Microtargeting for conservation

Widespread human action and behavior change is needed to achieve many conservation goals. Doing so at the requisite scale and pace will require the efficient delivery of outreach campaigns. Conservation gains will be greatest when efforts are directed toward places of high conservation value (or need) and tailored to critical actors. Recent strategic conservation planning has relied primarily on spatial assessments of biophysical attributes, largely ignoring the human dimensions. Elsewhere, marketers, political campaigns, and others use microtargeting—predictive analytics of big data—to identify people most likely to respond positively to particular messages or interventions. Conservationists have not yet widely capitalized on these techniques. To investigate the effectiveness of microtargeting to improve conservation, we developed a propensity model to predict restoration behavior among 203,645 private landowners in a 5,200,000 ha study area in the Chesapeake Bay Watershed (U.S.A.). To isolate the additional value microtargeting may offer beyond geospatial prioritization, we analyzed a new high-resolution land-cover data set and cadastral data to identify private owners of riparian areas needing restoration. Subsequently, we developed and evaluated a restoration propensity model based on a database of landowners who had conducted restoration in the past and those who had not (n = 4978). Model validation in a parallel database (n = 4989) showed owners with the highest scorers for propensity to conduct restoration (i.e., top decile) were over twice as likely as average landowners to have conducted restoration (135%). These results demonstrate that microtargeting techniques can dramatically increase the efficiency and efficacy of conservation programs, above and beyond the advances offered by biophysical prioritizations alone, as well as facilitate more robust research of many social–ecological systems.     

Bird conservation and the land sharing-sparing continuum in farmland-dominated landscapes of lowland England

Empirical evidence from many regions suggests that most species would be least negatively affected if human food demand were met through high-yield agricultural production and conservation of nonfarm ecosystems (land sparing), rather than through wildlife-friendly farming over a larger area (land sharing). However, repeated glaciation and a long history of agriculture may lead to different results in regions such as western Europe. We compared the consequences of land sparing and land sharing on breeding bird species in 2 lowland regions of England, The Fens, with 101 species, and Salisbury Plain, with 83. We derived density–yield responses for each species and then estimated regional population size under regional food production strategies, including land sharing and land sparing, a range of intermediate strategies, and a novel mixed strategy. In both regions, more species achieved maximum regional population size under land sparing than land sharing. In The Fens, the majority of birds were loser species (estimated to have smaller populations under all food production strategies than in the preagricultural baseline scenario), whereas in Salisbury Plain the majority were winners (smaller populations in the preagricultural baseline scenario). Loser species overwhelmingly achieved maximum regional population size under land sparing, whereas winner species achieved maximum regional population size under either land sharing or an intermediate strategy, highlighting the importance of defining which groups of species are the target of conservation. A novel 3-compartment strategy (combining high-yield farming, natural habitat, and low-yield farming) often performed better than either land sharing or land sparing. Our results support intermediate or 3-compartment land-sparing strategies to maximize bird populations across lowland agricultural landscapes. To deliver conservation outcomes, any shift toward land sparing must, however, ensure yield increases are sustainable in the long term, do not entail increased negative effects on surrounding areas, and are linked to allocation of land for nature.     

Using the past to contextualize anthropogenic impacts on the present and future distribution of an endemic Caribbean mammal

Island species are difficult to conserve because they face the synergy of climate change, invasive species, deforestation, and increasing human population densities in areas where land mass is shrinking. The Caribbean island of Hispaniola presents particular challenges because of geopolitical complexities that span 2 countries and hinder coordinated management of species across the island. We employed species distribution modeling to evaluate the impacts of climatic change and anthropogenic activities on the distribution of an endemic mammal of conservation concern, the Hispaniolan solenodon (Solenodon paradoxus). We aggregated occurrence points for this poorly known species for the Last Glacial Maximum (LGM) and the present (1975–2016) based on museum collections, online biodiversity databases, and new field surveys. We quantified degree of overlap between periods and scenarios with Schoener's D. Through a conservation paleobiology lens, we found that over time humans played an increasing role in shaping the distribution of S. paradoxus, thus, providing a foundation for developing conservation strategies on appropriate spatiotemporal scales. Human population density was the single most important predictor of S. paradoxus occurrence. Densities >166 people/km² corresponded to a near-zero probability of occurrence. Models that accounted for climate but not anthropogenic variables falsely identified suitable habitat in Haiti, where on-the-ground surveys confirm habitat is unavailable. Climate-only models also significantly overestimated the potential for habitat connectivity between isolated populations. Our work highlights that alternative fates for S. paradoxus in the Anthropocene exist across the political border between the Dominican Republic and Haiti due to the fundamentally different economic and political realities of each country. Relationships in the fossil record confirm that Hispaniola's sociopolitical boundary is not biologically significant but instead represents one imposed on the island's fauna in the past 500 years by colonial activity. Our approach reveals how a paleontological perspective can contribute to concrete management insights.     

