Assessing Sustainability at Multiple Scales in a Rotational Bushmeat Hunting System

Abstract: Results of many studies show unsustainable levels of bushmeat hunting across West/Central Africa. Nevertheless, these results are usually derived from snapshot sustainability indices in which critical parameters are often taken from the literature. Simple, more informative tools for assessing sustainability are needed. We evaluated the impact of bushmeat hunting across a range of temporal, spatial, and taxonomic scales in a comparison of different measures of sustainability. Over 15 months in 2002–2004 in and around a village close to Equatorial Guinea's Monte Alén National Park, we collected data via a village offtake survey, hunter‐camp bushmeat‐consumption diaries, hunter interviews, and following hunters during hunts. We compared 2003 data with a previous offtake survey (1998–1999) and interview reports back to 1990. In the past 14 years, average distance from the village at which hunters operated remained constant, with hunters switching back and forth between long‐established camps, although trapping effort increased. In the past 5 years, overall offtake and number of active hunters did not change substantially, although catch per unit effort (CPUE) decreased slightly. Although the proportion of the two most commonly trapped species (Cephalophus monticola and Atherurus africanus) and gun‐hunted primates increased in the offtake, species presumably less robust to trapping decreased slightly. Apparent sustainability in economic terms may be masking gradual local extirpation of more vulnerable species before and during this study. Our results suggest that changes in prey profiles and CPUE may be the most accurate indicators of actual sustainability; these indices can be monitored with simple village‐based offtake surveys and hunter interviews to improve community management of bushmeat hunting.     

Effectiveness of Scat‐Detection Dogs in Determining Species Presence in a Tropical Savanna Landscape

Abstract: Most protected areas are too small to sustain populations of wide‐ranging mammals; thus, identification and conservation of high‐quality habitat for those animals outside parks is often a high priority, particularly for regions where extensive land conversion is occurring. This is the case in the vicinity of Emas National Park, a small protected area in the Brazilian Cerrado. Over the last 40 years the native vegetation surrounding the park has been converted to agriculture, but the region still supports virtually all of the animals native to the area. We determined the effectiveness of scat‐detection dogs in detecting presence of five species of mammals threatened with extinction by habitat loss: maned wolf (Chrysocyon brachyurus), puma (Puma concolor), jaguar (Panthera onca), giant anteater (Myrmecophaga tridactyla), and giant armadillo (Priodontes maximus). The probability of scat detection varied among the five species and among survey quadrats of different size, but was consistent across team, season, and year. The probability of occurrence, determined from the presence of scat, in a randomly selected site within the study area ranged from 0.14 for jaguars, which occur primarily in the forested areas of the park, to 0.91 for maned wolves, the most widely distributed species in our study area. Most occurrences of giant armadillos in the park were in open grasslands, but in the agricultural matrix they tended to occur in riparian woodlands. At least one target species occurred in every survey quadrat, and giant armadillos, jaguars, and maned wolves were more likely to be present in quadrats located inside than outside the park. The effort required for detection of scats was highest for the two felids. We were able to detect the presence for each of five wide‐ranging species inside and outside the park and to assign occurrence probabilities to specific survey sites. Thus, scat dogs provide an effective survey tool for rare species even when accurate detection likelihoods are required. We believe the way we used scat‐detection dogs to determine the presence of species can be applied to the detection of other mammalian species in other ecosystems.     

Spatiotemporal Variability of Modeled Watershed Scale Surface‐Depression Storage and Runoff for the Conterminous United States

This study explores the viability of using simulated monthly runoff as a proxy for landscape‐scale surface‐depression storage processes simulated by the United States Geological Survey’s National Hydrologic Model (NHM) infrastructure across the conterminous United States (CONUS). Two different temporal resolution model codes (daily and monthly) were run in the NHM with the same spatial discretization. Simulated values of daily surface‐depression storage (treated as a decimal fraction of maximum volume) as computed by the daily Precipitation‐Runoff Modeling System (NHM‐PRMS) and normalized runoff (0 to 1) as computed by the Monthly Water Balance Model (NHM‐MWBM) were aggregated to monthly and annual values for each hydrologic response unit (HRU) in the CONUS geospatial fabric (HRU; n = 109,951) and analyzed using Spearman’s rank correlation test. Correlations between simulated runoff and surface‐depression storage aggregated to monthly and annual values were compared to identify where which time scale had relatively higher correlation values across the CONUS. Results show Spearman’s rank values >0.75 (highly correlated) for the monthly time scale in 28,279 HRUs (53.35%) compared to the annual time scale in 41,655 HRUs (78.58%). The geographic distribution of HRUs with highly correlated monthly values show areas where surface‐depression storage features are known to be common (e.g., Prairie Pothole Region, Florida).     

