High-Quality, Chromosome-Level Reference Genomes of the Viviparous Caribbean Skinks Spondylurus nitidus and S. culebrae.

New World mabuyine skinks are a diverse radiation of morphologically cryptic lizards with unique reproductive biologies. Recent studies examining population-level data (morphological, ecological, and genomic) have uncovered novel biodiversity and phenotypes, including the description of dozens of new species and insights into the evolution of their highly complex placental structures. Beyond the potential for this diverse group to serve as a model for the evolution of viviparity in lizards, much of the taxonomic diversity is concentrated in regions experiencing increasing environmental instability from climate and anthropogenic change. Consequently, a better understanding of genome structure and diversity will be an important tool in the adaptive management and conservation of this group. Skinks endemic to Caribbean islands are particularly vulnerable to global change with several species already considered likely extinct and several remaining species either endangered or threatened. Combining PacBio long-read sequencing, Hi-C, and RNAseq data, here we present the first genomic resources for this group by describing new chromosome-level reference genomes for the Puerto Rican Skink Spondylurus nitidus and the Culebra Skink S. culebrae. Results indicate two high quality genomes, both ∼1.4 Gb, assembled nearly telomere to telomere with complete mitochondrion assembly and annotation.

Bee species richness through time in an urbanizing landscape of the southeastern United States.

Compared to non-urban environments, cities host ecological communities with altered taxonomic diversity and functional trait composition. However, we know little about how these urban changes take shape over time. Using historical bee (Apoidea: Anthophila) museum specimens supplemented with online repositories and researcher collections, we investigated whether bee species richness tracked urban and human population growth over the past 118 years. We also determined which species were no longer collected, whether those species shared certain traits, and if collector behavior changed over time. We focused on Wake County, North Carolina, United States where human population size has increased over 16 times over the last century along with the urban area within its largest city, Raleigh, which has increased over four times. We estimated bee species richness with occupancy models, and rarefaction and extrapolation curves to account for imperfect detection and sample coverage. To determine if bee traits correlated with when species were collected, we compiled information on native status, nesting habits, diet breadth, and sociality. We used non-metric multidimensional scaling to determine if individual collectors contributed different bee assemblages over time. In total, there were 328 species collected in Wake County. We found that although bee species richness varied, there was no clear trend in bee species richness over time. However, recent collections (since 2003) were missing 195 species, and there was a shift in trait composition, particularly lost species were below-ground nesters. The top collectors in the dataset differed in how often they collected bee species, but this was not consistent between historic and contemporary time periods; some contemporary collectors grouped closer together than others, potentially due to focusing on urban habitats. Use of historical collections and complimentary analyses can fill knowledge gaps to help understand temporal patterns of species richness in taxonomic groups that may not have planned long-term data.

High-resolution dynamically downscaled rainfall and temperature projections for ecological life zones within Puerto Rico and for the US Virgin Islands.

The Weather Research and Forecasting (WRF) model and a combination of the Regional Spectral Model (RSM) and the Japanese Meteorological Agency Non-Hydrostatic Model (NHM) were used to dynamically downscale selected CMIP5 global climate models to provide 2-km projections with hourly model output for Puerto Rico and the U.S. Virgin Islands. Two 20-year time slices were downscaled for historical (1986-2005) and future (2041-2060) periods following RCP8.5. Projected changes to mean and extreme temperature and precipitation were quantified for Holdridge life zones within Puerto Rico and for the U.S. Virgin Islands. The evaluation reveals a persistent cold bias for all islands in the U.S. Caribbean, a dry bias across Puerto Rico, and a wet bias on the windward side of mountains within the U.S. Virgin Islands. Despite these biases, model simulations show a robust drying pattern for all islands that is generally larger for Puerto Rico (25% annual rainfall reduction for some life zones) than the U.S. Virgin Islands (12% island average). The largest precipitation reductions are found during the more convectively active afternoon and evening hours. Within Puerto Rico, the model uncertainty increases for the wetter life zones, especially for precipitation. Across the life zones, both models project unprecedented maximum and minimum temperatures that may exceed 200 days annually above the historical baseline with only small changes to the frequency of extreme rainfall. By contrast, in the U.S. Virgin Islands, there is no consensus on the location of the largest drying relative to the windward and leeward side of the islands. However, the models project the largest increases in maximum temperature on the southern side of St. Croix and in higher elevations of St. Thomas and St. John.

