Using the theory of island biogeography as a framework, we seek to determine the potential impact of the lack of connectivity between parks and protected areas on large-scale conservation efforts. We analyze lessons learned from the current Yellowstone to Yukon (Y2Y) initiative and develop recommendations to improve connectivity while incorporating the motivations, needs, and emotions of stakeholder groups. We strongly encourage ecologists, geographers, biologists, and other academics and activists to partake wholly and enthusiastically in community-engaged scholarship through outreach, capacity building, and social capital building through the proven frameworks of consensus-based and structured decisionmaking. Further, we argue that large-scale conservation initiatives may greatly benefit from an approach focused on small, more tangible actions when working toward a larger goal. As human populations and urban–wildland interfaces continue to grow rapidly, former models of park and protected area development become increasingly ineffective. We must adopt new strategies, such as those listed here, in order to increase landscape connectivity and provide effective conservation for all species. [This is a paper from “Systemic Threats to Parks & Protected Areas,” the 2020 George Wright Society Student Summit.]

Wildlife viewing is an important activity that has the potential to raise money for conservation efforts and support small, local ecotourism operations, and communities. It is often assumed to be low impact since it is non-consumptive; however, research shows there can be negative impacts to wildlife as a result of viewing activities, which we explore in different examples below. We provide recommendations for organizations that manage these operations to keep in mind as they consider the potential impacts of these activities and develop strategies to minimize them.

Unlabelled

The majority of emerging zoonoses originate in wildlife, and many are caused by viruses. However, there are no rigorous estimates of total viral diversity (here termed "virodiversity") for any wildlife species, despite the utility of this to future surveillance and control of emerging zoonoses. In this case study, we repeatedly sampled a mammalian wildlife host known to harbor emerging zoonotic pathogens (the Indian Flying Fox, Pteropus giganteus) and used PCR with degenerate viral family-level primers to discover and analyze the occurrence patterns of 55 viruses from nine viral families. We then adapted statistical techniques used to estimate biodiversity in vertebrates and plants and estimated the total viral richness of these nine families in P. giganteus to be 58 viruses. Our analyses demonstrate proof-of-concept of a strategy for estimating viral richness and provide the first statistically supported estimate of the number of undiscovered viruses in a mammalian host. We used a simple extrapolation to estimate that there are a minimum of 320,000 mammalian viruses awaiting discovery within these nine families, assuming all species harbor a similar number of viruses, with minimal turnover between host species. We estimate the cost of discovering these viruses to be ~$6.3 billion (or ~$1.4 billion for 85% of the total diversity), which if annualized over a 10-year study time frame would represent a small fraction of the cost of many pandemic zoonoses.

Importance

Recent years have seen a dramatic increase in viral discovery efforts. However, most lack rigorous systematic design, which limits our ability to understand viral diversity and its ecological drivers and reduces their value to public health intervention. Here, we present a new framework for the discovery of novel viruses in wildlife and use it to make the first-ever estimate of the number of viruses that exist in a mammalian host. As pathogens continue to emerge from wildlife, this estimate allows us to put preliminary bounds around the potential size of the total zoonotic pool and facilitates a better understanding of where best to allocate resources for the subsequent discovery of global viral diversity.

It is currently unclear whether changes in viral communities will ever be predictable. Here we investigate whether viral communities in wildlife are inherently structured (inferring predictability) by looking at whether communities are assembled through deterministic (often predictable) or stochastic (not predictable) processes. We sample macaque faeces across nine sites in Bangladesh and use consensus PCR and sequencing to discover 184 viruses from 14 viral families. We then use network modelling and statistical null-hypothesis testing to show the presence of non-random deterministic patterns at different scales, between sites and within individuals. We show that the effects of determinism are not absolute however, as stochastic patterns are also observed. In showing that determinism is an important process in viral community assembly we conclude that it should be possible to forecast changes to some portion of a viral community, however there will always be some portion for which prediction will be unlikely.

