INTEGRATING SOCIO‐ECONOMIC AND BIOPHYSICAL DATA TO UNDERPIN COLLABORATIVE WATERSHED MANAGEMENT1

ABSTRACT: Watersheds are widely accepted as a useful geography for organizing natural resource management in Australia and the United States. It is assumed that effective action needs to be underpinned by an understanding of the interactions between people and the environment. While there has been some social research as part of watershed planning, there have been few attempts to integrate socio‐economic and biophysical data to improve the efficacy of watershed management. This paper explores that topic. With limited resources for social research, watershed partners in Australia chose to focus on gathering spatially referenced socio‐economic data using a mail survey to private landholders that would enable them to identify and refine priority issues, develop and improve communication with private landholders, choose policy options to accomplish watershed targets, and evaluate the achievement of intermediate watershed plan objectives. Experience with seven large watershed projects provides considerable insight about the needs of watershed planners, how to effectively engage them, and how to collect and integrate social data as part of watershed management.     

Nipped in the Bud: Why Regional Scale Adaptive Management Is Not Blooming

Adaptive management is an approach to managing natural resources that emphasizes learning from the implementation of policies and strategies. Adaptive management appears to offer a solution to the management gridlock caused by increasing complexity and uncertainty. The concept of adaptive management has been embraced by natural resource managers worldwide, but there are relatively few published examples of adaptive management in use. In this article, we explore two watershed management projects in southeastern Australia to better understand the potential of adaptive management in regional scale programs through qualitative, case study–based investigation. The program logic of one case implies the use of passive adaptive management, whereas the second case claims to be based on active adaptive management. Data were created using participant observation, semistructured interviews with individuals and groups, and document review. Using thematic content and metaphor analysis to explore the case data, we found that each case was successful as an implementation project. However, the use of both passive and active adaptive management was constrained by deeply entrenched social norms and institutional frameworks. We identified seven “imperatives” that guided the behavior of project stakeholders, and that have consequences for the use of adaptive management. Reference to recent evaluations of the Adaptive Management Areas of the Pacific Northwest of the United States suggests that some of these imperatives and their consequences have broad applicability. The implications of our findings are discussed, and suggestions for improving the outcomes of regional scale adaptive management are provided.     

A Landscape Ecology Assessment of the Tensas River Basin

A group of landscape ecological indicators were applied to biophysical data masked to the Tensas River Basin. The indicators were used to identify and prioritize sources of nutrients in a Mississippi/Atchafalaya River System sub-basin. Remotely sensed data were used for change detection assessment. With these methods, we were able to look at land use practices over the past twenty years in the Tensas River Basin of Louisiana. A simple land use classification was applied to multispectral scanner (MSS) data from 1972 and 1991. The landscape analysis methods described in this paper will show how to use these methods to assess the impact of human land use practices that are being implemented to improve environmental quality. Landscape assessment methods can be used as a simple, timely, cost effective approach for monitoring, targeting, and modeling ecosystem health in watersheds. Although this study was conducted in the southeast, the methods described in this paper may be applicable to western landscapes.     

Modeling Runoff Response to Land Cover and Rainfall Spatial Variability in Semi-Arid Watersheds

Hydrologic response is an integrated indicator of watershed condition, and significant changes in land cover may affect the overall health and function of a watershed. This paper describes a procedure for evaluating the effects of land cover change and rainfall spatial variability on watershed response. Two hydrologic models were applied on a small semi-arid watershed; one model is event-based with a one-minute time step (KINEROS), and the second is a continuous model with a daily time step (SWAT). The inputs to the models were derived from Geographic Information System (GIS) theme layers of USGS digital elevation models, the State Soil Geographic Database (STATSGO) and the Landsat-based North American Landscape Characterization classification (NALC) in conjunction with available literature and look up tables. Rainfall data from a network of 10 raingauges and historical stream flow data were used to calibrate runoff depth using the continuous hydrologic model from 1966 to 1974. No calibration was carried out for the event-based model, in which six storms from the same period were used in the calculation of runoff depth and peak runoff. The assumption on which much of this study is based is that land cover change and rainfall spatial variability affect the rainfall-runoff relationships on the watershed. To validate this assumption, simulations were carried out wherein the entire watershed was transformed from the 1972 NALC land cover, which consisted of a mixture of desertscrub and grassland, to a single uniform land cover type such as riparian, forest, oak woodland, mesquite woodland, desertscrub, grassland, urban, agriculture, and barren. This study demonstrates the feasibility of using widely available data sets for parameterizing hydrologic simulation models. The simulation results show that both models were able to characterize the runoff response of the watershed due to changes of land cover.     

