When all life counts in conservation

Conservation science involves the collection and analysis of data. These scientific practices emerge from values that shape who and what is counted. Currently, conservation data are filtered through a value system that considers native life the only appropriate subject of conservation concern. We examined how trends in species richness, distribution, and threats change when all wildlife count by adding so-called non-native and feral populations to the International Union for Conservation of Nature Red List and local species richness assessments. We focused on vertebrate populations with founding members taken into and out of Australia by humans (i.e., migrants). We identified 87 immigrant and 47 emigrant vertebrate species. Formal conservation accounts underestimated global ranges by an average of 30% for immigrants and 7% for emigrants; immigrations surpassed extinctions in Australia by 52 species; migrants were disproportionately threatened (33% of immigrants and 29% of emigrants were threatened or decreasing in their native ranges); and incorporating migrant populations into risk assessments reduced global threat statuses for 15 of 18 species. Australian policies defined most immigrants as pests (76%), and conservation was the most commonly stated motivation for targeting these species in killing programs (37% of immigrants). Inclusive biodiversity data open space for dialogue on the ethical and empirical assumptions underlying conservation science.     

Incorporating putatively neutral and adaptive genomic data into marine conservation planning

The availability of genomic data for an increasing number of species makes it possible to incorporate evolutionary processes into conservation plans. Recent studies show how genetic data can inform spatial conservation prioritization (SCP), but they focus on metrics of diversity and distinctness derived primarily from neutral genetic data sets. Identifying adaptive genetic markers can provide important information regarding the capacity for populations to adapt to environmental change. Yet, the effect of including metrics based on adaptive genomic data into SCP in comparison to more widely used neutral genetic metrics has not been explored. We used existing genomic data on a commercially exploited species, the giant California sea cucumber (Parastichopus californicus), to perform SCP for the coastal region of British Columbia (BC), Canada. Using a RAD-seq data set for 717 P. californicus individuals across 24 sampling locations, we identified putatively adaptive (i.e., candidate) single nucleotide polymorphisms (SNPs) based on genotype–environment associations with seafloor temperature. We calculated various metrics for both neutral and candidate SNPs and compared SCP outcomes with independent metrics and combinations of metrics. Priority areas varied depending on whether neutral or candidate SNPs were used and on the specific metric used. For example, targeting sites with a high frequency of warm-temperature-associated alleles to support persistence under future warming prioritized areas in the southern coastal region. In contrast, targeting sites with high expected heterozygosity at candidate loci to support persistence under future environmental uncertainty prioritized areas in the north. When combining metrics, all scenarios generated intermediate solutions, protecting sites that span latitudinal and thermal gradients. Our results demonstrate that distinguishing between neutral and adaptive markers can affect conservation solutions and emphasize the importance of defining objectives when choosing among various genomic metrics for SCP.     

The moral residue of conservation

Should conservationists use lethal management to control introduced wildlife populations? Should they kill individual animals to protect endangered species? Are trade-offs that prioritize some values at the expense of others morally appropriate? These sorts of ethical questions are common in conservation. In debating such questions, conservationists often seem to presume 1 of 2 possible answers: the act in question is right or it is wrong. But morality in conservation is considerably more complex than this simple binary suggests. A robust conservation ethic requires a vocabulary that gives voice to the uncertainty and unease that arise when what seems to be the best available course of action also seems to involve a measure of wrongdoing. The philosophical literature on moral residue and moral dilemmas supplies this vocabulary. Moral dilemmas arise when one must neglect certain moral requirements to fulfill others. Under such circumstances, even the best possible decision leaves a moral residue, which is experienced emotionally as some form of grief. Examples of conservation scenarios that leave a moral residue include management of introduced rabbits in Australia, trophy hunting in Africa, and forest management trade-offs in the Pacific Northwest. Moral residue is integral to the moral experience of conservationists today, and grief is an appropriate response to many decisions conservationists must make. Article impact statement: Defensible conservation decisions may neglect moral requirements, leaving a moral residue; conservationists should respond with grief.     

