Gary N. Bastin

A leakiness index for assessing landscape function using remote sensing

The cover, number, size, shape, spatial arrangement and orientation of vegetation patches are attributes that have been used to indicate how well landscapes function to retain, not ‘leak’, vital system resources such as rainwater and soil. We derived and tested a directional leakiness index (DLI) for this resource retention function. We used simulated landscape maps where resource flows over map surfaces were directional and where landscape patch attributes were known. Although DLI was most strongly related to patch cover, it also logically related to patch number, size, shape, arrangement and orientation. If the direction of resource flow is multi-directional, a variant of DLI, the multi-directional leakiness index (MDLI) can be used. The utility of DLI and MDLI was demonstrated by applying these indices to three Australian savanna landscapes differing in their remotely sensed vegetation patch attributes. These leakiness indices clearly positioned these three landscapes along a function-dysfunction continuum, where dysfunctional landscapes are leaky (poorly retain resources).

Assessing landscape health by scaling with remote sensing : when is it not enough?

Assessment of the health of landscapes, by monitoring their condition over space and time, is needed to better understand the processes for sustaining or, in many cases, repairing them. Remote sensing is a tool that can efficiently identify and assess areas of landscape damage at different scales and help land managers solve specific problems. Remote sensing may appear to be a panacea for all monitoring situations but sometimes the information it provides is not enough by itself. In this paper we give examples of both scenarios—when remote sensing alone is adequate and when it is not. When remotely sensed data alone is not sufficient, monitoring problems can be solved by incorporating additional finer scale data. We use a five-step procedure based on scaling to help land managers answer the question: when is remote sensing data alone not sufficient to underpin the information needs required to achieve a specific management goal?

Vegetation changes in a semiarid tropical savanna, northern Australia: 1973–2002

We measured vegetation changes inside and outside two exclosures built in 1973 on red calcareous loam soils located in Conkerberry Paddock on Victoria River Research Station in northern Australia. These two exclosures were unburnt since their establishment in 1973 until exclosure 1 was unintentionally burnt late in the dry season (October) of 2001. Data from permanent transects and examples from photopoints illustrate that from mostly bare soils in 1973, total pasture biomass recovered relatively rapidly both inside and outside exclosures (in about five years). This initial recovery was primarily due to the establishment of annual grasses and forbs. After this five year period, there was a consistent increase in the biomass of perennial grasses, such as Heteropogon contortus and Dichanthium spp. Also in the first five years after exclosure, the exotic shrub, Calotropis procera,invaded the study area, but then largely disappeared in a period of lower wet-season rainfall in the late 1980s. The density of native tree species, particularly Hakea arborescens, Eucalyptus pruinosa and Lysiphyllum cunninghamii increased in general, but more so inside one or other of the exclosures. Although the late dry-season fire of 2001 reduced the density of larger H. arborescens and L. cunninghamii inside the exclosure at Site 1, this effect was not apparent for smaller trees and for trees outside this exclosure. Our findings show that savanna vegetation can change massively in the medium term (29 years) and that exclosure from cattle grazing can contribute to our understanding of the role of livestock in such change. However, exclosures by themselves do not provide adequate information about the processes leading to vegetation change replicated experimental studies are needed. That substantial increase in the biomass and proportion of perennial grasses occurred with light to moderate cattle grazing implies that these rangelands can be managed for production, although control of woody vegetation is an issue.

The Australian Collaborative Rangelands Information System: preparing for a climate of change

Change is a constant in Australia’s rangelands. Appropriate management of this change requires a sound knowledge of drivers (e.g. climate variability, livestock grazing), their impacts on natural resources (state and trend), socio-economic outcomes, and how these feed back through learning and adaptive management to affect drivers and their impacts. Information is required at scales from enterprise to national, with regional and broader level information serving to influence rangelands governance through institutional arrangements, policy and funding programs. The Australian Collaborative Rangelands Information System (ACRIS) collates and analyses data from national sources and from its State and Territory jurisdictional partners to track and understand change at regional to national scales. ACRIS has recently reported changes between 1992 and 2005 in several biophysical and socio-economic themes at bioregional resolution. This paper describes the processes used to collate and analyse the often disparate data, to synthesise information across data types and to integrate emergent higher order information across drivers, impacts and outcomes to provide more complete understanding of change. Data gaps and inconsistencies were a major challenge, and we illustrate how some of these issues were addressed by using indicators to report changes in biodiversity. ACRIS now needs to foster increased coordinated monitoring activity and develop its reporting capacity to become the valued information system for Australia’s rangelands. We propose that future improvements will be best structured within a hierarchically nested framework that provides consistent overarching data at national scale relevant to the variety of rangeland values (e.g. change in ground cover) but focuses on regionally-relevant ecosystem services, and their appropriate measures, at the regional scale. A key challenge is to implement consistent and systematic methods for monitoring biodiversity within this hierarchical framework, given limited institutional resources. Finally, ACRIS needs to develop a dynamic web-based delivery system to enable more frequent and flexible reporting of interpreted change than is possible through periodic published reports.