Effectiveness of conservation easements in agricultural regions

Conservation easements are a standard technique for preventing habitat loss, particularly in agricultural regions with extensive cropland cultivation, yet little is known about their effectiveness. I developed a spatial econometric approach to propensity‐score matching and used the approach to estimate the amount of habitat loss prevented by a grassland conservation easement program of the U.S. federal government. I used a spatial autoregressive probit model to predict tract enrollment in the easement program as of 2001 based on tract agricultural suitability, habitat quality, and spatial interactions among neighboring tracts. Using the predicted values from the model, I matched enrolled tracts with similar unenrolled tracts to form a treatment group and a control group. To measure the program's impact on subsequent grassland loss, I estimated cropland cultivation rates for both groups in 2014 with a second spatial probit model. Between 2001 and 2014, approximately 14.9% of control tracts were cultivated and 0.3% of treated tracts were cultivated. Therefore, approximately 14.6% of the protected land would have been cultivated in the absence of the program. My results demonstrate that conservation easements can significantly reduce habitat loss in agricultural regions; however, the enrollment of tracts with low cropland suitability may constrain the amount of habitat loss they prevent. My results also show that spatial econometric models can improve the validity of control groups and thereby strengthen causal inferences about program effectiveness in situations when spatial interactions influence conservation decisions.     

Understanding the distribution of bushmeat hunting effort across landscapes by testing hypotheses about human foraging

Mitigating the massive impacts of defaunation on natural ecosystems requires understanding and predicting hunting effort across the landscape. But such understanding has been hindered by the difficulty of assessing the movement patterns of hunters in thick forests and across complex terrain. We statistically tested hypotheses about the spatial distribution of hunting with circuit theory and structural equation models. We used a data set of >7000 known kill locations in Guyana and hunter movement models to test these methods. Comparing models with different resistance layers (i.e., different estimates of how terrain and land cover influence human movement speed) showed that rivers, on average, limited movement rather than serving as transport arteries. Moreover, far more kills occurred close to villages than in remote areas. This, combined with the lack of support for structural equation models that included latent terms for prey depletion driven by past overhunting, suggests that kill locations in this system tended to be driven by where hunters were currently foraging rather than by influences of historical harvest. These analyses are generalizable to a variety of ecosystems, species, and data types, providing a powerful way of enhancing maps and predictions of hunting effort across complex landscapes.     

Temporal Analysis of Genetic Structure to Assess Population Dynamics of Reintroduced Swift Foxes

Reintroductions are increasingly used to reestablish species, but a paucity of long‐term postrelease monitoring has limited understanding of whether and when viable populations subsequently persist. We conducted temporal genetic analyses of reintroduced populations of swift foxes (Vulpes velox) in Canada (Alberta and Saskatchewan) and the United States (Montana). We used samples collected 4 years apart, 17 years from the initiation of the reintroduction, and 3 years after the conclusion of releases. To assess program success, we genotyped 304 hair samples, subsampled from the known range in 2000 and 2001, and 2005 and 2006, at 7 microsatellite loci. We compared diversity, effective population size, and genetic connectivity over time in each population. Diversity remained stable over time and there was evidence of increasing effective population size. We determined population structure in both periods after correcting for differences in sample sizes. The geographic distribution of these populations roughly corresponded with the original release locations, which suggests the release sites had residual effects on the population structure. However, given that both reintroduction sites had similar source populations, habitat fragmentation, due to cropland, may be associated with the population structure we found. Although our results indicate growing, stable populations, future connectivity analyses are warranted to ensure both populations are not subject to negative small‐population effects. Our results demonstrate the importance of multiple sampling years to fully capture population dynamics of reintroduced populations. Análisis Temporal de la Estructura Genética para Evaluar la Dinámica Poblacional de Zorros (Vulpes velox) Reintroducidos     

How Research‐Prioritization Exercises Affect Conservation Policy

Abstract: Conservation scientists are concerned about the apparent lack of impact their research is having on policy. By better aligning research with policy needs, conservation science might become more relevant to policy and increase its real‐world salience in the conservation of biological diversity. Consequently, some conservation scientists have embarked on a variety of exercises to identify research questions that, if answered, would provide the evidence base with which to develop and implement effective conservation policies. I synthesized two existing approaches to conceptualizing research impacts. One widely used approach classifies the impacts of research as conceptual, instrumental, and symbolic. Conceptual impacts occur when policy makers are sensitized to new issues and change their beliefs or thinking. Instrumental impacts arise when scientific research has a direct effect on policy decisions. The use of scientific research results to support established policy positions are symbolic impacts. The second approach classifies research issues according to whether scientific knowledge is developed fully and whether the policy issue has been articulated clearly. I believe exercises to identify important research questions have objectives of increasing the clarity of policy issues while strengthening science–policy interactions. This may facilitate the transmission of scientific knowledge to policy makers and, potentially, accelerate the development and implementation of effective conservation policy. Other, similar types of exercises might also be useful. For example, identification of visionary science questions independent of current policy needs, prioritization of best practices for transferring scientific knowledge to policy makers, and identification of questions about human values and their role in political processes could all help advance real‐world conservation science. It is crucial for conservation scientists to understand the wide variety of ways in which their research can affect policy and be improved systematically.     