Using environmental and geographic data to optimize ex situ collections and preserve evolutionary potential

Maintenance of biodiversity through seed banks and botanical gardens, where the wealth of species’ genetic variation may be preserved ex situ, is a major goal of conservation. However, challenges can persist in optimizing ex situ collections if trade-offs exist among cost, effort, and conserving species evolutionary potential, particularly when genetic data are not available. We evaluated the genetic consequences of population preservation informed by geographic (isolation by distance [IBD]) and environmental (isolation by environment [IBE]) distance for ex situ collections for which population provenance is available. We used 19 genetic and genomic data sets from 15 plant species to assess the proportion of population genetic differentiation explained by geographic and environmental factors and to simulate ex situ collections prioritizing source populations based on pairwise geographic distance, environmental distance, or both. Specifically, we tested the impact prioritizing sampling based on these distances may have on the capture of neutral, functional, or putatively adaptive genetic diversity and differentiation. Individually, IBD and IBE explained limited population genetic differences across all 3 genetic marker classes (IBD, 10–16%; IBE, 1–5.5%). Together, they explained a substantial proportion of population genetic differences for functional (45%) and adaptive (71%) variation. Simulated ex situ collections revealed that inclusion of IBD, IBE, or both increased allelic diversity and genetic differentiation captured among populations, particularly for loci that may be important for adaptation. Thus, prioritizing population collections based on environmental and geographic distance data can optimize genetic variation captured ex situ. For the vast majority of plant species for which there is no genetic information, these data are invaluable to conservation because they can guide preservation of genetic variation needed to maintain evolutionary potential within collections.     

The potential for biodiversity offsetting to fund effective invasive species control

Compensating for biodiversity losses in 1 location by conserving or restoring biodiversity elsewhere (i.e., biodiversity offsetting) is being used increasingly to compensate for biodiversity losses resulting from development. We considered whether a form of biodiversity offsetting, enhancement offsetting (i.e., enhancing the quality of degraded natural habitats through intensive ecological management), can realistically secure additional funding to control biological invaders at a scale and duration that results in enhanced biodiversity outcomes. We suggest that biodiversity offsetting has the potential to enhance biodiversity values through funding of invasive species control, but it needs to meet 7 key conditions: be technically possible to reduce invasive species to levels that enhance native biodiversity; be affordable; be sufficiently large to compensate for the impact; be adaptable to accommodate new strategic and tactical developments while not compromising biodiversity outcomes; acknowledge uncertainties associated with managing pests; be based on an explicit risk assessment that identifies the cost of not achieving target outcomes; and include financial mechanisms to provide for in‐perpetuity funding. The challenge then for conservation practitioners, advocates, and policy makers is to develop frameworks that allow for durable and effective partnerships with developers to realize the full potential of enhancement offsets, which will require a shift away from traditional preservation‐focused approaches to biodiversity management. El Potencial de la Compensación de la Biodiversidad para Financiar Controles Efectivos de Especies Invasoras     

Association of extinction risk of saproxylic beetles with ecological degradation of forests in Europe

To reduce future loss of biodiversity and to allocate conservation funds effectively, the major drivers behind large‐scale extinction processes must be identified. A promising approach is to link the red‐list status of species and specific traits that connect species of functionally important taxa or guilds to resources they rely on. Such traits can be used to detect the influence of anthropogenic ecosystem changes and conservation efforts on species, which allows for practical recommendations for conservation. We modeled the German Red List categories as an ordinal index of extinction risk of 1025 saproxylic beetles with a proportional‐odds linear mixed‐effects model for ordered categorical responses. In this model, we estimated fixed effects for intrinsic traits characterizing species biology, required resources, and distribution with phylogenetically correlated random intercepts. The model also allowed predictions of extinction risk for species with no red‐list category. Our model revealed a higher extinction risk for lowland and large species as well as for species that rely on wood of large diameter, broad‐leaved trees, or open canopy. These results mirror well the ecological degradation of European forests over the last centuries caused by modern forestry, that is the conversion of natural broad‐leaved forests to dense conifer‐dominated forests and the loss of old growth and dead wood. Therefore, conservation activities aimed at saproxylic beetles in all types of forests in Central and Western Europe should focus on lowlands, and habitat management of forest stands should aim at increasing the amount of dead wood of large diameter, dead wood of broad‐leaved trees, and dead wood in sunny areas.     

