Effects of uncertainty and variability on population declines and IUCN Red List classifications

The International Union for Conservation of Nature (IUCN) Red List Categories and Criteria is a quantitative framework for classifying species according to extinction risk. Population models may be used to estimate extinction risk or population declines. Uncertainty and variability arise in threat classifications through measurement and process error in empirical data and uncertainty in the models used to estimate extinction risk and population declines. Furthermore, species traits are known to affect extinction risk. We investigated the effects of measurement and process error, model type, population growth rate, and age at first reproduction on the reliability of risk classifications based on projected population declines on IUCN Red List classifications. We used an age‐structured population model to simulate true population trajectories with different growth rates, reproductive ages and levels of variation, and subjected them to measurement error. We evaluated the ability of scalar and matrix models parameterized with these simulated time series to accurately capture the IUCN Red List classification generated with true population declines. Under all levels of measurement error tested and low process error, classifications were reasonably accurate; scalar and matrix models yielded roughly the same rate of misclassifications, but the distribution of errors differed; matrix models led to greater overestimation of extinction risk than underestimations; process error tended to contribute to misclassifications to a greater extent than measurement error; and more misclassifications occurred for fast, rather than slow, life histories. These results indicate that classifications of highly threatened taxa (i.e., taxa with low growth rates) under criterion A are more likely to be reliable than for less threatened taxa when assessed with population models. Greater scrutiny needs to be placed on data used to parameterize population models for species with high growth rates, particularly when available evidence indicates a potential transition to higher risk categories.     

Multiyear monitoring of survival following mitigation-driven translocation of a long-lived threatened reptile

Translocation is used by managers to mitigate the negative impacts of development on species. Moving individuals to a new location is challenging, and many translocation attempts have failed. Robust, posttranslocation monitoring is therefore important for evaluating effects of translocation on target species. We evaluated the efficacy of a translocation designed to mitigate the effects of a utility-scale solar energy project on the U.S. federally listed Mojave desert tortoise (Gopherus agassizii). The species is a long-lived reptile threatened by a variety of factors, including habitat loss due to renewable energy development in the Mojave Desert and portions of the Colorado Desert in southern California (southwestern United States). We translocated 58 individual tortoises away from the project's construction site and intensively monitored them over 5 years (2012–2017). We monitored these individuals and tortoises located in the translocation release area (resident tortoises; n = 112) and control tortoises (n = 149) in a nearby location. We used our tortoise encounter data and known-fate survival models to estimate annual and cumulative survival. Translocated tortoises in each of 2 size classes (120–160 mm, >160 mm) did not survive at lower rates than resident and control tortoises over the study period. For models with different sets of biotic and abiotic covariates, annual and cumulative estimates of survival were always >0.87 and >0.56, respectively. Larger tortoises tended to have higher survival, but translocated tortoises were not differentially affected by the covariates used to model variation in survival. Based on these findings, our translocation design and study protocols could inform other translocation projects for desert species. Our case study highlights the benefits of combining rigorous scientific monitoring with well-designed, mitigation-driven management actions to reduce the negative effects of development on species of conservation concern.     

Effect of decision rules in choice experiments on hunting and bushmeat trade

Providing insight on decisions to hunt and trade bushmeat can facilitate improved management interventions that typically include enforcement, alternative employment, and donation of livestock. Conservation interventions to regulate bushmeat hunting and trade have hitherto been based on assumptions of utility- (i.e., personal benefits) maximizing behavior, which influences the types of incentives designed. However, if individuals instead strive to minimize regret, interventions may be misguided. We tested support for 3 hypotheses regarding decision rules through a choice experiment in Tanzania. We estimated models based on the assumptions of random utility maximization (RUM) and pure random regret maximization (P-RRM) and combinations thereof. One of these models had an attribute-specific decision rule and another had a class-specific decision rule. The RUM model outperformed the P-RRM model, but the attribute-specific model performed better. Allowing respondents with different decision rules and preference heterogeneity within each decision rule in a class-specific model performed best, revealing that 55% of the sample used a P-RRM decision rule. Individuals using a P-RRM decision rule responded less to enforcement, salary, and livestock donation than did individuals using the RUM decision rule. Hence, 3 common strategies, enforcement, alternative income-generating activities, and providing livestock as a substitute protein, are likely less effective in changing the behavior of more than half of respondents. Only salary elicited a large (i.e. elastic) response, and only for one RUM class. Policies to regulate the bushmeat trade based solely on the assumption of individuals maximizing utility, may fail for a significant proportion of the sample. Despite the superior performance of models that allow both RUM and P-RRM decision rules there are drawbacks that must be considered before use in the Global South, where very little is known about the social–psychology of decision making.     

