Improving protected area effectiveness through consideration of different human-pressure baselines

Previous assessments of the effectiveness of protected areas (PAs) focused primarily on changes in human pressure over time and did not consider the different human-pressure baselines of PAs, thereby potentially over- or underestimating PA effectiveness. We developed a framework that considers both human-pressure baseline and change in human pressure over time and assessed the effectiveness of 338 PAs in China from 2010 to 2020. The initial state of human pressure on PAs was taken as the baseline, and changes in human pressure index (HPI) were further analyzed under different baselines. We used the random forest models to identify the management measures that most improved effectiveness in resisting human pressure for the PAs with different baselines. Finally, the relationships between the changes in the HPI and the changes in natural ecosystems in PAs were analyzed with different baselines. Of PAs with low HPI baselines, medium HPI baselines, and high HPI baselines, 76.92% (n=150), 11.11% (n=12), and 22.86% (n=8) , respectively, showed positive effects in resisting human pressure. Overall, ignoring human-pressure baselines somewhat underestimated the positive effects of PAs, especially for those with low initial human pressure. For PAs with different initial human pressures, different management measures should be taken to improve effectiveness and reduce threats to natural ecosystems. We believe our framework is useful for assessing the effectiveness of PAs globally, and we recommend it be included in the Convention on Biological Diversity Post-2020 Strategy.     

A field experiment characterizing variable detection rates during plant surveys

Surveys aimed at finding threatened and invasive species can be challenging due to individual rarity and low and variable individual detection rates. Detection rate in plant surveys typically varies due to differences among observers, among the individual plants being surveyed (targets), and across background environments. Interactions among these 3 components may occur but are rarely estimated due to limited replication and control during data collection. We conducted an experiment to investigate sources of variation in detection of 2 Pilosella species that are invasive and sparsely distributed in the Alpine National Park, Australia. These species are superficially similar in appearance to other yellow-flowered plants occurring in this landscape. We controlled the presence and color of flowers on target Pilosella plants and controlled their placement in plots, which were selected for their variation in cover of non-target yellow flowers and dominant vegetation type. Observers mimicked Pilosella surveys in the plots and reported 1 categorical and 4 quantitative indicators of their survey experience level. We applied survival analysis to detection data to model the influence of both controlled and uncontrolled variables on detection rate. Orange- and yellow-flowering Pilosella in grass- and heath-dominated vegetation were detected at a higher rate than nonflowering Pilosella. However, this detection gain diminished as the cover of other co-occurring yellow-flowering species increased. Recent experience with Pilosella surveys improved detection rate. Detection experiments are a direct and accessible means of understanding detection processes and interpreting survey data for threatened and invasive species. Our detection findings have been used for survey planning and can inform progress toward eradication. Interaction of target and background characteristics determined detection rate, which enhanced predictions in the Pilosella eradication program and demonstrated the difficulty of transferring detection findings into untested environments.     

Evaluating the success of functional restoration after reintroduction of a lost avian pollinator

Conservation translocation is a common method for species recovery, for which one increasingly frequent objective is restoring lost ecological functions to promote ecosystem recovery. However, few conservation translocation programs explicitly state or monitor function as an objective, limiting the ability to test assumptions, learn from past efforts, and improve management. We evaluated whether translocations of hihi (Notiomystis cincta), a threatened New Zealand passerine, achieved their implicit objective of restoring lost pollination function. Through a pollinator-exclusion experiment, we quantified, with log response ratios (lnR), the effects of birds on fruit set and seed quality in hangehange (Geniostoma ligustrifolium), a native flowering shrub. We isolated the contributions of hihi by making comparisons across sites with and without hihi. Birds improved fruit set more at sites without hihi (lnR = 1.27) than sites with hihi (lnR = 0.50), suggesting other avian pollinators compensated for and even exceeded hihi contributions to fruit set. Although birds improved seed germination only at hihi sites (lnR = 0.22–0.41), plants at sites without hihi had germination rates similar to hihi sites because they produced 26% more filled seeds, regardless of pollination condition. Therefore, although our results showed hihi improved seed quality, they also highlighted the complexity of ecological functions. When an important species is lost, ecosystems may be able to achieve similar function through different means. Our results underscore the importance of stating and monitoring the ecological benefits of conservation translocations when functional restoration is a motivation to ensure these programs are achieving their objectives.     

