Interactive effects of multiscale diversification practices on farmland bird stress

Farmland diversification practices (i.e., methods used to produce food sustainably by enhancing biodiversity in cropping systems) are sometimes considered beneficial to both agriculture and biodiversity, but most studies of these practices rely on species richness, diversity, or abundance as a proxy for habitat quality. Biodiversity assessments may miss early clues that populations are imperiled when species presence does not imply persistence. Physiological stress indicators may help identify low-quality habitats before population declines occur. We explored how avian stress indicators respond to on-farm management practices and surrounding seminatural area (1-km radius) across 21 California strawberry farms. We examined whether commonly used biodiversity metrics correlate with stress responses in wild birds. We used ∼1000 blood and feather samples and body mass and wing chord measurements, mostly from passerines, to test the effects of diversification practices on four physiological stress indicators: heterophil to lymphocyte ratios (H:L), body condition, hematocrit values, and feather growth rates of individual birds. We then tested the relationship between physiological stress indicators and species richness, abundance, occurrence, and diversity derived from 285 bird point count surveys. After accounting for other biological drivers, landscape context mediated the effect of local farm management on H:L and body condition. Local diversification practices were associated with reduced individual stress in intensive agricultural landscapes but increased it in landscapes surrounded by relatively more seminatural area. Feathers grew more slowly in landscapes dominated by strawberry production, suggesting that nutritional condition was lower here than in landscapes with more crop types and seminatural areas. We found scant evidence that species richness, abundance, occurrence, or diversity metrics were correlated with the individual's physiological stress, suggesting that reliance on these metrics may obscure the impacts of management on species persistence. Our findings underscore the importance of considering landscape context when designing local management strategies to promote wildlife conservation.     

Parasites as conservation tools

Parasite success typically depends on a close relationship with one or more hosts; therefore, attributes of parasitic infection have the potential to provide indirect details of host natural history and are biologically relevant to animal conservation. Characterization of parasite infections has been useful in delineating host populations and has served as a proxy for assessment of environmental quality. In other cases, the utility of parasites is just being explored, for example, as indicators of host connectivity. Innovative studies of parasite biology can provide information to manage major conservation threats by using parasite assemblage, prevalence, or genetic data to provide insights into the host. Overexploitation, habitat loss and fragmentation, invasive species, and climate change are major threats to animal conservation, and all of these can be informed by parasites.     

Assessing conservation status with extensive but low-resolution data: Application of frequentist and Bayesian models to endangered Athabasca River rainbow trout

Use of extensive but low-resolution abundance data is common in the assessment of species at-risk status based on quantitative decline criteria under International Union for Conservation of Nature (IUCN) and national endangered species legislation. Such data can be problematic for 3 reasons. First, statistical power to reject the null hypothesis of no change is often low because of small sample size and high sampling uncertainty leading to a high frequency of type II errors. Second, range-wide assessments composed of multiple site-specific observations do not effectively weight site-specific trends into global trends. Third, uncertainty in site-specific temporal trends and relative abundance are not propagated at the appropriate spatial scale. A common result is the propensity to underestimate the magnitude of declines and therefore fail to identify the appropriate at-risk status for a species. We used 3 statistical approaches, from simple to more complex, to estimate temporal decline rates for a designatable unit (DU) of rainbow trout in the Athabasca River watershed in western Canada. This DU is considered a native species for purposes of listing because of its genetic composition characterized as >0.95 indigenous origin in the face of continuing introgressive hybridization with introduced populations in the watershed. Analysis of abundance trends from 57 time series with a fixed-effects model identified 33 sites with negative trends, but only 2 were statistically significant. By contrast, a hierarchical linear mixed model weighted by site-specific abundance provided a DU-wide decline estimate of 16.4% per year and a 3-generation decline of 93.2%. A hierarchical Bayesian mixed model yielded a similar 3-generation decline trend of 91.3% and the posterior distribution showed that the estimate had a >99% probability of exceeding thresholds for an endangered listing. We conclude that the Bayesian approach was the most useful because it provided a probabilistic statement of threshold exceedance in support of an at-risk status recommendation.     

