Using a Bayesian network to clarify areas requiring research in a host–pathogen system

Bayesian network analyses can be used to interactively change the strength of effect of variables in a model to explore complex relationships in new ways. In doing so, they allow one to identify influential nodes that are not well studied empirically so that future research can be prioritized. We identified relationships in host and pathogen biology to examine disease‐driven declines of amphibians associated with amphibian chytrid fungus (Batrachochytrium dendrobatidis). We constructed a Bayesian network consisting of behavioral, genetic, physiological, and environmental variables that influence disease and used them to predict host population trends. We varied the impacts of specific variables in the model to reveal factors with the most influence on host population trend. The behavior of the nodes (the way in which the variables probabilistically responded to changes in states of the parents, which are the nodes or variables that directly influenced them in the graphical model) was consistent with published results. The frog population had a 49% probability of decline when all states were set at their original values, and this probability increased when body temperatures were cold, the immune system was not suppressing infection, and the ambient environment was conducive to growth of B. dendrobatidis. These findings suggest the construction of our model reflected the complex relationships characteristic of host–pathogen interactions. Changes to climatic variables alone did not strongly influence the probability of population decline, which suggests that climate interacts with other factors such as the capacity of the frog immune system to suppress disease. Changes to the adaptive immune system and disease reservoirs had a large effect on the population trend, but there was little empirical information available for model construction. Our model inputs can be used as a base to examine other systems, and our results show that such analyses are useful tools for reviewing existing literature, identifying links poorly supported by evidence, and understanding complexities in emerging infectious‐disease systems.     

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.     

Key considerations and challenges in the application of social-network research for environmental decision making

Attempts to better understand the social context in which conservation and environmental decisions are made has led to increased interest in human social networks. To improve the use of social-network analysis in conservation, we reviewed recent studies in the literature in which such methods were applied. In our review, we looked for problems in research design and analysis that limit the utility of network analysis. Nineteen of 55 articles published from January 2016 to June 2019 exhibited at least 1 of the following problems: application of analytical methods inadequate or sensitive to incomplete network data; application of statistical approaches that ignore dependency in the network; or lack of connection between the theoretical base, research question, and choice of analytical techniques. By drawing attention to these specific areas of concern and highlighting research frontiers and challenges, including causality, network dynamics, and new approaches, we responded to calls for increasing the rigorous application of social science in conservation.     

Emergent conservation outcomes of shared risk perception in human-wildlife systems

Human perception of risks related to economic damages caused by nearby wildlife can be transmitted through social networks. Understanding how sharing risk information within a human community alters the spatial dynamics of human-wildlife interactions has important implications for the design and implementation of effective conservation actions. We developed an agent-based model that simulates farmer livelihood decisions and activities in an agricultural landscape shared with a population of a generic wildlife species (wildlife-human interactions in shared landscapes [WHISL]). In the model, based on risk perception and economic information, farmers decide how much labor to allocate to farming and whether and where to exclude wildlife from their farms (e.g., through fencing, trenches, or vegetation thinning). In scenarios where the risk perception of farmers was strongly influenced by other farmers, exclusion of wildlife was widespread, resulting in decreased quality of wildlife habitat and frequency of wildlife damages across the landscape. When economic losses from encounters with wildlife were high, perception of risk increased and led to highly synchronous behaviors by farmers in space and time. Interactions between wildlife and farmers sometimes led to a spillover effect of wildlife damage displaced from socially and spatially connected communities to less connected neighboring farms. The WHISL model is a useful conservation-planning tool because it provides a test bed for theories and predictions about human-wildlife dynamics across a range of different agricultural landscapes.     

Effects of amusing memes on concern for unappealing species

There is limited knowledge of the mechanisms that can inspire people's concern and engagement in the protection of unpopular and unappealing species. We analyzed Polish people's interest in themed internet memes featuring the proboscis monkey (Nasalis larvatus) and the consequences of this interest for conservation marketing. We examined Google Trends data, used Google Search, and searched popular media materials to estimate interest in the proboscis monkey in Poland. Photos of the proboscis monkey when presented with humor in internet memes attracted as much interest as usually more popular species (e.g., koala, panda, and orangutan) used in marketing by nongovernmental organizations. Amusing internet memes spread by social media positively correlated with increasing interest in the unappealing species, such as proboscis monkey. Interest in amusing internet memes positively correlated with individuals’ decisions to donate to 6 crowdfunding actions. Thus, conservation marketing that includes amusing memes and social media may provide a worthwhile complement to traditional campaigns and are likely to influence individuals who are unaffected by the usual means.     

Use of linkage mapping and centrality analysis across habitat gradients to conserve connectivity of gray wolf populations in western North America

Centrality metrics evaluate paths between all possible pairwise combinations of sites on a landscape to rank the contribution of each site to facilitating ecological flows across the network of sites. Computational advances now allow application of centrality metrics to landscapes represented as continuous gradients of habitat quality. This avoids the binary classification of landscapes into patch and matrix required by patch-based graph analyses of connectivity. It also avoids the focus on delineating paths between individual pairs of core areas characteristic of most corridor- or linkage-mapping methods of connectivity analysis. Conservation of regional habitat connectivity has the potential to facilitate recovery of the gray wolf (Canis lupus), a species currently recolonizing portions of its historic range in the western United States. We applied 3 contrasting linkage-mapping methods (shortest path, current flow, and minimum-cost-maximum-flow) to spatial data representing wolf habitat to analyze connectivity between wolf populations in central Idaho and Yellowstone National Park (Wyoming). We then applied 3 analogous betweenness centrality metrics to analyze connectivity of wolf habitat throughout the northwestern United States and southwestern Canada to determine where it might be possible to facilitate range expansion and interpopulation dispersal. We developed software to facilitate application of centrality metrics. Shortest-path betweenness centrality identified a minimal network of linkages analogous to those identified by least-cost-path corridor mapping. Current flow and minimum-cost-maximum-flow betweenness centrality identified diffuse networks that included alternative linkages, which will allow greater flexibility in planning. Minimum-cost-maximum-flow betweenness centrality, by integrating both land cost and habitat capacity, allows connectivity to be considered within planning processes that seek to maximize species protection at minimum cost. Centrality analysis is relevant to conservation and landscape genetics at a range of spatial extents, but it may be most broadly applicable within single- and multispecies planning efforts to conserve regional habitat connectivity.     

