Two types of passive samplers--semipermeable membrane devices (SPMDs) and polar organic chemical integrative samplers (POCIS)--were deployed in spring 2008 to assess bioavailable concentrations of aquatic contaminants in five cave streams and resurgences in Perry County, Missouri. Study sites represent areas of high cave biodiversity and the only known habitat for grotto sculpin (Cottus carolinae). Time-weighted average (TWA) water concentrations were calculated for 20 compounds (n = 9 SPMDs; n = 11 POCIS) originating primarily from agricultural sources, including two organochlorine insecticides, dieldrin and heptachlor epoxide, which were found at levels exceeding U.S. EPA criteria for the protection of aquatic life. GIS data were used to quantify and map sinkhole distribution and density within the study area. Infiltration of storm runoff and its influence on contaminant transport were also evaluated using land cover and hydrological data. This work provides evidence of cave stream contamination by a mix of organic chemicals and demonstrates the applicability of passive samplers for monitoring water quality in dynamic karst environments where rapid transmission of storm runoff makes instantaneous water sampling difficult.

Sustainable management of dryland river systems is often complicated by extreme variability of precipitation in time and space, especially across large catchment areas. Understanding regional water quality changes in southern African dryland rivers and wetland systems is especially important because of their high subsistence value and provision of ecosystem services essential to both public and animal health. We quantified seasonal variation of Escherichia coli (E. coli) and Total Suspended Solids (TSS) in the Chobe River using spatiotemporal and geostatistical modeling of water quality time series data collected along a transect spanning a mosaic of protected, urban, and developing urban land use. We found significant relationships in the dry season between E. coli concentrations and protected land use (p = 0.0009), floodplain habitat (p = 0.016), and fecal counts from elephant (p = 0.017) and other wildlife (p = 0.001). Dry season fecal loading by both elephant (p = 0.029) and other wildlife (p = 0.006) was also an important predictor of early wet season E. coli concentrations. Locations of high E. coli concentrations likewise showed close spatial agreement with estimates of wildlife biomass derived from aerial survey data. In contrast to the dry season, wet season bacterial water quality patterns were associated only with TSS (p<0.0001), suggesting storm water and sediment runoff significantly influence E. coli loads. Our data suggest that wildlife populations, and elephants in particular, can significantly modify river water quality patterns. Loss of habitat and limitation of wildlife access to perennial rivers and floodplains in water-restricted regions may increase the impact of species on surface water resources. Our findings have important implications to land use planning in southern Africa’s dryland river ecosystems.

Abstract:Complex couplings and feedback among climate, fire, and herbivory drive short-and long-term patterns of land cover change (LCC) in savanna ecosystems. However, understanding of spatial and temporal LCC patterns in these environments is limited, particularly for semi-arid regions transitional between arid and more mesic climates. Here, we use post-classification analysis of Landsat TM (1990), ETM+ (2003), and OLI (2013) satellite imagery to classify and assess net and gross LCC for the Chobe District, a 21,000 km 2 area encompassing urban, peri-urban, rural, communally-managed (Chobe Enclave), and protected land (Chobe National Park, CNP, and six protected forest reserves). We then evaluate spatiotemporal patterns of LCC in relation to precipitation, fire detections (MCD14M, 2001(MCD14M, -2013 from the Moderate Resolution Imaging Spectroradiometer (MODIS), and dry season elephant (Loxodonta africana) aerial survey data (2003, 2006, 2012, 2013). Woodland cover declined over the study period by 1514 km 2 (16.2% of initial class total), accompanied by expansion of shrubland (1305 km 2 , 15.7%) and grassland (265 km 2 , 20.3%). Net LCC differed importantly in protected areas, with higher woodland losses observed in forest reserves compared to the CNP. Loss of woodland was also higher in communally-managed land for the study period, despite gains from 2003-2013. Gross (class) changes were characterized by extensive exchange between woodland and shrubland during both time steps, and a large expansion of shrubland into grassland and bare ground from 2003-2013. MODIS active fire detections were highly variable from year to year and among the different protected areas, ranging from 1.8 fires*year −1 /km 2 in the Chobe Forest Reserve to 7.1 fires*year −1 /km 2 in the Kasane Forest Reserve Extension. Clustering and timing of dry season fires suggests that ignitions were predominately from anthropogenic sources. Annual fire count was significantly related to total annual rainfall (p = 0.009, adj. R 2 = 0.50), with a 41% increase in average fire occurrence in years when rainfall exceeded long-term mean annual precipitation (MAP). Loss of woodland was significantly associated with fire in locations experiencing 15 or more ignitions during the period 2001-2013 (p = 0.024). Although elephant-mediated damage is often cited as a major cause of woodland degradation in northern Botswana, we observed little evidence of unsustainable pressure on woodlands from growing elephant populations. Our data indicate broad-scale LCC processes in semi-arid savannas in Southern Africa are strongly coupled to environmental and anthropogenic forcings. Increased seasonal variability is likely to have important effects on the distribution of savanna plant communities due to climate-fire feedbacks. Long-term monitoring of LCC in these ecosystems is essential to improving land use planning and management strategies that protect biodiversity, as well as traditional cultures and livelihoods under future climate change scenarios for Southern Afr...

Little is known about the role of surface water in the propagation of antibiotic resistance (AR), or the relationship between AR and water quality declines. While healthcare and agricultural sectors are considered the main contributors to AR dissemination, few studies have been conducted in their absence. Using linear models and Bayesian kriging, we evaluate AR among Escherichia coli water isolates collected bimonthly from the Chobe River in Northern Botswana (n = 1997, n = 414 water samples; July 2011–May 2012) in relation to water quality dynamics (E. coli, fecal coliform, and total suspended solids), land use, season, and AR in wildlife and humans within this system. No commercial agricultural or large medical facilities exist within this region. Here, we identify widespread AR in surface water, with land use and season significant predicators of AR levels. Mean AR was significantly higher in the wet season than the dry season (p = 0.003), and highest in the urban landscape (2.15, SD = 0.098) than the protected landscape (1.39, SD = 0.051). In-water E. coli concentrations were significantly positively associated with mean AR in the wet season (p < 0.001) but not in the dry season (p = 0.110), with TSS negatively associated with mean AR across seasons (p = 0.016 and p = 0.029), identifying temporal and spatial relationships between water quality variables and AR. Importantly, when human, water, and wildlife isolates were examined, similar AR profiles were identified (p < 0.001). Our results suggest that direct human inputs are sufficient for extensive dispersal of AR into the environment, with landscape features, season, and water quality variables influencing AR dynamics. Focused and expensive efforts to minimize pollution from agricultural sources, while important, may only provide incremental benefits to the management of AR across complex landscapes. Controlling direct human AR inputs into the environment remains a critical and pressing challenge.