Effects of site-selection bias on estimates of biodiversity change

Estimates of biodiversity change are essential for the management and conservation of ecosystems. Accurate estimates rely on selecting representative sites, but monitoring often focuses on sites of special interest. How such site-selection biases influence estimates of biodiversity change is largely unknown. Site-selection bias potentially occurs across four major sources of biodiversity data, decreasing in likelihood from citizen science, museums, national park monitoring, and academic research. We defined site-selection bias as a preference for sites that are either densely populated (i.e., abundance bias) or species rich (i.e., richness bias). We simulated biodiversity change in a virtual landscape and tracked the observed biodiversity at a sampled site. The site was selected either randomly or with a site-selection bias. We used a simple spatially resolved, individual-based model to predict the movement or dispersal of individuals in and out of the chosen sampling site. Site-selection bias exaggerated estimates of biodiversity loss in sites selected with a bias by on average 300–400% compared with randomly selected sites. Based on our simulations, site-selection bias resulted in positive trends being estimated as negative trends: richness increase was estimated as 0.1 in randomly selected sites, whereas sites selected with a bias showed a richness change of −0.1 to −0.2 on average. Thus, site-selection bias may falsely indicate decreases in biodiversity. We varied sampling design and characteristics of the species and found that site-selection biases were strongest in short time series, for small grains, organisms with low dispersal ability, large regional species pools, and strong spatial aggregation. Based on these findings, to minimize site-selection bias, we recommend use of systematic site-selection schemes; maximizing sampling area; calculating biodiversity measures cumulatively across plots; and use of biodiversity measures that are less sensitive to rare species, such as the effective number of species. Awareness of the potential impact of site-selection bias is needed for biodiversity monitoring, the design of new studies on biodiversity change, and the interpretation of existing data.     

Identifying robust strategies for assisted migration in a competitive stochastic metacommunity

Assisted migration (AM) is the translocation of species beyond their historical range to locations that are expected to be more suitable under future climate change. However, a relocated population may fail to establish in its donor community if there is high uncertainty in decision-making, climate, and interactions with the recipient ecological community. To quantify the benefit to persistence and risk of establishment failure of AM under different management scenarios (e.g., choosing target species, proportion of population to relocate, and optimal location to relocate), we built a stochastic metacommunity model to simulate several species reproducing, dispersing, and competing on a temperature gradient as temperature increases over time. Without AM, the species were vulnerable to climate change when they had low population sizes, short dispersal, and strong poleward competition. When relocating species that exemplified these traits, AM increased the long-term persistence of the species most when relocating a fraction of the donor population, even if the remaining population was very small or rapidly declining. This suggests that leaving behind a fraction of the population could be a robust approach, allowing managers to repeat AM in case they move the species to the wrong place and at the wrong time, especially when it is difficult to identify a species’ optimal climate. We found that AM most benefitted species with low dispersal ability and least benefited species with narrow thermal tolerances, for which AM increased extinction risk on average. Although relocation did not affect the persistence of nontarget species in our simple competitive model, researchers will need to consider a more complete set of community interactions to comprehensively understand invasion potential.     

Effects of flow regimes altered by dams on survival, population declines, and range-wide losses of California river-breeding frogs

Widespread alteration of natural hydrologic patterns by large dams combined with peak demands for power and water delivery during summer months have resulted in frequent aseasonal flow pulses in rivers of western North America. Native species in these ecosystems have evolved with predictable annual flood-drought cycles; thus, their likelihood of persistence may decrease in response to disruption of the seasonal synchrony between stable low-flow conditions and reproduction. We evaluated whether altered flow regimes affected 2 native frogs in California and Oregon (U.S.A.) at 4 spatial and temporal extents. We examined changes in species distribution over approximately 50 years, current population density in 11 regulated and 16 unregulated rivers, temporal trends in abundance among populations occupying rivers with different hydrologic histories, and within-year patterns of survival relative to seasonal hydrology. The foothill yellow-legged frog (Rana boylii), which breeds only in flowing water, is more likely to be absent downstream of large dams than in free-flowing rivers, and breeding populations are on average 5 times smaller in regulated rivers than in unregulated rivers. Time series data (range = 8 - 19 years) from 5 populations of yellow-legged frogs and 2 populations of California red-legged frogs (R. draytonii) across a gradient of natural to highly artificial timing and magnitude of flooding indicate that variability of flows in spring and summer is strongly correlated with high mortality of early life stages and subsequent decreases in densities of adult females. Flow management that better mimics natural flow timing is likely to promote persistence of these species and others with similar phenology.     

