If you build it, will they come? A comparative landscape analysis of ocelot roadkill locations and crossing structures.

Wildlife-vehicle collisions can have a substantial influence on the mortality rates of many wildlife populations. Crossing structures are designed to mitigate the impact of road mortality by allowing safe passage of wildlife above or below roads, and connect to suitable areas on both sides of the road. Ocelots (Leopardus pardalis) are a federally endangered felid in the United States, with remnant populations of <80 individuals remaining in the Lower Rio Grande Valley of South Texas. Vehicle collisions are the greatest known source of mortality for ocelots in Texas. Crossing structures designed for ocelot use have been implemented throughout South Texas since the 1990s, however, ocelots rarely use them. We compared landscape characteristics between ocelot crossing structures and ocelot-vehicle collision sites. We quantified the spatial distribution of woody and herbaceous cover types surrounding ocelot crossing structures (n = 56) and ocelot-vehicle collision sites (n = 26) at multiple spatial extents and compared landscape metrics between these location types. The landscape surrounding ocelot crossing structures had 17-22% more open herbaceous cover >1,050 m from the road, and 1.2-5.8 ha larger herbaceous patches >450 m from the road compared to ocelot-vehicle collision sites. Additionally, many crossing structures installed during the 1990's are situated >100 km away from an extant ocelot population. Results from this study can guide conservation planners to place future road crossing structures in areas more likely to be used by ocelots. Our results also emphasize that reliable scientific data must be used for effective mitigation efforts. In the absence of data, post-installation assessments can improve the placement of future structures.

Status and distribution of jaguarundi in Texas and Northeastern México: Making the case for extirpation and initiation of recovery in the United States.

The jaguarundi (Puma yagouaroundi) is a small felid with a historical range from central Argentina through southern Texas. Information on the current distribution of this reclusive species is needed to inform recovery strategies in the United States where its last record was in 1986 in Texas. From 2003 to 2021, we conducted camera-trap surveys across southern Texas and northern Tamaulipas, México to survey for medium-sized wild cats (i.e., ocelots [Leopardus pardalis], bobcats [Lynx rufus], and jaguarundi). After 350,366 trap nights at 685 camera sites, we did not detect jaguarundis at 16 properties or along 2 highways (1050 km2) in Texas. However, we recorded 126 jaguarundi photographic detections in 15,784 trap nights on 2 properties (125.3 km2) in the northern Sierra of Tamaulipas, Tamaulipas, México. On these properties, latency to detection was 72 trap nights, with a 0.05 probability of detection per day and 0.73 photographic event rate every 100 trap nights. Due to a lack of confirmed class I sightings (e.g., specimen, photograph) in the 18 years of this study, and no other class I observations since 1986 in the United States, we conclude that the jaguarundi is likely extirpated from the United States. Based on survey effort and results from México, we would have expected to detect jaguarundis over the course of the study if still extant in Texas. We recommend that state and federal agencies consider jaguarundis as extirpated from the United States and initiate recovery actions as mandated in the federal jaguarundi recovery plan. These recovery actions include identification of suitable habitat in Texas, identification of robust populations in México, and re-introduction of the jaguarundi to Texas.

Assessing changes in clusters of wildlife road mortalities after the construction of wildlife mitigation structures.

Collisions with vehicles can be a major threat to wildlife populations, so wildlife mitigation structures, including exclusionary fencing and wildlife crossings, are often constructed. To assess mitigation structure effectiveness, it is useful to compare wildlife road mortalities (WRMs) before, during, and after mitigation structure construction; however, differences in survey methodologies may make comparisons of counts impractical. Location-based cluster analyses provide a means to assess how WRM spatial patterns have changed over time. We collected WRM data between 2015 and 2019 on State Highway 100 in Texas, USA. Five wildlife crossings and exclusionary fencing were installed in this area between September 2016 and May 2018 for the endangered ocelot (Leopardus pardalis) and other similarly sized mammals. Roads intersecting State Highway 100 were mitigated by gates, wildlife guards, and wing walls. However, these structures may have provided wildlife access to the highway. We combined local hot spot analysis and time series analysis to assess how WRM cluster intensity changed after mitigation structure construction at fine spatial and temporal scales and generalized linear regression to assess how gaps in fencing and land cover were related to WRM cluster intensity in the before, during, and after construction periods. Overall, WRMs/survey day decreased after mitigation structure construction and most hot spots occurred where there were more fence gaps, and, while cluster intensity increased in a few locations, these were not at fence gaps. Cluster intensity of WRMs increased when nearer to fence gaps in naturally vegetated areas, especially forested areas, and decreased nearer to fence gaps in areas with less natural vegetation. We recommend that if fence gaps are necessary in forested areas, less permeable mitigation structures, such as gates, should be used. Local hot spot analysis, coupled with time series and regression techniques, can effectively assess how WRM clustering changes over time.

The status of geo-environmental health in Mississippi: Application of spatiotemporal statistics to improve health and air quality.

