Search for: All records

ABSTRACT Conservation initiatives depend on interactions among organizations and communities that have different goals. Multilevel hierarchies provide a common decision‐making structure with different actors responsible for conservation decisions over nested spatial scales. We examine consequences of hierarchical decision‐making for spatial prioritization of new protected areas. We combine insights from general theory, an algebraic example, and a numerical application, the latter motivated by federal‐to‐state grant‐giving in the western United States. Working through a decision‐making hierarchy means fewer species can be protected for a given budget than suggested by analyses that ignore the role of conservation institutions in decision‐making. This efficiency cost results from higher level decision‐makers—the federal government in our numerical application—giving up control to lower level actors—state governments in this case. Ensuring close agreement over spatial priorities between actors can limit potential losses in how much biodiversity can be protected. By reallocating funds among lower level actors, the higher level actor can mitigate remaining losses. Spatial optimization approaches that ignore the integral role of institutions in conservation, like decision‐making hierarchies, overestimate what protected area programs can achieve and risk misallocating limited conservation funds. Accounting for multilevel decision‐making reveals where building consensus among actors will be particularly important and suggests alternative strategies that conservation funders can pursue. 

Illicit Wildlife Trade (IWT) is a serious global crime that negatively impacts biodiversity, human health, national security, and economic development. Many flora and fauna are trafficked in different product forms. We investigate a network interdiction problem for wildlife trafficking and introduce a new model to tackle key challenges associated with IWT. Our model captures the interdiction problem faced by law enforcement impeding IWT on flight networks, though it can be extended to other types of transportation networks. We incorporate vital issues unique to IWT, including the need for training and difficulty recognizing illicit wildlife products, the impact of charismatic species and geopolitical differences, and the varying amounts of information and objectives traffickers may use when choosing transit routes. Additionally, we incorporate different detection probabilities at nodes and along arcs depending on law enforcement’s interdiction and training actions. We present solutions for several key IWT supply chains using realistic data from conservation research, seizure databases, and international reports. We compare our model to two benchmark models and highlight key features of the interdiction strategy. We discuss the implications of our models for combating IWT in practice and highlight critical areas of concern for stakeholders. 

Given declines in biodiversity and ecosystem services, funding to support conservation must be invested effectively. However, funds for conservation often come with geographic restrictions on where they can be spent. We introduce a method to demonstrate to supporters of conservation how much more could be achieved if they were to allow greater flexibility over conservation funding. Specifically, we calculated conservation exchange rates that summarized gains in conservation outcomes available if funding originating in one location could be invested elsewhere. We illustrate our approach by considering nongovernmental organization funding and major federal programs within the US and a range of conservation objectives focused on biodiversity and ecosystem services. We show that large improvements in biodiversity and ecosystem service provision are available if geographic constraints on conservation funding were loosened. Finally, we demonstrate how conservation exchange rates can be used to spotlight promising opportunities for relaxing geographic funding restrictions. 

Wildlife trafficking is a global phenomenon posing many negative impacts on socio-environmental systems. Scientific exploration of wildlife trafficking trends and the impact of interventions is signifi-cantly encumbered by a suite of data reuse challenges. We describe a novel, open-access data directory on wildlife trafficking and a corresponding visualization tool that can be used to identify data for multiple purposes, such as exploring wildlife trafficking hotspots and convergence points with other crime, discovering key drivers or deterrents of wildlife trafficking, and uncovering structural patterns. Keyword searches, expert elicitation, and peer- reviewed publications were used to search for extant sources used by industry and non-profit organizations, as well as those leveraged to publish academic research articles. The open-access data direc-tory is designed to be a living document and searchable according to multiple measures. The directory can be instrumental in the data- driven analysis of unsustainable illegal wildlife trade, supply chain structure via link prediction models, the value of demand and supply reduction initiatives via multi-item knapsack problems, or trafficking behavior and transportation choices via network inter-diction problems.