Shifting elasmobranch community assemblage at Cocos Island—an isolated marine protected area

Fishing pressure has increased the extinction risk of many elasmobranch (shark and ray) species. Although many countries have established no‐take marine reserves, a paucity of monitoring data means it is still unclear if reserves are effectively protecting these species. We examined data collected by a small group of divers over the past 21 years at one of the world's oldest marine protected areas (MPAs), Cocos Island National Park, Costa Rica. We used mixed effects models to determine trends in relative abundance, or probability of occurrence, of 12 monitored elasmobranch species while accounting for variation among observers and from abiotic factors. Eight of 12 species declined significantly over the past 2 decades. We documented decreases in relative abundance for 6 species, including the iconic scalloped hammerhead shark (Sphyrna lewini) (?45%), whitetip reef shark (Triaenodon obesus) (?77%), mobula ray (Mobula spp.) (?78%), and manta ray (Manta birostris) (?89%), and decreases in the probability of occurrence for 2 other species. Several of these species have small home ranges and should be better protected by an MPA, which underscores the notion that declines of marine megafauna will continue unabated in MPAs unless there is adequate enforcement effort to control fishing. In addition, probability of occurrence at Cocos Island of tiger (Galeocerdo cuvier), Galapagos (Carcharhinus galapagensis), blacktip (Carcharhinus limbatus), and whale (Rhincodon typus) sharks increased significantly. The effectiveness of MPAs cannot be evaluated by examining single species because population responses can vary depending on life history traits and vulnerability to fishing pressure.     

Design and risk assessment tool for vegetative treatment areas receiving agricultural wastewater: Preliminary results

Vegetative treatment areas (VTAs) are commonly being used as an alternative method of agricultural process wastewater treatment. However, it is also apparent that to completely prevent discharge of pollutants to the surrounding environment, settling of particulates and bound constituents from overland flow through VTAs is not sufficient. For effective remediation of dissolved agricultural pollutants, VTAs must infiltrate incoming wastewater. A simple water balance model for predicting VTA soil saturation and surface discharge in landscapes characterized by sloping terrain and a shallow restrictive layer is presented and discussed. The model accounts for the cumulative effect of successive rainfall events and wastewater input on soil moisture status and depth to water table. Nash–Sutcliffe efficiencies ranged from 0.65 to 0.81 for modeled and observed water table elevations after calibration of saturated hydraulic conductivity. Precipitation data from relatively low, average, and high annual rainfall years were used with soil, site, and contributing area data from an example VTA for simulations and comparisons. Model sensitivity to VTA width and contributing area (i.e. barnyard, feedlot, silage bunker, etc.) curve number was also investigated. Results of this analysis indicate that VTAs should be located on steeper slopes with deeper, more-permeable soils, which effectively lowers the shallow water table. In sloping landscapes (>2%), this model provides practitioners an easy-to-use VTA design and/or risk assessment tool that is more hydrological process-based than current methods.     

Incorporating Variable Source Area Hydrology into a Spatially Distributed Direct Runoff Model1

Buchanan, Brian, Zachary M. Easton, Rebecca Schneider, and M. Todd Walter, 2011. Incorporating Variable Source Area Hydrology Into a Spatially Distributed Direct Runoff Model. Journal of the American Water Resources Association (JAWRA) 48(1): 43‐60. DOI: 10.1111/j.1752‐1688.2011.00594.x Abstract: Few hydrologic models simulate both variable source area (VSA) hydrology, and runoff‐routing at high enough spatial resolutions to capture fine‐scale hydrologic pathways connecting VSA to the stream network. This paper describes a geographic information system‐based operational model that simulates the spatio‐temporal dynamics of VSA runoff generation and distributed runoff‐routing, including through complex artificial drainage networks. The model combines the Natural Resource Conservation Service’s Curve Number (CN) equation for estimating storm runoff with the topographic index concept for predicting the locations of VSA and a runoff‐routing algorithm into a new spatially distributed direct hydrograph (SDDH) model (SDDH‐VSA). Using a small agricultural watershed in central New York, SDDH‐VSA results were compared to those from a SDDH model using the traditional land use assumptions for the CN (SDDH‐CN). The SDDH‐VSA model generally agreed better with observed discharge than the SDDH‐CN model (average, Nash‐Sutcliffe efficiency of 0.69 vs. 0.58, respectively) and resulted in more realistic spatial patterns of runoff‐generating areas. The SDDH approach did not correctly capture the timing of runoff from small storms in dry periods. Despite this type of limitation, SDDH‐VSA extends the applicability of the SDDH technique to VSA conditions, providing a basis for new tools to help identify critical management areas and assess water quality risks due to landscape alterations.     