A comparison of coffee floral traits under two different agricultural practices.

Floral traits and rewards are important in mediating interactions between plants and pollinators. Agricultural management practices can affect abiotic factors known to influence floral traits; however, our understanding of the links between agricultural practices and floral trait expression is still poorly understood. Variation in floral morphological, nectar, and pollen traits of two important agricultural species, Coffea arabica and C. canephora, was assessed under different agricultural practices (sun and shade). Corolla diameter and corolla tube length were larger and pollen total nitrogen content greater in shade plantations of C. canephora than sun plantations. Corolla tube length and anther filament length were larger in shade plantations of C. arabica. No effect of agricultural practice was found on nectar volume, sugar or caffeine concentrations, or pollen production. Pollen total nitrogen content was lower in sun than shade plantations of C. canephora, but no difference was found between sun and shade for C. arabica. This study provides baseline data on the influence of agronomic practices on C. arabica and C. canephora floral traits and also helps fill a gap in knowledge about the effects of shade trees on floral traits, which can be pertinent to other agroforestry systems.

Partitioning global change: Assessing the relative importance of changes in climate and land cover for changes in avian distribution.

Understanding the relative impact of climate change and land cover change on changes in avian distribution has implications for the future course of avian distributions and appropriate management strategies. Due to the dynamic nature of climate change, our goal was to investigate the processes that shape species distributions, rather than the current distributional patterns. To this end, we analyzed changes in the distribution of Eastern Wood Pewees (Contopus virens) and Red-eyed Vireos (Vireo olivaceus) from 1997 to 2012 using Breeding Bird Survey data and dynamic correlated-detection occupancy models. We estimated the local colonization and extinction rates of these species in relation to changes in climate (hours of extreme temperature) and changes in land cover (amount of nesting habitat). We fit six nested models to partition the deviance explained by spatial and temporal components of land cover and climate. We isolated the temporal components of environmental variables because this is the essence of global change. For both species, model fit was significantly improved when we modeled vital rates as a function of spatial variation in climate and land cover. Model fit improved only marginally when we added temporal variation in climate and land cover to the model. Temporal variation in climate explained more deviance than temporal variation in land cover, although both combined only explained 20% (Eastern Wood Pewee) and 6% (Red-eyed Vireo) of temporal variation in vital rates. Our results showing a significant correlation between initial occupancy and environmental covariates are consistent with biological expectation and previous studies. The weak correlation between vital rates and temporal changes in covariates indicated that we have yet to identify the most relevant components of global change influencing the distributions of these species and, more importantly, that spatially significant covariates are not necessarily driving temporal shifts in avian distributions.

Optimal treatment allocations in space and time for on-line control of an emerging infectious disease.

A key component in controlling the spread of an epidemic is deciding where, when and to whom to apply an intervention. We develop a framework for using data to inform these decisions in realtime. We formalize a treatment allocation strategy as a sequence of functions, one per treatment period, that map up-to-date information on the spread of an infectious disease to a subset of locations where treatment should be allocated. An optimal allocation strategy optimizes some cumulative outcome, e.g. the number of uninfected locations, the geographic footprint of the disease or the cost of the epidemic. Estimation of an optimal allocation strategy for an emerging infectious disease is challenging because spatial proximity induces interference between locations, the number of possible allocations is exponential in the number of locations, and because disease dynamics and intervention effectiveness are unknown at out-break. We derive a Bayesian on-line estimator of the optimal allocation strategy that combines simulation-optimization with Thompson sampling. The estimator proposed performs favourably in simulation experiments. This work is motivated by and illustrated using data on the spread of white nose syndrome, which is a highly fatal infectious disease devastating bat populations in North America.

Ecological regime shift drives declining growth rates of sea turtles throughout the West Atlantic.

