Conducting conservation social science surveys online

The coronavirus (COVID-19) pandemic is affecting the environment and conservation research in fundamental ways. Many conservation social scientists are now administering survey questionnaires online, but they must do so while ensuring rigor in data collection. Further, they must address a suite of unique challenges, such as the increasing use of mobile devices by participants and avoiding bots or other survey fraud. We reviewed recent literature on online survey methods to examine the state of the field related to online data collection and dissemination. We illustrate the review with examples of key methodological decisions made during a recent national study of people who feed wild birds, in which survey respondents were recruited through an online panel and a sample generated via a project participant list. Conducting surveys online affords new opportunities for participant recruitment, design, and pilot testing. For instance, online survey panels can provide quick access to large and diverse samples of people. Based on the literature review and our own experiences, we suggest that to ensure high-quality online surveys one should account for potential sampling and nonresponse error, design survey instruments for use on multiple devices, test the instrument, and use multiple protocols to identify data quality problems. We also suggest that research funders, journal editors, and policy makers can all play a role in ensuring high-quality survey data are used to inform effective conservation programs and policies.     

Digital data sources and methods for conservation culturomics

Ongoing loss of biological diversity is primarily the result of unsustainable human behavior. Thus, the long-term success of biodiversity conservation depends on a thorough understanding of human–nature interactions. Such interactions are ubiquitous but vary greatly in time and space and are difficult to monitor efficiently at large spatial scales. However, the Information Age also provides new opportunities to better understand human–nature interactions because many aspects of daily life are recorded in a variety of digital formats. The emerging field of conservation culturomics aims to take advantage of digital data sources and methods to study human–nature interactions and thus to provide new tools for studying conservation at relevant temporal and spatial scales. Nevertheless, technical challenges associated with the identification, access, and analysis of relevant data hamper the wider adoption of culturomics methods. To help overcome these barriers, we propose a conservation culturomics research framework that addresses data acquisition, analysis, and inherent biases. The main sources of culturomic data include web pages, social media, and other digital platforms from which metrics of content and engagement can be obtained. Obtaining raw data from these platforms is usually desirable but requires careful consideration of how to access, store, and prepare the data for analysis. Methods for data analysis include network approaches to explore connections between topics, time-series analysis for temporal data, and spatial modeling to highlight spatial patterns. Outstanding challenges associated with culturomics research include issues of interdisciplinarity, ethics, data biases, and validation. The practical guidance we offer will help conservation researchers and practitioners identify and obtain the necessary data and carry out appropriate analyses for their specific questions, thus facilitating the wider adoption of culturomics approaches for conservation applications.     

Developing shared qualitative models for complex systems

Understanding complex systems is essential to ensure their conservation and effective management. Models commonly support understanding of complex ecological systems and, by extension, their conservation. Modeling, however, is largely a social process constrained by individuals’ mental models (i.e., a small-scale internal model of how a part of the world works based on knowledge, experience, values, beliefs, and assumptions) and system complexity. To account for both system complexity and the diversity of knowledge of complex systems, we devised a novel way to develop a shared qualitative complex system model. We disaggregated a system (carbonate coral reefs) into smaller subsystem modules that each represented a functioning unit, about which an individual is likely to have more comprehensive knowledge. This modular approach allowed us to elicit an individual mental model of a defined subsystem for which the individuals had a higher level of confidence in their knowledge of the relationships between variables. The challenge then was to bring these subsystem models together to form a complete, shared model of the entire system, which we attempted through 4 phases: develop the system framework and subsystem modules; develop the individual mental model elicitation methods; elicit the mental models; and identify and isolate differences for exploration and identify similarities to cocreate a shared qualitative model. The shared qualitative model provides opportunities to develop a quantitative model to understand and predict complex system change.     

