Recovery units under the Endangered Species Act should be used more widely

Recovering species is the main goal of the Endangered Species Act (ESA). In the face of limited conservation budgets, diverse tools are needed to efficiently recover species. Recovery units may be one such tool - designated portions of a species’ range that must be recovered individually before an entire species can be considered recovered. Recovery units allow for spatial flexibility in developing recovery goals and may be used in regulatory decisions such as ESA section 7 consultation. Despite the advantages, very little information exists on how recovery units have been developed and used. We mined available public data to determine the number and types of species for which recovery units have been designated; evaluated species and geographic characteristics associated with recovery unit designation; and examined how recovery units have been used in implementing the ESA, such as during consultation. We found 49 listed species had designated recovery units through December 2017, and that these species typically had relatively large ranges and were well-studied. We found taxonomic biases in recovery unit designation as well, with fish species being disproportionately likely to have recovery units and plants disproportionately less. These species were also more likely to have their recovery units considered and used in subsequent ESA implementation – a probability that decreased as time since unit designation passed. Improvements in recovery priority numbers among species with recovery units indicate that the theoretical benefits of this tool may have translated to improved status. These data indicate that recovery units could be applied to additional wide-ranging species to improve recovery under the ESA.

Coproduce Conservation Technology With Conservation Decision Makers and Practitioners to Increase Its Impact

Addressing the biodiversity crisis will mean developing and adopting new resources and methods that effectively improve public conservation efforts. Technologies have a long track record of increasing the efficiency of carrying out time-consuming tasks or even making new feats possible, and if applied thoughtfully, can serve as a key means of strengthening conservation outcomes. Yet technology development sometimes proceeds without clear mechanisms for application and scaling, or key adopters like government agencies are not able to use the technologies. To overcome these discrepancies, we recommend the use of a coproduction model of conservation technology development that starts from detailed knowledge of conservation laws, regulations, policies, and their implementation; identifies choke points in those processes amenable to technological solutions; and then develops those solutions while integrating existing users and needs. To illustrate the model, we describe three tools recently developed to help improve the efficiency and effectiveness of implementing the U.S. Endangered Species Act. We also highlight several outstanding questions and challenges that the broad conservation technology and policy communities may help address.

Supporting habitat conservation with automated change detection in Google Earth Engine

A significant limitation in biodiversity conservation has been the effective implementation of laws and regulations that protect species' habitats from degradation. Flexible, efficient, and effective monitoring and enforcement methods are needed to help conservation policies realize their full benefit. As remote sensing data become more numerous and accessible, they can be used to identify and quantify land-cover changes and habitat loss. However, these data remain underused for systematic conservation monitoring in part because of a lack of simple tools. We adapted 2 algorithms that automatically identify differences between pairs of images. We used free, publicly available satellite data to evaluate their ability to rapidly detect land-cover changes in a variety of land-cover types. We compared algorithm predictions with ground-truthed results at 100 sites of known change in the United States. We also compared algorithm predictions to manually created polygons delineating anthropogenic change in 4 case studies involving imperiled species' habitat: oil and gas development in the range of the Greater Sage Grouse (Centrocercus urophasianus); sand mining operations in the range of the dunes sagebrush lizard (Sceloporus arenicolus); loss of Piping Plover (Charadrius melodus) coastal habitat after Hurricane Michael (2018); and residential development in St. Andrew beach mouse (Peromyscus polionotus peninsularis) habitat. Both algorithms effectively discriminated between pixels corresponding to land-cover change and unchanged pixels as indicated by area under a receiver operating characteristic curve >0.90. The algorithm that was most effective differed among the case-study habitat types, and both effectively delineated habitat loss as indicated by low omission (min. = 0.0) and commission (min. = 0.0) rates, and moderate polygon overlap (max. = 47%). Our results showed how these algorithms can be used to help close the implementation gap of monitoring and enforcement in biodiversity conservation. We provide a free online tool that can be used to run these analyses (https://conservationist.io/habitatpatrol).

Benchmark for the ESA: Having a Backbone Is Good for Recovery

To forestall the current rate of global extinction, we need to identify strategies that successfully recover species. In the last decade, the recovery record for the United States Endangered Species Act (ESA) has improved. Our aim was to review federal delisting documents for recovered species and quantify patterns in taxonomy, history of threats, policy, funding and actions that are associated with species recovery. In comparison to species still listed, the average recovered species was a vertebrate, had been listed longer under the ESA, was exposed to a lower number of threats at the time of listing, and received relatively higher levels of funding. Based on our review, we suggest the following strategies to improve species recovery: provide more time for ESA protection, allocate more funding for recovery, maintain environmental regulations that facilitate recovery, establish more private landowner agreements, and increase the area of protected lands.

