Trends in anecdotal fox sightings in Tasmania accounted for by psychological factors

There has been little evaluation of anecdotal sightings as a means to confirm new incursions of invasive species. This paper explores the potential for equivocal information communicated by the media to account for patterns of anecdotal reports. In 2001, it was widely reported that red foxes (Vulpes vulpes) had been deliberately released in the island state of Tasmania (Australia), although this claim was later revealed to be baseless. Regardless, by 2013 a total of 3153 anecdotal fox sightings had been reported by members of the public, which implied their distribution was wide. For each month in 2001–2003, we defined a monthly media index (MMI) of fox‐related media coverage, an index of their relative seasonal abundance (abundance), and a factor denoting claims of fox evidence (claimed evidence) regardless of its evidentiary quality. We fitted a generalized linear model with Poisson error for monthly totals of anecdotal sightings with factors of year and claimed evidence and covariates of MMI, abundance, and hours of darkness. The collective effect of psychological factors (MMI, claimed evidence, and year) relative to biophysical factors (photoperiod and abundance) was highly significant (χ² = 122.1, df = 6, p < 0.0001), whereas anticipated changes in abundance had no significant influence on reported sightings (p = 0.15). An annual index of fox media from 2001 to 2010 was strongly associated with the yearly tally of anecdotal sightings (p = 0.018). The odds ratio of sightings ranked as reliable by the fox eradication program in any year decreased exponentially at a rate of 0.00643 as the total number of sightings increased (p < 0.0001) and was indicative of an observer‐expectancy bias. Our results suggest anecdotal sightings are highly susceptible to cognitive biases and when used to qualify and quantify species presence can contribute to flawed risk assessments.     

Costs of Integrating Economics and Conservation Planning

Abstract: Recent literature on systematic conservation planning has focused strongly on economics. It is a necessary component of efficient conservation planning because the question is about effective resource allocation. Nevertheless, there is an increasing tendency toward economic factors overriding biological considerations. Focusing too narrowly on economic cost may lead us back toward solutions resembling those obtained by opportunistic choice of areas, the avoidance of which was the motivation for development of systematic approaches. Moreover, there are many overlooked difficulties in incorporating economic considerations reliably into conservation planning because available economic data and the free market are complex. For instance, economies based on free markets tend to be shortsighted, whereas biodiversity conservation aims far into the future. Although economic data are necessary, they should not be relied on too heavily or considered separately from other sociopolitical factors. We suggest focusing on development of more‐comprehensive ecological‐economic modeling, while not forgetting the importance of purely biological analyses that are needed as a point of reference for evaluating conservation outcomes.     

Catalyzing sustainable fisheries management through behavior change interventions

Small-scale fisheries are an important livelihood and primary protein source for coastal communities in many of the poorest regions in the world, yet many are overfished and thus require effective and scalable management solutions. Positive ecological and socioeconomic responses to management typically lag behind immediate costs borne by fishers from fishing pressure reductions necessary for fisheries recovery. These short-term costs challenge the long-term success of these interventions. However, social marketing may increase perceptions of management benefits before ecological and socioeconomic benefits are fully realized, driving new social norms and ultimately long-term sustainable behavior change. By conducting underwater visual surveys to quantify ecological conditions and by conducting household surveys with community members to quantify their perceptions of management support and socioeconomic conditions, we assessed the impact of a standardized small-scale fisheries management intervention that was implemented across 41 sites in Brazil, Indonesia, and the Philippines. The intervention combines TURF reserves (community-based territorial use rights for fishing coupled with no-take marine reserves) with locally tailored social-marketing behavior change campaigns. Leveraging data across 22 indicators and 4 survey types, along with data from 3 control sites, we found that ecological and socioeconomic impacts varied and that communities supported the intervention and were already changing their fishing practices. These results suggest that communities were developing new social norms and fishing more sustainably before long-term ecological and socioeconomic benefits of fisheries management materialized.     