Rainfall Runoff Relationships for a Cloud Forest Watershed in Central America: Implications for Water Resource Engineering1

Caballero, Luis A., Alon Rimmer, Zachary M. Easton, and Tammo S. Steenhuis, 2012. Rainfall Runoff Relationships for a Cloud Forest Watershed in Central America: Implications for Water Resource Engineering. Journal of the American Water Resources Association (JAWRA) 48(5): 1022‐1031. DOI: 10.1111/j.1752‐1688.2012.00668.x Abstract: Understanding the basic relationships between rainfall and runoff is vital for effective management and utilization of scarce water resources. Especially, this is important in Central America with widespread potable water shortage during the dry months of the monsoon. Potential good water sources are cloud forests, but little information concerning its potential is available to water supply engineers. Our objective is to define rainfall‐runoff‐base flow relationships for a cloud forest catchment. Flumes were installed for measuring river flow in four subwatersheds in La Tigra National Park, Honduras. One of the four watersheds was a 636‐ha subwatershed (WS1) with 60% cloud forest coverage. Precipitation averaged 1,130 mm/yr over the entire basin. About half of the total rainfall became runoff for the cloud forest watershed whereas, for the adjacent undisturbed forested watershed, the total discharge was <20% of the amount of precipitation. Infiltration rates were generally greater than rainfall rates. Therefore, most rainfall infiltrated into the soil, especially in the upper, steep, and well‐drained portions of the watershed. Direct runoff was generated from saturated areas near the river and exposed bedrock. This research provides compelling evidence that base flow is the primary contributor to streamflow during both wet and dry seasons in cloud forest catchments. Protecting these flow processes over time is critical for the sustained provision of potable water.     

Modeling watershed-scale effectiveness of agricultural best management practices to reduce phosphorus loading

Planners advocate best management practices (BMPs) to reduce loss of sediment and nutrients in agricultural areas. However, the scientific community lacks tools that use readily available data to investigate the relationships between BMPs and their spatial locations and water quality. In rural, humid regions where runoff is associated with saturation-excess processes from variable source areas (VSAs), BMPs are potentially most effective when they are located in areas that produce the majority of the runoff. Thus, two critical elements necessary to predict the water quality impact of BMPs include correct identification of VSAs and accurate predictions of nutrient reduction due to particular BMPs. The objective of this research was to determine the effectiveness of BMPs using the Variable Source Loading Function (VSLF) model, which captures the spatial and temporal evolutions of VSAs in the landscape. Data from a long-term monitoring campaign on a 164-ha farm in the New York City source watersheds in the Catskills Mountains of New York state were used to evaluate the effectiveness of a range of BMPs. The data spanned an 11-year period over which a suite of BMPs, including a nutrient management plan, riparian buffers, filter strips and fencing, was installed to reduce phosphorus (P) loading. Despite its simplicity, VSLF predicted the spatial distribution of runoff producing areas well. Dissolved P reductions were simulated well by using calibrated reduction factors for various BMPs in the VSLF model. Total P losses decreased only after cattle crossings were installed in the creek. The results demonstrated that BMPs, when sited with respect to VSAs, reduce P loss from agricultural watersheds, providing useful information for targeted water quality management.     