Scale Mismatches,Conservation Planning,and the Value of Social‐Network Analyses

Many of the challenges conservation professionals face can be framed as scale mismatches. The problem of scale mismatch occurs when the planning for and implementation of conservation actions is at a scale that does not reflect the scale of the conservation problem. The challenges in conservation planning related to scale mismatch include ecosystem or ecological process transcendence of governance boundaries; limited availability of fine‐resolution data; lack of operational capacity for implementation; lack of understanding of social‐ecological system components; threats to ecological diversity that operate at diverse spatial and temporal scales; mismatch between funding and the long‐term nature of ecological processes; rate of action implementation that does not reflect the rate of change of the ecological system; lack of appropriate indicators for monitoring activities; and occurrence of ecological change at scales smaller or larger than the scale of implementation or monitoring. Not recognizing and accounting for these challenges when planning for conservation can result in actions that do not address the multiscale nature of conservation problems and that do not achieve conservation objectives. Social networks link organizations and individuals across space and time and determine the scale of conservation actions; thus, an understanding of the social networks associated with conservation planning will help determine the potential for implementing conservation actions at the required scales. Social‐network analyses can be used to explore whether these networks constrain or enable key social processes and how multiple scales of action are linked. Results of network analyses can be used to mitigate scale mismatches in assessing, planning, implementing, and monitoring conservation projects. Discordancia de Escalas, Planificación de la Conservación y el Valor del Análisis de Redes Sociales     

Fundamental insights on when social network data are most critical for conservation planning

As declines in biodiversity accelerate, there is an urgent imperative to ensure that every dollar spent on conservation counts toward species protection. Systematic conservation planning is a widely used approach to achieve this, but there is growing concern that it must better integrate the human social dimensions of conservation to be effective. Yet, fundamental insights about when social data are most critical to inform conservation planning decisions are lacking. To address this problem, we derived novel principles to guide strategic investment in social network information for systematic conservation planning. We considered the common conservation problem of identifying which social actors, in a social network, to engage with to incentivize conservation behavior that maximizes the number of species protected. We used simulations of social networks and species distributed across network nodes to identify the optimal state-dependent strategies and the value of social network information. We did this for a range of motif network structures and species distributions and applied the approach to a small-scale fishery in Kenya. The value of social network information depended strongly on both the distribution of species and social network structure. When species distributions were highly nested (i.e., when species-poor sites are subsets of species-rich sites), the value of social network information was almost always low. This suggests that information on how species are distributed across a network is critical for determining whether to invest in collecting social network data. In contrast, the value of social network information was greatest when social networks were highly centralized. Results for the small-scale fishery were consistent with the simulations. Our results suggest that strategic collection of social network data should be prioritized when species distributions are un-nested and when social networks are likely to be centralized.     

Characterizing the trophy hunting debate on Twitter

Social media is an arena of debate for contentious political and social topics. One conservation topic debated online is the acceptability of trophy hunting, a debate that has implications for national and international policy. We used a mixed-methods approach (grounded theory and quantitative clustering) to identify themes in the trophy hunting debate on Twitter. We examined commonly co-occurring categories that describe people's stances on trophy hunting. We identified 12 categories and 4 preliminary archetypes opposing trophy hunting—activism, scientific, condemning, and objecting—whose opposition derived from different moral reasoning. Few tweets (22) in our sample of 500 supported trophy hunting, whereas 350 opposed it. The debate was hostile; 7% of tweets in our sample were categorized as abusive. Online debates can be unproductive, and our findings may be important for stakeholders wishing to effectively engage in the trophy hunting debate on Twitter. More generally, we contend that because social media is increasingly influential, it is important to formally contextualize public responses to contentious conservation topics in order to aid communication of conservation evidence and to integrate diverse public perspectives in conservation practice.     

Evaluating outcomes of conservation with multidimensional indicators of well-being

Many conservation interventions are hypothesized to be beneficial for both the environment and people's well-being, but this has rarely been tested rigorously. We examined the effects of adoption or nonadoption of a conservation intervention on 3 dimensions of people's well-being (material, relational, and subjective) over time. We focused on a fisheries bycatch management initiative intended to reduce environmental externalities associated with resource extraction. We collected panel data from fishers (n = 250) in villages with (adopters and nonadopters) and without (control) the conservation intervention 3 times over 2 years. We found no evidence that adoption reduced any of the 3 dimensions of well-being in the local populations affected by the intervention. There were modest improvements in material (t = –1.58) and subjective livelihood well-being (p = 0.04) for adopters relative to nonadopters over time. The variations in well-being experiences (in terms of magnitude of change) among adopters, nonadopters, and controls across the different domains over time affirmed the dynamic and social nature of well-being.     