Mitigating Impact of Devils Lake Flooding on the Sheyenne River Sulfate Concentration

Devils Lake is a terminal lake located in northeast North Dakota. Because of its glacial origin and accumulated salts from evaporation, the lake has a high concentration of sulfate compared to the surrounding water bodies. From 1993 to 2011, Devils Lake water levels rose by ~10 m, which flooded surrounding communities and increased the chance of an overspill to the Sheyenne River. To control the flooding, the State of North Dakota constructed two outlets to pump the lake water to the river. However, the pumped water has raised concerns about of water quality degradation and potential flooding risk of the Sheyenne River. To investigate these perceived impacts, a Soil and Water Assessment Tool (SWAT) model was developed for the Sheyenne River and it was linked to a coupled SWAT and CE‐QUAL‐W2 model that was developed for Devils Lake in a previous study. While the current outlet schedule has attempted to maintain the total river discharge within the confines of a two‐year flood (36 m³/s), our simulation from 2012 to 2018 revealed that the diversion increased the Sheyenne River sulfate concentration from an average of 125 to >750 mg/L. Furthermore, a conceptual optimization model was developed with a goal of better preserving the water quality of the Sheyenne River while effectively mitigating the flooding of Devils Lake. The optimal solution provides a “win–win” outlet management that maintains the efficiency of the outlets while reducing the Sheyenne River sulfate concentration to ≤600 mg/L.     

Low‐concentration hydrogen peroxide decontamination for Bacillus spore contamination in buildings

Remediation and recovery efforts after a release of Bacillus anthracis (anthrax) spores may be difficult and costly. In addition, response and recovery technologies may be focused on critical resources, leaving the small business or homeowner without remediation options. This study evaluates the efficacy of relatively low levels of hydrogen peroxide vapor (HPV) delivered from off‐the‐shelf equipment for the inactivation of Bacillus spores within an indoor environment. Decontamination evaluations were conducted in a house using both Bacillus atrophaeus var. globigii (Bg; as surrogates for B. anthracis) inoculated on the carpet and galvanized metal as coupons and Geobacillus stearothermophilus (Gs) as biological indicators on steel. The total decontamination time ranged from 4 to 7 days. Using the longer exposure times, low concentrations of HPV (average levels below 20 parts per million) effectively inactivated Bg and Gs spores on the materials tested. The HPV was generated with commercial humidifiers and household‐strength hydrogen peroxide solutions. The presence of home furnishings did not have a significant impact on HPV efficacy. This simple, inexpensive, and effective decontamination method could have significant utility for remediation following a B. anthracis spore release, such as following a terrorist attack.     

Dynamics of local governance in natural resource conservation in the Okavango Delta,Botswana

There has been a shift in natural resource management worldwide. This paper describes how modern institutions and policies influence management and shape access to and utilization of resources by rural communities in the Okavango Delta, Botswana. It is rooted in the framework of adaptive co‐governance within social‐ecological systems, and employs a critical literature review to analyse access to and use of natural resources in rural Botswana. Prior to the establishment of community‐based natural resource management (CBNRM) in Botswana in 1989, resource governance was dominated by strong traditional institutions that were responsible for natural resource management and decision‐making. Contemporary natural resource governance is characterized by a bureaucratic system that invariably undermines the role of traditional institutions in natural resource governance. Findings indicate that policies and regulatory instruments deny rural communities adequate access to and utilization of resources available within their immediate environment. In spite of an orientation towards an anthropocentric approach to natural resource management (as in the case of CBNRM), the current governance system continues to undermine the inclusion of local resource users as legitimate stakeholders in the decision‐making process.     

Irrigation Water Allocation Using an Inexact Two‐Stage Quadratic Programming with Fuzzy Input under Climate Change

Agricultural irrigation accounts for nearly 70% of the total water use around the world. Uncertainties and climate change together exacerbate the complexity of optimal allocation of water resources for irrigation. An interval‐fuzzy two‐stage stochastic quadratic programming model is developed for determining the plans for water allocation for irrigation with maximum benefits. The model is shown to be applicable when inputs are expressed as discrete, fuzzy or random. In order to reflect the effect of marginal utility on benefit and cost, the model can also deal with nonlinearities in the objective function. Results from applying the model to a case study in the middle reaches of the Heihe River basin, China, show schemes for water allocation for irrigation of different crops in every month of the crop growth period under various flow levels are effective for achieving high economic benefits. Different climate change scenarios are used to analyze the impact of changing water requirement and water availability on irrigation water allocation. The proposed model can aid the decision maker in formulating desired irrigation water management policies in the wake of uncertainties and changing environment.     