An occupancy‐based quantification of the highly imperiled status of desert fishes of the southwestern United States

Desert fishes are some of the most imperiled vertebrates worldwide due to their low economic worth and because they compete with humans for water. An ecological complex of fishes, 2 suckers (Catostomus latipinnis, Catostomus discobolus) and a chub (Gila robusta) (collectively managed as the so‐called three species) are endemic to the U.S. Colorado River Basin, are affected by multiple stressors, and have allegedly declined dramatically. We built a series of occupancy models to determine relationships between trends in occupancy, local extinction, and local colonization rates, identify potential limiting factors, and evaluate the suitability of managing the 3 species collectively. For a historical period (1889–2011), top performing models (AICc) included a positive time trend in local extinction probability and a negative trend in local colonization probability. As flood frequency decreased post‐development local extinction probability increased. By the end of the time series, 47% (95% CI 34‐61) and 15% (95% CI 6‐33) of sites remained occupied by the suckers and the chub, respectively, and models with the 2 species of sucker as one group and the chub as the other performed best. For a contemporary period (2001?2011), top performing (based on AIC_c) models included peak annual discharge. As peak discharge increased, local extinction probability decreased and local colonization probability increased. For the contemporary period, results of models that split all 3 species into separate groups were similar to results of models that combined the 2 suckers but not the chub. Collectively, these results confirmed that declines in these fishes were strongly associated with water development and that relative to their historic distribution all 3 species have declined dramatically. Further, the chub was distinct in that it declined the most dramatically and therefore may need to be managed separately. Our modeling approach may be useful in other situations in which targeted data are sparse and conservation status and best management approach for multiple species are uncertain.     

Planning for ex situ conservation in the face of uncertainty

Ex situ conservation strategies for threatened species often require long‐term commitment and financial investment to achieve management objectives. We present a framework that considers the decision to adopt ex situ management for a target species as the end point of several linked decisions. We used a decision tree to intuitively represent the logical sequence of decision making. The first decision is to identify the specific management actions most likely to achieve the fundamental objectives of the recovery plan, with or without the use of ex‐situ populations. Once this decision has been made, one decides whether to establish an ex situ population, accounting for the probability of success in the initial phase of the recovery plan, for example, the probability of successful breeding in captivity. Approaching these decisions in the reverse order (attempting to establish an ex situ population before its purpose is clearly defined) can lead to a poor allocation of resources, because it may restrict the range of available decisions in the second stage. We applied our decision framework to the recovery program for the threatened spotted tree frog (Litoria spenceri) of southeastern Australia. Across a range of possible management actions, only those including ex situ management were expected to provide >50% probability of the species’ persistence, but these actions cost more than use of in situ alternatives only. The expected benefits of ex situ actions were predicted to be offset by additional uncertainty and stochasticity associated with establishing and maintaining ex situ populations. Naïvely implementing ex situ conservation strategies can lead to inefficient management. Our framework may help managers explicitly evaluate objectives, management options, and the probability of success prior to establishing a captive colony of any given species.     

Current Practice and Future Prospects for Social Data in Coastal and Ocean Planning

Coastal and ocean planning comprises a broad field of practice. The goals, political processes, and approaches applied to planning initiatives may vary widely. However, all planning processes ultimately require adequate information on both the biophysical and social attributes of a planning region. In coastal and ocean planning practice, there are well‐established methods to assess biophysical attributes; however, less is understood about the role and assessment of social data. We conducted the first global assessment of the incorporation of social data in coastal and ocean planning. We drew on a comprehensive review of planning initiatives and a survey of coastal and ocean practitioners. There was significantly more incorporation of social data in multiuse versus conservation‐oriented planning. Practitioners engaged a wide range of social data, including governance, economic, and cultural attributes of planning regions and human impacts data. Less attention was given to ecosystem services and social–ecological linkages, both of which could improve coastal and ocean planning practice. Although practitioners recognize the value of social data, little funding is devoted to its collection and incorporation in plans. Increased capacity and sophistication in acquiring critical social and ecological data for planning is necessary to develop plans for more resilient coastal and ocean ecosystems and communities. We suggest that improving social data monitoring, and in particular spatial social data, to complement biophysical data, is necessary for providing holistic information for decision‐support tools and other methods. Moving beyond people as impacts to people as beneficiaries, through ecosystem services assessments, holds much potential to better incorporate the tenets of ecosystem‐based management into coastal and ocean planning by providing targets for linked biodiversity conservation and human welfare outcomes. La Práctica Actual y los Prospectos Futuros para los Datos Sociales en la Planeación Costera y Oceánica     

