A counterfactual approach to measure the impact of wet grassland conservation on U.K. breeding bird populations

Wet grassland populations of wading birds in the United Kingdom have declined severely since 1990. To help mitigate these declines, the Royal Society for the Protection of Birds has restored and managed lowland wet grassland nature reserves to benefit these and other species. However, the impact of these reserves on bird population trends has not been evaluated experimentally due to a lack of control populations. We compared population trends from 1994 to 2018 among 5 bird species of conservation concern that breed on these nature reserves with counterfactual trends created from matched breeding bird survey observations. We compared reserve trends with 3 different counterfactuals based on different scenarios of how reserve populations could have developed in the absence of conservation. Effects of conservation interventions were positive for all 4 targeted wading bird species: Lapwing (Vanellus vanellus), Redshank (Tringa totanus), Curlew (Numenius arquata), and Snipe (Gallinago gallinago). There was no positive effect of conservation interventions on reserves for the passerine, Yellow Wagtail (Motacilla flava). Our approach using monitoring data to produce valid counterfactual controls is a broadly applicable method allowing large-scale evaluation of conservation impact.     

Using expert knowledge to support Endangered Species Act decision-making for data-deficient species

Many questions relevant to conservation decision-making are characterized by extreme uncertainty due to lack of empirical data and complexity of the underlying ecologic processes, leading to a rapid increase in the use of structured protocols to elicit expert knowledge. Published ecologic applications often employ a modified Delphi method, where experts provide judgments anonymously and mathematical aggregation techniques are used to combine judgments. The Sheffield elicitation framework (SHELF) differs in its behavioral approach to synthesizing individual judgments into a fully specified probability distribution for an unknown quantity. We used the SHELF protocol remotely to assess extinction risk of three subterranean aquatic species that are being considered for listing under the U.S. Endangered Species Act. We provided experts an empirical threat assessment for each known locality over a video conference and recorded judgments on the probability of population persistence over four generations with online submission forms and R-shiny apps available through the SHELF package. Despite large uncertainty for all populations, there were key differences between species’ risk of extirpation based on spatial variation in dominant threats, local land use and management practices, and species’ microhabitat. The resulting probability distributions provided decision makers with a full picture of uncertainty that was consistent with the probabilistic nature of risk assessments. Discussion among experts during SHELF's behavioral aggregation stage clearly documented dominant threats (e.g., development, timber harvest, animal agriculture, and cave visitation) and their interactions with local cave geology and species’ habitat. Our virtual implementation of the SHELF protocol demonstrated the flexibility of the approach for conservation applications operating on budgets and time lines that can limit in-person meetings of geographically dispersed experts.     

Focus and social contagion of environmental organization advocacy on Twitter

Agriculture, overexploitation, and urbanization remain the major threats to biodiversity in the Anthropocene. The attention these threats garner among leading environmental nongovernmental organizations (eNGOs) and the wider public is critical in fostering the political will necessary to reverse biodiversity declines worldwide. I analyzed the advocacy of leading eNGOs on Twitter by scraping account timelines, screening content for advocacy relating to biodiversity threats and, for prevalent threats, further screening content for positive and negative emotional language with a sentiment lexicon. Twitter advocacy was dominated by the major threats of climate change and overexploitation and the minor threat of plastic pollution. The major threats of agriculture, urbanization, invasions, and pollution were rarely addressed. Content relating to overexploitation and plastic pollution was more socially contagious than other content. Increasing emotional negativity further increased social contagion, whereas increasing emotional positivity did not. Scientists, policy makers, and eNGOs should consider how narrowly focused advocacy on platforms like Twitter will contribute to effective global biodiversity conservation.     

Reconciling multiple counterfactuals when evaluating biodiversity conservation impact in social-ecological systems

When evaluating the impact of a biodiversity conservation intervention, a counterfactual is typically needed. Counterfactuals are possible alternative system trajectories in the absence of an intervention. Comparing observed outcomes against the chosen counterfactual allows the impact (change attributable to the intervention) to be determined. Because counterfactuals by definition never occur, they must be estimated. Sometimes, there may be many plausible counterfactuals, including various drivers of biodiversity change and defined on a range of spatial or temporal scales. Here, we posit that, by definition, conservation interventions always take place in social-ecological systems (SES) (i.e., ecological systems integrated with human actors). Evaluating the impact of an intervention in an SES, therefore, means taking into account the counterfactuals assumed by different human actors. Use of different counterfactuals by different actors will give rise to perceived differences in the impacts of interventions, which may lead to disagreement about its success or the effectiveness of the underlying approach. Despite that there are biophysical biodiversity trends, it is often true that no single counterfactual is definitively the right one for conservation assessment, so multiple evaluations of intervention efficacy could be considered justifiable. Therefore, we propose calculating the sum of perceived differences, which captures the range of impact estimates associated with different actors in a given SES. The sum of perceived differences gives some indication of how closely actors in an SES agree on the impacts of an intervention. We applied the concept of perceived differences to a set of global, national, and regional case studies (e.g., global realization of Aichi Target 11 for marine protected areas, effect of biodiversity offsetting on vegetation condition in Australia, and influence of conservation measures on an endangered ungulate in Central Asia). We explored approaches for minimizing the sum, including a combination of negotiation and structured decision making, careful alignment of expectations on scope and measurement, and explicit recognition of any intractable differences between stakeholders.     