Nipah virus (NiV) is an emerging bat-borne zoonotic virus that causes near-annual outbreaks of fatal encephalitis in South Asia-one of the most populous regions on Earth. In Bangladesh, infection occurs when people drink date-palm sap contaminated with bat excreta. Outbreaks are sporadic, and the influence of viral dynamics in bats on their temporal and spatial distribution is poorly understood. We analyzed data on host ecology, molecular epidemiology, serological dynamics, and viral genetics to characterize spatiotemporal patterns of NiV dynamics in its wildlife reservoir, Pteropus medius bats, in Bangladesh. We found that NiV transmission occurred throughout the country and throughout the year. Model results indicated that local transmission dynamics were modulated by density-dependent transmission, acquired immunity that is lost over time, and recrudescence. Increased transmission followed multiyear periods of declining seroprevalence due to bat-population turnover and individual loss of humoral immunity. Individual bats had smaller host ranges than other Pteropus species (spp.), although movement data and the discovery of a Malaysia-clade NiV strain in eastern Bangladesh suggest connectivity with bats east of Bangladesh. These data suggest that discrete multiannual local epizootics in bat populations contribute to the sporadic nature of NiV outbreaks in South Asia. At the same time, the broad spatial and temporal extent of NiV transmission, including the recent outbreak in Kerala, India, highlights the continued risk of spillover to humans wherever they may interact with pteropid bats and the importance of limiting opportunities for spillover throughout Pteropuss range.

As part of a public health behavior change and communication strategy related to the identification of a novel ebolavirus in bats in Sierra Leone in 2016, a consortium of experts launched an effort to create a widely accessible resource for community awareness and education on reducing disease risk. The resulting picture book, Living Safely With Bats, includes technical content developed by a consortium of experts in public health, animal health, conservation, bats, and disease ecology from 30 countries. The book has now been adapted, translated, and used in more than 20 countries in Africa and Asia. We review the processes used to integrate feedback from local stakeholders and multidisciplinary experts. We also provide recommendations for One Health and other practitioners who choose to pursue the development and evaluation of this or similar zoonotic disease risk mitigation tools.

In an effort to strengthen global capacity to prevent, detect, and control infectious diseases in animals and people, the United States Agency for International Development's (USAID) Emerging Pandemic Threats (EPT) PREDICT project funded development of regional, national, and local One Health capacities for early disease detection, rapid response, disease control, and risk reduction. From the outset, the EPT approach was inclusive of social science research methods designed to understand the contexts and behaviors of communities living and working at human-animal-environment interfaces considered high-risk for virus emergence. Using qualitative and quantitative approaches, PREDICT behavioral research aimed to identify and assess a range of socio-cultural behaviors that could be influential in zoonotic disease emergence, amplification, and transmission. This broad approach to behavioral risk characterization enabled us to identify and characterize human activities that could be linked to the transmission dynamics of new and emerging viruses. This paper provides a discussion of implementation of a social science approach within a zoonotic surveillance framework. We conducted in-depth ethnographic interviews and focus groups to better understand the individual- and community-level knowledge, attitudes, and practices that potentially put participants at risk for zoonotic disease transmission from the animals they live and work with, across 6 interface domains. When we asked highly-exposed individuals (ie. bushmeat hunters, wildlife or guano farmers) about the risk they perceived in their occupational activities, most did not perceive it to be risky, whether because it was normalized by years (or generations) of doing such an activity, or due to lack of information about potential risks. Integrating the social sciences allows investigations of the specific human activities that are hypothesized to drive disease emergence, amplification, and transmission, in order to better substantiate behavioral disease drivers, along with the social dimensions of infection and transmission dynamics. Understanding these dynamics is critical to achieving health security--the protection from threats to health-- which requires investments in both collective and individual health security. Involving behavioral sciences into zoonotic disease surveillance allowed us to push toward fuller community integration and engagement and toward dialogue and implementation of recommendations for disease prevention and improved health security.

Host-virus associations have co-evolved under ecological and evolutionary selection pressures that shape cross-species transmission and spillover to humans. Observed virus-host associations provide relevant context for newly discovered wildlife viruses to assess knowledge gaps in host-range and estimate pathways for potential human infection. Using models to predict virus-host networks, we predicted the likelihood of humans as hosts for 513 newly discovered viruses detected by large-scale wildlife surveillance at high-risk animal-human interfaces in Africa, Asia, and Latin America. Predictions indicated that novel coronaviruses are likely to infect a greater number of host species than viruses from other families. Our models further characterize novel viruses through prioritization scores and directly inform surveillance targets to identify host ranges for newly discovered viruses.