Somatic growth is an integrated, individual-based response to environmental conditions, especially in ectotherms. Growth dynamics of large, mobile animals are particularly useful as bio-indicators of environmental change at regional scales. We assembled growth rate data from throughout the West Atlantic for green turtles, Chelonia mydas, which are long-lived, highly migratory, primarily herbivorous mega-consumers that may migrate over hundreds to thousands of kilometers. Our dataset, the largest ever compiled for sea turtles, has 9690 growth increments from 30 sites from Bermuda to Uruguay from 1973 to 2015. Using generalized additive mixed models, we evaluated covariates that could affect growth rates; body size, diet, and year have significant effects on growth. Growth increases in early years until 1999, then declines by 26% to 2015. The temporal (year) effect is of particular interest because two carnivorous species of sea turtles-hawksbills, Eretmochelys imbricata, and loggerheads, Caretta caretta-exhibited similar significant declines in growth rates starting in 1997 in the West Atlantic, based on previous studies. These synchronous declines in productivity among three sea turtle species across a trophic spectrum provide strong evidence that an ecological regime shift (ERS) in the Atlantic is driving growth dynamics. The ERS resulted from a synergy of the 1997/1998 El Niño Southern Oscillation (ENSO)-the strongest on record-combined with an unprecedented warming rate over the last two to three decades. Further support is provided by the strong correlations between annualized mean growth rates of green turtles and both sea surface temperatures (SST) in the West Atlantic for years of declining growth rates (r = -.94) and the Multivariate ENSO Index (MEI) for all years (r = .74). Granger-causality analysis also supports the latter finding. We discuss multiple stressors that could reinforce and prolong the effect of the ERS. This study demonstrates the importance of region-wide collaborations.

The effect of urban growth on landscape-scale restoration for a fire-dependent songbird.

A landscape-scale perspective on restoration ecology has been advocated, but few studies have informed restoration with landscape metrics or addressed broad-scale threats. Threats such as urban growth may affect restoration effectiveness in a landscape context. Here, we studied longleaf pine savanna in the rapidly urbanizing southeastern United States where a habitat-specialist bird, Bachman's sparrow (Peucaea aestivalis), is closely associated with savanna vegetation structure and frequent fire. Our objectives were to construct a species distribution model for Bachman's sparrow, determine the relationship between fire and urbanization, quantify the urban growth effect (2010-2090), identify potential restoration areas, and determine the interaction between restoration potential and urban growth by 2050. Number of patches, patch size, and isolation metrics were used to evaluate scenarios. The species distribution model was 88% accurate and emphasized multiscale canopy cover characteristics, fire, and percent habitat. Fires were less common <600 m from urban areas, and this fire suppression effect exacerbated urban growth effects. For restoration scenarios, canopy cover reduction by 30% resulted in nearly double the amount of habitat compared to the prescribed fire scenario; canopy cover reduction resulted in larger patch sizes and less patch isolation compared to current conditions. The effect of urban growth on restoration scenarios was unequal. Seventy-four percent of restoration areas from the prescribed fire scenario overlapped with projected urban growth, whereas the canopy cover reduction scenario only overlapped by 9%. We emphasize the benefits of simultaneously considering the effects of urban growth and landscape-scale restoration potential to promote a landscape with greater patch sizes and less isolation.

Integrating multiple data sources in species distribution modeling: a framework for data fusion.

The last decade has seen a dramatic increase in the use of species distribution models (SDMs) to characterize patterns of species' occurrence and abundance. Efforts to parameterize SDMs often create a tension between the quality and quantity of data available to fit models. Estimation methods that integrate both standardized and non-standardized data types offer a potential solution to the tradeoff between data quality and quantity. Recently several authors have developed approaches for jointly modeling two sources of data (one of high quality and one of lesser quality). We extend their work by allowing for explicit spatial autocorrelation in occurrence and detection error using a Multivariate Conditional Autoregressive (MVCAR) model and develop three models that share information in a less direct manner resulting in more robust performance when the auxiliary data is of lesser quality. We describe these three new approaches ("Shared," "Correlation," "Covariates") for combining data sources and show their use in a case study of the Brown-headed Nuthatch in the Southeastern U.S. and through simulations. All three of the approaches which used the second data source improved out-of-sample predictions relative to a single data source ("Single"). When information in the second data source is of high quality, the Shared model performs the best, but the Correlation and Covariates model also perform well. When the information quality in the second data source is of lesser quality, the Correlation and Covariates model performed better suggesting they are robust alternatives when little is known about auxiliary data collected opportunistically or through citizen scientists. Methods that allow for both data types to be used will maximize the useful information available for estimating species distributions.

Modeling climate change, urbanization, and fire effects on Pinus palustris ecosystems of the southeastern U.S.

