Experimental analysis of the influence of pest management practice on the efficacy of an endemic arthropod natural enemy complex of the diamondback moth.

Maximizing the contribution of endemic natural enemies to integrated pest management (IPM) programs requires a detailed knowledge of their interactions with the target pest. This experimental field study evaluated the impact of the endemic natural enemy complex of Plutella xylostella (L.) (Lepidoptera: Yponomeutidae) on pest populations in commercial cabbage crops in southeastern Queensland, Australia. Management data were used to score pest management practices at experimental sites on independent Brassica farms practicing a range of pest management strategies, and mechanical methods of natural enemy exclusion were used to assess the impact of natural enemies on introduced cohorts of P. xylostella at each site. Natural enemy impact was greatest at sites adopting IPM and least at sites practicing conventional pest management strategies. At IPM sites, the contribution of natural enemies to P. xylostella mortality permitted the cultivation of marketable crops with no yield loss but with a substantial reduction in insecticide inputs. Three species of larval parasitoids (Diadegma semiclausum Hellen [Hymenoptera: Ichneumonidae], Apanteles ippeus Nixon [Hymenoptera: Braconidae], and Oomyzus sokolowskii Kurdjumov [Hymenoptera: Eulophidae]) and one species of pupal parasitoid Diadromus collaris Gravenhorst (Hymenoptera: Ichneumonidae) attacked immature P. xylostella. The most abundant groups of predatory arthropods caught in pitfall traps were Araneae (Lycosidae) > Coleoptera (Carabidae, Coccinelidae, Staphylinidae) > Neuroptera (Chrysopidae) > Formicidae, whereas on crop foliage Araneae (Clubionidae, Oxyopidae) > Coleoptera (Coccinelidae) > Neuroptera (Chrysopidae) were most common. The abundance and diversity of natural enemies was greatest at sites that adopted IPM, correlating greater P. xylostella mortality at these sites. The efficacy of the natural enemy complex to pest mortality under different pest management regimes and appropriate strategies to optimize this important natural resource are discussed.

Simulation modelling applied to runoff modelling using mapscript

Dynamic spatial analysis addresses computational aspects of space–time processing. This paper describes the development of a spatial analysis tool and modelling framework that together offer a solution for simulating landscape processes. A better approach to integrating landscape spatial analysis with Geographical Information Systems is advocated in this paper. Enhancements include special spatial operators and map algebra language constructs to handle dispersal and advective flows over landscape surfaces. These functional components to landscape modelling are developed in a modular way and are linked together in a modelling framework that performs dynamic simulation. The concepts and modelling framework are demonstrated using a hydrological modelling example. The approach provides a modelling environment for scientists and land resource managers to write and to visualize spatial process models with ease.

SimuMap: a computational system for spatial modelling

The paper presents a computational system based upon formal principles to run spatial models for environmental processes. The simulator is named SimuMap because it is typically used to simulate spatial processes over a mapped representation of terrain. A model is formally represented in SimuMap as a set of coupled sub-models. The paper considers the situation where spatial processes operate at different time levels, but are still integrated. An example of such a situation commonly occurs in watershed hydrology where overland flow and stream channel flow have very different flow rates but are highly related as they are subject to the same terrain runoff processes. SimuMap is able to run a network of sub-models that express different time-space derivatives for water flow processes. Sub-models may be coded generically with a map algebra programming language that uses a surface data model. To address the problem of differing time levels in simulation, the paper: (i) reviews general approaches for numerical solvers, (ii) considers the constraints that need to be enforced to use more adaptive time steps in discrete time specified simulations, and (iii) scaling transfer rates in equations that use different time bases for time-space derivatives. A multistep scheme is proposed for SimuMap. This is presented along with a description of its visual programming interface, its modelling formalisms and future plans. (C) 2003 Elsevier Ltd. All rights reserved.

Habitat use by Darling Downs population of the grassland earless dragon: implications for conservation.

A population of the grassland earless dragon (Tympanocryptis pinguicolla) on the Darling Downs, Queensland, Australia, had been considered extinct until its recent rediscovery. We determined factors affecting grassland earless dragon abundance and prey availability in 3 habitats. Mean dragon body condition and prey numbers were higher in sorghum than grasslands and grass verges. Poisson regression analyses indicated that the dragon numbers were 10 times higher in sorghum, and that this may result from differences in prey numbers as well as other habitat conditions. Tracking data indicated selection of open versus closed microhabitat. Sorghum planted in rows provided alternating open and closed microhabitats for optimal thermoregulation conditions. Grasslands and grass verges were more uniformly shaded. Of individuals we tracked in the sorghum stubble, 85.7% used litter as overnight refuges. Litter was abundant in sorghum and sparse in grass habitats. The practices of minimum tillage and resting stubble strips possibly mitigate agricultural impacts on dragons and provide continuous access to suitable habitat. Changes in agricultural practices that affect the habitat suitability will potentially have detrimental impacts on the population. Our data suggest that conservation efforts be focused on maintaining suitability of habitats in crop fields. We recommend monitoring dragon abundance at control and trial sites of any new agricultural practices; this will provide opportunity to modify or stop undesirable practices before adoption by farmers. Conservation agencies may use our data as a baseline for monitoring long-term viability of the population.