Major shifts in Amazon wildlife populations from recent intensification of floods and drought

In the western Amazon Basin, recent intensification of river‐level cycles has increased flooding during the wet seasons and decreased precipitation during the dry season. Greater than normal floods occurred in 2009 and in all years from 2011 to 2015 during high‐water seasons, and a drought occurred during the 2010 low‐water season. During these years, we surveyed populations of terrestrial, arboreal, and aquatic wildlife in a seasonally flooded Amazonian forest in the Loreto region of Peru (99,780 km²) to study the effects of intensification of natural climatic fluctuations on wildlife populations and in turn effects on resource use by local people. Shifts in fish and terrestrial mammal populations occurred during consecutive years of high floods and the drought of 2010. As floods intensified, terrestrial mammal populations decreased by 95%. Fish, waterfowl, and otter (Pteronura brasiliensis) abundances increased during years of intensive floods, whereas river dolphin and caiman populations had stable abundances. Arboreal species, including, macaws, game birds, primates, felids, and other arboreal mammals had stable populations and were not affected directly by high floods. The drought of 2010 had the opposite effect: fish, waterfowl, and dolphin populations decreased, and populations of terrestrial and arboreal species remained stable. Ungulates and large rodents are important sources of food and income for local people, and large declines in these animals has shifted resource use of people living in the flooded forests away from hunting to a greater reliance on fish.     

Audience segmentation to improve targeting of conservation interventions for hunters

Audience segmentation could help improve the effectiveness of conservation interventions. Marketers use audience segmentation to define the target audience of a campaign. The technique involves subdividing a general population into groups that share similar profiles, such as sociodemographic or behavioral characteristics. Interventions are then designed to target the group or groups of interest. We explored the potential of audience segmentation for use in defining conservation target groups with a case study of hunters in Liberia. Using 2 data sets describing households (n = 476) and hunters (n = 205), we applied a clustering method in which infinite binomial mixture models group hunters and households according to livelihood and behavior variables and a simple method to define target groups based on hunting impact (hunting households and high-impact hunters). Clusters of hunters and households differed in their experiences with confiscation of catch at roadblocks and participation in livelihood-support programs, indicating that these interventions operate unevenly across subsets of the population. By contrast, the simple method masked these insights because profiles of hunting households and high-impact hunters were similar to those of the general population. Clustering results could be used to guide the development of livelihood and regulatory interventions. For example, a commonly promoted agricultural activity, cocoa farming, was practiced by only 2% (out of 87) of the largest hunter cluster of nonlocal gun hunters but was prevalent among local trappers, suggesting that assistance aimed at cocoa farmers is less appropriate for the former group. Our results support the use of audience segmentation across multiple variables to improve targeted intervention designs in conservation.     

Environmental solutions sparked by environmental history

Environmental solutions require a decision-making process that is ultimately political, in that they involve decisions with uncertain outcomes and stakeholders with conflicting viewpoints. If this process seeks broad alignment between the government and public, then reconciling conflicting viewpoints is a key to the legitimacy of these decisions. We show that ecological baselines can be particularly powerful tools for creating a common understanding for public support (legitimacy) and conformity to new rules or regulations (legality) that enable the solution. They are powerful because they move the discussion of solutions from the abstract to the concrete by providing a conceptual model for a common expectation (e.g., restoring habitat). They provide narratives of the past (ecological histories) that readjust the future expectations of individuals on how to perceive and respond to new policy. While ecological baselines offer scientists benchmarks for reinstating ecological functions, they also normalize public and government discussion of solutions. This social normalization of public issues may assist government policy and influence social views, practices, and behaviors that adopt the policy. For science to more effectively inform conservation, we encourage interdisciplinary thinking (science- and human-centered) because it can provide public support and government legitimacy for investing in environmental solutions.     