Agricultural BMP Effectiveness and Dominant Hydrological Flow Paths: Concepts and a Review

We present a conceptual framework that relates agricultural best management practice (BMP) effectiveness with dominant hydrological flow paths to improve nonpoint source (NPS) pollution management. We use the framework to analyze plot, field and watershed scale published studies on BMP effectiveness to develop transferable recommendations for BMP selection and placement at the watershed scale. The framework is based on the location of the restrictive layer in the soil profile and distinguishes three hydrologic land types. Hydrologic land type A has the restrictive layer at the surface and BMPs that increase infiltration are effective. In land type B1, the surface soil has an infiltration rate greater than the prevailing precipitation intensity, but there is a shallow restrictive layer causing lateral flow and saturation excess overland flow. Few structural practices are effective for these land types, but pollutant source management plans can significantly reduce pollutant loading. Hydrologic land type B2 has deep, well‐draining soils without restrictive layers that transport pollutants to groundwater via percolation. Practices that increased pollutant residence time in the mixing layer or increased plant water uptake were found as the most effective BMPs in B2 land types. Matching BMPs to the appropriate land type allows for better targeting of hydrologically sensitive areas within a watershed, and potentially more significant reductions of NPS pollutant loading.     

Assessing BMP Effectiveness and Guiding BMP Planning Using Process‐Based Modeling

There is an increasing need for improved process‐based planning tools to assist watershed managers in the selection and placement of effective best management practices (BMPs). In this article, we present an approach, based on the Water Erosion Prediction Project model and a pesticide transport model, to identify dominant hydrologic flow paths and critical source areas for a variety of pollutant types. We use this approach to compare the relative impacts of BMPs on hydrology, erosion, sediment, and pollutant delivery within different landscapes. Specifically, we focus on using this approach to understand what factors promoted and/or hindered BMP effectiveness at three Conservation Effects Assessment Project watersheds: Paradise Creek Watershed in Idaho, Walnut Creek Watershed in Iowa, and Goodwater Creek Experimental Watershed in Missouri. These watersheds were first broken down into unique land types based on soil and topographic characteristics. We used the model to assess BMP effectiveness in each of these land types. This simple process‐based modeling approach provided valuable insights that are not generally available to planners when selecting and locating BMPs and helped explain fundamental reasons why long‐term improvement in water quality of these three watersheds has yet to be completely realized.     

Site-selection bias and apparent population declines in long-term studies

Detecting population declines is a critical task for conservation biology. Logistical difficulties and the spatiotemporal variability of populations make estimation of population declines difficult. For statistical reasons, estimates of population decline may be biased when study sites are chosen based on abundance of the focal species. In this situation, apparent population declines are likely to be detected even if there is no decline. This site-selection bias is mentioned in the literature but is not well known. We used simulations and real population data to examine the effects of site-selection biases on inferences about population trends. We used a left-censoring method to detect population-size patterns consistent with site-selection bias. The site-selection bias is an important consideration for conservation biologists, and we offer suggestions for minimizing or mitigating it in study design and analysis. Article impact statement: Estimates of population declines are biased if studies begin in large populations, and time-series data show a signature of such an effect.     

Streamflow Responses to Climate Change: Analysis of Hydrologic Indicators in a New York City Water Supply Watershed

Recent works have indicated that climate change in the northeastern United States is already being observed in the form of shorter winters, higher annual average air temperature, and more frequent extreme heat and precipitation events. These changes could have profound effects on aquatic ecosystems, and the implications of such changes are less understood. The objective of this study was to examine how future changes in precipitation and temperature translate into changes in streamflow using a physically based semidistributed model, and subsequently how changes in streamflow could potentially impact stream ecology. Streamflow parameters were examined in a New York City water supply watershed for changes from model‐simulated baseline conditions to future climate scenarios (2081‐2100) for ecologically relevant factors of streamflow using the Indicators of Hydrologic Alterations tool. Results indicate that earlier snowmelt and reduced snowpack advance the timing and increase the magnitude of discharge in the winter and early spring (November‐March) and greatly decrease monthly streamflow later in the spring in April. Both the rise and fall rates of the hydrograph will increase resulting in increased flashiness and flow reversals primarily due to increased pulses during winter seasons. These shifts in timing of peak flows, changes in seasonal flow regimes, and changes in the magnitudes of low flow can all influence aquatic organisms and have the potential to impact stream ecology.