Linking mountaintop removal mining to water quality for imperiled species using satellite data.

Environmental laws need sound data to protect species and ecosystems. In 1996, a proliferation of mountaintop removal coal mines in a region home to over 50 federally protected species was approved under the Endangered Species Act. Although this type of mining can degrade terrestrial and aquatic habitats, the available data and tools limited the ability to analyze spatially extensive, aggregate effects of such a program. We used two large, public datasets to quantify the relationship between mountaintop removal coal mining and water quality measures important to the survival of imperiled species at a landscape scale across Kentucky, Tennessee, Virginia, and West Virginia. We combined an annual map of the extent of surface mines in this region from 1985 to 2015 generated from Landsat satellite imagery with public water quality data collected over the same time period from 4,260 monitoring stations within the same area. The water quality data show that chronic and acute thresholds for levels of aluminum, arsenic, cadmium, conductivity, copper, lead, manganese, mercury, pH, selenium, and zinc safe for aquatic life were exceeded thousands of times between 1985 and 2015 in streams that are important to the survival and recovery of species on the Endangered Species List. Linear mixed models showed that levels of manganese, sulfate, sulfur, total dissolved solids, total suspended solids, and zinc increased by 6.73E+01 to 6.87E+05 µg/L and conductivity by 3.30E+06 µS /cm for one percent increase in the mined proportion of the area draining into a monitoring station. The proportion of a drainage area that was mined also increased the likelihood that chronic thresholds for copper, lead, and zinc required to sustain aquatic life were exceeded. Finally, the proportion of a watershed that was mined was positively related to the likelihood that a waterway would be designated as impaired under the Clean Water Act. Together these results demonstrate that the extent of mountaintop removal mining, which can be derived from public satellite data, is predictive of water quality measures important to imperiled species-effects that must be considered under environmental law. These findings and the public data used in our analyses are pertinent to ongoing re-evaluations of the effects of current mine permitting regulations to the recovery and survival of federally protected species.

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).

Respaldo a la Conservación de Hábitat con la Detección Automatizada de Cambio en Google Earth Resumen Una limitación significativa en la conservación de la biodiversidad ha sido la implementación efectiva de las leyes y regulaciones que protegen los hábitats de las especies de la degradación. El monitoreo flexible, eficiente y efectivo y los métodos de aplicación son necesarios para que las normas de conservación puedan llevar a cabo su potencial completo. Conforme los datos de telemetría se vuelven cada vez más numerosos y accesibles, su uso puede extenderse a la identificación y cuantificación de los cambios en la cobertura del suelo y la pérdida del hábitat. Sin embargo, estos datos todavía están subutilizados en cuanto al monitoreo sistemático de la conservación en parte debido a la falta de herramientas simples y sencillas. Adaptamos dos algoritmos que identifican automáticamente las diferencias entre pares de imágenes. Utilizamos datos satelitales gratuitos y disponibles para el público para con ellos evaluar la habilidad que tienen los algoritmos para detectar rápidamente los cambios en la cobertura del suelo dentro de una variedad de tipos de cobertura de suelo. Comparamos las predicciones algorítmicas con los resultados de algunas investigaciones en 100 sitios con cambios conocidos en los Estados Unidos. También comparamos las predicciones algorítmicas con polígonos creados manualmente que delinean el cambio antropogénico en cuatro estudios de caso que involucran al hábitat de una especie en peligro: desarrollos de petróleo y gas en la distribución de Centrocercus urophasianus; minas de arena en la distribución de Sceloporus arenicolus; la pérdida del hábitat costero de Charadrius melodus después del huracán Michael (2018); y los desarrollos residenciales en el hábitat de Peromyscus polionotus peninsularis. Ambos algoritmos discriminaron efectivamente entre los píxeles que correspondían al cambio en la cobertura del suelo y los píxeles sin cambio así indicados por el área bajo la curva de característica de receptor operante >0.90. El algoritmo más efectivo difirió entre los tipos de hábitat para los estudios de caso, mientras que ambos algoritmos delinearon efectivamente la pérdida de hábitat así indicada por la baja tasa de omisión (min. = 0.0) y comisión (min. = 0.0) y el traslape moderado de polígonos (max. = 47%). Nuestros resultados mostraron cómo pueden usarse estos algoritmos para ayudar a cerrar la brecha en la implementación del monitoreo y aplicación en la conservación de la biodiversidad. Proporcionamos una herramienta gratuita en línea que puede usarse para realizar estos análisis: https://conservationist.io/habitatpatrol.

Novel data show expert wildlife agencies are important to endangered species protection.

To protect biodiversity, conservation laws should be evaluated and improved using data. We provide a comprehensive assessment of how a key provision of the U.S. Endangered Species Act (ESA) is implemented: consultation to ensure federal actions do not jeopardize the existence of listed species. Data from all 24,893 consultations recorded by the National Marine Fisheries Service (NMFS) from 2000-2017 show federal agencies and NMFS frequently agreed (79%) on how federal actions would affect listed species. In cases of disagreement, agencies most often (71%) underestimated effects relative to the conclusions of species experts at NMFS. Such instances can have deleterious consequences for imperiled species. In 22 consultations covering 14 species, agencies concluded that an action would not harm species while NMFS determined the action would jeopardize species' existence. These results affirm the importance of the role of NMFS in preventing federal actions from jeopardizing listed species. Excluding expert agencies from consultation compromises biodiversity conservation, but we identify approaches that improve consultation efficiency without sacrificing species protections.

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.

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 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.

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.