Geographic Analysis of Species Richness and Community Attributes of Forest Birds from Survey Data in the Mid-Atlantic Integrated Assessment Region

Species richness of local communities is a state variable commonly used in community ecology and conservation biology. Investigation of spatial and temporal variations in richness and identification of factors associated with these variations form a basis for specifying management plans, evaluating these plans, and for testing hypotheses of theoretical interest. However, estimation of species richness is not trivial: species can be missed by investigators during sampling sessions. Sampling artifacts can lead to erroneous conclusions on spatial and temporal variation in species richness. Here we use data from the North American Breeding Bird Survey to estimate parameters describing the state of bird communities in the Mid-Atlantic Assessment (MAIA) region: species richness, extinction probability, turnover and relative species richness. We use a recently developed approach to estimation of species richness and related parameters that does not require the assumption that all the species are detected during sampling efforts. The information presented here is intended to visualize the state of bird communities in the MAIA region. We provide information on 1975 and 1990. We also quantified the changes between these years. We summarized and mapped the community attributes at a scale of management interest (watershed units).     

Daily cycling of the crystalline style in the omnivorous,Deposit-feeding estuarine snail Ilyanassa obsoleta

Crystalline styles are present in nearly all bivalve mollusks, and are known to undergo cyclic changes in size and/or occurrence in many species. A few gastropod species are known to possess styles, but such cycles as may exist are unknown or not well documented. Results reported here show that Ilyanassa obsoleta (Say) in a sandflat population lose and regain their crystalline styles each day. Styles were consistently low in frequency just after dawn. The presence of this kind of rhythm in a deposit-feeding gastropod has not previously been noted. It is suggested that this cycle may have played a key role in the evolution of this widespread and numerically abundant species.     

A Multi‐Scale Soil Moisture Monitoring Strategy for California: Design and Validation

A multi‐scale soil moisture monitoring strategy for California was designed to inform water resource management. The proposed workflow classifies soil moisture response units (SMRUs) using publicly available datasets that represent soil, vegetation, climate, and hydrology variables, which control soil water storage. The SMRUs were classified, using principal component analysis and unsupervised K‐means clustering within a geographic information system, and validated, using summary statistics derived from measured soil moisture time series. Validation stations, located in the Sierra Nevada, include transect of sites that cross the rain‐to‐snow transition and a cluster of sites located at similar elevations in a snow‐dominated watershed. The SMRUs capture unique responses to varying climate conditions characterized by statistical measures of central tendency, dispersion, and extremes. A topographic position index and landform classification is the final step in the workflow to guide the optimal placement of soil moisture sensors at the local‐scale. The proposed workflow is highly flexible and can be implemented over a range of spatial scales and input datasets can be customized. Our approach captures a range of soil moisture responses to climate across California and can be used to design and optimize soil moisture monitoring strategies to support runoff forecasts for water supply management or to assess landscape conditions for forest and rangeland management.     

Subsurface application of manures slurries for conservation tillage and pasture soils and their impact on the nitrogen balance

Injection of cattle and swine slurries can provide soil incorporation in no-till and perennial forage production. Injection is expected to substantially reduce N loss due to ammonia (NH3) volatilization, but a portion of that N conservation may be offset by greater denitrification and leaching losses. This paper reviews our current knowledge of the impacts of subsurface application of cattle and swine slurries on the N balance and outlines areas where a greater understanding is needed. Several publications have shown that liquid manure injection using disk openers, chisels, or tines can be expected to Sreduce NH, emissions by at least 40%, and often by 90% or more, relative to broadcast application. However, the limited number of studies that have also measured denitrification losses have shown that increased denitrification with subsurface application can offset as much as half of the N conserved by reducing NH3 emissions. Because the greenhouse gas nitrous oxide (N2O) is one product of denitrification, the possible increases in N2O emission with injection require further consideration. Subsurface manure application generally does not appear to increase leaching potential when manure is applied at recommended rates. Plant utilization of conserved N was shown in only a portion of the published studies, indicating that further work is needed to better synchronize manure N availability and crop uptake. At this time in the United States, the economic and environmental benefits from reducing losses of N as NH3 are expected to outweigh potential liability from increases in denitrification with subsurface manure application. To fully evaluate the trade-offs among manure application methods, a detailed environmental and agricultural economic assessment is needed to estimate the true costs of potential increases in NO2O emissions with manure injection.     

A multiple additive regression tree analysis of three exposure measures during Hurricane Katrina

This paper analyses structural and personal exposure to Hurricane Katrina. Structural exposure is measured by flood height and building damage; personal exposure is measured by the locations of 911 calls made during the response. Using these variables, this paper characterises the geography of exposure and also demonstrates the utility of a robust analytical approach in understanding health‐related challenges to disadvantaged populations during recovery. Analysis is conducted using a contemporary statistical approach, a multiple additive regression tree (MART), which displays considerable improvement over traditional regression analysis. By using MART, the percentage of improvement in R‐squares over standard multiple linear regression ranges from about 62 to more than 100 per cent. The most revealing finding is the modelled verification that African Americans experienced disproportionate exposure in both structural and personal contexts. Given the impact of exposure to health outcomes, this finding has implications for understanding the long‐term health challenges facing this population.