A landscape-scale framework to identify refugia from multiple stressors

From a conservation perspective, quantifying potential refugial capacity has been predominantly focused on climate refugia, which is critical for maintaining the persistence of species and ecosystems. However, protection from other stressors, such as human-induced changes in fire and hydrology, that cause habitat loss, degradation, and fragmentation is also necessary to ensure that conservation efforts focused on climate are not undermined by other threats. Thus, conceptual and methodological advances for quantifying potential refugia from multiple anthropogenic stressors are important to support conservation efforts. We devised a new conceptual approach, the domains of refugia, for assessing refugial capacity that identifies areas where exposure to multiple stressors is low. In our framework, patterns of environmental variability (e.g., increased frequency of warm summers), thresholds of resilience, and extent and intensity of stressors are used to identify areas of potential refugia from a suite of ongoing anthropogenic stressors (e.g., changes in fire regime). To demonstrate its utility, we applied the framework to a Southern California landscape. Sites with high refugial capacity (super-refugia sites) had on average 30% fewer extremely warm summers, 20% fewer fire events, 10% less exposure to altered river channels and riparian areas, and 50% fewer recreational trails than the surrounding landscape. Our results suggest that super-refugia sites (∼8200 km²) for some natural communities are underrepresented in the existing protected area network, a finding that can inform efforts to expand protected areas. Our case study highlights how considering exposure to multiple stressors can inform planning and practice to conserve biodiversity in a changing world.     

Translating habitat class to land cover to map area of habitat of terrestrial vertebrates

Area of habitat (AOH) is defined as the “habitat available to a species, that is, habitat within its range” and is calculated by subtracting areas of unsuitable land cover and elevation from the range. The International Union for the Conservation of Nature (IUCN) Habitats Classification Scheme provides information on species habitat associations, and typically unvalidated expert opinion is used to match habitat to land-cover classes, which generates a source of uncertainty in AOH maps. We developed a data-driven method to translate IUCN habitat classes to land cover based on point locality data for 6986 species of terrestrial mammals, birds, amphibians, and reptiles. We extracted the land-cover class at each point locality and matched it to the IUCN habitat class or classes assigned to each species occurring there. Then, we modeled each land-cover class as a function of IUCN habitat with (SSG, using) logistic regression models. The resulting odds ratios were used to assess the strength of the association between each habitat and land-cover class. We then compared the performance of our data-driven model with those from a published translation table based on expert knowledge. We calculated the association between habitat classes and land-cover classes as a continuous variable, but to map AOH as binary presence or absence, it was necessary to apply a threshold of association. This threshold can be chosen by the user according to the required balance between omission and commission errors. Some habitats (e.g., forest and desert) were assigned to land-cover classes with more confidence than others (e.g., wetlands and artificial). The data-driven translation model and expert knowledge performed equally well, but the model provided greater standardization, objectivity, and repeatability. Furthermore, our approach allowed greater flexibility in the use of the results and uncertainty to be quantified. Our model can be modified for regional examinations and different taxonomic groups.     

A stochastic model for estimating sustainable limits to wildlife mortality in a changing world

Human-caused mortality of wildlife is a pervasive threat to biodiversity. Assessing the population-level impact of fisheries bycatch and other human-caused mortality of wildlife has typically relied upon deterministic methods. However, population declines are often accelerated by stochastic factors that are not accounted for in such conventional methods. Building on the widely applied potential biological removal (PBR) equation, we devised a new population modeling approach for estimating sustainable limits to human-caused mortality and applied it in a case study of bottlenose dolphins affected by capture in an Australian demersal otter trawl fishery. Our approach, termed sustainable anthropogenic mortality in stochastic environments (SAMSE), incorporates environmental and demographic stochasticity, including the dependency of offspring on their mothers. The SAMSE limit is the maximum number of individuals that can be removed without causing negative stochastic population growth. We calculated a PBR of 16.2 dolphins per year based on the best abundance estimate available. In contrast, the SAMSE model indicated that only 2.3–8.0 dolphins could be removed annually without causing a population decline in a stochastic environment. These results suggest that reported bycatch rates are unsustainable in the long term, unless reproductive rates are consistently higher than average. The difference between the deterministic PBR calculation and the SAMSE limits showed that deterministic approaches may underestimate the true impact of human-caused mortality of wildlife. This highlights the importance of integrating stochasticity when evaluating the impact of bycatch or other human-caused mortality on wildlife, such as hunting, lethal control measures, and wind turbine collisions. Although population viability analysis (PVA) has been used to evaluate the impact of human-caused mortality, SAMSE represents a novel PVA framework that incorporates stochasticity for estimating acceptable levels of human-caused mortality. It offers a broadly applicable, stochastic addition to the demographic toolbox to evaluate the impact of human-caused mortality on wildlife.     

Genomic erosion in a demographically recovered bird species during conservation rescue