Managing ecosystems for resilience and sustainability requires understanding how they will respond to future anthropogenic drivers such as climate change and urbanization. In fire-dependent ecosystems, predicting this response requires a focus on how these drivers will impact fire regimes. Here, we use scenarios of climate change, urbanization and management to simulate the future dynamics of the critically endangered and fire-dependent longleaf pine (Pinus palustris) ecosystem. We investigated how climate change and urbanization will affect the ecosystem, and whether the two conservation goals of a 135% increase in total longleaf area and a doubling of fire-maintained open-canopy habitat can be achieved in the face of these drivers. Our results show that while climatic warming had little effect on the wildfire regime, and thus on longleaf pine dynamics, urban growth led to an 8% reduction in annual wildfire area. The management scenarios we tested increase the ecosystem's total extent by up to 62% and result in expansion of open-canopy longleaf by as much as 216%, meeting one of the two conservation goals for the ecosystem. We find that both conservation goals for this ecosystem, which is climate-resilient but vulnerable to urbanization, are only attainable if a greater focus is placed on restoration of non-longleaf areas as opposed to maintaining existing longleaf stands. Our approach demonstrates the importance of accounting for multiple relevant anthropogenic threats in an ecosystem-specific context in order to facilitate more effective management actions.

The southern megalopolis: using the past to predict the future of urban sprawl in the Southeast U.S.

The future health of ecosystems is arguably as dependent on urban sprawl as it is on human-caused climatic warming. Urban sprawl strongly impacts the urban ecosystems it creates and the natural and agro-ecosystems that it displaces and fragments. Here, we project urban sprawl changes for the next 50 years for the fast-growing Southeast U.S. Previous studies have focused on modeling population density, but the urban extent is arguably as important as population density per se in terms of its ecological and conservation impacts. We develop simulations using the SLEUTH urban growth model that complement population-driven models but focus on spatial pattern and extent. To better capture the reach of low-density suburban development, we extend the capabilities of SLEUTH by incorporating street-network information. Our simulations point to a future in which the extent of urbanization in the Southeast is projected to increase by 101% to 192%. Our results highlight areas where ecosystem fragmentation is likely, and serve as a benchmark to explore the challenging tradeoffs between ecosystem health, economic growth and cultural desires.

Guidelines for a priori grouping of species in hierarchical community models.

Recent methodological advances permit the estimation of species richness and occurrences for rare species by linking species-level occurrence models at the community level. The value of such methods is underscored by the ability to examine the influence of landscape heterogeneity on species assemblages at large spatial scales. A salient advantage of community-level approaches is that parameter estimates for data-poor species are more precise as the estimation process "borrows" from data-rich species. However, this analytical benefit raises a question about the degree to which inferences are dependent on the implicit assumption of relatedness among species. Here, we assess the sensitivity of community/group-level metrics, and individual-level species inferences given various classification schemes for grouping species assemblages using multispecies occurrence models. We explore the implications of these groupings on parameter estimates for avian communities in two ecosystems: tropical forests in Puerto Rico and temperate forests in northeastern United States. We report on the classification performance and extent of variability in occurrence probabilities and species richness estimates that can be observed depending on the classification scheme used. We found estimates of species richness to be most precise and to have the best predictive performance when all of the data were grouped at a single community level. Community/group-level parameters appear to be heavily influenced by the grouping criteria, but were not driven strictly by total number of detections for species. We found different grouping schemes can provide an opportunity to identify unique assemblage responses that would not have been found if all of the species were analyzed together. We suggest three guidelines: (1) classification schemes should be determined based on study objectives; (2) model selection should be used to quantitatively compare different classification approaches; and (3) sensitivity of results to different classification approaches should be assessed. These guidelines should help researchers apply hierarchical community models in the most effective manner.

Plasma metabolites and migration physiology of semipalmated sandpipers: refueling performance at five latitudes.

Long-distance bird migration is fueled by energy gathered at stopover sites along the migration route. The refueling rate at stopover sites is a determinant of time spent at stopovers and impacts the overall speed of migration. Refueling rate during spring migration may influence the fitness of individuals via changes in the probability of successful migration and reproduction during the subsequent breeding season. We evaluated four plasma lipid metabolites (triglycerides, phospholipids, beta-OH-butyrate, and glycerol) as measures of refueling rate in free-living semipalmated sandpipers (Calidris pusilla) captured at non-breeding areas. We described the spatial and temporal variation in metabolite concentrations among one winter site in the Dominican Republic and four stopover sites in the South Atlantic and Mid-Atlantic Coastal Plain regions of North America. Triglycerides and beta-OH-butyrate clearly identified spatial variation in refueling rate and stopover habitat quality. Metabolite profiles indicated that birds had higher refueling rates at one site in the Mid-Atlantic Coastal Plain than at three sites on the South Atlantic Coastal Plain and one site in the Dominican Republic. Temporal variation in lipid metabolites during the migration season suggested that male semipalmated sandpipers gained more weight at stopovers on the South Atlantic Coastal Plain than did females, evidence of differential migration strategies for the sexes. Plasma lipid metabolites provide information on migration physiology that may help determine stopover habitat quality and reveal how migratory populations use stopover sites to refuel and successfully complete long-distance migrations.

