Use of a Business Excellence Model to Improve Conservation Programs

Abstract: The current shortfall in effectiveness within conservation biology is illustrated by increasing interest in “evidence‐based conservation,” whose proponents have identified the need to benchmark conservation initiatives against actions that lead to proven positive effects. The effectiveness of conservation policies, approaches, and evaluation is under increasing scrutiny, and in these areas models of excellence used in business could prove valuable. Typically, conservation programs require years of effort and involve rigorous long‐term implementation processes. Successful balance of long‐term efforts alongside the achievement of short‐term goals is often compromised by management or budgetary constraints, a situation also common in commercial businesses. “Business excellence” is an approach many companies have used over the past 20 years to ensure continued success. Various business excellence evaluations have been promoted that include concepts that could be adapted and applied in conservation programs. We describe a conservation excellence model that shows how scientific processes and results can be aligned with financial and organizational measures of success. We applied the model to two well‐documented species conservation programs. In the first, the Po’ouli program, several aspects of improvement were identified, such as more authority for decision making in the field and better integration of habitat management and population recovery processes. The second example, the black‐footed ferret program, could have benefited from leadership effort to reduce bureaucracy and to encourage use of best‐practice species recovery approaches. The conservation excellence model enables greater clarity in goal setting, more‐effective identification of job roles within programs, better links between technical approaches and measures of biological success, and more‐effective use of resources. The model could improve evaluation of a conservation program's effectiveness and may be used to compare different programs, for example during reviews of project performance by sponsoring organizations.     

Value of protected areas to avian persistence across 20 years of climate and land-use change

Establishing protected areas, where human activities and land cover changes are restricted, is among the most widely used strategies for biodiversity conservation. This practice is based on the assumption that protected areas buffer species from processes that drive extinction. However, protected areas can maintain biodiversity in the face of climate change and subsequent shifts in distributions have been questioned. We evaluated the degree to which protected areas influenced colonization and extinction patterns of 97 avian species over 20 years in the northeastern United States. We fitted single-visit dynamic occupancy models to data from Breeding Bird Atlases to quantify the magnitude of the effect of drivers of local colonization and extinction (e.g., climate, land cover, and amount of protected area) in heterogeneous landscapes that varied in the amount of area under protection. Colonization and extinction probabilities improved as the amount of protected area increased, but these effects were conditional on landscape context and species characteristics. In this forest-dominated region, benefits of additional land protection were greatest when both forest cover in a grid square and amount of protected area in neighboring grid squares were low. Effects did not vary with species’ migratory habit or conservation status. Increasing the amounts of land protection benefitted the range margins species but not the core range species. The greatest improvements in colonization and extinction rates accrued for forest birds relative to open-habitat or generalist species. Overall, protected areas stemmed extinction more than they promoted colonization. Our results indicate that land protection remains a viable conservation strategy despite changing habitat and climate, as protected areas both reduce the risk of local extinction and facilitate movement into new areas. Our findings suggest conservation in the face of climate change favors creation of new protected areas over enlarging existing ones as the optimal strategy to reduce extinction and provide stepping stones for the greatest number of species.     

A spatial approach to combatting wildlife crime

Poaching can have devastating impacts on animal and plant numbers, and in many countries has reached crisis levels, with illegal hunters employing increasingly sophisticated techniques. We used data from an 8‐year study in Savé Valley Conservancy, Zimbabwe, to show how geographic profiling—a mathematical technique originally developed in criminology and recently applied to animal foraging and epidemiology—can be adapted for use in investigations of wildlife crime. The data set contained information on over 10,000 incidents of illegal hunting and the deaths of 6,454 wild animals. We used a subset of data for which the illegal hunters’ identities were known. Our model identified the illegal hunters’ home villages based on the spatial locations of the hunting incidences (e.g., snares). Identification of the villages was improved by manipulating the probability surface inside the conservancy to reflect the fact that although the illegal hunters mostly live outside the conservancy, the majority of hunting occurs inside the conservancy (in criminology terms, commuter crime). These results combined with rigorous simulations showed for the first time how geographic profiling can be combined with GIS data and applied to situations with more complex spatial patterns, for example, where landscape heterogeneity means some parts of the study area are less likely to be used (e.g., aquatic areas for terrestrial animals) or where landscape permeability differs (e.g., forest bats tend not to fly over open areas). More broadly, these results show how geographic profiling can be used to target antipoaching interventions more effectively and more efficiently and to develop management strategies and conservation plans in a range of conservation scenarios.     

