Using Great Basin cottonwoods to study climate change and evolution

The mountains of Great Basin National Park represent important “natural laboratories” for studying the ecological and evolutionary consequences of past climate change. The Cottonwood Ecology group at Northern Arizona University is interested in examining whether genetic changes in Nevada’s cottonwood populations have resulted in the adaptation of dependent organisms to new hosts

The development and evaluation of exercises for meaningful responses in reading in grade two

Research chapter for this study will be found in Ash, Dorothea: "Development and evaluation of silent reading exercises in grade one" Thesis (M.A.)--Boston Universit

Landscape drivers of genomic diversity and divergence in woodland Eucalyptus

Spatial genetic patterns are influenced by numerous factors, and they can vary even among coexisting, closely related species due to differences in dispersal and selection. Eucalyptus (L'Héritier 1789; the “eucalypts”) are foundation tree species that provide essential habitat and modulate ecosystem services throughout Australia. Here we present a study of landscape genomic variation in two woodland eucalypt species, using whole-genome sequencing of 388 individuals of Eucalyptus albens and Eucalyptus sideroxylon. We found exceptionally high genetic diversity (π ≈ 0.05) and low genome-wide, interspecific differentiation (FST = 0.15) and intraspecific differentiation between localities (FST ≈ 0.01–0.02). We found no support for strong, discrete population structure, but found substantial support for isolation by geographic distance (IBD) in both species. Using generalized dissimilarity modelling, we identified additional isolation by environment (IBE). Eucalyptus albens showed moderate IBD, and environmental variables have a small but significant amount of additional predictive power (i.e. IBE). Eucalyptus sideroxylon showed much stronger IBD and moderate IBE. These results highlight the vast adaptive potential of these species and set the stage for testing evolutionary hypotheses of interspecific adaptive differentiation across environmentsAustralian Research Council, Grant/Award Number: CE140100008, DP150103591 and DE19010032

Landscape drivers of genomic diversity and divergence in woodland Eucalyptus

Spatial genetic patterns are influenced by numerous factors, and they can vary even among coexisting, closely related species due to differences in dispersal and selection. Eucalyptus (L'Héritier 1789; the "eucalypts") are foundation tree species that provide essential habitat and modulate ecosystem services throughout Australia. Here we present a study of landscape genomic variation in two woodland eucalypt species, using whole-genome sequencing of 388 individuals of Eucalyptus albens and Eucalyptus sideroxylon. We found exceptionally high genetic diversity (π ≈ 0.05) and low genome-wide, interspecific differentiation (FST = 0.15) and intraspecific differentiation between localities (FST ≈ 0.01-0.02). We found no support for strong, discrete population structure, but found substantial support for isolation by geographic distance (IBD) in both species. Using generalized dissimilarity modelling, we identified additional isolation by environment (IBE). Eucalyptus albens showed moderate IBD, and environmental variables have a small but significant amount of additional predictive power (i.e. IBE). Eucalyptus sideroxylon showed much stronger IBD and moderate IBE. These results highlight the vast adaptive potential of these species and set the stage for testing evolutionary hypotheses of interspecific adaptive differentiation across environments

Multi-scale habitat modelling identifies spatial conservation priorities for mainland clouded leopards (Neofelis nebulosa)

Aim Deforestation is rapidly altering Southeast Asian landscapes, resulting in some of the highest rates of habitat loss worldwide. Among the many species facing declines in this region, clouded leopards rank notably for their ambassadorial potential and capacity to act as powerful levers for broader forest conservation programmes. Thus, identifying core habitat and conservation opportunities are critical for curbing further Neofelis declines and extending umbrella protection for diverse forest biota similarly threatened by widespread habitat loss. Furthermore, a recent comprehensive habitat assessment of Sunda clouded leopards (N. diardi) highlights the lack of such information for the mainland species (N. nebulosa) and facilitates a comparative assessment. Location Southeast Asia. Methods Species–habitat relationships are scale‐dependent, yet <5% of all recent habitat modelling papers apply robust approaches to optimize multivariate scale relationships. Using one of the largest camera trap datasets ever collected, we developed scale‐optimized species distribution models for two con‐generic carnivores, and quantitatively compared their habitat niches. Results We identified core habitat, connectivity corridors, and ranked remaining habitat patches for conservation prioritization. Closed‐canopy forest was the strongest predictor, with ~25% lower Neofelis detections when forest cover declined from 100 to 65%. A strong, positive association with increasing precipitation suggests ongoing climate change as a growing threat along drier edges of the species’ range. While deforestation and land use conversion were deleterious for both species, N. nebulosa was uniquely associated with shrublands and grasslands. We identified 800 km2 as a minimum patch size for supporting clouded leopard conservation. Main conclusions We illustrate the utility of multi‐scale modelling for identifying key habitat requirements, optimal scales of use and critical targets for guiding conservation prioritization. Curbing deforestation and development within remaining core habitat and dispersal corridors, particularly in Myanmar, Laos and Malaysia, is critical for supporting evolutionary potential of clouded leopards and conservation of associated forest biodiversity.Dr. Holly Reed Conservation Fund; Langtang National Park; World Animal Protection; Robertson Foundation; Point Defiance Zoo & Aquariu

Predicting biodiversity richness in rapidly changing landscapes: climate, low human pressure or protection as salvation?