Speaking across boundaries to explore the potential for interdisciplinarity in ecosystem services knowledge production

Conservation is likely to be most successful if it draws on knowledge from across the natural and social sciences. The ecosystem services concept has been called a boundary object in that it facilitates development of such interdisciplinary knowledge because it offers a common platform for researchers, policy makers, and practitioners. However, a question that remains is to what extent the interdisciplinary knowledge needed is provided by disciplinary diversity within the field. We asked where is knowledge on ecosystem services produced, how interdisciplinary is this knowledge, and which disciplines facilitate the greatest disciplinary integration? We defined interdisciplinarity as the extent to which published research draws on knowledge that crosses disciplinary borders and used citations as a quantitative indicator of communication among disciplines, based on journal classification. We used disciplinary diversity, richness, and heterocitation as measures of interdisciplinarity and betweenness centrality as a measure of disciplinary integration. Our data set contained 22,153 publications on ecosystem services, published from 1983 to 2018. We found that ecosystem services research matured; average yearly output growth was 33.8%, more than the 8–9% growth in scientific output across all fields. Over time, the network clustering coefficient, measuring connectedness of individual disciplines, rose from 0.388 to 0.727, suggesting increased density in the network of citations. Researchers in the field published more articles (3566 in 2018 alone) across more disciplines (77 unique disciplines in 2018). However, this growth was not mirrored by an increase in the diversity (stable at 0.7–0.9) or richness (averaging 0.35 unique disciplines per citation) of citation patterns. Heterocitation scores, or out-of-group citations, for arts, humanities, social sciences, and law ranged from 56% to 64%, which was lower than we expected, although this may serve to protect the integrity of social science disciplines and attract broader engagement from within. Ultimately, a small number of productive disciplines are central to supporting disciplinary integration. However, opportunities exist for conservation practice to draw on a broader field of research, to realize the potential that the diverse body of knowledge of interdisciplinary work offers.     

Network analysis of a stakeholder community combatting illegal wildlife trade

The illegal wildlife trade has emerged as a growing and urgent environmental issue. Stakeholders involved in the efforts to curb wildlife trafficking include nongovernmental organizations (NGOs), academia, and state government and enforcement bodies. The extent to which these stakeholders work and communicate among each other is fundamental to effectively combatting illicit trade. Using the United Kingdom as a case study, we used a social network analysis and semistructured interviews of stakeholders to assess communication relationships in the counter wildlife trafficking community. The NGOs consistently occupied 4 of the 5 most central positions in the generated networks, whereas academic institutions routinely occupied 4 of the 5 most peripheral positions. However, NGOs were the least diverse in their communication practices compared with the other stakeholder groups. Stakeholders identified personal relationships as the most important aspect of functioning communication. Participant insights also showed that stakeholder-specific variables (e.g., ethical and confidentiality concerns), competition, and fundraising can have a confounding effect on intercommunication. Evaluating communication networks and intrastakeholder communication trends is essential to creating cohesive, productive, and efficient responses to the challenges of combatting illegal wildlife trade. Article impact statement: Communication among those combatting illegal wildlife trade is confounded by stakeholder variables (ethics, confidentiality), competition, and fundraising.     

An introduction to decision science for conservation

Biodiversity conservation decisions are difficult, especially when they involve differing values, complex multidimensional objectives, scarce resources, urgency, and considerable uncertainty. Decision science embodies a theory about how to make difficult decisions and an extensive array of frameworks and tools that make that theory practical. We sought to improve conceptual clarity and practical application of decision science to help decision makers apply decision science to conservation problems. We addressed barriers to the uptake of decision science, including a lack of training and awareness of decision science; confusion over common terminology and which tools and frameworks to apply; and the mistaken impression that applying decision science must be time consuming, expensive, and complex. To aid in navigating the extensive and disparate decision science literature, we clarify meaning of common terms: decision science, decision theory, decision analysis, structured decision-making, and decision-support tools. Applying decision science does not have to be complex or time consuming; rather, it begins with knowing how to think through the components of a decision utilizing decision analysis (i.e., define the problem, elicit objectives, develop alternatives, estimate consequences, and perform trade-offs). This is best achieved by applying a rapid-prototyping approach. At each step, decision-support tools can provide additional insight and clarity, whereas decision-support frameworks (e.g., priority threat management and systematic conservation planning) can aid navigation of multiple steps of a decision analysis for particular contexts. We summarize key decision-support frameworks and tools and describe to which step of a decision analysis, and to which contexts, each is most useful to apply. Our introduction to decision science will aid in contextualizing current approaches and new developments, and help decision makers begin to apply decision science to conservation problems.     