Hybridization,agency discretion,and implementation of the U.S. Endangered Species Act

The U.S. Endangered Species Act (ESA) requires that the “best available scientific and commercial data” be used to protect imperiled species from extinction and preserve biodiversity. However, it does not provide specific guidance on how to apply this mandate. Scientific data can be uncertain and controversial, particularly regarding species delineation and hybridization issues. The U.S. Fish and Wildlife Service (FWS) had an evolving hybrid policy to guide protection decisions for individuals of hybrid origin. Currently, this policy is in limbo because it resulted in several controversial conservation decisions in the past. Biologists from FWS must interpret and apply the best available science to their recommendations and likely use considerable discretion in making recommendations for what species to list, how to define those species, and how to recover them. We used semistructured interviews to collect data on FWS biologists’ use of discretion to make recommendations for listed species with hybridization issues. These biologists had a large amount of discretion to determine the best available science and how to interpret it but generally deferred to the scientific consensus on the taxonomic status of an organism. Respondents viewed hybridization primarily as a problem in the context of the ESA, although biologists who had experience with hybridization issues were more likely to describe it in more nuanced terms. Many interviewees expressed a desire to continue the current case‐by‐case approach for handling hybridization issues, but some wanted more guidance on procedures (i.e., a “flexible” hybrid policy). Field‐level information can provide critical insight into which policies are working (or not working) and why. The FWS biologists’ we interviewed had a high level of discretion, which greatly influenced ESA implementation, particularly in the context of hybridization.     

Rank aggregation of local expert knowledge for conservation planning of the critically endangered saola

There has been much recent interest in using local knowledge and expert opinion for conservation planning, particularly for hard‐to‐detect species. Although it is possible to ask for direct estimation of quantities such as population size, relative abundance is easier to estimate. However, an expert's knowledge is often geographically restricted relative to the area of interest. Combining (or aggregating) experts’ assessments of relative abundance is difficult when each expert only knows a part of the area of interest. We used Google's PageRank algorithm to aggregate ranked abundance scores elicited from local experts through a rapid rural‐appraisal method. We applied this technique to conservation planning for the saola (Pseudoryx nghetinhensis), a poorly known bovid. Near a priority landscape for the species, composed of 3 contiguous protected areas, we asked groups of local people to indicate relative abundances of saola and other species by placing beans on community maps. For each village, we used this information to rank areas within the knowledge area of that village for saola abundance. We used simulations to compare alternative methods to aggregate the rankings from the different villages. The best‐performing method was then used to produce a single map of relative abundance across the entire landscape, an area larger than that known to any one village. This map has informed prioritization of surveys and conservation action in the continued absence of direct information about the saola.     

On nonepistemic values in conservation biology

Conservation biology is a uniquely interdisciplinary science with strong roots in ecology, but it also embraces a value‐laden and mission‐oriented framework. This combination of science and values causes conservation biology to be at the center of critique regarding the discipline's scientific credibility—especially the division between the realms of theory and practice. We identify this dichotomy between seemingly objective (fact‐based) and subjective (value‐laden) practices as the measure‐value dichotomy, whereby measure refers to methods and analyses used in conservation biology (i.e., measuring biodiversity) and value refers to nonepistemic values. We reviewed and evaluated several landmark articles central to the foundation of conservation biology and concepts of biodiversity with respect to their attempts to separate measures and values. We argue that the measure‐value dichotomy is false and that conservation biology can make progress in ways unavailable to other disciplines because its practitioners are tasked with engaging in both the realm of theory and the realm of practice. The entanglement of measures and values is by no means a weakness of conservation biology. Because central concepts such as biodiversity contain both factual and evaluative aspects, conservation biologists can make theoretical progress by examining, reviewing, and forming the values that are an integral part of those concepts. We suggest that values should be included and analyzed with respect to the methods, results, and conclusions of scientific work in conservation biology.     

