Factors influencing biodiversity and distributional gradients in mangroves

Numerous factors affect the distribution of mangrove plants. Most mangrove species are typically dispersed by water-buoyant propagules, allowing them to lake advantage of estuarine, coastal and ocean currents both to replenish existing stands and to establish new ones. The direction they travel depends on sea currents and land barriers, but the dispersal distance depends on the time that propagules remain buoyant and viable. This is expected to differ for each species. Similarly, each species will also differ in establishment success and growth development rate, and each has tolerance limits and growth responses which are apparently unique. Such attributes are presumably responsible for the characteristic distributional ranges of each species, as each responds to the environmental, physical and biotic settings they might occupy. In practice, species are often ordered by the interplay of different factors along environmental gradients, and these may conveniently be considered at four geographic scales-global, regional, estuarine and intertidal. We believe these influencing factors act similarly around the world, and to demonstrate this point, we present examples of distributional gradients from the two global biogeographic regions, the Atlantic East Pacific and the Indo-West Pacific.

Remotely sensed estimates of vegetation structural characteristics in restored wetlands, Southern California

Traditional field sampling approaches for ecological studies of restored habitat can only cover small areas in detail, con be time consuming, and are often invasive and destructive. Spatially extensive and non-invasive remotely sensed data can make field sampling more focused and efficient. The objective of this work was to investigate the feasibility and accuracy of hand-held and airborne remotely sensed data to estimate vegetation structural parameters for an indicator plant species in a restored wetland. High spatial resolution, digital, multispectral camera images were captured from an aircraft over Sweetwater Marsh (San Diego County, California) during each growing season between 1992-1996. Field data were collected concurrently, which included plant heights, proportional ground cover and canopy architecture type, and spectral radiometer measurements. Spartina foliosa (Pacific cordgrass) is the indicator species for the restoration monitoring. A conceptual model summarizing the controls on the spectral reflectance properties of Pacific cordgrass was established. Empirical models were developed relating the stem length, density, and canopy architecture of cordgrass to normalized-difference-vegetation-index values. The most promising results were obtained from empirical estimates of total ground cover using image data that had been stratified into high, middle, and low marsh zones. As part of on-going restoration monitoring activities, this model is being used to provide maps of estimated vegetation cover.

Effects of data characteristics on the results of reserve selection algorithms

We tested the effects of four data characteristics on the results of reserve selection algorithms. The data characteristics were nestedness of features (land types in this case), rarity of features, size variation of sites (potential reserves) and size of data sets (numbers of sites and features). We manipulated data sets to produce three levels, with replication, of each of these data characteristics while holding the other three characteristics constant. We then used an optimizing algorithm and three heuristic algorithms to select sites to solve several reservation problems. We measured efficiency as the number or total area of selected sites, indicating the relative cost of a reserve system. Higher nestedness increased the efficiency of all algorithms (reduced the total cost of new reserves). Higher rarity reduced the efficiency of all algorithms (increased the total cost of new reserves). More variation in site size increased the efficiency of all algorithms expressed in terms of total area of selected sites. We measured the suboptimality of heuristic algorithms as the percentage increase of their results over optimal (minimum possible) results. Suboptimality is a measure of the reliability of heuristics as indicative costing analyses. Higher rarity reduced the suboptimality of heuristics (increased their reliability) and there is some evidence that more size variation did the same for the total area of selected sites. We discuss the implications of these results for the use of reserve selection algorithms as indicative and real-world planning tools.

Socio-economic, migrant and geographic differentials in coronary heart disease occurrence in New South Wales

Objective: This study examines the variation in coronary heart disease (CHD) mortality and acute myocardial infarction (AMI) by socio-economic status (SES), country of birth (COB) and geography (urban/rural) in the total population of New South Wales (Australia) in 1991-95. Method: CHD deaths and AMI are from complete enumerations of deaths and hospital admissions, respectively; and population denominators are from census information. Data are examined separately by sex, and comparisons of SES groups (based on municipalities), COB and region are analysed using Poisson regression, after adjustment for age. Results: The study identified higher risk for AMI admissions and CHD mortality in lower SES populations with significant linear trends, for both sexes, adjusted for age, region and COB. According to the population attributable fractions (PAF), 23-41% of the risk of CHD occurrence is due to SES lower than the highest quartile. The higher age-adjusted risk for CHD occurrence in rural and remote populations for both sexes, compared with urban communities, was lessened by adjustment for COB, and all but abolished when also adjusted for SES. COB analysis indicated significantly lower age-adjusted AMI admissions and CHD mortality compared with the Australian-born, Conclusions: Higher risks for CHD in rural populations compared with the capital city (Sydney) are due, in part, to lower SES, lesser migrant composition. Implications: Strategies for reducing CHD differentials should consider demographic factors and the fundamental need to reduce socio-economic inequalities, as well as targeting appropriate prevention measures.

