A Bayesian hierarchical approach to quantifying stakeholder attitudes toward conservation in the presence of reporting error

Stakeholder support is vital for achieving conservation success, yet there are few reliable mechanisms to monitor stakeholder attitudes toward conservation. Approaches used to assess attitudes rarely account for bias arising from reporting error, which can lead to falsely reporting a positive attitude toward conservation (false-positive error) or not reporting a positive attitude when the respondent has a positive attitude toward conservation (false-negative error). Borrowing from developments in applied conservation science, we used a Bayesian hierarchical model to quantify stakeholder attitudes as the probability of having a positive attitude toward wildlife notionally (or in abstract terms) and at localized scales while accounting for reporting error. We compared estimates from our model, Likert scores, and naïve estimates (i.e., proportion of respondents reporting a positive attitude in at least 1 question that was only susceptible to false-negative error) with true stakeholder attitudes through simulations. We then applied the model in a survey of tea estate staff on their attitudes toward Asian elephants (Elephas maximus) in the Kaziranga–Karbi Anglong landscape of northeast India. In simulations, Bayesian model estimates of stakeholder attitudes toward wildlife were less biased than naïve estimates or Likert scores. After accounting for reporting errors, we estimated the probability of having a positive attitude toward elephants notionally as 0.85 in the Kaziranga landscape, whereas the proportion of respondents who had positive attitudes toward elephants at a localized scale was 0.50. In comparison, without accounting for reporting errors, naïve estimates of proportions of respondents with positive attitudes toward elephants were 0.69 and 0.23 notionally and at local scales, respectively. False (positive and negative) reporting probabilities were consistently not 0 (0.22–0.68). Regular and reliable assessment of stakeholder attitudes–combined with inference on drivers of positive attitudes–can help assess the success of initiatives aimed at facilitating human behavioral change and inform conservation decision making.     

Scientists' opinions on the global status and management of biological diversity

The large investments needed if loss of biological diversity is to be stemmed will likely lead to increased public and political scrutiny of conservation strategies and the science underlying them. It is therefore crucial to understand the degree of consensus or divergence among scientists on core scientific perceptions and strategies most likely to achieve given objectives. I developed an internet survey designed to elucidate the opinions of conservation scientists. Conservation scientists (n =583) were unanimous (99.5%) in their view that a serious loss of biological diversity is likely, very likely, or virtually certain. Scientists' agreement that serious loss is very likely or virtually certain ranged from 72.8% for Western Europe to 90.9% for Southeast Asia. Tropical coral ecosystems were perceived as the most seriously affected by loss of biological diversity; 88.0% of respondents familiar with that ecosystem type agreed that a serious loss is very likely or virtually certain. With regard to conservation strategies, scientists most often viewed understanding how people and nature interact in certain contexts and the role of biological diversity in maintaining ecosystem function as their priorities. Protection of biological diversity for its cultural and spiritual values and because of its usefulness to humans were low priorities, which suggests that many scientists do not fully support the utilitarian concept of ecosystem services. Many scientists expressed a willingness to consider conservation triage, engage in active conservation interventions, and consider reframing conservation goals and measures of success for conservation of biological diversity in an era of climate change. Although some heterogeneity of opinion is evident, results of the survey show a clear consensus within the scientific community on core issues of the extent and geographic scope of loss of biological diversity and on elements that may contribute to successful conservation strategies in the future.     

Relationship between conservation biology and ecology shown through machine reading of 32,000 articles

Conservation biology was founded on the idea that efforts to save nature depend on a scientific understanding of how it works. It sought to apply ecological principles to conservation problems. We investigated whether the relationship between these fields has changed over time through machine reading the full texts of 32,000 research articles published in 16 ecology and conservation biology journals. We examined changes in research topics in both fields and how the fields have evolved from 2000 to 2014. As conservation biology matured, its focus shifted from ecology to social and political aspects of conservation. The 2 fields diverged and now occupy distinct niches in modern science. We hypothesize this pattern resulted from increasing recognition that social, economic, and political factors are critical for successful conservation and possibly from rising skepticism about the relevance of contemporary ecological theory to practical conservation.     

Tracking Chinese newspaper coverage of elephant ivory through topic modeling

Mass media worldwide has contributed to increasing awareness of the illegal wildlife trade and its significant impact on wildlife conservation. We used mass media coverage as a proxy for macro-level public opinion to analyze the media framing of elephant ivory in 6394 Chinese newspaper articles published from 2000 to 2021 and thus determine the effects of wildlife policies on public opinion. We focused on 2 events: the Convention on International Trade in Endangered Species of Wild Fauna and Flora (CITES) approval of China as a trading partner in the purchase and import of ivory stockpiles from Africa in July 2008 and the Chinese government's announcement of a domestic ivory ban in December 2016. Using latent Dirichlet allocation topic modeling, we identified 8 topics about elephant ivory and grouped them into 3 frames: ivory arts and culture, ivory crimes, and elephant conservation. Over the last 2 decades, topics related to ivory crimes remained the most prevalent in news articles. Topics about ivory arts and culture showed a significant shift in media salience before and after the 2 events (from 0.44 to 0.19 and from 0.08 to 0.15, respectively, p < 0.05), whereas the other 2 frames did not change significantly. Contrary to popular belief, our results indicated that Chinese macro-level public opinion on ivory had become more negative following the CITES approval of ivory importation and less negative after the ivory ban announcement, at least for certain periods. The relationship between mass media, public opinion, and wildlife trade policies is complex and requires further examination of the sociopolitical dynamics that influence media narratives. Our results showed the value of topic modeling in monitoring and assessing media representations of wildlife issues in the era of big data. Conservationists should remain vigilant of mass media coverage and collaborate with media practitioners to produce comprehensive narratives on wildlife issues if resources permit.     