Dynamics in the global protected-area estate since 2004

Nations of the world have committed to a number of goals and targets to address global environmental challenges. Protected areas have for centuries been a key strategy in conservation and play a major role in addressing current challenges. The most important tool used to track progress on protected-area commitments is the World Database on Protected Areas (WDPA). Periodic assessments of the world's protected-area estate show steady growth over the last 2 decades. However, the current method, which uses the latest version of the WDPA, does not show the true dynamic nature of protected areas over time and does not provide information on sites removed from the WDPA. In reality, this method can only show growth or remain stable. We used GIS tools in an approach to assess protected-area change over time based on 12 temporally distinct versions of the WDPA that quantify area added and removed from the WDPA annually from 2004 to 2016. Both the narrative of continual growth of protected area and the counter-narrative of protected area removal were overly simplistic. The former because growth was almost entirely in the marine realm and the latter because some areas removed were reprotected in later years. On average 2.5 million km² was added to the WDPA annually and 1.1 million km² was removed. Reasons for the inclusion and removal of protected areas in the WDPA database were in part due to data-quality issues but also to on-the-ground changes. To meet the 17% protected-area component of Aichi Biodiversity Target 11 by 2020, which stood at 14.7% in 2016, either the rate of protected-area removal must decrease or the rate of protected-area designation and addition to the WDPA must increase.     

Quantifying biases in marine-protected-area placement relative to abatable threats

Marine protected areas (MPAs) are a critical defense against biodiversity loss in the world's oceans, but to realize near-term conservation benefits, they must be established where major threats to biodiversity occur and can be mitigated. We quantified the degree to which MPA establishment has targeted stoppable threats (i.e., threats that can be abated through effectively managed MPAs alone) by combining spatially explicit marine biodiversity threat data in 2008 and 2013 and information on the location and potential of MPAs to halt threats. We calculated an impact metric to determine whether countries are protecting proportionally more high- or low-threat ecoregions and compared observed values with random protected-area allocation. We found that protection covered <2% of ecoregions in national waters with high levels of abatable threat in 2013, which is ∼59% less protection in high-threat areas than if MPAs had been placed randomly. Relatively low-threat ecoregions had 6.3 times more strict protection (International Union for Conservation of Nature categories I–II) than high-threat ecoregions. Thirty-one ecoregions had high levels of stoppable threat but very low protection, which presents opportunities for MPAs to yield more significant near-term conservation benefits. The extent of the global MPA estate has increased, but the establishment of MPAs where they can reduce threats that are driving biodiversity loss is now urgently needed.     

Detecting deterrence from patrol data

The threat posed to protected areas by the illegal killing of wildlife is countered principally by ranger patrols that aim to detect and deter potential offenders. Deterring poaching is a fundamental conservation objective, but its achievement is difficult to identify, especially when the prime source of information comes in the form of the patrols’ own records, which inevitably contain biases. The most common metric of deterrence is a plot of illegal activities detected per unit of patrol effort (CPUE) against patrol effort (CPUE-E). We devised a simple, mechanistic model of law breaking and law enforcement in which we simulated deterrence alongside exogenous changes in the frequency of offences under different temporal patterns of enforcement effort. The CPUE-E plots were not reliable indicators of deterrence. However, plots of change in CPUE over change in effort (ΔCPUE-ΔE) reliably identified deterrence, regardless of the temporal distribution of effort or any exogenous change in illegal activity levels as long as the time lag between patrol effort and subsequent behavioral change among offenders was approximately known. The ΔCPUE-ΔE plots offered a robust, simple metric for monitoring patrol effectiveness; were no more conceptually complicated than the basic CPUE-E plots; and required no specialist knowledge or software to produce. Our findings demonstrate the need to account for temporal autocorrelation in patrol data and to consider appropriate (and poaching-activity-specific) intervals for aggregation. They also reveal important gaps in understanding of deterrence in this context, especially the mechanisms by which it occurs. In practical applications, we recommend the use of ΔCPUE-ΔE plots in preference to other basic metrics and advise that deterrence should be suspected only if there is a clear negative slope. Distinct types of illegal activity should not be grouped together for analysis, especially if the signs of their occurrence have different persistence times in the environment.