Hunting for common ground between wildlife governance and commons scholarship

Wildlife hunting is essential to livelihoods and food security in many parts of the world, yet present rates of extraction may threaten ecosystems and human communities. Thus, governing sustainable wildlife use is a major social dilemma and conservation challenge. Commons scholarship is well positioned to contribute theoretical insights and analytic tools to better understand the interface of social and ecological dimensions of wildlife governance, yet the intersection of wildlife studies and commons scholarship is not well studied. We reviewed existing wildlife-hunting scholarship, drawing on a database of 1,410 references, to examine the current overlap with commons scholarship through multiple methods, including social network analysis and deductive coding. We found that a very small proportion of wildlife scholarship incorporated commons theories and frameworks. The social network of wildlife scholarship was densely interconnected with several major publication clusters, whereas the wildlife commons scholarship was sparse and isolated. Despite the overarching gap between wildlife and commons scholarship, a few scholars are studying wildlife commons. The small body of scholarship that bridges these disconnected literatures provides valuable insights into the understudied relational dimensions of wildlife and other overlapping common-pool resources. We suggest increased engagement among wildlife and commons scholars and practitioners to improve the state of knowledge and practice of wildlife governance across regions, particularly for bushmeat hunting in the tropics, which is presently understudied through a common-pool resource lens. Our case study of the Republic of Congo showed how the historical context and interrelationships between hunting and forest rights are essential to understanding the current state of wildlife governance and potential for future interventions. A better understanding of the interconnections between wildlife and overlapping common-pool resource systems may be key to understanding present wildlife governance challenges and advancing the common-pool resource research agenda.     

Characterizing Spatial Uncertainty when Integrating Social Data in Conservation Planning

Recent conservation planning studies have presented approaches for integrating spatially referenced social (SRS) data with a view to improving the feasibility of conservation action. We reviewed the growing conservation literature on SRS data, focusing on elicited or stated preferences derived through social survey methods such as choice experiments and public participation geographic information systems. Elicited SRS data includes the spatial distribution of willingness to sell, willingness to pay, willingness to act, and assessments of social and cultural values. We developed a typology for assessing elicited SRS data uncertainty which describes how social survey uncertainty propagates when projected spatially and the importance of accounting for spatial uncertainty such as scale effects and data quality. These uncertainties will propagate when elicited SRS data is integrated with biophysical data for conservation planning and may have important consequences for assessing the feasibility of conservation actions. To explore this issue further, we conducted a systematic review of the elicited SRS data literature. We found that social survey uncertainty was commonly tested for, but that these uncertainties were ignored when projected spatially. Based on these results we developed a framework which will help researchers and practitioners estimate social survey uncertainty and use these quantitative estimates to systematically address uncertainty within an analysis. This is important when using SRS data in conservation applications because decisions need to be made irrespective of data quality and well characterized uncertainty can be incorporated into decision theoretic approaches.     