Work plan for analytical support of an integrated ecosystem assessment of the California Current Large Marine Ecosystem, FY11 ‐ FY13

NOAA/NCCOS is conducting the following work for the NOAA California Current Integrated Ecosystem Assessment, in support of the NOAA/NMFS Northwest Fisheries Science Center.

Transitioning to routine breast cancer risk assessment and management in primary care: what can we learn from cardiovascular disease?

To capitalise on advances in breast cancer prevention, all women would need to have their breast cancer risk formally assessed. With ~85% of Australians attending primary care clinics at least once a year, primary care is an opportune location for formal breast cancer risk assessment and management. This study assessed the current practice and needs of primary care clinicians regarding assessment and management of breast cancer risk. Two facilitated focus group discussions were held with 17 primary care clinicians (12 GPs and 5 practice nurses (PNs)) as part of a larger needs assessment. Primary care clinicians viewed assessment and management of cardiovascular risk as an intrinsic, expected part of their role, often triggered by practice software prompts and facilitated by use of an online tool. Conversely, assessment of breast cancer risk was not routine and was generally patient- (not clinician-) initiated, and risk management (apart from routine screening) was considered outside the primary care domain. Clinicians suggested that routine assessment and management of breast cancer risk might be achieved if it were widely endorsed as within the remit of primary care and supported by an online risk-assessment and decision aid tool that was integrated into primary care software. This study identified several key issues that would need to be addressed to facilitate the transition to routine assessment and management of breast cancer risk in primary care, based largely on the model used for cardiovascular disease.

Remotely sensed data for ecosystem analyses: Combining hierarchy and scene models

Remotely sensed data have been used extensively for environmental monitoring and modeling at a number of spatial scales; however, a limited range of satellite imaging systems often. constrained the scales of these analyses. A wider variety of data sets is now available, allowing image data to be selected to match the scale of environmental structure(s) or process(es) being examined. A framework is presented for use by environmental scientists and managers, enabling their spatial data collection needs to be linked to a suitable form of remotely sensed data. A six-step approach is used, combining image spatial analysis and scaling tools, within the context of hierarchy theory. The main steps involved are: (1) identification of information requirements for the monitoring or management problem; (2) development of ideal image dimensions (scene model), (3) exploratory analysis of existing remotely sensed data using scaling techniques, (4) selection and evaluation of suitable remotely sensed data based on the scene model, (5) selection of suitable spatial analytic techniques to meet information requirements, and (6) cost-benefit analysis. Results from a case study show that the framework provided an objective mechanism to identify relevant aspects of the monitoring problem and environmental characteristics for selecting remotely sensed data and analysis techniques.

Assessment of relationships between precipitation and satellite derived vegetation condition in South Australia

The normalised difference vegetation index (NDVI) has evolved as a primary tool for monitoring continental-scale vegetation changes and interpreting the impact of short to long-term climatic events on the biosphere. The objective of this research was to assess the nature of relationships between precipitation and vegetation condition, as measured by the satellite-derived NDVI within South Australia. The correlation, timing and magnitude of the NDVI response to precipitation were examined for different vegetation formations within the State (forest, scrubland, shrubland, woodland and grassland). Results from this study indicate that there are strong relationships between precipitation and NDVI both spatially and temporally within South Australia. Differences in the timing of the NDVI response to precipitation were evident among the five vegetation formations. The most significant relationship between rainfall and NDVI was within the forest formation. Negative correlations between NDVI and precipitation events indicated that vegetation green-up is a result of seasonal patterns in precipitation. Spatial patterns in the average NDVI over the study period closely resembled the boundaries of the five classified vegetation formations within South Australia. Spatial variability within the NDVI data set over the study period differed greatly between and within the vegetation formations examined depending on the location within the state. ACRONYMS AVHRR Advanced Very High Resolution Radiometer ENVSAEnvironments of South Australia EOS Terra-Earth Observing System EVIEnhanced Vegetation Index MODIS Moderate Resolution Imaging Spectro-radiometer MVC Maximum Value Composite NDVINormalised Difference Vegetation Index NIRNear Infra-Red NOAANational Oceanic and Atmospheric Administration SPOT Systeme Pour l’Observation de la Terre. [ABSTRACT FROM AUTHOR]