Sustainability and comanagement of subsistence hunting in an indigenous reserve in Guyana

Although hunting is a key component of subsistence strategies of many Amazonians, it is also one of the greatest threats to wildlife. Because indigenous reserves comprise over 20% of Amazonia, effective conservation often requires that conservation professionals work closely with indigenous groups to manage resource use. We used hunter‐generated harvesting data in spatially explicit biodemographic models to assess the sustainability of subsistence hunting of indigenous Waiwai in Guyana. We collected data through a hunter self‐monitoring program, systematic follows of hunters, and semistructured interviews. We used these data to predict future densities of 2 indicator species, spider monkeys (Ateles paniscus) and bearded sakis (Chiropotes sagulatus), under different scenarios of human population expansion and changing hunting technology. We used encounter rates from transect surveys and hunter catch‐per‐unit effort (CPUE) to validate model predictions. Paca (Cuniculus paca) (198 /year), Currosaw (Crax alector) (168), and spider monkey (117) were the most frequently harvested species. Predicted densities of spider monkeys were statistically indistinguishable from empirically derived transect data (Kolmogorov–Smirnov D = 0.67, p = 0.759) and CPUE (D = 0.32, p = 1.000), demonstrating the robustness of model predictions. Ateles paniscus and C. sagulatus were predicted to be extirpated from <13% of the Waiwai reserve in 20 years, even under the most intensive hunting scenarios. Our results suggest Waiwai hunting is currently sustainable, primarily due to their low population density and use of bow and arrow. Continual monitoring is necessary, however, particularly if human population increases are accompanied by a switch to shotgun‐only hunting. We suggest that hunter self‐monitoring and biodemographic modeling can be used effectively in a comanagement approach in which indigenous parabiologists continuously provide hunting data that is then used to update model parameters and validate model predictions.     

Level of environmental threat posed by horticultural trade in Cactaceae

Ornamental horticulture has been identified as an important threat to plant biodiversity and is a major pathway for plant invasions worldwide. In this context, the family Cactaceae is particularly challenging because it is considered the fifth most threatened large taxonomic group in the world; several species are among the most widespread and damaging invasive species; and Cactaceae is one of the most popular horticultural plant groups. Based on the Convention on International Trade in Endangered Species of Wild Flora and Fauna and the 11 largest online auction sites selling cacti, we documented the international cactus trade. To provide an in‐depth look at the dynamics of the industry, we surveyed the businesses involved in the cactus trade in South Africa (a hotspot of cactus trade and invasions). We purchased seeds of every available species and used DNA barcoding to identify species to the genus level. Although <20% of this trade involved threatened species and <3% involved known invasive species, many species were identified by a common name. However, only 0.02% of the globally traded cacti were collected from wild populations. Despite a large commercial network, all South African imports (of which 15% and 1.5% were of species listed as threatened and invasive, respectively) came from the same source. With DNA barcoding, we identified 24% of the species to genus level. Based on our results, we believe that if trade restrictions are placed on the small proportion of cacti that are invasive and there is no major increase in harvesting of native populations, then the commercial trade in cactus poses a negligible environmental threat. However, there are currently no effective methods for easily identifying which cacti are traded, and both the illicit harvesting of cacti from the wild and the informal trade in invasive taxa pose on‐going conservation challenges.     

Performance of IUCN proxies for generation length

One of the criteria used by the International Union for Conservation of Nature (IUCN) to assess threat status is the rate of decline in abundance over 3 generations or 10 years, whichever is longer. The traditional method for calculating generation length (T) uses age‐specific survival and fecundity, but these data are rarely available. Consequently, proxies that require less information are often used, which introduces potential biases. The IUCN recommends 2 proxies based on adult mortality rate, = α + 1/d, and reproductive life span, = α + z^*RL, where α is age at first reproduction, d is adult mortality rate, RL is reproductive life span, and z is a coefficient derived from data for comparable species. We used published life tables for 78 animal and plant populations to evaluate precision and bias of these proxies by comparing and with true generation length. Mean error rates in estimating T were 31% for and 20% for , but error rates for were 16% when we subtracted 1 year ( ), as suggested by theory; also provided largely unbiased estimates regardless of the true generation length. Performance of depends on compilation of detailed data for comparable species, but our results suggest taxonomy is not a reliable indicator of comparability. All 3 proxies depend heavily on a reliable estimate of age at first reproduction, as we illustrated with 2 test species. The relatively large mean errors for all proxies emphasized the importance of collecting the detailed life‐history information necessary to calculate true generation length. Unfortunately, publication of such data is less common than it was decades ago. We identified generic patterns of age‐specific change in vital rates that can be used to predict expected patterns of bias from applying .     