A simple, sufficient, and consistent method to score the status of threats and demography of imperiled species

Managers of large, complex wildlife conservation programs need information on the conservation status of each of many species to help strategically allocate limited resources. Oversimplifying status data, however, runs the risk of missing information essential to strategic allocation. Conservation status consists of two components, the status of threats a species faces and the species' demographic status. Neither component alone is sufficient to characterize conservation status. Here we present a simple key for scoring threat and demographic changes for species using detailed information provided in free-form textual descriptions of conservation status. This key is easy to use (simple), captures the two components of conservation status without the cost of more detailed measures (sufficient), and can be applied by different personnel to any taxon (consistent). To evaluate the key's utility, we performed two analyses. First, we scored the threat and demographic status of 37 species recently recommended for reclassification under the Endangered Species Act (ESA) and 15 control species, then compared our scores to two metrics used for decision-making and reports to Congress. Second, we scored the threat and demographic status of all non-plant ESA-listed species from Florida (54 spp.), and evaluated scoring repeatability for a subset of those. While the metrics reported by the U.S. Fish and Wildlife Service (FWS) are often consistent with our scores in the first analysis, the results highlight two problems with the oversimplified metrics. First, we show that both metrics can mask underlying demographic declines or threat increases; for example, ∼40% of species not recommended for reclassification had changes in threats or demography. Second, we show that neither metric is consistent with either threats or demography alone, but conflates the two. The second analysis illustrates how the scoring key can be applied to a substantial set of species to understand overall patterns of ESA implementation. The scoring repeatability analysis shows promise, but indicates thorough training will be needed to ensure consistency. We propose that large conservation programs adopt our simple scoring system for threats and demography. By doing so, program administrators will have better information to monitor program effectiveness and guide their decisions.

Data contradict common perceptions about a controversial provision of the US Endangered Species Act

Separating myth and reality is essential for evaluating the effectiveness of laws. Section 7 of the US Endangered Species Act (Act) directs federal agencies to help conserve threatened and endangered species, including by consulting with the US Fish and Wildlife Service (FWS) or National Marine Fisheries Service on actions the agencies authorize, fund, or carry out. Consultations ensure that actions do not violate the Act's prohibitions on "jeopardizing" listed species or "destroying or adversely modifying" these species' critical habitat. Because these prohibitions are broad, many people consider section 7 the primary tool for protecting species under the Act, whereas others believe section 7 severely impedes economic development. This decades-old controversy is driven primarily by the lack of data on implementation: past analyses are either over 25 y old or taxonomically restricted. We analyze data on all 88,290 consultations recorded by FWS from January 2008 through April 2015. In contrast to conventional wisdom about section 7 implementation, no project was stopped or extensively altered as a result of FWS finding jeopardy or adverse modification during this period. We also show that median consultation duration is far lower than the maximum allowed by the Act, and several factors drive variation in consultation duration. The results discredit many of the claims about the onerous nature of section 7 but also raise questions as to how federal agencies could apply this tool more effectively to conserve species. We build on the results to identify ways to improve the effectiveness of consultations for imperiled species conservation and increase the efficiency of consultations.

Extensive cross-environment fitness variation lies along few axes of genetic variation in the model alga, Chlamydomonas reinhardtii

Variation is essential to ecological and evolutionary dynamics, but genetic variation of quantitative traits may be concentrated in a limited number of dimensions, constraining ecoevolutionary dynamics. We describe high-dimension variation in natural accessions of the model alga, Chlamydomonas reinhardtii, and test the hypothesis that extensive fitness variation across 30 environments is constrained to a small number of axes. We used high-throughput phenotyping to investigate morphological, fitness, and genotype × environment (G × E) variation in 18 natural C. reinhardtii accessions in 30 environments. The organismal phenotypes of cell cycle, cell size, and phototactic behavior exhibited substantial genetic variation between lines, and we found up to 74-fold fitness variation across accessions and environments. Approximately 47% of the extensive G × E variation is accounted for by the first two principal components (PCs) of the G-matrix corresponding to covariation in metals response, nitrogen availability, or salt and nutrient response. The natural variation of C. reinhardtii accessions supports the hypothesis that, despite abundant genetic variation across single environments, the species' adaptive response should be constrained along few major axes of selection. These results highlight the utility of natural accessions for integrating ecoevolutionary and genetic research.

The sex chromosomes of frogs: variability and tolerance offer clues to genome evolution and function

Frog sex chromosomes offer an ideal system for advancing our understanding of genome evolution and function because of the variety of sex determination systems in the group, the diversity of sex chromosome maturation states, the ease of experimental manipulation during early development. After briefly reviewing sex chromosome biology generally, we focus on what is known about frog sex determination, sex chromosome evolution, and recent, genomics-facilitated advances in the field. In closing we highlight gaps in our current knowledge of frog sex chromosomes, and suggest priorities for future research that can advance broad knowledge of gene dose and sex chromosome evolution.