Automated conservation assessment of the orchid family with deep learning

International Union for Conservation of Nature (IUCN) Red List assessments are essential for prioritizing conservation needs but are resource intensive and therefore available only for a fraction of global species richness. Automated conservation assessments based on digitally available geographic occurrence records can be a rapid alternative, but it is unclear how reliable these assessments are. We conducted automated conservation assessments for 13,910 species (47.3% of the known species in the family) of the diverse and globally distributed orchid family (Orchidaceae), for which most species (13,049) were previously unassessed by IUCN. We used a novel method based on a deep neural network (IUC-NN). We identified 4,342 orchid species (31.2% of the evaluated species) as possibly threatened with extinction (equivalent to IUCN categories critically endangered [CR], endangered [EN], or vulnerable [VU]) and Madagascar, East Africa, Southeast Asia, and several oceanic islands as priority areas for orchid conservation. Orchidaceae provided a model with which to test the sensitivity of automated assessment methods to problems with data availability, data quality, and geographic sampling bias. The IUC-NN identified possibly threatened species with an accuracy of 84.3%, with significantly lower geographic evaluation bias relative to the IUCN Red List and was robust even when data availability was low and there were geographic errors in the input data. Overall, our results demonstrate that automated assessments have an important role to play in identifying species at the greatest risk of extinction.     

Determinants of population persistence and abundance of terrestrial and arboreal vertebrates stranded in tropical forest land-bridge islands

Megadams are among the key modern drivers of habitat and biodiversity loss in emerging economies. The Balbina Hydroelectric Dam of Central Brazilian Amazonia inundated 312,900 ha of primary forests and created approximately 3500 variable-sized islands that still harbor vertebrate populations after nearly 3 decades after isolation. We estimated the species richness, abundance, biomass, composition, and group size of medium- to large-bodied forest vertebrates in response to patch, landscape, and habitat-quality metrics across 37 islands and 3 continuous forest sites throughout the Balbina archipelago. We conducted 1168 km of diurnal censuses and had 12,420 camera-trapping days along 81 transects with 207 camera stations. We determined the number of individuals (or groups) detected per 10 km walked and the number of independent photographs per 10 camera-trapping days, respectively, for each species. We recorded 34 species, and patch area was the most significant predictor of vertebrate population relative abundance and aggregate biomass. The maximum group size of several group-living species was consistently larger on large islands and in continuous patches than on small islands. Most vertebrate populations were extirpated after inundation. Remaining populations are unlikely to survive further ecological disruptions. If all vertebrate species were once widely distributed before inundation, we estimated that approximately 75% of all individual vertebrates were lost from all 3546 islands and 7.4% of the animals in all persisting insular populations are highly likely to be extirpated. Our results demonstrate that population abundance estimates should be factored into predictions of community disassembly on small islands to robustly predict biodiversity outcomes. Given the rapidly escalating hydropower infrastructure projects in developing counties, we suggest that faunal abundance and biomass estimates be considered in environmental impact assessments and large strictly protected reserves be established to minimize detrimental effects of dams on biodiversity. Conserving large tracts of continuous forests represents the most critical conservation measure to ensure that animal populations can persist at natural densities in Amazonian forests.     

Global protected-area coverage and human pressure on tidal flats

Tidal flats are a globally distributed coastal ecosystem important for supporting biodiversity and ecosystem services. Local to continental-scale studies have documented rapid loss of tidal habitat driven by human impacts, but assessments of progress in their conservation are lacking. With an internally consistent estimate of distribution and change, based on Landsat satellite imagery, now available for the world's tidal flats, we examined tidal flat representation in protected areas (PAs) and human pressure on tidal flats. We determined tidal flat representation and its net change in PAs by spatially overlaying tidal flat maps with the World Database of Protected Areas. Similarly, we overlaid the most recent distribution map of tidal flats (2014–2016) with the human modification map (HM_c) (range from 0, no human pressure, to 1, very high human pressure) to estimate the human pressure exerted on this ecosystem. Sixty-eight percent of the current extent of tidal flats is subject to moderate to very high human pressure (HM_c > 0.1), but 31% of tidal flat extent occurred in PAs, far exceeding PA coverage of the marine (6%) and terrestrial (13%) realms. Net change of tidal flat extent inside PAs was similar to tidal flat net change outside PAs from 1999 to 2016. Substantial shortfalls in protection of tidal flats occurred across Asia, where large intertidal extents coincided with high to very high human pressure (HM_c > 0.4–1.0) and net tidal flat losses up to 86.4 km² (95% CI 83.9–89.0) occurred inside individual PAs in the study period. Taken together, our results show substantial progress in PA designation for tidal flats globally, but that PA status alone does not prevent all habitat loss. Safeguarding the world's tidal flats will thus require deeper understanding of the factors that govern their dynamics and effective policy that promotes holistic coastal and catchment management strategies.     