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.     

Testing the feasibility of a hypothetical whaling‐conservation permit market in Norway

A cap‐and‐trade system for managing whale harvests represents a potentially useful approach to resolve the current gridlock in international whale management. The establishment of whale permit markets, open to both whalers and conservationists, could reveal the strength of conservation demand, about which little is known. This lack of knowledge makes it difficult to predict the outcome of a hypothetical whale permit market. We developed a bioeconomic model to evaluate the influence of economic uncertainty about demand for whale conservation or harvest. We used simulations over a wide range of parameterizations of whaling and conservation demands to examine the potential ecological consequences of the establishment of a whale permit market in Norwegian waters under bounded (but substantial) economic uncertainty. Uncertainty variables were slope of whaling and conservation demand, participation level of conservationists and their willingness to pay for whale conservation, and functional forms of demand, including linear, quadratic, and log‐linear forms. A whale‐conservation market had the potential to yield a wide range of conservation and harvest outcomes, the most likely outcomes were those in which conservationists bought all whale permits.     

Using environmental heterogeneity to plan for sea‐level rise

Environmental heterogeneity is increasingly being used to select conservation areas that will provide for future biodiversity under a variety of climate scenarios. This approach, termed conserving nature's stage (CNS), assumes environmental features respond to climate change more slowly than biological communities, but will CNS be effective if the stage were to change as rapidly as the climate? We tested the effectiveness of using CNS to select sites in salt marshes for conservation in coastal Georgia (U.S.A.), where environmental features will change rapidly as sea level rises. We calculated species diversity based on distributions of 7 bird species with a variety of niches in Georgia salt marshes. Environmental heterogeneity was assessed across six landscape gradients (e.g., elevation, salinity, and patch area). We used 2 approaches to select sites with high environmental heterogeneity: site complementarity (environmental diversity [ED]) and local environmental heterogeneity (environmental richness [ER]). Sites selected based on ER predicted present‐day species diversity better than randomly selected sites (up to an 8.1% improvement), were resilient to areal loss from SLR (1.0% average areal loss by 2050 compared with 0.9% loss of randomly selected sites), and provided habitat to a threatened species (0.63 average occupancy compared with 0.6 average occupancy of randomly selected sites). Sites selected based on ED predicted species diversity no better or worse than random and were not resilient to SLR (2.9% average areal loss by 2050). Despite the discrepancy between the 2 approaches, CNS is a viable strategy for conservation site selection in salt marshes because the ER approach was successful. It has potential for application in other coastal areas where SLR will affect environmental features, but its performance may depend on the magnitude of geological changes caused by SLR. Our results indicate that conservation planners that had heretofore excluded low‐lying coasts from CNS planning could include coastal ecosystems in regional conservation strategies.     

Applying network theory to prioritize multispecies habitat networks that are robust to climate and land‐use change

Designing connected landscapes is among the most widespread strategies for achieving biodiversity conservation targets. The challenge lies in simultaneously satisfying the connectivity needs of multiple species at multiple spatial scales under uncertain climate and land‐use change. To evaluate the contribution of remnant habitat fragments to the connectivity of regional habitat networks, we developed a method to integrate uncertainty in climate and land‐use change projections with the latest developments in network‐connectivity research and spatial, multipurpose conservation prioritization. We used land‐use change simulations to explore robustness of species’ habitat networks to alternative development scenarios. We applied our method to 14 vertebrate focal species of periurban Montreal, Canada. Accounting for connectivity in spatial prioritization strongly modified conservation priorities and the modified priorities were robust to uncertain climate change. Setting conservation priorities based on habitat quality and connectivity maintained a large proportion of the region's connectivity, despite anticipated habitat loss due to climate and land‐use change. The application of connectivity criteria alongside habitat‐quality criteria for protected‐area design was efficient with respect to the amount of area that needs protection and did not necessarily amplify trade‐offs among conservation criteria. Our approach and results are being applied in and around Montreal and are well suited to the design of ecological networks and green infrastructure for the conservation of biodiversity and ecosystem services in other regions, in particular regions around large cities, where connectivity is critically low.     