Gene networks and metacommunities: dispersal differences can override adaptive advantage

Dispersal is an important mechanism contributing to both ecological and evolutionary dynamics. In metapopulation and metacommunity ecology, dispersal enables new patches to be colonized; in evolution, dispersal counter-acts local selection, leading to regional homogenization. Here, I consider a three-patch metacommunity in which two species, each with a limiting quantitative trait underlain by gene networks of 16 to 256 genes, compete with one another and disperse among patches. Incorporating dispersal among heterogeneous patches introduces a tradeoff not observed in single-patch simulations: if the difference between gene network size of the two species is greater than the difference in dispersal ability (e.g., if the ratio of network sizes is larger than the ratio of dispersal abilities), then genetic architecture drives community outcome. However, if the difference in dispersal abilities is greater than gene network differences, then any adaptive advantages afforded by genetic architecture are over-ridden by dispersal. Thus, in addition to the selective pressures imposed by competition that shape the genetic architecture of quantitative traits, dispersal among patches creates an escape that may further alter the effects of different genetic architectures. These results provide a theoretical expectation for what we may observe as the field of ecological genomics develops.

Smaller gene networks permit longer persistence in fast-changing environments

The environments in which organisms live and reproduce are rarely static, and as the environment changes, populations must evolve so that phenotypes match the challenges presented. The quantitative traits that map to environmental variables are underlain by hundreds or thousands of interacting genes whose allele frequencies and epistatic relationships must change appropriately for adaptation to occur. Extending an earlier model in which individuals possess an ecologically-critical trait encoded by gene networks of 16 to 256 genes and random or scale-free topology, I test the hypothesis that smaller, scale-free networks permit longer persistence times in a constantly-changing environment. Genetic architecture interacting with the rate of environmental change accounts for 78% of the variance in trait heritability and 66% of the variance in population persistence times. When the rate of environmental change is high, the relationship between network size and heritability is apparent, with smaller and scale-free networks conferring a distinct advantage for persistence time. However, when the rate of environmental change is very slow, the relationship between network size and heritability disappears and populations persist the duration of the simulations, without regard to genetic architecture. These results provide a link between genes and population dynamics that may be tested as the -omics and bioinformatics fields mature, and as we are able to determine the genetic basis of ecologically-relevant quantitative traits.

Evolution of competitive ability: an adaptation speed vs. accuracy tradeoff rooted in gene network size

Ecologists have increasingly come to understand that evolutionary change on short time-scales can alter ecological dynamics (and vice-versa), and this idea is being incorporated into community ecology research programs. Previous research has suggested that the size and topology of the gene network underlying a quantitative trait should constrain or facilitate adaptation and thereby alter population dynamics. Here, I consider a scenario in which two species with different genetic architectures compete and evolve in fluctuating environments. An important trade-off emerges between adaptive accuracy and adaptive speed, driven by the size of the gene network underlying the ecologically-critical trait and the rate of environmental change. Smaller, scale-free networks confer a competitive advantage in rapidly-changing environments, but larger networks permit increased adaptive accuracy when environmental change is sufficiently slow to allow a species time to adapt. As the differences in network characteristics increase, the time-to-resolution of competition decreases. These results augment and refine previous conclusions about the ecological implications of the genetic architecture of quantitative traits, emphasizing a role of adaptive accuracy. Along with previous work, in particular that considering the role of gene network connectivity, these results provide a set of expectations for what we may observe as the field of ecological genomics develops.

Smaller, scale-free gene networks increase quantitative trait heritability and result in faster population recovery

One of the goals of biology is to bridge levels of organization. Recent technological advances are enabling us to span from genetic sequence to traits, and then from traits to ecological dynamics. The quantitative genetics parameter heritability describes how quickly a trait can evolve, and in turn describes how quickly a population can recover from an environmental change. Here I propose that we can link the details of the genetic architecture of a quantitative trait--i.e., the number of underlying genes and their relationships in a network--to population recovery rates by way of heritability. I test this hypothesis using a set of agent-based models in which individuals possess one of two network topologies or a linear genotype-phenotype map, 16-256 genes underlying the trait, and a variety of mutation and recombination rates and degrees of environmental change. I find that the network architectures introduce extensive directional epistasis that systematically hides and reveals additive genetic variance and affects heritability: network size, topology, and recombination explain 81% of the variance in average heritability in a stable environment. Network size and topology, the width of the fitness function, pre-change additive variance, and certain interactions account for ∼75% of the variance in population recovery times after a sudden environmental change. These results suggest that not only the amount of additive variance, but importantly the number of loci across which it is distributed, is important in regulating the rate at which a trait can evolve and populations can recover. Taken in conjunction with previous research focused on differences in degree of network connectivity, these results provide a set of theoretical expectations and testable hypotheses for biologists working to span levels of organization from the genotype to the phenotype, and from the phenotype to the environment.