when a conservation group has identified multiple sites for protection. First, we estimated the maximum payment landowners could potentially demand, which is set when groups of landowners act as a cooperative. Next, through the simulation of conservation auctions, we explored the amount of money above landowners’ WTA (i.e., surplus) that conservation groups could cede to secure conservation agreements, again investigating the influence of landowner cooperatives. The simulations showed the informational advantage landowners held could make conservation investments up to 42% more expensive than suggested by the site WTAs. Moreover, all auctions resulted in landowners obtaining payments greater than their WTA; thus, it may be unrealistic to assume landowners will accept conservation contracts with minimum payments. Of particular significance for species conservation, conservation objectives focused on overall species richness, which therefore recognize site complementarity, create an incentive for landowners to form cooperatives to capture surplus. To the contrary, objectives in which sites are substitutes, such as the maximization of species occurrences, create a disincentive for cooperative formation. La Habilidad de Propietarios y Sus Cooperativas para Implementar Pagos Mayores que los Costos de Oportunidad en Contratos de Conservación     

Effects of Harvesting Flowers from Shrubs on the Persistence and Abundance of Wild Shrub Populations at Multiple Spatial Extents

Abstract: Wildflower harvesting is an economically important activity of which the ecological effects are poorly understood. We assessed how harvesting of flowers affects shrub persistence and abundance at multiple spatial extents. To this end, we built a process‐based model to examine the mean persistence and abundance of wild shrubs whose flowers are subject to harvest (serotinous Proteaceae in the South African Cape Floristic Region). First, we conducted a general sensitivity analysis of how harvesting affects persistence and abundance at nested spatial extents. For most spatial extents and combinations of demographic parameters, persistence and abundance of flowering shrubs decreased abruptly once harvesting rate exceeded a certain threshold. At larger extents, metapopulations supported higher harvesting rates before their persistence and abundance decreased, but persistence and abundance also decreased more abruptly due to harvesting than at smaller extents. This threshold rate of harvest varied with species’ dispersal ability, maximum reproductive rate, adult mortality, probability of extirpation or local extinction, strength of Allee effects, and carrying capacity. Moreover, spatial extent interacted with Allee effects and probability of extirpation because both these demographic properties affected the response of local populations to harvesting more strongly than they affected the response of metapopulations. Subsequently, we simulated the effects of harvesting on three Cape Floristic Region Proteaceae species and found that these species reacted differently to harvesting, but their persistence and abundance decreased at low rates of harvest. Our estimates of harvesting rates at maximum sustainable yield differed from those of previous investigations, perhaps because researchers used different estimates of demographic parameters, models of population dynamics, and spatial extent than we did. Good demographic knowledge and careful identification of the spatial extent of interest increases confidence in assessments and monitoring of the effects of harvesting. Our general sensitivity analysis improved understanding of harvesting effects on metapopulation dynamics and allowed qualitative assessment of the probability of extirpation of poorly studied species.     

Inbreeding Depression Accumulation across Life‐History Stages of the Endangered Takahe

Abstract: Studies evaluating the impact of inbreeding depression on population viability of threatened species tend to focus on the effects of inbreeding at a single life‐history stage (e.g., juvenile survival). We examined the effects of inbreeding across the full life‐history continuum, from survival up to adulthood, to subsequent reproductive success, and to the recruitment of second‐generation offspring, in wild Takahe ( Porphyrio hochstetteri ) by analyzing pedigree and fitness data collected over 21 breeding seasons. Although the effect size of inbreeding at individual life‐history stages was small, inbreeding depression accumulated across multiple life‐history stages and ultimately reduced long‐term fitness (i.e., successful recruitment of second‐generation offspring). The estimated total lethal equivalents (2B) summed across all life‐history stages were substantial (16.05, 95% CI 0.08–90.8) and equivalent to an 88% reduction in recruitment of second‐generation offspring for closely related pairs (e.g., sib–sib pairings) relative to unrelated pairs (according to the pedigree). A history of small population size in the Takahe could have contributed to partial purging of the genetic load and the low level of inbreeding depression detected at each single life‐history stage. Nevertheless, our results indicate that such “purged” populations can still exhibit substantial inbreeding depression, especially when small but negative fitness effects accumulate across the species’ life history. Because inbreeding depression can ultimately affect population viability of small, isolated populations, our results illustrate the importance of measuring the effects of inbreeding across the full life‐history continuum.     

Incorporating multidimensional behavior into a risk management tool for a critically endangered and migratory species

Conservation of migratory species exhibiting wide-ranging and multidimensional behaviors is challenged by management efforts that only utilize horizontal movements or produce static spatial–temporal products. For the deep-diving, critically endangered eastern Pacific leatherback turtle, tools that predict where turtles have high risks of fisheries interactions are urgently needed to prevent further population decline. We incorporated horizontal–vertical movement model results with spatial–temporal kernel density estimates and threat data (gear-specific fishing) to develop monthly maps of spatial risk. Specifically, we applied multistate hidden Markov models to a biotelemetry data set (n = 28 leatherback tracks, 2004–2007). Tracks with dive information were used to characterize turtle behavior as belonging to 1 of 3 states (transiting, residential with mixed diving, and residential with deep diving). Recent fishing effort data from Global Fishing Watch were integrated with predicted behaviors and monthly space-use estimates to create maps of relative risk of turtle–fisheries interactions. Drifting (pelagic) longline fishing gear had the highest average monthly fishing effort in the study region, and risk indices showed this gear to also have the greatest potential for high-risk interactions with turtles in a residential, deep-diving behavioral state. Monthly relative risk surfaces for all gears and behaviors were added to South Pacific TurtleWatch (SPTW) ( https://www.upwell.org/sptw ), a dynamic management tool for this leatherback population. These modifications will refine SPTW's capability to provide important predictions of potential high-risk bycatch areas for turtles undertaking specific behaviors. Our results demonstrate how multidimensional movement data, spatial–temporal density estimates, and threat data can be used to create a unique conservation tool. These methods serve as a framework for incorporating behavior into similar tools for other aquatic, aerial, and terrestrial taxa with multidimensional movement behaviors.     

Assigning trend-based conservation status despite high uncertainty

Estimates of temporal trends in species’ occupancy are essential for conservation policy and planning, but limitations to the data and models often result in very high trend uncertainty. A critical source of uncertainty that degrades scientific credibility is that caused by disagreement among studies or models. Modelers are aware of this uncertainty but usually only partially estimate it and communicate it to decision makers. At the same time, there is growing awareness that full disclosure of uncertainty is critical for effective translation of science into policies and plans. But what are the most effective approaches to estimating uncertainty and communicating uncertainty to decision makers? We explored how alternative approaches to estimating and communicating uncertainty of species trends could affect decisions concerning conservation status of freshwater fishes. We used ensemble models to propagate trend uncertainty within and among models and communicated this uncertainty with categorical distributions of trend direction and magnitude. All approaches were designed to fit an established decision-making system used to assign species conservation status by the New Zealand government. Our results showed how approaches that failed to fully disclose uncertainty, while simplifying the information presented, could hamper species conservation or lead to ineffective decisions. We recommend an approach that was recently used effectively to communicate trend uncertainty to a panel responsible for setting the conservation status of New Zealand's freshwater fishes.