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.     

Using Twitter to communicate conservation science from a professional conference

Scientists are increasingly using Twitter as a tool for communicating science. Twitter can promote scholarly discussion, disseminate research rapidly, and extend and diversify the scope of audiences reached. However, scientists also caution that if Twitter does not accurately convey science due to the inherent brevity of this media, misinformation could cascade quickly through social media. Data on whether Twitter effectively communicates conservation science and the types of user groups receiving these tweets are lacking. To address these knowledge gaps, we examined live tweeting as a means of communicating conservation science at the 2013 International Congress for Conservation Biology (ICCB). We quantified and compared the user groups sending and reading live tweets. We also surveyed presenters to determine their intended audiences, which we compared with the actual audiences reached through live tweeting. We also asked presenters how effectively tweets conveyed their research findings. Twitter reached 14 more professional audience categories relative to those attending and live tweeting at ICCB. However, the groups often reached through live tweeting were not the presenters’ intended audiences. Policy makers and government and non‐governmental organizations were rarely reached (0%, 4%, and 6% of audience, respectively), despite the intent of the presenters. Plenary talks were tweeted about 6.9 times more than all other oral or poster presentations combined. Over half the presenters believed the tweets about their talks were effective. Ineffective tweets were perceived as vague or missing the presenters’ main message. We recommend that presenters who want their science to be communicated accurately and broadly through Twitter should provide Twitter‐friendly summaries that incorporate relevant hashtags and usernames. Our results suggest that Twitter can be used to effectively communicate speakers’ findings to diverse audiences beyond conference walls.     

Paradigms for parasite conservation

Parasitic species, which depend directly on host species for their survival, represent a major regulatory force in ecosystems and a significant component of Earth's biodiversity. Yet the negative impacts of parasites observed at the host level have motivated a conservation paradigm of eradication, moving us farther from attainment of taxonomically unbiased conservation goals. Despite a growing body of literature highlighting the importance of parasite‐inclusive conservation, most parasite species remain understudied, underfunded, and underappreciated. We argue the protection of parasitic biodiversity requires a paradigm shift in the perception and valuation of their role as consumer species, similar to that of apex predators in the mid‐20th century. Beyond recognizing parasites as vital trophic regulators, existing tools available to conservation practitioners should explicitly account for the unique threats facing dependent species. We built upon concepts from epidemiology and economics (e.g., host‐density threshold and cost‐benefit analysis) to devise novel metrics of margin of error and minimum investment for parasite conservation. We define margin of error as the risk of accidental host extinction from misestimating equilibrium population sizes and predicted oscillations, while minimum investment represents the cost associated with conserving the additional hosts required to maintain viable parasite populations. This framework will aid in the identification of readily conserved parasites that present minimal health risks. To establish parasite conservation, we propose an extension of population viability analysis for host–parasite assemblages to assess extinction risk. In the direst cases, ex situ breeding programs for parasites should be evaluated to maximize success without undermining host protection. Though parasitic species pose a considerable conservation challenge, adaptations to conservation tools will help protect parasite biodiversity in the face of an uncertain environmental future.     

Assessing the current state of ecological connectivity in a large marine protected area system

The establishment of marine protected areas (MPAs) is a critical step in ensuring the continued persistence of marine biodiversity. Although the area protected in MPAs is growing, the movement of individuals (or larvae) among MPAs, termed connectivity, has only recently been included as an objective of many MPAs. As such, assessing connectivity is often neglected or oversimplified in the planning process. For promoting population persistence, it is important to ensure that protected areas in a system are functionally connected through dispersal or adult movement. We devised a multi-species model of larval dispersal for the Australian marine environment to evaluate how much local scale connectivity is protected in MPAs and determine whether the extensive system of MPAs truly functions as a network. We focused on non-migratory species with simplified larval behaviors (i.e., passive larval dispersal) (e.g., no explicit vertical migration) as an illustration. Of all the MPAs analyzed (approximately 2.7 million km²), outside the Great Barrier Reef and Ningaloo Reef, <50% of MPAs (46-80% of total MPA area depending on the species considered) were functionally connected. Our results suggest that Australia's MPA system cannot be referred to as a single network, but rather a collection of numerous smaller networks delineated by natural breaks in the connectivity of reef habitat. Depending on the dispersal capacity of the taxa of interest, there may be between 25 and 47 individual ecological networks distributed across the Australian marine environment. The need to first assess the underlying natural connectivity of a study system prior to implementing new MPAs represents a key research priority for strategically enlarging MPA networks. Our findings highlight the benefits of integrating multi-species connectivity into conservation planning to identify opportunities to better incorporate connectivity into the design of MPA systems and thus to increase their capacity to support long-term, sustainable biodiversity outcomes.