The role of a knowledge broker in improving knowledge and understanding of climate change in the Australian rangelands

This paper considers the role of a knowledge broker to coordinate and connect activity within a cross-disciplinary project to deliver climate change science and research to regional natural resource management (NRM) planning in the Australian rangelands. We use the Rangelands Cluster Project as a case study. Due to the additional challenges facing project delivery in the rangelands such as remoteness, distance and low and sparsely distributed population, the project development phase included the central role of a knowledge broker to support the project objectives: identifying climate change information needs, providing quality information that can be incorporated into NRM planning, and establishing networks of researchers and NRM planners across the rangelands. The knowledge broker facilitated a process that included face-to-face meetings, workshops, surveys, email and teleconferencing to establish relationships and identify priorities as well as to refine project outputs. This facilitation allowed clearer communication between parties who were very remote from each other and worked in different disciplines, ensuring the different expertise was brought into the project, connections made and relationships formed.

Coded T-mark continuums: a graphical method for reporting rangeland monitoring data

In this paper we describe a new method of graphically presenting rangeland monitoring data as coded time-mark continuums. This method aims to provide people with an interest in rangelands (stakeholders) with succinct information, which they need to assess rangeland condition and change. This new method graphs data for indicators of rangeland condition as time or T-marks along gradients or continuums. The ends of these continuums are reference points, which are values for indicators defining highly functional to very dysfunctional rangeland systems. The T-marks for an indicator along its continuum are also coded as to how changes relate to combinations of recent seasonal conditions and longer-term management effects. Codes are based on a two-way matrix combining ‘seasonal quality’ (e.g. rainfall in a specified period relative to the long-term record) and expected responses from land management (i.e. increase, decrease or no change relative to that predicted from seasonal quality). Monitoring data available in the Australian Collaborative Rangeland Information System were used to illustrate the use of coded T-mark continuums. We show succinctly how one indicator changed in two different rangeland regions and how multiple indicators changed within one region.

Performance of different vegetation indices in assessing degradation of community grazing lands in Indian arid zone

Vegetation in arid community grazinglands shows monsoonal growth. Its matching phenology with crops makes its detection difficult during July to September. While crops are harvested during September-October, using satellite data thereafter for the natural vegetation seems most appropriate but by then it turns dry. An index capable of sensing dry vegetation was needed since conventional NDVI is sensitive to greenness of vegetation. Performance of NDVI vis-à-vis another index, PD54, based on cover was therefore compared in assessing degradation of grazinglands. The PD54 was used to isolate anthropogenic impacts from environmental induced degradation by analyzing satellite images from dry and wet seasons. Substantial absence of appreciable vegetation response indicated poor resilience and severe degradation. Five grazinglands in Shergarh tehsil of Jodhpur district in Rajasthan were studied following above approach. Ground radiometric observations were recorded. Satellite data of IRS 1C/1D/P6 with LISS 3 sensor for both pre and post monsoon season were acquired for three contrasting wet-dry season events. These were geometrically registered and radiometrically calibrated to calculate an index of vegetation cover PD54 as well as NDVI. PD54 is a perpendicular vegetation index based on the green and red spectral band width. The PD54 and NDVI calculated from spectro-radiometer were related to vegetation cover measured on ground in permanent plots. This confirmed that PD54 was superior index for estimating cover in arid dry grasslands. These ground vegetation trends in a good rainfall year (2001) with drought year (2002) were related with satellite data for a protected and four unprotected grazinglands. NDVI failed to detect any vegetation in protected areas supporting excellent grass cover which was succinctly brought out by PD54. Successful validation of PD54 in detecting degradation of 13 additional sites confirmed its efficacy. These findings have implication in forage availability assessments, forage forecasting, drought preparedness, pastoralism and transhumance.