Rates of biodiversity loss in Southeast Asia are among the highest in the world, and the Indo-Burma and South-Central China Biodiversity Hotspots rank among the world’s most threatened. Developing robust multi-species conservation models is critical for stemming biodiversity loss both here and globally. We used a large and geographically extensive remote-camera survey and multi-scale, multivariate optimization species distribution modelling to investigate the factors driving biodiversity across these two adjoining biodiversity hotspots. Four major findings emerged from the work. (i) We identified clear spatial patterns of species richness, with two main biodiverse centres in the Thai-Malay Peninsula and in the mountainous region of Southwest China. (ii) Carnivores in particular, and large ungulates to a lesser degree, were the strongest indicators of species richness. (iii) Climate had the largest effect on biodiversity, followed by protected status and human footprint. (iv) Gap analysis between the biodiversity model and the current system of protected areas revealed that the majority of areas supporting the highest predicted biodiversity are not protected. Our results highlighted several key locations that should be prioritized for expanding the protected area network to maximize conservation effectiveness. We demonstrated the importance of switching from single-species to multi-species approaches to highlight areas of high priority for biodiversity conservation. In addition, since these areas mostly occur over multiple countries, we also advocate for a paradigmatic focus on transboundary conservation planning.The majority of the team, as well as the data, were part of the core WildCRU effort supported principally by a Robertson Foundation grant to DWM

Mean Annual Precipitation Focal Mean 32km-radius Window

Data for this GIS raster layer was obtained from the WorldClim Global Climate Data Portal (http://worldclim.org/version2). We then used neighborhood statistics in ArcGIS to calculate the focal mean of MAP within a 32km-radius moving window. We re-sampled the source data from its native 30-arcsec resolution (~1km) to 250m. Units are in millimeters of precipitation. Coordinate system: Asia South Albers Equal Area Conic

% Closed Forest 16km-radius Window

Using Hansen et al.’s (2013) original percent forest cover layer (http://earthenginepartners.appspot.com/science-2013-global-forest/download_v1.2.html), we reclassified >40% forest cover as ‘closed forest’. We then used FRAGSTATS (McGarigal, Cushman, Neel, & Ene, 2012) to calculate the percentage of the landscape occupied by closed forest habitat within a 16km-radius moving window. The data is in raster .tif format for use in GIS. We resampled the source data from its native 30m resolution to 250m resolution. Coordinate system: Asia South Albers Equal Area Conic

Shrubland/Grassland Correlation Length 16km-radius Window

Original data for this GIS raster layer was obtained from the ESA CCI Land Cover Layer 300m 2015 (www.esa-landcover-cci.org). We first reclassified the original data layer, denoting shrubland/grassland as present (1) or absent (0). We then used FRAGSTATS (McGarigal, Cushman, Neel, & Ene, 2012) to calculate the correlation length or area-weighted mean of gyration within a 16km-radius moving window. Correlation length measures the average distance an individual can travel within a habitat patch, or in this case the average extensiveness of shrubland/grassland habitat within a 16km-radius window. We re-sampled the source data from its native 300m resolution to 250m. Units are in meters. Coordinate system: Asia South Albers Equal Area Conic

Compound Topographic Index Focal Mean 500m-radius Window

This GIS raster was derived from Jarvis, Reuter, Nelson, & Guevara's (2008) digital elevation model (http://srtm.csi.cgiar.org) using the Geomorphometry & Gradient Metrics Toolbox (Evans, Oakleaf, Cushman, & Theobald, 2014) in ArcGIS 10.2.2 (ESRI, Redlands, CA, USA, 2011). Compound topographic index (CTI) characterizes flow accumulation. Low elevation drainages incur high CTI, whereas mountaintops and ridgelines exhibit low CTI. We then used neighborhood statistics in ArcGIS to calculate the focal mean within a 500m-radius moving window. We re-sampled the native 90m resolution DEM to 250m. Coordinate system: Asia South Albers Equal Area Conic