The pink pigeon (Nesoenas mayeri) is an endemic species of Mauritius that has made a remarkable recovery after a severe population bottleneck in the 1970s to early 1990s. Prior to this bottleneck, an ex situ population was established from which captive-bred individuals were released into free-living subpopulations to increase population size and genetic variation. This conservation rescue led to rapid population recovery to 400–480 individuals, and the species was twice downlisted on the International Union for the Conservation of Nature (IUCN) Red List. We analyzed the impacts of the bottleneck and genetic rescue on neutral genetic variation during and after population recovery (1993–2008) with restriction site-associated sequencing, microsatellite analyses, and quantitative genetic analysis of studbook data of 1112 birds from zoos in Europe and the United States. We used computer simulations to study the predicted changes in genetic variation and population viability from the past into the future. Genetic variation declined rapidly, despite the population rebound, and the effective population size was approximately an order of magnitude smaller than census size. The species carried a high genetic load of circa 15 lethal equivalents for longevity. Our computer simulations predicted continued inbreeding will likely result in increased expression of deleterious mutations (i.e., a high realized load) and severe inbreeding depression. Without continued conservation actions, it is likely that the pink pigeon will go extinct in the wild within 100 years. Conservation rescue of the pink pigeon has been instrumental in the recovery of the free-living population. However, further genetic rescue with captive-bred birds from zoos is required to recover lost variation, reduce expression of harmful deleterious variation, and prevent extinction. The use of genomics and modeling data can inform IUCN assessments of the viability and extinction risk of species, and it helps in assessments of the conservation dependency of populations.     

Using land-use history and multiple baselines to determine bird responses to cocoa agroforestry

Agroforests can play an important role in biodiversity conservation in complex landscapes. A key factor distinguishing among agroforests is land-use history – whether agroforests are established inside forests or on historically forested but currently open lands. The disparity between land-use histories means the appropriate biodiversity baselines may differ, which should be accounted for when assessing the conservation value of agroforests. Specifically, comparisons between multiple baselines in forest and open land could enrich understanding of species’ responses by contextualizing them. We made such comparisons based on data from a recently published meta-analysis of the effects of cocoa (Theobroma cacao) agroforestry on bird diversity. We regrouped rustic, mixed shade cocoa, and low shade cocoa agroforests, based on land-use history, into forest-derived and open-land-derived agroforests and compared bird species diversity (species richness, abundance, and Shannon's index values) between forest and open land, which represented the 2 alternative baselines. Bird diversity was similar in forest-derived agroforests and forests (Hedges’ g* estimate [SE] = -0.3144 [0.3416], p = 0.36). Open-land-derived agroforests were significantly less diverse than forests (g* = 1.4312 [0.6308], p = 0.023) and comparable to open lands (g* = -0.1529 [0.5035], p = 0.76). Our results highlight how land-use history determined the conservation value of cocoa agroforests. Forest-derived cocoa agroforests were comparable to the available – usually already degraded – forest baselines, but entail future degradation risks. In contrast, open-land-derived cocoa agroforestry may offer restoration opportunities. Our results showed that comparisons among multiple baselines may inform relative contributions of agroforestry systems to bird conservation on a landscape scale.     

The Potential for Species Conservation in Tropical Secondary Forests

Abstract: In the wake of widespread loss of old‐growth forests throughout the tropics, secondary forests will likely play a growing role in the conservation of forest biodiversity. We considered a complex hierarchy of factors that interact in space and time to determine the conservation potential of tropical secondary forests. Beyond the characteristics of local forest patches, spatial and temporal landscape dynamics influence the establishment, species composition, and persistence of secondary forests. Prospects for conservation of old‐growth species in secondary forests are maximized in regions where the ratio of secondary to old‐growth forest area is relatively low, older secondary forests have persisted, anthropogenic disturbance after abandonment is relatively low, seed‐dispersing fauna are present, and old‐growth forests are close to abandoned sites. The conservation value of a secondary forest is expected to increase over time, as species arriving from remaining old‐growth forest patches accumulate. Many studies are poorly replicated, which limits robust assessments of the number and abundance of old‐growth species present in secondary forests. Older secondary forests are not often studied and few long‐term studies are conducted in secondary forests. Available data indicate that both old‐growth and second‐growth forests are important to the persistence of forest species in tropical, human‐modified landscapes.     

The Future of Scattered Trees in Agricultural Landscapes

Abstract: Mature trees scattered throughout agricultural landscapes are critical habitat for some biota and provide a range of ecosystem services. These trees are declining in intensively managed agricultural landscapes globally. We developed a simulation model to predict the rates at which these trees are declining, identified the key variables that can be manipulated to mitigate this decline, and compared alternative management proposals. We used the initial numbers of trees in the stand, the predicted ages of these trees, their rate of growth, the number of recruits established, the frequency of recruitment, and the rate of tree mortality to simulate the dynamics of scattered trees in agricultural landscapes. We applied this simulation model to case studies from Spain, United States, Australia, and Costa Rica. We predicted that mature trees would be lost from these landscapes in 90–180 years under current management. Existing management recommendations for these landscapes—which focus on increasing recruitment—would not reverse this trend. The loss of scattered mature trees was most sensitive to tree mortality, stand age, number of recruits, and frequency of recruitment. We predicted that perpetuating mature trees in agricultural landscapes at or above existing densities requires a strategy that keeps mortality among established trees below around 0.5% per year, recruits new trees at a rate that is higher than the number of existing trees, and recruits new trees at a frequency in years equivalent to around 15% of the maximum life expectancy of trees. Numbers of mature trees in landscapes represented by the case studies will decline before they increase, even if strategies of this type are implemented immediately. This decline will be greater if a management response is delayed.