Automated conservation assessment of the orchid family with deep learning

International Union for Conservation of Nature (IUCN) Red List assessments are essential for prioritizing conservation needs but are resource intensive and therefore available only for a fraction of global species richness. Automated conservation assessments based on digitally available geographic occurrence records can be a rapid alternative, but it is unclear how reliable these assessments are. We conducted automated conservation assessments for 13,910 species (47.3% of the known species in the family) of the diverse and globally distributed orchid family (Orchidaceae), for which most species (13,049) were previously unassessed by IUCN. We used a novel method based on a deep neural network (IUC-NN). We identified 4,342 orchid species (31.2% of the evaluated species) as possibly threatened with extinction (equivalent to IUCN categories critically endangered [CR], endangered [EN], or vulnerable [VU]) and Madagascar, East Africa, Southeast Asia, and several oceanic islands as priority areas for orchid conservation. Orchidaceae provided a model with which to test the sensitivity of automated assessment methods to problems with data availability, data quality, and geographic sampling bias. The IUC-NN identified possibly threatened species with an accuracy of 84.3%, with significantly lower geographic evaluation bias relative to the IUCN Red List and was robust even when data availability was low and there were geographic errors in the input data. Overall, our results demonstrate that automated assessments have an important role to play in identifying species at the greatest risk of extinction.     

Ethics and governance for internet-based conservation science research

Internet-based research is increasingly important for conservation science and has wide-ranging applications and contexts, including culturomics, illegal wildlife trade, and citizen science. However, online research methods pose a range of ethical and legal challenges. Online data may be protected by copyright, database rights, or contract law. Privacy rights may also restrict the use and access of data, as well as ethical requirements from institutions. Online data have real-world meaning, and the ethical treatment of individuals and communities must not be marginalized when conducting internet-based research. As ethics frameworks originally developed for biomedical applications are inadequate for these methods, we propose that research activities involving the analysis of preexisting online data be treated analogous to offline social science methods, in particular, nondeceptive covert observation. By treating internet users and their data with respect and due consideration, conservationists can uphold the public trust needed to effectively address real-world issues.     

Conservation of biodiversity through taxonomy,data publication,and collaborative infrastructures

Taxonomy is the foundation of biodiversity science because it furthers discovery of new species. Globally, there have never been so many people involved in naming species new to science. The number of new marine species described per decade has never been greater. Nevertheless, it is estimated that tens of thousands of marine species, and hundreds of thousands of terrestrial species, are yet to be discovered; many of which may already be in specimen collections. However, naming species is only a first step in documenting knowledge about their biology, biogeography, and ecology. Considering the threats to biodiversity, new knowledge of existing species and discovery of undescribed species and their subsequent study are urgently required. To accelerate this research, we recommend, and cite examples of, more and better communication: use of collaborative online databases; easier access to knowledge and specimens; production of taxonomic revisions and species identification guides; engagement of nonspecialists; and international collaboration. “Data‐sharing” should be abandoned in favor of mandated data publication by the conservation science community. Such a step requires support from peer reviewers, editors, journals, and conservation organizations. Online data publication infrastructures (e.g., Global Biodiversity Information Facility, Ocean Biogeographic Information System) illustrate gaps in biodiversity sampling and may provide common ground for long‐term international collaboration between scientists and conservation organizations.     

Population Viability Analysis with Species Occurrence Data from Museum Collections

Abstract: The most comprehensive data on many species come from scientific collections. Thus, we developed a method of population viability analysis (PVA) in which this type of occurrence data can be used. In contrast to classical PVA, our approach accounts for the inherent observation error in occurrence data and allows the estimation of the population parameters needed for viability analysis. We tested the sensitivity of the approach to spatial resolution of the data, length of the time series, sampling effort, and detection probability with simulated data and conducted PVAs for common, rare, and threatened species. We compared the results of these PVAs with results of standard method PVAs in which observation error is ignored. Our method provided realistic estimates of population growth terms and quasi‐extinction risk in cases in which the standard method without observation error could not. For low values of any of the sampling variables we tested, precision decreased, and in some cases biased estimates resulted. The results of our PVAs with the example species were consistent with information in the literature on these species. Our approach may facilitate PVA for a wide range of species of conservation concern for which demographic data are lacking but occurrence data are readily available.