Synergies and trade-offs among integrated conservation approaches in Mexico

Integrated conservation approaches (ICAs) are employed by governments, communities, and nongovernmental organizations worldwide seeking to achieve outcomes with dual benefits for biodiversity conservation and poverty alleviation. Although ICAs are frequently implemented concurrently, interactions among ICAs and the synergies or trade-offs that result are rarely considered during program design, implementation, and evaluation. In support of more deliberate and effective use of ICAs, we examined interactions among four well-known strategies: biosphere reserves (BRs), voluntary protected areas (VPAs), payments for ecosystem services (PES), and community forest management (CFM). Through a comparative case study, we analyzed interactions among spatially or temporally clustered ICAs implemented on communally held and managed lands in three ecologically and socioeconomically distinct regions of Mexico. Our research methods combined policy analysis with data gathered through participant observation and semistructured interviews (n = 78) and focus groups (n = 5) with government officials, implementers, and participants involved in ICAs in 28 communities. Despite the significant differences among the regions in which they were implemented, we found that key actors at each level of involvement generally perceived interactions among ICAs as synergistic. The PES programs were perceived to strengthen protected areas by reducing forest cover loss in and around BRs, fostering proconservation attitudes, and incentivizing the establishment of VPAs. Communities that invested PES income in CFM were motivated to conserve forests beyond the duration of PES programs, and CFM in buffer zones was perceived to strengthen BRs by maintaining forest cover and generating income for communities. We also identified key social and environmental factors that can influence these interaction effects among ICAs. Based on these findings, we recommend further study of ICA interactions and intentionally complementary policy design to maximize positive environmental and social outcomes.     

Evaluation of pay-for-release conservation incentives for unintentionally caught threatened species

In the developing world, the exploitation of threatened species jeopardizes their permanence in the wild. Because not all captures are intentional, for instance when capture methods have low selectivity, pressure on these species may be lessened by releasing living incidentally caught animals. However, it is often unrealistic to expect people to voluntarily do so because it means foregoing the benefits of resource extraction. Financial incentives for such animal release may foster conservation objectives. Reducing human–animal conflicts, protecting natural habitat, and conserving nests of threatened species are examples of conservation benefits that can be built on financial reward systems. However, incentives aiming to protect unintentionally captured threatened species are scarce. We considered pay for release, a type of ecosystem-service payment designed to foster the release of incidentally captured threatened species. We aimed to determine the best conditions to implement this scheme, its potential benefits (e.g., incentivizing the release of threatened species), and pitfalls and priority research needs (e.g., required conditions for pay for release to work) to show that its global applicability is possible. Given that approaches solely based on education and law enforcement may be ineffective under some circumstances, we argue that pay for release can protect incidentally captured endangered species if used under conditions conducive for its success. When local participants’ intrinsic motivation for conservation is weak, but the release of incidentally live-caught animals into their habitats is readily achievable, pay-for-release schemes could jump start urgently needed conservation efforts against indiscriminate animal harvesting.     

Validating graph-based connectivity models with independent presence–absence and genetic data sets

Habitat connectivity is a key objective of current conservation policies and is commonly modeled by landscape graphs (i.e., sets of habitat patches [nodes] connected by potential dispersal paths [links]). These graphs are often built based on expert opinion or species distribution models (SDMs) and therefore lack empirical validation from data more closely reflecting functional connectivity. Accordingly, we tested whether landscape graphs reflect how habitat connectivity influences gene flow, which is one of the main ecoevolutionary processes. To that purpose, we modeled the habitat network of a forest bird (plumbeous warbler [Setophaga plumbea]) on Guadeloupe with graphs based on expert opinion, Jacobs’ specialization indices, and an SDM. We used genetic data (712 birds from 27 populations) to compute local genetic indices and pairwise genetic distances. Finally, we assessed the relationships between genetic distances or indices and cost distances or connectivity metrics with maximum-likelihood population-effects distance models and Spearman correlations between metrics. Overall, the landscape graphs reliably reflected the influence of connectivity on population genetic structure; validation R² was up to 0.30 and correlation coefficients were up to 0.71. Yet, the relationship among graph ecological relevance, data requirements, and construction and analysis methods was not straightforward because the graph based on the most complex construction method (species distribution modeling) sometimes had less ecological relevance than the others. Cross-validation methods and sensitivity analyzes allowed us to make the advantages and limitations of each construction method spatially explicit. We confirmed the relevance of landscape graphs for conservation modeling but recommend a case-specific consideration of the cost-effectiveness of their construction methods. We hope the replication of independent validation approaches across species and landscapes will strengthen the ecological relevance of connectivity models.     