Acoustically detected year-round presence of right whales in an urbanized migration corridor

Species' conservation relies on understanding their seasonal habitats and migration routes. North Atlantic right whales (Eubalaena glacialis), listed as endangered under the U.S. Endangered Species Act, migrate from the southeastern U.S. coast to Cape Cod Bay, Massachusetts, a federally designated critical habitat, from February through May to feed. The whales then continue north across the Gulf of Maine to northern waters (e.g., Bay of Fundy). To enter Cape Cod Bay, right whales must traverse an area of dense shipping and fishing activity in Massachusetts Bay, where there are no mandatory regulations for the protection of right whales or management of their habitat. We used passive acoustic recordings of right whales collected in Massachusetts Bay from May 2007 through October 2010 to determine the annual spatial and temporal distribution of the whales and their calling activity. We detected right whales in the bay throughout the year, in contrast to results from visual surveys. Right whales were detected on at least 24% of days in each month, with the exception of June 2007, in which there were no detections. Averaged over all years, right whale calls were most abundant from February through May. During this period, calls were most frequent between 17:00 and 20:00 local time; no diel pattern was apparent in other months. The spatial distribution of the approximate locations of calling whales suggests they may use Massachusetts Bay as a conduit to Cape Cod Bay in the spring and as they move between the Gulf of Maine and waters to the south in September through December. Although it is unclear how dependent right whales are on the bay, the discovery of their widespread presence in Massachusetts Bay throughout the year suggests this region may need to be managed to reduce the probability of collisions with ships and entanglement in fishing gear.     

Inadvertent advocacy

Policy advocacy is an issue regularly debated among conservation scientists. These debates have focused on intentional policy advocacy by scientists, but advocacy can also be unintentional. I define inadvertent policy advocacy as the act of unintentionally expressing personal policy preferences or ethical judgments in a way that is nearly indistinguishable from scientific judgments. A scientist may be well intentioned and intellectually honest but still inadvertently engage in policy advocacy. There are two ways to inadvertently engage in policy advocacy. First, a scientist expresses an opinion that she or he believes is a scientific judgment but it is actually an ethical judgment or personal policy preference. Second, a scientist expresses an opinion that he or she knows is an ethical judgment or personal policy preference but inadvertently fails to effectively communicate the nature of the opinion to policy makers or the public. I illustrate inadvertent advocacy with three examples: recovery criteria in recovery plans for species listed under the U.S. Endangered Species Act, a scientific peer review of a recovery plan for the Northern Spotted Owl (Strix occidentalis caurina), and the International Union for Conservation of Nature's definition of threatened. In each example, scientists expressed ethical judgments or policy preferences, but their value judgments were not identified as such, and, hence, their value judgments were opaque to policy makers and the public. Circumstances suggest their advocacy was inadvertent. I believe conservation scientists must become acutely aware of the line between science and policy and avoid inadvertent policy advocacy because it is professional negligence, erodes trust in scientists and science, and perpetuates an ethical vacuum that undermines the rational political discourse necessary for the evolution of society's values. The principal remedy for inadvertent advocacy is education of conservation scientists in an effort to help them understand how science and values interact to fulfill the mission of conservation science.     

Establishing IUCN Red List Criteria for Threatened Ecosystems

Abstract: The potential for conservation of individual species has been greatly advanced by the International Union for Conservation of Nature's (IUCN) development of objective, repeatable, and transparent criteria for assessing extinction risk that explicitly separate risk assessment from priority setting. At the IV World Conservation Congress in 2008, the process began to develop and implement comparable global standards for ecosystems. A working group established by the IUCN has begun formulating a system of quantitative categories and criteria, analogous to those used for species, for assigning levels of threat to ecosystems at local, regional, and global levels. A final system will require definitions of ecosystems; quantification of ecosystem status; identification of the stages of degradation and loss of ecosystems; proxy measures of risk (criteria); classification thresholds for these criteria; and standardized methods for performing assessments. The system will need to reflect the degree and rate of change in an ecosystem's extent, composition, structure, and function, and have its conceptual roots in ecological theory and empirical research. On the basis of these requirements and the hypothesis that ecosystem risk is a function of the risk of its component species, we propose a set of four criteria: recent declines in distribution or ecological function, historical total loss in distribution or ecological function, small distribution combined with decline, or very small distribution. Most work has focused on terrestrial ecosystems, but comparable thresholds and criteria for freshwater and marine ecosystems are also needed. These are the first steps in an international consultation process that will lead to a unified proposal to be presented at the next World Conservation Congress in 2012.     

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.     

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.     

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.