Catchment planning tool

Catchment managers need to prioritize areas for conservation and restoration because they have limited resources and compete with other land uses (Margules and Pressey, 2000). The Catchment Planning Tool (CPT) arose from the growing need by natural resource managers to identify and prioritize areas for conservation and restoration activities at the catchment scale (Marsh et al., 2007). The problem faced by efforts to develop environmental software is how to create a program that addresses all the needs of different audiences. Generally, attempts are made to develop a stand-alone tool that has every conceivable functionality. However, a more pragmatic approach is to develop a generic program that can accommodate the various issues faced by different catchment managers. Our solution was to develop the CPT (Figure 1), a Geographic Information System (GIS) program that utilizes The Invisible Modelling Environment (TIME) code base (Rahman et al., 2003) to display and interrogate spatial data. A plug-in system was built into the design of the CPT to allow it to communicate with any models that provide some prerequisite identification details. In the CPT, a plug-in is a program that provides extra functionality to the CPT, or that can access the CPT's functionality via the CPT's plug-in application programming interface (API). The CPT was designed to be able to use a combination of plug-ins to assess in-stream biological and environmental attributes and to predict the effects of environmental and management changes on rivers at a catchment scale. This ability of the CPT to easily plug-in programs makes it easy to extend the functionality of the CPT, giving it the flexibility required to address the different challenges that face a wide range of catchment managers. The basic CPT configuration includes the core CPT application, that displays GIS data and hosts plug-ins, a plug-in manager to organize other plug-ins, and a GIS Toolbox plug-in. The GIS Toolbox plug-in provides a collection of GIS functionality that can be used for both terrestrial and riverine applications. Catchment delineation from digital elevation models (DEM) and the routing of river properties (e.g. taxa composition and stream constituents) through a river system are examples of the functionality that is specific for river studies. TIME code implemented based on Prosser et al. (2001) was used to provide the catchment delineation functionality. The delineation of catchments enables the creation of a river network composed of nodes and links. By knowing the from-node and the to-node of a link, properties of streams can be routed up and down the network. For specific environmental problems, further plug-ins can be added to the basic CPT configuration to extend its functionality. MARXAN is a software program that is used for optimizing reserve design (Ball and Possingham, 2000; Possingham et al., 2000). A MARXAN plug-in was developed for the CPT. This paper demonstrates some of the functionality available within the basic CPT configuration and uses the MARXAN plug-in as an example of how the basic CPT functionality can be extended. The example shows how resource managers could employ the CPT plug-in architecture to seamlessly combine various models (MARXAN in this instance) and GIS functionality under one computer program. Figure 1. The Catchment Planning Tool (CPT) is a GIS interface for displaying and analyzing spatial data. Its functionality can be extended by adding plug-ins that are organized under the Plugins menu. (Figure Presented)

Local stream habitat variables predicted from catchment scale characteristics are useful for predicting fish distribution

South-east Queensland (Australia) streams were described by 21 local habitat variables that were chosen because of their potential association with fish distribution. An Assessment by a Nearest Neighbour Analysis (ANNA) model used large-scale variables that are robust to human influence to predict what the values of each of the 21 local habitat variables at each site would be without modification from human activity. The ANNA model used elevation, stream order, distance from source and longitude to predict the local habitat variables; other candidate predictor variables (mean rainfall, latitude and catchment area) were not found to be useful. The ANNA model was able to predict five of the 21 local habitat variables (average width, sand (%), cobble (%), rocks (%) and large woody debris) with an R2 of at least 0.2. The observed values of these five local habitat variables were used to model the distributions of individual fish species. The species distribution models were developed using logistic regression based on a subset of the data (some of the data were withheld for model validation) and a forward stepwise model selection procedure. There was no difference in predictive performance of fish distribution models for model predictions based on observed values and model predictions based on ANNA predicted values of local habitat variables in the withheld data (p-value = 0.85). Therefore, it is possible to predict the suitability of sites as habitat for given fish species using estimated (estimates based on large-scale variables) natural values of local habitat variables.No Full Tex

Overview: the 15th Jkuat Scientific, Technological and Industrialization Conference

The conference provided a forum through which the university showcases ongoing contributions it is making to the society; created a forum for constantly improving the University’s approach to development-oriented scientific research, as it strives to remain a leader in this area; provided a forum for research peers from local and international institutions to discuss, share and publish vital information; provided an opportunity for the industrial/business sectors and policymakers to interact with researchers, so as to get new ideas and products for infusion into the production system and research and provoked policy makers to appreciate the need for substantial and long-term investments in scientific research, innovation and industrialization

Identifying priority sites for the conservation of freshwater fish biodiversity in a Mediterranean basin with a high degree of threatened endemics

The Guadiana River basin’s freshwater fish species richness, endemicity and threatened status (92% of native species are threatened) highlight the need for a large-scale study to identify priority areas for their conservation. One of the most common problems in conservation planning is the assessment of a site’s relative value for the conservation of regional biodiversity. Here we used a two-tiered approach, which integrates an assessment of biodiversity loss and the evaluation of conservation value through site-specific measures. These measures based on the reference condition approach introduce the ability to make objective comparisons throughout the Guadiana River basin, thus avoiding a priori target areas. We identified a set of biodiversity priority areas of special conservation significance—which contain rare taxa as well as intact fish communities—because of their outstanding contribution to the basin’s biodiversity. The inclusion of complete sub-basins in these priority areas might guarantee an optimal solution in terms of spatial aggregation and connectivity. However, the high spatial fragmentation to which the Guadiana River basin is submitted due to river regulation highlights the necessity of a systematic approach to evaluate the capability of the identified priority areas to maintain the Guadiana’s freshwater fish biodiversity