Additive effects of vertebrate predators on insects in a Puerto Rican coffee plantation.

A variety of studies have established the value of shaded coffee plantations as habitat for birds. While the value of birds as biological controls in coffee has received some attention, the interactions between birds and other predators of insects have not been tested. We used exclosures to examine the effects of vertebrate predators on the arthropods associated with coffee, in particular the coffee leafminer (Leucoptera coffeella) and the flatid planthopper Petrusa epilepsis, in a shaded coffee plantation in Puerto Rico. We used a 2 x 2 factorial design with four treatments: exclusion of birds, lizards, birds and lizards, and control (no exclusion). Abundance of insects > 5 mm increased when birds or both birds and lizards were removed. Birds and lizards had an additive effect for insects < 5 mm and for all insects combined. Coffee leafminers showed a weak response to removal of predators while planthopper abundance increased significantly in the absence of avian predators. Arthropod predators and parasitoids did not differ significantly between treatments. Our findings suggest that vertebrate insectivores have an additive effect on insects in coffee and may help control abundances of some coffee pests. Equally important, we present evidence suggesting that they do not interfere with other known natural enemies of coffee pests.

How do frugivores track resources? Insights from spatial analyses of bird foraging in a tropical forest.

Frugivores often track ripe fruit abundance closely across local areas despite the ephemeral and typically patchy distributions of this resource. We use spatial auto- and cross-correlation analyses to quantify spatial patterns of fruit abundance and avian frugivory across a 4-month period within a forested 4.05-ha study grid in Puerto Rico. Analyses focused on two tanager species, Spindalis portoricensis and Nesospingus speculiferus, and their principal food plants. Three broad questions are addressed: (1). at what spatial scales is fruit abundance and frugivory patchy; (2). at what spatial scales do frugivores respond to fruit abundance; and (3). to what extent do spatial patterns of frugivory overlap between bird species? Fruit patch size, species composition, and heterogeneity was variable among months, despite fruit patch locations remaining relatively consistent between months. Positive correlations between frugivory and fruit abundance suggested tanagers successfully tracked fruit abundance. Frugivory was, however, more localized than fruit abundance. Scales of spatial overlap in frugivory and monthly variation in the foraging locations of the two tanager species suggested that interspecific facilitation may have been important in determining bird foraging locations. In particular, S. portoricensis, a specialist frugivore, may have relied on the loud calls of the gregarious generalist, N. speculiferus, to find new foraging areas. Such a mechanism could help explain the formation of mixed species feeding flocks and highlights the potential importance of facilitation between species that share resources.

Avian fruit preferences across a Puerto Rican forested landscape: pattern consistency and implications for seed removal.

Avian fruit consumption may ensure plant reproductive success when frugivores show consistent preference patterns and effectively remove and disperse seeds. In this study we examined avian fruit preferences and their seed-removal services at five study sites in north-central Puerto Rico. At each site, we documented the diet of seven common fruit-eating avian species from February to September 1998. Using foraging observations and area-based estimates of fruit abundance, we examined preference patterns of birds. We found that 7 out of 68 fleshy-fruited plant species were responsible for most of the fruit diet of birds. Seventeen plant species were preferred and four of them were repeatedly preferred across several study sites and times by at least one avian species. Preferred plant species comprised a small percentage of fleshy fruits at each site (<15% in four out of five study sites), but showed extended phenology patterns. The quantity of seeds removed by frugivore species was not strictly related to preferences. Some frugivores showing no preference could effectively remove more seeds from plants at some locations than species exhibiting constancy in their patterns of preference. Only two frugivores, Euphonia musica and Vireo altiloquous, removed most of the seeds of plants for which they exhibited repeated preference across the landscape. Preference patterns, particularly those exhibiting consistency in space and time for plant species having prolonged fruiting periods, may have important mechanistic consequences for the persistence, succession, and regeneration of tropical plant communities.