The bean method as a tool to measure sensitive behavior

Conservationists need to measure human behavior to guide decisions and evaluate their impact. However, activities can be misreported and reporting accuracy may change following conservation interventions, making it hard to verify any apparent changes. Techniques for asking sensitive questions are increasingly integrated into survey designs to improve data quality, but some can be costly or hard for nonexperts to implement. We demonstrate a straightforward, low-cost approach, the bean method in which respondents give anonymous answers by adding a colored bean to a jar to denote a yes or no response. We applied the bean method to measure wild-meat hunting and trading over 2 years at a conservation-project (hunting reduction) site in Gola Forest, Liberia. We extended the technique to accommodate questions about hunting and meat-selling frequency. We compared responses given using the bean method and direct questioning for groups that did and did not participate in conservation interventions. Results from the bean method corresponded to those from direct questioning, and there was no indication of change in question sensitivity following conservation interventions. Estimates from both methods indicated that wild-meat trading decreased in project and nonproject households (from 36% to 20%) and that hunting decreased in 1 project group (38–28%). Where inconsistent answers were given (2–6% of respondents), differences were in both directions and were most likely attributable to measurement error. The bean method was quick and straightforward to administer in a low-literacy setting. We showed how it can be modified for answers of more than 2 categories and consider it a valuable tool that could be adapted for a wide range of conservation settings.     

Bridging gaps in demographic analysis with phylogenetic imputation

Phylogenetically informed imputation methods have rarely been applied to estimate missing values in demographic data but may be a powerful tool for reconstructing vital rates of survival, maturation, and fecundity for species of conservation concern. Imputed vital rates could be used to parameterize demographic models to explore how populations respond when vital rates are perturbed. We used standardized vital rate estimates for 50 bird species to assess the use of phylogenetic imputation to fill gaps in demographic data. We calculated imputation accuracy for vital rates of focal species excluded from the data set either singly or in combination and with and without phylogeny, body mass, and life-history trait data. We used imputed vital rates to calculate demographic metrics, including generation time, to validate the use of imputation in demographic analyses. Covariance among vital rates and other trait data provided a strong basis to guide imputation of missing vital rates in birds, even in the absence of phylogenetic information. Mean NRMSE for null and phylogenetic models differed by <0.01 except when no vital rates were available or for vital rates with high phylogenetic signal (Pagel's λ > 0.8). In these cases, including body mass and life-history trait data compensated for lack of phylogenetic information: mean normalized root mean square error (NRMSE) for null and phylogenetic models differed by <0.01 for adult survival and <0.04 for maturation rate. Estimates of demographic metrics were sensitive to the accuracy of imputed vital rates. For example, mean error in generation time doubled in response to inaccurate estimates of maturation time. Accurate demographic data and metrics, such as generation time, are needed to inform conservation planning processes, for example through International Union for Conservation of Nature Red List assessments and population viability analysis. Imputed vital rates could be useful in this context but, as for any estimated model parameters, awareness of the sensitivities of demographic model outputs to the imputed vital rates is essential.     

Addressing behavior in pollinator conservation policies to combat the implementation gap

Solutions for conserving biodiversity lie in changing people's behavior. Ambitious international and national conservation policies frequently fail to effectively mitigate biodiversity loss because they rarely apply behavior-change theories. We conducted a gap analysis of conservation behavior-change interventions advocated in national conservation strategies with the Behavior Change Wheel (BCW), a comprehensive framework for systematically characterizing and designing behavior-change interventions. Using pollinator conservation as a case study, we classified the conservation actions listed in national pollinator initiatives in relation to intervention functions and policy categories of the BCW. We included all national-level policy documents from the European Union available in March 2019 that focused on conservation of pollinators (n = 8). A total of 610 pollinator conservation actions were coded using in-depth directed content analysis, resulting in the identification of 787 intervention function and 766 policy category codes. Overall, these initiatives did not employ the entire breadth of behavioral interventions. Intervention functions most frequently identified were education (23%) and environmental restructuring (19%). Least frequently identified intervention functions were incentivization (3%), and restriction (2%) and coercion were completely absent (0%). Importantly, 41% of all pollinator conservation actions failed to identify whose behavior was to be changed. Building on these analyses, we suggest that reasons for the serious implementation gap in national and international conservation policies is founded in insufficient understanding of which behavioral interventions to employ for most beneficial impacts on biodiversity and how to clearly specify the intervention targets. We recommend that policy advisors engage with behavior-change theory to design effective behavior-change interventions that underpin successful conservation policies.