Incorporating evolutionary processes into population viability models

We examined how ecological and evolutionary (eco‐evo) processes in population dynamics could be better integrated into population viability analysis (PVA). Complementary advances in computation and population genomics can be combined into an eco‐evo PVA to offer powerful new approaches to understand the influence of evolutionary processes on population persistence. We developed the mechanistic basis of an eco‐evo PVA using individual‐based models with individual‐level genotype tracking and dynamic genotype–phenotype mapping to model emergent population‐level effects, such as local adaptation and genetic rescue. We then outline how genomics can allow or improve parameter estimation for PVA models by providing genotypic information at large numbers of loci for neutral and functional genome regions. As climate change and other threatening processes increase in rate and scale, eco‐evo PVAs will become essential research tools to evaluate the effects of adaptive potential, evolutionary rescue, and locally adapted traits on persistence.     

A review of selection‐based tests of abiotic surrogates for species representation

Because conservation planners typically lack data on where species occur, environmental surrogates—including geophysical settings and climate types—have been used to prioritize sites within a planning area. We reviewed 622 evaluations of the effectiveness of abiotic surrogates in representing species in 19 study areas. Sites selected using abiotic surrogates represented more species than an equal number of randomly selected sites in 43% of tests (55% for plants) and on average improved on random selection of sites by about 8% (21% for plants). Environmental diversity (ED) (42% median improvement on random selection) and biotically informed clusters showed promising results and merit additional testing. We suggest 4 ways to improve performance of abiotic surrogates. First, analysts should consider a broad spectrum of candidate variables to define surrogates, including rarely used variables related to geographic separation, distance from coast, hydrology, and within‐site abiotic diversity. Second, abiotic surrogates should be defined at fine thematic resolution. Third, sites (the landscape units prioritized within a planning area) should be small enough to ensure that surrogates reflect species’ environments and to produce prioritizations that match the spatial resolution of conservation decisions. Fourth, if species inventories are available for some planning units, planners should define surrogates based on the abiotic variables that most influence species turnover in the planning area. Although species inventories increase the cost of using abiotic surrogates, a modest number of inventories could provide the data needed to select variables and evaluate surrogates. Additional tests of nonclimate abiotic surrogates are needed to evaluate the utility of conserving nature's stage as a strategy for conservation planning in the face of climate change.     

Using abiotic variables to predict importance of sites for species representation

In systematic conservation planning, species distribution data for all sites in a planning area are used to prioritize each site in terms of the site's importance toward meeting the goal of species representation. But comprehensive species data are not available in most planning areas and would be expensive to acquire. As a shortcut, ecologists use surrogates, such as occurrences of birds or another well‐surveyed taxon, or land types defined from remotely sensed data, in the hope that sites that represent the surrogates also represent biodiversity. Unfortunately, surrogates have not performed reliably. We propose a new type of surrogate, predicted importance, that can be developed from species data for a q% subset of sites. With species data from this subset of sites, importance can be modeled as a function of abiotic variables available at no charge for all terrestrial areas on Earth. Predicted importance can then be used as a surrogate to prioritize all sites. We tested this surrogate with 8 sets of species data. For each data set, we used a q% subset of sites to model importance as a function of abiotic variables, used the resulting function to predict importance for all sites, and evaluated the number of species in the sites with highest predicted importance. Sites with the highest predicted importance represented species efficiently for all data sets when q = 25% and for 7 of 8 data sets when q = 20%. Predicted importance requires less survey effort than direct selection for species representation and meets representation goals well compared with other surrogates currently in use. This less expensive surrogate may be useful in those areas of the world that need it most, namely tropical regions with the highest biodiversity, greatest biodiversity loss, most severe lack of inventory data, and poorly developed protected area networks.