Peter C. Catling

Modelling distributions of arboreal and ground-dwelling mammals in relation to climate, nutrients, plant chemical defences and vegetation structure in the eucalypt forests of southeastern Australia

Abstract Numerous studies over the past 15 years have investigated relationships between the distributions of arboreal and ground-dwelling mammals and environmental, structural and leaf compositional variables in the temperate Eucalyptus forests of southeastern and northeastern New South Wales, Australia. This paper draws together the general trends emerging from these studies and identifies some clear messages for the future modelling of regional biodiversity in these forests. The studies on arboreal mammals (all are marsupials in these forests) reviewed here generally fall into two broad categories: those that conclude that the nutrient status of forests is the prime determinant of habitat quality for arboreal marsupials and those that put equal or greater emphasis on variables related to structural characteristics of forests. Recent studies suggest a hierarchical model that is consistent with both of these emphases. They postulate that a proportion of temperature eucalypt forests, regardless of their climatic or structural characteristics, cannot support permanent populations of arboreal marsupials, especially leaf-eating species, due to low food quality and/or high phytochemical toxicity. Above a postulated nutritional or phytotoxicological ‘threshold’, food quality is adequate and other variables, including climatic and structural ones, apparently interact to determine habitat quality. Hence, differences in the extent to which different studies sample regional environmental variability, the range of nutrient status and forest structure, are likely to greatly affect which variables appear most significant in models of habitat requirements. Structural characteristics (measured as habitat complexity) of the forest have emerged as explanatory variables for the ground-living mammals also. Variables such as nutrients, lithology, terrain and climate exhibit a different trend to that seen for arboreal marsupials. Relative abundance of small ground-dwelling mammals is negatively correlated with site nutrient status as indicated by nutrient concentrations in tree foliage. Small mammals are present at all measured nutrient levels, but their abundance falls substantially as habitat complexity decreases. The influence of nutrients is masked in habitats of high complexity, there being no relationship with nutrient status. Many ground-living mammals occur across the gradients of lithology, terrain and climate, although there is wide variation in relative abundance for some species. The importance of structural variables for explaining distributions of both arboreal and ground-living fauna in eucalypt forests indicates that adequate modelling of habitat requirements for these fauna can only be achieved if surveys obtain adequate data on forest structure to encompass gradients in seral stage and disturbance history. The present-day mammalian fauna of the southeastern Australian forests has been influenced strongly by the effects of urbanisation, clearing for farming, forestry activities and fire on forest structural complexity and nutrient dynamics as well as by predation by introduced camivores. While modelling with respect to broadly defined climatic and terrain variables might be useful for broad-scale spatial prediction of faunal distributions, such models are unlikely to provide descriptions of habitat requirements or predictions of impacts of forest management at a scale necessary for sustainable management of faunal biodiversity.

The distribution and abundance of ground-dwelling mammals in relation to time since wildfire and vegetation structure in south-eastern Australia

Vegetation undergoes a natural succession after wildfire. Following an initial flush of vegetation, when light and other resources become limiting, the stand structure rapidly reaches a maximum. As a result, vegetation structure does not form an even distribution over the landscape, but rather a patchwork pattern. The position and characteristics of a patch of habitat in the landscape may be critical in determining the faunal composition. In this paper a sequence of ‘habitat complexity scores’ (which describe vegetation structure independently of plant species) collected over 20 years following a wildfire was utilised to estimate vegetation structure in relation to time since fire. This information was compared with data collected over the same period on medium-sized and large grounddwelling mammals to examine the response of mammals to changes in vegetation structure. Models are presented of the response of ground-dwelling mammals to time since wildfire and to changes in habitat complexity scores, with predictions up to 25 years after wildfire.

Predicting the complexity of habitat in forests from airborne videography for wildlife management

Abstract Airborne videographic remote sensing is a relatively recent technology that can provide spatial data for a variety of forest management issues. This letter presents a methodology which demonstrates that videographic data can accurately predict the complexity of fauna habitat across forested landscapes at two metre resolution. This provided an excellent tool for stratifying the forest into fauna habitats to predict the composition, spatial distribution and abundance of faunal groups.

Prediction of the spatial distribution and relative abundance of ground-dwelling mammals using remote sensing imagery and simulation models

We present an approach that allows current, retrospective and future relative abundances of mammal species to be predicted across landscapes. A spatial generalized regression model of species relative abundance based on habitat quality and time since disturbance was combined with coverages of the spatial distribution of habitat quality derived from a simulation model which predicts the historical and future spatial arrangement of forest habitat. The strength of this approach is that the input habitat data can be derived as part of a standard forest inventory mapping program with the addition of high spatial resolution remote sensing imagery. Furthermore, it operates at the scale used for wildlife management in Australia, which makes it widely applicable. To demonstrate the approach we use data collected over 20 years on the long-nosed potoroo (Potorous tridactylus) and the large wallabies (red-necked wallaby, Macropus rufogriseus, and swamp wallaby, Wallabia bicolor) and their habitats following wildfire. Results indicate the relative abundance of the potoroo has increased, from initially sparse numbers of less than 0.5 % of plot-night occurrences to close to 3% approximately twenty years after a major fire event. The large wallabies by contrast decreased in relative abundance from about 20% since the major fire event. Presently the relative abundance of large wallabies was modelled at 2% of plot-nights with tracks which was very low. Predictions of future relative abundance without additional disturbance were low, with the region likely to be unsuitable for the species in the next 5 years. These models offer tools for investigating the current and historical abundances of key species which can provide data to forest managers for wildlife management thereby translating current scientific understanding into tools suitable for every-day use by forest managers.

Procedures for predicting habitat and structural attributes in eucalypt forests using high spatial resolution remotely sensed imagery

SUMMARY Forest resource information is increasingly needed at fine spatial scales for operational and strategic applications including monitoring indicators of ecologically sustainable forest management, planning of harvesting operations and implementation of silvicultural prescriptions, and the maintenance of biodiversity and ecological sustainability. High resolution remotely sensed imagery is one data source that can provide cost effective information for forest management. This paper presents two methodologies that allow these data to be modelled to predict forest structure in eucalypt forests. One method emphasises the tree crown as the primary indicator of forest structure and utilises algorithms which automatically delineate tree canopies in high spatial resolution data. The second method investigates the spectral variability of the forest in relation to its habitat quality (biomass of tree canopy, shrubs, ground cover and litter) for ground-dwelling fauna. Both methods utilised the near infrared (...

Prediction of historical forest habitat patterns using binomial distributions and simple Boolean logic from high spatial resolution remote sensing

The identification of forest habitat, its spatial pattern and use by selected taxa is a vital step for the protection of biodiversity. The use of airborne videography and frequency distribution models based on historical habitat complexity data can provide detailed information on the spatial and temporal variation of habitat, respectively. The two techniques, however, have not been jointly applied to link the temporal variation in habitat to the spatial variation of habitat over the landscape to provide a complete historical picture of the variation of habitat quality of a forest estate. In this paper, a processing methodology is developed which allows the current spatial distribution of habitat quality to be used as a base to make retrospective predictions of the spatial extent and pattern of habitat quality over the landscape. This is achieved by projecting the spatial distribution of habitat complexity scores derived from the videography, backward in time using a combination of simple Boolean logic, estimated binomial distributions, and the use of random fluctuations to mimic natural forest dynamics that are likely to have occurred over the modeling period. The simulations provide information on the type and condition of habitat in recent history and can be linked to models predicting the abundance of a variety of common and endangered taxa.