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.     

Using a Systematic Approach to Select Flagship Species for Bird Conservation

Conservation marketing campaigns that focus on flagship species play a vital role in biological diversity conservation because they raise funds and change people's behavior. However, most flagship species are selected without considering the target audience of the campaign, which can hamper the campaign's effectiveness. To address this problem, we used a systematic and stakeholder‐driven approach to select flagship species for a conservation campaign in the Serra do Urubu in northeastern Brazil. We based our techniques on environmental economic and marketing methods. We used choice experiments to examine the species attributes that drive preference and latent‐class models to segment respondents into groups by preferences and socioeconomic characteristics. We used respondent preferences and information on bird species inhabiting the Serra do Urubu to calculate a flagship species suitability score. We also asked respondents to indicate their favorite species from a set list to enable comparison between methods. The species’ traits that drove audience preference were geographic distribution, population size, visibility, attractiveness, and survival in captivity. However, the importance of these factors differed among groups and groups differed in their views on whether species with small populations and the ability to survive in captivity should be prioritized. The popularity rankings of species differed between approaches, a result that was probably related to the different ways in which the 2 methods measured preference. Our new approach is a transparent and evidence‐based method that can be used to refine the way stakeholders are engaged in the design of conservation marketing campaigns.     

Estimating the footprint of pollution on coral reefs with models of species turnover

Ecological communities typically change along gradients of human impact, although it is difficult to estimate the footprint of impacts for diffuse threats such as pollution. We developed a joint model (i.e., one that includes multiple species and their interactions with each other and environmental covariates) of benthic habitats on lagoonal coral reefs and used it to infer change in benthic composition along a gradient of distance from logging operations. The model estimated both changes in abundances of benthic groups and their compositional turnover, a type of beta diversity. We used the model to predict the footprint of turbidity impacts from past and recent logging. Benthic communities far from logging were dominated by branching corals, whereas communities close to logging had higher cover of dead coral, massive corals, and soft sediment. Recent impacts were predicted to be small relative to the extensive impacts of past logging because recent logging has occurred far from lagoonal reefs. Our model can be used more generally to estimate the footprint of human impacts on ecosystems and evaluate the benefits of conservation actions for ecosystems.     

Text analysis tools for identification of emerging topics and research gaps in conservation science

Keeping track of conceptual and methodological developments is a critical skill for research scientists, but this task is increasingly difficult due to the high rate of academic publication. As a crisis discipline, conservation science is particularly in need of tools that facilitate rapid yet insightful synthesis. We show how a common text‐mining method (latent Dirichlet allocation, or topic modeling) and statistical tests familiar to ecologists (cluster analysis, regression, and network analysis) can be used to investigate trends and identify potential research gaps in the scientific literature. We tested these methods on the literature on ecological surrogates and indicators. Analysis of topic popularity within this corpus showed a strong emphasis on monitoring and management of fragmented ecosystems, while analysis of research gaps suggested a greater role for genetic surrogates and indicators. Our results show that automated text analysis methods need to be used with care, but can provide information that is complementary to that given by systematic reviews and meta‐analyses, increasing scientists’ capacity for research synthesis.     

The immediate costs and long-term benefits of assisted gene flow in large populations

With the genetic health of many plant and animal populations deteriorating due to climate change outpacing adaptation, interventions, such as assisted gene flow (AGF), may provide genetic variation necessary for populations to adapt to climate change. We ran genetic simulations to mimic different AGF scenarios in large populations and measured their outcomes on population-level fitness to determine circumstances in which it is worthwhile to perform AGF. In the absence of inbreeding depression, AGF was beneficial within a few generations only when introduced genotypes had much higher fitness than local individuals and traits affecting fitness were controlled by a few genes of large effect. AGF was harmful over short periods (e.g., first ∼10–20 generations) if there was strong outbreeding depression or introduced deleterious genetic variation. When the adaptive trait was controlled by many loci of small effect, the benefits of AGF took over 10 generations to realize—potentially too long for most climate-related management scenarios. The genomic integrity of the recipient population typically remained intact following AGF; the amount of genetic material from the donor population usually constituted no more of the recipient population's genome than the fraction of the population introduced. Significant genomic turnover (e.g., >50% replacement) only occurred when the selective advantage of the adaptive trait and translocation fraction were extremely high. Our results will be useful when adaptive management is used to maintain the genetic health and productivity of large populations under climate change.