Judging adaptive management practices of U.S. agencies

All U.S. federal agencies administering environmental laws purport to practice adaptive management (AM), but little is known about how they actually implement this conservation tool. A gap between the theory and practice of AM is revealed in judicial decisions reviewing agency adaptive management plans. We analyzed all U.S. federal court opinions published through 1 January 2015 to identify the agency AM practices courts found most deficient. The shortcomings included lack of clear objectives and processes, monitoring thresholds, and defined actions triggered by thresholds. This trio of agency shortcuts around critical, iterative steps characterizes what we call AM‐lite. Passive AM differs from active AM in its relative lack of management interventions through experimental strategies. In contrast, AM‐lite is a distinctive form of passive AM that fails to provide for the iterative steps necessary to learn from management. Courts have developed a sophisticated understanding of AM and often offer instructive rather than merely critical opinions. The role of the judiciary is limited by agency discretion under U.S. administrative law. But courts have overturned some agency AM‐lite practices and insisted on more rigorous analyses to ensure that the promised benefits of structured learning and fine‐tuned management have a reasonable likelihood of occurring. Nonetheless, there remains a mismatch in U.S. administrative law between the flexibility demanded by adaptive management and the legal objectives of transparency, public participation, and finality.     

Using global sensitivity analysis of demographic models for ecological impact assessment

Population viability analysis (PVA) is widely used to assess population‐level impacts of environmental changes on species. When combined with sensitivity analysis, PVA yields insights into the effects of parameter and model structure uncertainty. This helps researchers prioritize efforts for further data collection so that model improvements are efficient and helps managers prioritize conservation and management actions. Usually, sensitivity is analyzed by varying one input parameter at a time and observing the influence that variation has over model outcomes. This approach does not account for interactions among parameters. Global sensitivity analysis (GSA) overcomes this limitation by varying several model inputs simultaneously. Then, regression techniques allow measuring the importance of input‐parameter uncertainties. In many conservation applications, the goal of demographic modeling is to assess how different scenarios of impact or management cause changes in a population. This is challenging because the uncertainty of input‐parameter values can be confounded with the effect of impacts and management actions. We developed a GSA method that separates model outcome uncertainty resulting from parameter uncertainty from that resulting from projected ecological impacts or simulated management actions, effectively separating the 2 main questions that sensitivity analysis asks. We applied this method to assess the effects of predicted sea‐level rise on Snowy Plover (Charadrius nivosus). A relatively small number of replicate models (approximately 100) resulted in consistent measures of variable importance when not trying to separate the effects of ecological impacts from parameter uncertainty. However, many more replicate models (approximately 500) were required to separate these effects. These differences are important to consider when using demographic models to estimate ecological impacts of management actions.     

Antipoaching standards in onshore hydrocarbon concessions drawn from a Central African case study

Unsustainable hunting outside protected areas is threatening tropical biodiversity worldwide and requires conservationists to engage increasingly in antipoaching activities. Following the example of ecocertified logging companies, we argue that other extractive industries managing large concessions should engage in antipoaching activities as part of their environmental management plans. Onshore hydrocarbon concessions should also adopt antipoaching protocols as a standard because they represent a biodiversity threat comparable to logging. We examined the spatiotemporal patterns of small‐ and large‐mammal poaching in an onshore oil concession in Gabon, Central Africa, with a Bayesian occupancy model based on signs of poaching collected from 2010 to 2015 on antipoaching patrols. Patrol locations were initially determined based on local intelligence and past patrol successes (adaptive management) and subsequently with a systematic sampling of the concession. We generated maps of poaching probability in the concession and determined the temporal trends of this threat over 5 years. The spatiotemporal patterns of large‐ and small‐mammal poaching differed throughout the concession, and likely these groups will need different management strategies. By elucidating the relationship between site‐specific sampling effort and detection probability, the Bayesian method allowed us to set goals for future antipoaching patrols. Our results indicate that a combination of systematic sampling and adaptive management data is necessary to infer spatiotemporal patterns with the statistical method we used. On the basis of our case study, we recommend hydrocarbon companies interested in implementing efficient antipoaching activities in their onshore concessions to lay the foundation of long‐needed industry standards by: adequately measuring antipoaching effort; mixing adaptive management and balanced sampling; setting goals for antipoaching effort; pairing patrols with large‐mammal monitoring; supporting antipoaching patrols across the landscape; restricting access to their concessions; performing random searches for bushmeat and mammal products at points of entry; controlling urban and agricultural expansion; supporting bushmeat alternatives; and supporting land‐use planning.