Traps and transformations influencing the financial viability of tourism on private‐land conservation areas

The ability of private conservation organizations to remain financially viable is a key factor influencing their effectiveness. One‐third of financially motivated private‐land conservation areas (PLCAs) surveyed in South Africa are unprofitable, raising questions about landowners’ abilities to effectively adapt their business models to the socioeconomic environment. In any complex system, options for later adaptation can be constrained by starting conditions (path dependence). We tested 3 hypothesized drivers of path dependence in PLCA ecotourism and hunting business models: (H1) the initial size of a PLCA limits the number of mammalian game and thereby predators that can be sustained; (H2) initial investments in infrastructure limit the ability to introduce predators; and (H3) rainfall limits game and predator abundance. We further assessed how managing for financial stability (optimized game stocking) or ecological sustainability (allowing game to fluctuate with environmental conditions) influenced the ability to overcome path dependence. A mechanistic PLCA model based on simple ecological and financial rules was run for different initial conditions and management strategies, simulating landowner options for adapting their business model annually. Despite attempts by simulated landowners to increase profits, adopted business models after 13 years were differentiated by initial land and infrastructural assets, supporting H1 and H2. A conservation organization's initial assets can cause it to become locked into a financially vulnerable business model. In our 50‐year simulation, path dependence was overcome by fewer of the landowners who facilitated natural ecological variability than those who maintained constant hunting rates and predator numbers, but the latter experienced unsustainably high game densities in low rainfall years. Management for natural variability supported long‐term ecological sustainability but not shorter term socioeconomic sustainability for PLCAs. Our findings highlight trade‐offs between ecological and economic sustainability and suggest a role for governmental support of the private conservation industry.     

Reach and messages of the world's largest ivory burn

Recent increases in ivory poaching have depressed African elephant populations. Successful enforcement has led to ivory stockpiling. Stockpile destruction is becoming increasingly popular, and most destruction has occurred in the last 5 years. Ivory destruction is intended to send a strong message against ivory consumption, both in promoting a taboo on ivory use and catalyzing policy change. However, there has been no effort to establish the distribution and extent of media reporting on ivory destruction events globally. We analyzed media coverage of the largest ivory destruction event in history (Kenya, 30 April 2016) across 11 nation states connected to ivory trade. We used an online‐media crawling tool to search online media outlets and subjected 5 of the largest print newspapers (by circulation) in 5 nations of interest to content analysis. Most online news on the ivory burn came from the United States (81% of 1944 articles), whereas most of the print news articles came from Kenya (61% of 157 articles). Eighty‐six to 97% of all online articles reported the burn as a positive conservation action, whereas 4–50% discussed ivory burning as having a negative impact on elephant conservation. Most articles discussed law enforcement and trade bans as effective for elephant conservation. There was more relative search interest globally in the 2016 Kenyan ivory burn than any other burn in 5 years. Ours is the first attempt to track the reach of media coverage relative to an ivory burn and provides a case study in tracking the effects of a conservation‐marketing event.     

Biofluorescence as a survey tool for cryptic marine species

As ecosystems come under increasing anthropogenic pressure, rare species face the highest risk of extinction. Paradoxically, data necessary to evaluate the conservation status of rare species are often lacking because of the challenges of detecting species with low abundance. One group of fishes subject to this undersampling bias are those with cryptic body patterns. Twenty‐one percent of cryptic fish species assessed for their extinction risk (International Union for Conservation of Nature [IUCN]) are data deficient. We developed a nondestructive method for surveying cryptically patterned marine fishes based on the presence of biofluorescence (underwater biofluorescence census, UBC). Blue LED torches were used to investigate how widespread biofluorescence was in cryptic reef fishes in the Coral Triangle region. The effectiveness of UBC to generate abundance data was tested on a data‐deficient pygmy seahorse species (Hippocampus bargibanti) and compared with data obtained from standard underwater visual census (UVC) surveys. We recorded 95 reef fish species displaying biofluorescence, 73 of which had not been previously described as biofluorescent. Of those fish with cryptic patterns, 87% were biofluorescent compared with 9% for noncryptic fishes. The probability of species displaying biofluorescence was 70.9 times greater for cryptic species than for noncryptic species. Almost twice the number of H. bargibanti was counted using the UBC compared with UVC. For 2 triplefin species (Ucla xenogrammus, Enneapterygius tutuilae), the abundance detected with UBC was triple that detected with UVC. The UBC method was effective at finding cryptic species that would otherwise be difficult to detect and thus will reduce interobserver variability inherent to UVC surveys. Biofluorescence is ubiquitous in cryptic fishes, making this method applicable across a wide range of species. Data collected using UBC could be used with multiple IUCN criteria to assess the extinction risk of cryptic species. Adopting this technique will enhance researchers’ ability to survey cryptic species and facilitate management and conservation of cryptic marine species.