Water Management Decision Making in the Face of Multiple Forms of Uncertainty and Risk

In the Wasatch Range Metropolitan Area of Northern Utah, water management decision makers confront multiple forms of uncertainty and risk. Adapting to these uncertainties and risks is critical for maintaining the long‐term sustainability of the region's water supply. This study draws on interview data to assess the major challenges climatic and social changes pose to Utah's water future, as well as potential solutions. The study identifies the water management adaptation decision‐making space shaped by the interacting institutional, social, economic, political, and biophysical processes that enable and constrain sustainable water management. The study finds water managers and other water actors see challenges related to reallocating water, including equitable water transfers and stakeholder cooperation, addressing population growth, and locating additional water supplies, as more problematic than the challenges posed by climate change. Furthermore, there is significant disagreement between water actors over how to best adapt to both climatic and social changes. This study concludes with a discussion of the path dependencies that present challenges to adaptive water management decision making, as well as opportunities for the pursuit of a new water management paradigm based on soft‐path solutions. Such knowledge is useful for understanding the institutional and social adaptations needed for water management to successfully address future uncertainties and risks.     

Sensitivity and Uncertainty of Ground‐Water Discharge Estimates for Semiarid Shrublands1

Abstract: We proposed a step‐by‐step approach to quantify the sensitivity of ground‐water discharge by evapotranspiration (ET) to three categories of independent input variables. To illustrate the approach, we adopt a basic ground‐water discharge estimation model, in which the volume of ground water lost to ET was computed as the product of the ground‐water discharge rate and the associated area. The ground‐water discharge rate was assumed to equal the ET rate minus local precipitation. The objective of this study is to outline a step‐by‐step procedure to quantify the contributions from individual independent variable uncertainties to the uncertainty of total ground‐water discharge estimates; the independent variables include ET rates of individual ET units, areas associated with the ET units, and precipitation in each subbasin. The specific goal is to guide future characterization efforts by better targeting data collection for those variables most responsible for uncertainty in ground‐water discharge estimates. The influential independent variables to be included in the sensitivity analysis are first selected based on the physical characteristics and model structure. Both regression coefficients and standardized regression coefficients for the selected independent variables are calculated using the results from sampling‐based Monte Carlo simulations. Results illustrate that, while as many as 630 independent variables potentially contribute to the calculation of the total annual ground‐water discharge for the case study area, a selection of seven independent variables could be used to develop an accurate regression model, accounting for more than 96% of the total variance in ground‐water discharge. Results indicate that the variability of ET rate for moderately dense desert shrubland contributes to about 75% of the variance in the total ground‐water discharge estimates. These results point to a need to better quantify ET rates for moderately dense shrubland to reduce overall uncertainty in estimates of ground‐water discharge. While the approach proposed here uses a basic ground‐water discharge model taken from an earlier study, the procedure of quantifying uncertainty and sensitivity can be generalized to handle other types of environmental models involving large numbers of independent variables.     

Modeling Postfire Response and Recovery using the Hydrologic Engineering Center Hydrologic Modeling System (HEC‐HMS)1

Abstract: This paper investigates application of the Army Corps of Engineers’ Hydrologic Engineering Center Hydrologic Modeling System (HEC‐HMS) to a burned watershed in San Bernardino County, California. We evaluate the HEC‐HMS’ ability to simulate discharge in prefire and postfire conditions in a semi arid watershed and the necessary parameterizations for modeling hydrologic response during the immediate, and subsequent recovery, period after a wildfire. The model is applied to City Creek watershed, which was 90% burned during the Old Fire of October 2003. An optimal spatial resolution for the HEC‐HMS model was chosen based on an initial sensitivity analysis of subbasin configurations and related model performance. Five prefire storms were calibrated for the selected model resolution, defining a set of parameters that reasonably simulate prefire conditions. Six postfire storms, two from each of the following rainy (winter) seasons were then selected to simulate postfire response and evaluate relative changes in parameter values and model behavior. There were clear trends in the postfire parameters [initial abstractions (I_a), curve number (CN), and lag time] that reveal significant (and expected) changes in watershed behavior. CN returns to prefire (baseline) values by the end of Year 2, while I_a approaches baseline by the end of the third rainy season. However, lag time remains significantly lower than prefire values throughout the three‐year study period. Our results indicate that recovery of soil conditions and related runoff response is not entirely evidenced by the end of the study period (three rainy seasons postfire). Understanding the evolution of the land surface and related hydrologic properties during the highly dynamic postfire period, and accounting for these changes in model parameterizations, will allow for more accurate and reliable discharge simulations in both the immediate, and subsequent, rainy seasons following fire.