A method of analysing stream channel response to environmental change: gauge data for the Tully River

Gauging data are available from numerous streams throughout Australia, and these data provide a basis for historical analysis of geomorphic change in stream channels in response to both natural phenomena and human activities. We present a simple method for analysis of these data, and a briefcase study of an application to channel change in the Tully River, in the humid tropics of north Queensland. The analysis suggests that this channel has narrowed and deepened, rather than aggraded: channel aggradation was expected, given the intensification of land use in the catchment, upstream of the gauging station. Limitations of the method relate to the time periods over which stream gauging occurred; the spatial patterns of stream gauging sites; the quality and consistency of data collection; and the availability of concurrent land-use histories on which to base the interpretation of the channel changes.

The last glacial cycle from the humid tropics of northeastern Australia: comparison of a terrestrial and a marine record

A detailed pollen record from the Ocean Drilling Program Site 820 core, located on the upper part of the continental slope off the coast of northeast Queensland, was constructed to compare with the existing pollen record from Lynch's Crater on the adjacent Atherton Tableland and allow the production of a regional picture of vegetation and environmental change through the last glacial cycle. Some broad similarities in patterns of vegetation change are revealed, despite the differences between sites and their pollen catchments, which can be related largely to global climate and sea-level changes. The original estimated time scale of the Lynch's Crater record is largely confirmed from comparison with the more thoroughly dated ODP record. Conversely, the Lynch's Crater pollen record has assisted in dating problematic parts of the ODP record. In contrast to Lynch's Crater, which reveals a sharp and sustained reduction in drier araucarian forest around 38,000 yrs BP, considered to have been the result of burning by Aboriginal people, the ODP record indicates, most likely, a stepwise reduction, dating from 140,000 yrs BP or beyond. The earliest reduction shows lack of a clear connection between Araucaria decline and increased burning and suggests that people may not have been involved at this stage. However, a further decline in araucarian forest, possibly around 45,000 yrs BP, which has a more substantial environmental impact and is not related to a time of major climate change, is likely, at least partially, the result of human burning. The suggestion, from the ODP core oxygen isotope record, of a regional sea-surface temperature increase of around 4 degrees C between about 400,000 and 250,000 yrs BP, may have had some influence on the overall decline in Araucaria and its replacement by sclerophyll vegetation. (C) 2000 Elsevier Science B.V. All rights reserved.

Empirical catchment-wide rainfall erosivity models for two rivers in the humid tropics of Australia

The concept of rainfall erosivity is extended to the estimation of catchment sediment yield and its variation over time. Five different formulations of rainfall erosivity indices, using annual, monthly and daily rainfall data, are proposed and tested on two catchments in the humid tropics of Australia. Rainfall erosivity indices, using simple power functions of annual and daily rainfall amounts, were found to be adequate in describing the interannual and seasonal variation of catchment sediment yield. The parameter values of these rainfall erosivity indices for catchment sediment yield are broadly similar to those for rainfall erosivity models in relation to the R-factor in the Universal Soil Loss Equation.

Identifying regional dust transport pathways: Application of kinematic trajectory modelling to a trans-Tasman case

PI kinematic trajectory model is used to investigate potential pathways of dust transport from Australia to New Zealand. Historically, these have been assumed to follow rather direct west-east trajectories spanning 2 to 3 days, often resulting in red snow events in the Southern Alps of New Zealand. However, results from the present study which examined the route taken by air parcels originating in southern Australia during dust storms on 24 and 25 May 1994, indicate that trans-Tasman dust transport trajectories are more diverse than previously thought, and display considerable variation during single events. These mon divergent pathways tie in more closely with aeolian dust sedimentation patterns identified by ocean coring in the Tasman Sea, and may account for the deposition of Australian dust on sub-Antarctic islands located well south of the Australian continent. Copyright 2000 John Wiley Sons, Ltd.

Monitoring growth in rapidly urbanizing areas using remotely sensed data

Urbanization and the ability to manage for a sustainable future present numerous challenges for geographers and planners in metropolitan regions. Remotely sensed data are inherently suited to provide information on urban land cover characteristics, and their change over time, at various spatial and temporal scales. Data models for establishing the range of urban land cover types and their biophysical composition (vegetation, soil, and impervious surfaces) are integrated to provide a hierarchical approach to classifying land cover within urban environments. These data also provide an essential component for current simulation models of urban growth patterns, as both calibration and validation data. The first stages of the approach have been applied to examine urban growth between 1988 and 1995 for a rapidly developing area in southeast Queensland, Australia. Landsat Thematic Mapper image data provided accurate (83% adjusted overall accuracy) classification of broad land cover types and their change over time. The combination of commonly available remotely sensed data, image processing methods, and emerging urban growth models highlights an important application for current and next generation moderate spatial resolution image data in studies of urban environments.