Clarifying values,risk perceptions,and attitudes to resolve or avoid social conflicts in invasive species management

Decision makers and researchers recognize the need to effectively confront the social dimensions and conflicts inherent to invasive species research and management. Yet, despite numerous contentious situations that have arisen, no systematic evaluation of the literature has examined the commonalities in the patterns and types of these emergent social issues. Using social and ecological keywords, we reviewed trends in the social dimensions of invasive species research and management and the sources and potential solutions to problems and conflicts that arise around invasive species. We integrated components of cognitive hierarchy theory and risk perceptions theory to provide a conceptual framework to identify, distinguish, and provide understanding of the driving factors underlying disputes associated with invasive species. In the ISI Web of Science database, we found 15,915 peer‐reviewed publications on biological invasions, 124 of which included social dimensions of this phenomenon. Of these 124, 28 studies described specific contentious situations. Social approaches to biological invasions have emerged largely in the last decade and have focused on both environmental social sciences and resource management. Despite being distributed in a range of journals, these 124 articles were concentrated mostly in ecology and conservation‐oriented outlets. We found that conflicts surrounding invasive species arose based largely on differences in value systems and to a lesser extent stakeholder and decision maker's risk perceptions. To confront or avoid such situations, we suggest integrating the plurality of environmental values into invasive species research and management via structured decision making techniques, which enhance effective risk communication that promotes trust and confidence between stakeholders and decision makers. Clarificar los Valores, Percepciones de Riesgo y Actitudes para Resolver o Evitar Conflictos Sociales en el Manejo de Especies Invasoras     

Evaluation of the use of psychometric scales in human–wildlife interaction research to determine attitudes and tolerance toward wildlife

Studies evaluating human–wildlife interactions (HWIs) in a conservation context often include psychometric scales to measure attitudes and tolerance toward wildlife. However, data quality is at risk when such scales are used without appropriate validation or reliability testing, potentially leading to erroneous interpretation or application of findings. We used 2 online databases (ProQuest Psych Info and Web of Science) to identify published HWI studies that included attitude and tolerance. We analyzed these studies to determine the methods used to measure attitudes or tolerance toward predators and other wildlife; determine the proportion of these methods applying psychometric scales; and evaluate the rigor with which the scales were used by examining whether the psychometric properties of validity and reliability were reported. From 2007 to 2017, 114 published studies were identified. Ninety-four (82%) used questionnaires and many of these (53 [56%]) utilized a psychometric scale. Most scales (39 [74%]) had at least 1 test of reliability reported, but reliance on a single test was notable, contrary to recommended practice. Fewer studies (35 [66%]) reported a test of validity, but this was primarily restricted to structural validity rather than more comprehensive testing. Encouragingly, HWI investigators increasingly utilized the necessary psychometric tools for designing and analyzing questionnaire data, but failure to assess the validity or reliability of psychometric scales used in over one-third of published HWI attitude research warrants attention. We advocate incorporation of more robust application of psychometric scales to advance understanding of stakeholder attitudes as they relate to HWI.     

Estimating the extent and structure of trade in horticultural orchids via social media

The wildlife trade is a lucrative industry involving thousands of animal and plant species. The increasing use of the internet for both legal and illegal wildlife trade is well documented, but there is evidence that trade may be emerging on new online technologies such as social media. Using the orchid trade as a case study, we conducted the first systematic survey of wildlife trade on an international social‐media website. We focused on themed forums (groups), where people with similar interests can interact by uploading images or text (posts) that are visible to other group members. We used social‐network analysis to examine the ties between 150 of these orchid‐themed groups to determine the structure of the network. We found 4 communities of closely linked groups based around shared language. Most trade occurred in a community that consisted of English‐speaking and Southeast Asian groups. In addition to the network analysis, we randomly sampled 30 groups from the whole network to assess the prevalence of trade in cultivated and wild plants. Of 55,805 posts recorded over 12 weeks, 8.9% contained plants for sale, and 22–46% of these posts pertained to wild‐collected orchids. Although total numbers of posts about trade were relatively small, the large proportion of posts advertising wild orchids for sale supports calls for better monitoring of social media for trade in wild‐collected plants.