Data enabled research with a spatial perspective may help to combat human diseases in an informed and cost-effective manner. Understanding the changing patterns of environmental degradation is essential to help in determining the health outcomes such as asthma of a community. In this research, Mississippi asthma-related prevalence data for 2003-2011 were analyzed using spatial statistical techniques in Geographic Information Systems. Geocoding by ZIP code, choropleth mapping, and hotspot analysis techniques were applied to map the spatial data. Disease rates were calculated for every ZIP code region from 2009 to 2011. The highest rates (4-5.5%) were found in Prairie in Monroe County for three consecutive years. Statistically significant hotspots were observed in urban regions of Jackson and Gulf port with steady increase near urban Jackson and the area between Jackson and meridian metropolis. For 2009-2011, spatial signatures of urban risk factors were found in dense population areas, which was confirmed from regression analysis of asthma patients with population data (linear increase of R2 = 0.648, as it reaches a population size of 3,5000 per ZIP code and the relationship decreased to 59% as the population size increased above 3,5000 to a maximum of 4,7000 per ZIP code). The observed correlation coefficient (r) between monthly mean O3 and asthma prevalence was moderately positive during 2009-2011 (r = 0.57). The regression model also indicated that 2011 annual PM2.5 has a statistically significant influence on the aggravation of the asthma cases (adjusted R-squared 0.93) and the 2011 PM2.5 depended on asthma per capita and poverty rate as well. The present study indicates that Jackson urban area and coastal Mississippi are to be observed for disease prevalence in future. The current results and GIS disease maps may be used by federal and state health authorities to identify at-risk populations and health advisory.

Geospatial interpolation and mapping of tropospheric ozone pollution using geostatistics.

Tropospheric ozone (O3) pollution is a major problem worldwide, including in the United States of America (USA), particularly during the summer months. Ozone oxidative capacity and its impact on human health have attracted the attention of the scientific community. In the USA, sparse spatial observations for O3 may not provide a reliable source of data over a geo-environmental region. Geostatistical Analyst in ArcGIS has the capability to interpolate values in unmonitored geo-spaces of interest. In this study of eastern Texas O3 pollution, hourly episodes for spring and summer 2012 were selectively identified. To visualize the O3 distribution, geostatistical techniques were employed in ArcMap. Using ordinary Kriging, geostatistical layers of O3 for all the studied hours were predicted and mapped at a spatial resolution of 1 kilometer. A decent level of prediction accuracy was achieved and was confirmed from cross-validation results. The mean prediction error was close to 0, the root mean-standardized-prediction error was close to 1, and the root mean square and average standard errors were small. O3 pollution map data can be further used in analysis and modeling studies. Kriging results and O3 decadal trends indicate that the populace in Houston-Sugar Land-Baytown, Dallas-Fort Worth-Arlington, Beaumont-Port Arthur, San Antonio, and Longview are repeatedly exposed to high levels of O3-related pollution, and are prone to the corresponding respiratory and cardiovascular health effects. Optimization of the monitoring network proves to be an added advantage for the accurate prediction of exposure levels.

An integrated WRF/HYSPLIT modeling approach for the assessment of PM(2.5) source regions over the Mississippi Gulf Coast region.

Fine particulate matter (PM(2.5)) is majorly formed by precursor gases, such as sulfur dioxide (SO(2)) and nitrogen oxides (NO(x)), which are emitted largely from intense industrial operations and transportation activities. PM(2.5) has been shown to affect respiratory health in humans. Evaluation of source regions and assessment of emission source contributions in the Gulf Coast region of the USA will be useful for the development of PM(2.5) regulatory and mitigation strategies. In the present study, the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model driven by the Weather Research & Forecasting (WRF) model is used to identify the emission source locations and transportation trends. Meteorological observations as well as PM(2.5) sulfate and nitric acid concentrations were collected at two sites during the Mississippi Coastal Atmospheric Dispersion Study, a summer 2009 field experiment along the Mississippi Gulf Coast. Meteorological fields during the campaign were simulated using WRF with three nested domains of 36, 12, and 4 km horizontal resolutions and 43 vertical levels and validated with North American Mesoscale Analysis. The HYSPLIT model was integrated with meteorological fields derived from the WRF model to identify the source locations using backward trajectory analysis. The backward trajectories for a 24-h period were plotted at 1-h intervals starting from two observation locations to identify probable sources. The back trajectories distinctly indicated the sources to be in the direction between south and west, thus to have origin from local Mississippi, neighboring Louisiana state, and Gulf of Mexico. Out of the eight power plants located within the radius of 300 km of the two monitoring sites examined as sources, only Watson, Cajun, and Morrow power plants fall in the path of the derived back trajectories. Forward dispersions patterns computed using HYSPLIT were plotted from each of these source locations using the hourly mean emission concentrations as computed from past annual emission strength data to assess extent of their contribution. An assessment of the relative contributions from the eight sources reveal that only Cajun and Morrow power plants contribute to the observations at the Wiggins Airport to a certain extent while none of the eight power plants contribute to the observations at Harrison Central High School. As these observations represent a moderate event with daily average values of 5-8 µg m(-3) for sulfate and 1-3 µg m(-3) for HNO(3) with differences between the two spatially varied sites, the local sources may also be significant contributors for the observed values of PM(2.5).