Predicting landscape-scale biodiversity recovery by natural tropical forest regrowth

Natural forest regrowth is a cost-effective, nature-based solution for biodiversity recovery, yet different socioenvironmental factors can lead to variable outcomes. A critical knowledge gap in forest restoration planning is how to predict where natural forest regrowth is likely to lead to high levels of biodiversity recovery, which is an indicator of conservation value and the potential provisioning of diverse ecosystem services. We sought to predict and map landscape-scale recovery of species richness and total abundance of vertebrates, invertebrates, and plants in tropical and subtropical second-growth forests to inform spatial restoration planning. First, we conducted a global meta-analysis to quantify the extent to which recovery of species richness and total abundance in second-growth forests deviated from biodiversity values in reference old-growth forests in the same landscape. Second, we employed a machine-learning algorithm and a comprehensive set of socioenvironmental factors to spatially predict landscape-scale deviation and map it. Models explained on average 34% of observed variance in recovery (range 9–51%). Landscape-scale biodiversity recovery in second-growth forests was spatially predicted based on socioenvironmental landscape factors (human demography, land use and cover, anthropogenic and natural disturbance, ecosystem productivity, and topography and soil chemistry); was significantly higher for species richness than for total abundance for vertebrates (median range-adjusted predicted deviation 0.09 vs. 0.34) and invertebrates (0.2 vs. 0.35) but not for plants (which showed a similar recovery for both metrics [0.24 vs. 0.25]); and was positively correlated for total abundance of plant and vertebrate species (Pearson r = 0.45, p = 0.001). Our approach can help identify tropical and subtropical forest landscapes with high potential for biodiversity recovery through natural forest regrowth.     

Socioeconomic development and ecological traits as predictors of human–bird conflicts

Because of the significant impacts on both human interests and bird conservation, it is imperative to identify patterns and anticipate drivers of human–bird conflicts (HBCs) worldwide. Through a global systematic review, following the PRISMA 2020 guidelines, we analyzed the socioeconomic factors and bird ecological traits driving the degree of knowledge and extent of HBCs. We included 166 articles published from 1971 to 2020 in our analyses through which we built a profile of the socioeconomic conditions of 52 countries with reported conflicts and the ecological traits of the 161 bird species involved in HBCs. Although HBC expanded worldwide, it had the greatest impact in less-developed countries (estimate 0. 66 [SE 0.13], p< 0.05), where agriculture is critical for rural livelihoods. Species with a relatively greater conflict extent had a relatively broader diet (estimate 0.80 [SE 0.22], p<0.05) and an increasing population trend (estimate 0.58 [SE 0.15], p<0.05) and affected human interests, such as agriculture and livestock raising. In countries with greater biodiversity, HBCs caused greater socioeconomic impacts than in more developed countries. Our results highlight the importance of understanding and addressing HBCs from multiple perspectives (ecological, sociocultural, and political) to effectively protect both biodiversity and local livelihoods.     

Lessons from other disciplines for setting management thresholds for biodiversity conservation

Successful, state-dependent management, in which the goal of management is to maintain a system in a desired state, involves defining the boundaries between different states. Once these boundaries have been defined, managers require a strategic action plan with thresholds that initiate management interventions to either maintain or return the system to a desired state. This approach to management is widely used across diverse industries from agriculture, to medicine, to information technology, but it has only been adopted in conservation management relatively recently. Conservation practitioners have expressed a willingness to integrate this structured approach in their management systems, but they have also voiced concerns, including lack of a robust process for doing so. Given the widespread use of state-dependent management in other fields, we conducted an extensive review of the literature on threshold-based management to gain insight into how and where it is applied and identify potential lessons for conservation management. We identified 22 industries using 75 different methods for setting management thresholds in 843 studies. Methods spanned six broad approaches, including expert driven, statistical, predictive, optimization, experimental, and artificial intelligence methods. The objectives of each of these studies influenced the approaches used, including the methods for setting thresholds and selecting actions, and the number of thresholds set. The role of value judgments in setting thresholds was clear; studies across all industries frequently involved experts in setting thresholds, often accompanied by computational tools to simulate the consequences of proposed thresholds under different conditions. Of the 30 conservation studies examined, two-thirds used expert-driven methods, consistent with prior evidence that experience-based information often drives conservation management decisions. The methods we identified from other disciplines could help conservation decision makers set thresholds for management interventions in different contexts, linking monitoring to management actions and ensuring that conservation interventions are timely and effective.