Defending the scientific integrity of conservation‐policy processes

Government agencies faced with politically controversial decisions often discount or ignore scientific information, whether from agency staff or nongovernmental scientists. Recent developments in scientific integrity (the ability to perform, use, communicate, and publish science free from censorship or political interference) in Canada, Australia, and the United States demonstrate a similar trajectory. A perceived increase in scientific‐integrity abuses provokes concerted pressure by the scientific community, leading to efforts to improve scientific‐integrity protections under a new administration. However, protections are often inconsistently applied and are at risk of reversal under administrations publicly hostile to evidence‐based policy. We compared recent challenges to scientific integrity to determine what aspects of scientific input into conservation policy are most at risk of political distortion and what can be done to strengthen safeguards against such abuses. To ensure the integrity of outbound communications from government scientists to the public, we suggest governments strengthen scientific integrity policies, include scientists’ right to speak freely in collective‐bargaining agreements, guarantee public access to scientific information, and strengthen agency culture supporting scientific integrity. To ensure the transparency and integrity with which information from nongovernmental scientists (e.g., submitted comments or formal policy reviews) informs the policy process, we suggest governments broaden the scope of independent reviews, ensure greater diversity of expert input and transparency regarding conflicts of interest, require a substantive response to input from agencies, and engage proactively with scientific societies. For their part, scientists and scientific societies have a responsibility to engage with the public to affirm that science is a crucial resource for developing evidence‐based policy and regulations in the public interest.     

Changes in bird‐migration patterns associated with human‐induced mortality

Many bird populations have recently changed their migratory behavior in response to alterations of the environment. We collected data over 16 years on male Great Bustards (Otis tarda), a species showing a partial migratory pattern (sedentary and migratory birds coexisting in the same breeding groups). We conducted population counts and radio tracked 180 individuals to examine differences in survival rates between migratory and sedentary individuals and evaluate possible effects of these differences on the migratory pattern of the population. Overall, 65% of individuals migrated and 35% did not. The average distance between breeding and postbreeding areas of migrant individuals was 89.9 km, and the longest average movement of sedentary males was 3.8 km. Breeding group and migration distance had no effect on survival. However, mortality of migrants was 2.4 to 3.5 times higher than mortality of sedentary birds. For marked males, collision with power lines was the main cause of death from unnatural causes (37.6% of all deaths), and migratory birds died in collisions with power lines more frequently than sedentary birds (21.3% vs 6.3%). The percentage of sedentary individuals increased from 17% in 1997 to 45% in 2012. These results were consistent with data collected from radio‐tracked individuals: The proportion of migratory individuals decreased from 86% in 1997–1999 to 44% in 2006–2010. The observed decrease in the migratory tendency was not related to climatic changes (temperatures did not change over the study period) or improvements in habitat quality (dry cereal farmland area decreased in the main study area). Our findings suggest that human‐induced mortality during migration may be an important factor shaping the migration patterns of species inhabiting humanized landscapes.     

The problem of estimating recent genetic connectivity in a changing world

Accurate understanding of population connectivity is important to conservation because dispersal can play an important role in population dynamics, microevolution, and assessments of extirpation risk and population rescue. Genetic methods are increasingly used to infer population connectivity because advances in technology have made them more advantageous (e.g., cost effective) relative to ecological methods. Given the reductions in wildlife population connectivity since the Industrial Revolution and more recent drastic reductions from habitat loss, it is important to know the accuracy of and biases in genetic connectivity estimators when connectivity has declined recently. Using simulated data, we investigated the accuracy and bias of 2 common estimators of migration (movement of individuals among populations) rate. We focused on the timing of the connectivity change and the magnitude of that change on the estimates of migration by using a coalescent‐based method (Migrate‐n) and a disequilibrium‐based method (BayesAss). Contrary to expectations, when historically high connectivity had declined recently: (i) both methods over‐estimated recent migration rates; (ii) the coalescent‐based method (Migrate‐n) provided better estimates of recent migration rate than the disequilibrium‐based method (BayesAss); (iii) the coalescent‐based method did not accurately reflect long‐term genetic connectivity. Overall, our results highlight the problems with comparing coalescent and disequilibrium estimates to make inferences about the effects of recent landscape change on genetic connectivity among populations. We found that contrasting these 2 estimates to make inferences about genetic‐connectivity changes over time could lead to inaccurate conclusions.