Demographic history of an elusive carnivore: using museums to inform management.

Elusive carnivores present a challenge to managers because traditional survey methods are not suitable. We applied a genetic approach using museum specimens to examine how historical and recent conditions influenced the demographic history of Puma concolor in western and southern Texas, USA. We used 10 microsatellite loci and indexed population trends by estimating historical and recent genetic diversity, genetic differentiation and effective population size. Mountain lions in southern Texas exhibited a 9% decline in genetic diversity, whereas diversity remained stable in western Texas. Genetic differentiation between western and southern Texas was minimal historically (F(ST) = 0.04, P < 0.01), but increased 2-2.5 times in our recent sample. An index of genetic drift for southern Texas was seven to eight times that of western Texas, presumably contributing to the current differentiation between western and southern Texas. Furthermore, southern Texas exhibited a >50% temporal decline in effective population size, whereas western Texas showed no change. Our results illustrate that population declines and genetic drift have occurred in southern Texas, likely because of contemporary habitat loss and predator control. Population monitoring may be needed to ensure the persistence of mountain lions in the southern Texas region. This study highlights the utility of sampling museum collections to examine demographic histories and inform wildlife management.

Air quality modeling for the urban Jackson, Mississippi Region using a high resolution WRF/Chem model.

In this study, an attempt was made to simulate the air quality with reference to ozone over the Jackson (Mississippi) region using an online WRF/Chem (Weather Research and Forecasting-Chemistry) model. The WRF/Chem model has the advantages of the integration of the meteorological and chemistry modules with the same computational grid and same physical parameterizations and includes the feedback between the atmospheric chemistry and physical processes. The model was designed to have three nested domains with the inner-most domain covering the study region with a resolution of 1 km. The model was integrated for 48 hours continuously starting from 0000 UTC of 6 June 2006 and the evolution of surface ozone and other precursor pollutants were analyzed. The model simulated atmospheric flow fields and distributions of NO2 and O3 were evaluated for each of the three different time periods. The GIS based spatial distribution maps for ozone, its precursors NO, NO2, CO and HONO and the back trajectories indicate that all the mobile sources in Jackson, Ridgeland and Madison contributing significantly for their formation. The present study demonstrates the applicability of WRF/Chem model to generate quantitative information at high spatial and temporal resolution for the development of decision support systems for air quality regulatory agencies and health administrators.

Simulation of atmospheric dispersion of elevated releases from point sources in Mississippi Gulf Coast with different meteorological data.

Atmospheric dispersion calculations are made using the HYSPLIT Particle Dispersion Model for studying the transport and dispersion of air-borne releases from point elevated sources in the Mississippi Gulf coastal region. Simulations are performed separately with three meteorological data sets having different spatial and temporal resolution for a typical summer period in 1-3 June 2006 representing a weak synoptic condition. The first two data are the NCEP global and regional analyses (FNL, EDAS) while the third is a meso-scale simulation generated using the Weather Research and Forecasting model with nested domains at a fine resolution of 4 km. The meso-scale model results show significant temporal and spatial variations in the meteorological fields as a result of the combined influences of the land-sea breeze circulation, the large scale flow field and diurnal alteration in the mixing depth across the coast. The model predicted SO(2) concentrations showed that the trajectory and the concentration distribution varied in the three cases of input data. While calculations with FNL data show an overall higher correlation, there is a significant positive bias during daytime and negative bias during night time. Calculations with EDAS fields are significantly below the observations during both daytime and night time though plume behavior follows the coastal circulation. The diurnal plume behavior and its distribution are better simulated using the mesoscale WRF meteorological fields in the coastal environment suggesting its suitability for pollution dispersion impact assessment in the local scale. Results of different cases of simulation, comparison with observations, correlation and bias in each case are presented.

A new inter-professional course preparing learners for life in rural communities.

The 'Professionals in Rural Practice' course was developed with the aim of preparing students enrolled in professional programs in Canada to become better equipped for the possible eventuality of professional work in a rural setting. To match the reality of living and working in a rural community, which by nature is interprofessional, the course designers were an interprofessional teaching team. In order to promote group cohesiveness the course included the participation of an interprofessional group of students and instructors from the disciplines of medicine, nursing, occupational therapy, physical therapy, teacher education, and theology. The format of the course included three-hour classes over an eight-week period and a two-day field experience in a rural community. The course utilized various experiential and interactive teaching and learning methods, along with a variety of assessment methods. Data were collected from student participants over two iterations of the course using a mixed methods approach. Results demonstrate that students value the interprofessional and experiential approach to learning and viewed this course as indispensable for gaining knowledge of other professions and preparation for rural practice. The data reveal important organizational and pedagogical considerations specific to interprofessional education, community based action research, and the unique interprofessional nature of training for life and work in a rural community. This study also indicates the potential value of further longitudinal study of participants in this course. Key words: Canada, community based action research, education, interdisciplinary, interprofessional.