Can Volunteers Collect Data that are Comparable to Professional Scientists? A Study of Variables Used in Monitoring the Outcomes of Ecosystem Rehabilitation

Having volunteers collect data can be a cost-effective strategy to complement or replace those collected by scientists. The quality of these data is essential where field-collected data are used to monitor progress against predetermined standards because they provide decision makers with confidence that choices they make will not cause more harm than good. The integrity of volunteer-collected data is often doubted. In this study, we made estimates of seven vegetation attributes and a composite measure of six of those seven, to simulate benchmark values. These attributes are routinely recorded as part of rehabilitation projects in Australia and elsewhere in the world. The degree of agreement in data collected by volunteers was compared with those recorded by professional scientists. Combined results showed that scientists collected data that was in closer agreement with benchmarks than those of volunteers, but when data collected by individuals were analyzed, some volunteers collected data that were in similar or closer agreement, than scientists. Both groups’ estimates were in closer agreement for particular attributes than others, suggesting that some attributes are more difficult to estimate than others, or that some are more subjective than others. There are a number of ways in which higher degrees of agreement could be achieved and introducing these will no doubt result in better, more effective programs, to monitor rehabilitation activities. Alternatively, less subjective measures should be sought when developing monitoring protocols. Quality assurance should be part of developing monitoring methods and explicitly budgeted for in project planning to prevent misleading declarations of rehabilitation success.     

Understanding farmer intentions to connect to a modernised delivery system in an Australian irrigation district: a reasoned action approach

Australian governments have sought to invest in irrigation infrastructure to improve the efficiency of water delivery to rural properties and improve water supply and on-farm efficiency. A programme of rationalising irrigation infrastructure has attracted criticism and doubts about its likely success. Attitude theory in the form of the Reasoned Action Model was applied to understand the intentions of landowners to connect to a ‘modernised’ irrigation system. Attitudes towards connecting to the system, social norms and perceptions of control over the behaviour provided an explanation of intentions to connect. Actual financial capability and other variables were important in discriminating a group of landowners who had already connected to the modernised system from farmers who had not.     

System Dynamics to Sustainable Water Resources Management in the Eastern Snake Plain Aquifer Under Water Supply Uncertainty1

Abstract: Water supply uncertainty continues to threaten the reliability of regional water resources in the western United States. Climate variability and water dispute potentials induce water managers to develop proactive adaptive management strategies to mitigate future hydroclimate impacts. The Eastern Snake Plain Aquifer in the state of Idaho is also facing these challenges in the sense that population growth and economic development strongly depend on reliable water resources from underground storage. Drought and subsequent water conflict often drive scientific research and political agendas because water resources availability and aquifer management for a sustainable rural economy are of great interest. In this study, a system dynamics approach is applied to address dynamically complex problems with management of the aquifer and associated surface‐water and groundwater interactions. Recharge and discharge dynamics within the aquifer system are coded in an environmental modeling framework to identify long‐term behavior of aquifer responses to uncertain future hydrological variability. The research shows that the system dynamics approach is a promising modeling tool to develop sustainable water resources planning and management in a collaborative decision‐making framework and also to provide useful insights and alternative opportunities for operational management, policy support, and participatory strategic planning to mitigate future hydroclimate impacts in human dimensions.     

A Conceptual Framework for Selecting and Analyzing Stressor Data to Study Species Richness at Large Spatial Scales

/ In this paper we develop a conceptual framework for selectingstressor data and analyzing their relationship to geographic patterns ofspecies richness at large spatial scales. Aspects of climate and topography,which are not stressors per se, have been most strongly linked withgeographic patterns of species richness at large spatial scales (e.g.,continental to global scales). The adverse impact of stressors (e.g., habitatloss, pollution) on species has been demonstrated primarily on much smallerspatial scales. To date, there has been a lack of conceptual developmenton how to use stressor data to study geographic patterns of speciesrichness at large spatial scales.The framework we developed includes four components: (1) clarification of theterms stress and stressor and categorization of factors affecting speciesrichness into three groups-anthropogenic stressors, natural stressors, andnatural covariates; (2) synthesis of the existing hypotheses for explaininggeographic patterns of species richness to identify the scales over whichstressors and natural covariates influence species richness and to providesupporting evidence for these relationships through review of previousstudies; (3) identification of three criteria for selection of stressor andcovariate data sets: (a) inclusion of data sets from each of the threecategories identified in item 1, (b) inclusion of data sets representingdifferent aspects of each category, and (c) to the extent possible, analysisof data quality; and (4) identification of two approaches for examiningscale-dependent relationships among stressors, covariates, and patterns ofspecies richness-scaling-up and regression-tree analyses.Based on this framework, we propose 10 data sets as a minimum data base forexamining the effects of stressors and covariates on species richness atlarge spatial scales. These data sets include land cover, roads, wetlands(numbers and loss), exotic species, livestock grazing, surface water pH,pesticide application, climate (and weather), topography, and streams.KEY WORDS: Anthropogenic impacts; Biodiversity; Environmental gradients;Geographic information systems; Hierarchy     

Denitrification Distributions in Four Valley and Ridge Riparian Ecosystems

/ Denitrification in riparian ecosystems can reduce the amount ofnitrogen transported from farm fields to streams. In this study, we examinedenitrification in four riparian ecosystems common to the Valley and Ridgephysiographic province in Pennsylvania, USA. The sites exhibit differentvegetation, are underlain by different rock types, and are downgradient offarm fields. Mean site denitrification rates ranging from 0.6 to 1.9 &mgr;gN/kg soil/day were measured using intact core incubation techniques. Thethree riparian sites covered with grass each exhibited greaterdenitrification rates than the wooded site. Denitrification rate wascorrelated with moisture content but not with nitrate-N or organic carboncontents. Denitrification rates were greatest near the soil surface and atpositions nearest the stream. Rates decreased uniformly with distance awayfrom the stream and also with depth in the soil for each site. While patternsof nitrate-N, moisture, and organic carbon content differ among the sites,their combined effects on denitrification support the observed, consistentdenitrification rate pattern.KEY WORDS: Denitrification; Riparian ecosystems