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Journal ArticleDOI

Ecological correlates of folivore abundance in north Queensland rainforests

TL;DR: It is shown that only a relatively small proportion of north Queensland rainforests support abundant populations of the endemic folivorous marsupials, and variation in folivore abundance with geology is plausibly explained as a response to the nutritional quality of foliage.
Abstract: The ecological factors controlling the distribution and abundance of the folivorous marsupials endemic to the rainforests of northern Australia are not understood. In this study, we surveyed folivore abundance at 40 sites stratified by altitude and geology in rainforests of the Atherton Tableland, north Queensland. All five species of folivore that inhabit the study area were more abundant in highland (800–1200 m) than in upland (400–800 m) forests. Allowing for the effects of altitude, four species of folivore were more abundant in forests on nutrient-rich basalts than in forests on nutrient-poor acid igneous or metamorphic rocks. The abundance of two folivore species also varied inversely with rainfall. Altitudinal variation in folivore abundance in the study area has been attributed to habitat destruction, Aboriginal hunting, the distribution of host plants and climate; however, none of these hypotheses has been tested. Variation in folivore abundance with geology is plausibly explained as a response to the nutritional quality of foliage. Foliage quality may also explain the inverse relationship between two of the folivores and rainfall. The results of this study show that only a relatively small proportion of north Queensland rainforests support abundant populations of the endemic folivorous marsupials.
Citations
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Journal ArticleDOI
TL;DR: The impacts of global climate change in the tropical rainforests of northeastern Australia have the potential to result in many extinctions, and bioclimatic models of spatial distribution for the regionally endemic rainforest vertebrates are developed to predict the effects of climate warming on species distributions.
Abstract: It is now widely accepted that global climate change is affecting many ecosystems around the globe and that its impact is increasing rapidly. Many studies predict that impacts will consist largely of shifts in latitudinal and altitudinal distributions. However, we demonstrate that the impacts of global climate change in the tropical rainforests of northeastern Australia have the potential to result in many extinctions. We develop bioclimatic models of spatial distribution for the regionally endemic rainforest vertebrates and use these models to predict the effects of climate warming on species distributions. Increasing temperature is predicted to result in significant reduction or complete loss of the core environment of all regionally endemic vertebrates. Extinction rates caused by the complete loss of core environments are likely to be severe, nonlinear, with losses increasing rapidly beyond an increase of 2 degrees C, and compounded by other climate-related impacts. Mountain ecosystems around the world, such as the Australian Wet Tropics bioregion, are very diverse, often with high levels of restricted endemism, and are therefore important areas of biodiversity. The results presented here suggest that these systems are severely threatened by climate change.

543 citations


Cites background from "Ecological correlates of folivore a..."

  • ...Rainforests on these poorer soils support lower densities of arboreal folivores (Kanowski et al. 2001)....

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  • ...It has previously been suggested that the limited altitudinal ranges of many species of mammalian folivores are determined by thermal tolerances (Winter 1997; Kanowski et al. 2001)....

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Journal ArticleDOI
TL;DR: In this article, an analysis using an artificial neural network model suggests that the tropical forests of north Queensland are highly sensitive to climate change within the range that is likely to occur in the next 50-100 years.
Abstract: An analysis using an artificial neural network model suggests that the tropical forests of north Queensland are highly sensitive to climate change within the range that is likely to occur in the next 50–100 years. The distribution and extent of environments suitable for 15 structural forest types were estimated, using the model, in 10 climate scenarios that include warming up to 1°C and altered precipitation from –10% to +20%. Large changes in the distribution of forest environments are predicted with even minor climate change. Increased precipitation favours some rainforest types, whereas decreased rainfall increases the area suitable for forests dominated by sclerophyllous genera such as Eucalyptus and Allocasuarina. Rainforest environments respond differentially to increased temperature. The area of lowland mesophyll vine forest environments increases with warming, whereas upland complex notophyll vine forest environments respond either positively or negatively to temperature, depending on precipitation. Highland rainforest environments (simple notophyll and simple microphyll vine fern forests and thickets), the habitat for many of the region’s endemic vertebrates, decrease by 50% with only a 1°C warming. Estimates of the stress to present forests resulting from spatial shifts of forest environments (assuming no change in the present forest distributions) indicate that several forest types would be highly stressed by a 1°C warming and most are sensitive to any change in rainfall. Most forests will experience climates in the near future that are more appropriate to some other structural forest type. Thus, the propensity for ecological change in the region is high and, in the long term, significant shifts in the extent and spatial distribution of forests are likely. A detailed spatial analysis of the sensitivity to climate change indicates that the strongest effects of climate change will be experienced at boundaries between forest classes and in ecotonal communities between rainforest and open woodland.

166 citations

Journal ArticleDOI
TL;DR: Using 2000 data on numbers of nests, clutch sizes, and emergence rates, the number of hatchlings that would have been lost assuming that the predation rates observed from four predator removal scenarios at HSNWR would have occurred in 2000 is estimated.

126 citations

Journal ArticleDOI
TL;DR: This paper used extensive abundance data and expected range shifts across altitudinal gradients to predict changes in total population size of rainforest birds of Australian tropical rainforests in response to climate warming.

125 citations

Journal ArticleDOI
TL;DR: In this article, a combination of weather data and spatial modeling is used to quantify thermally buffered environments in a regional tropical rainforest, and a spatial surface of maximum air temperature that takes into account important climate-mediating processes is constructed.
Abstract: Complex landscapes interact with meteorological processes to generate climatically suitable habitat (refuges) in otherwise hostile environments. Locating these refuges has practical importance in tropical montane regions where a high diversity of climatically specialized species is threatened by climate change. Here, we use a combination of weather data and spatial modeling to quantify thermally buffered environments in a regional tropical rainforest. We do this by constructing a spatial surface of maximum air temperature that takes into account important climate-mediating processes. We find a strong attenuating effect of elevation, distance from coast and foliage cover on maximum temperature. The core habitat of a disproportionately high number of endemic species (45%) is encompassed within just 25% of the coolest identified rainforest. We demonstrate how this data can be used to (i) identify important areas of cool habitat for protection and (ii) efficiently guide restoration in degraded landscapes to expand extant networks of critical cool habitat.

88 citations


Cites background from "Ecological correlates of folivore a..."

  • ...Third, much of the clearing has occurred on fertile basalt soils that are known to support mammal populations at greatest abundance (Newell, 1999; Kanowski et al., 2001)....

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References
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Book
01 Jan 1993
TL;DR: The GLIM language as mentioned in this paper is a language for experimental design that uses linear models and linear models with anova and GLIM analysis of Covariance in GLIM Linear Models Model Simplification Model Criticism Analysing Count Data: Poisson Errors AnalysING Proportion Data: Binomial Errors Binary Response Variables Data with Gamma Errors Survival Data Ecological Techniques What GLIM Doesn't Do Programming in GlIM Technical Appendices Statistical Tables Library of GLIM Programmes and Macros (on disk)
Abstract: Preface An Ecological Example The GLIM Language Introduction to Experimental Design Understanding Data: Graphical Analysis Understanding Data: Basic Statistics Regression and GLIM Anova and GLIM Analysis of Covariance in GLIM Linear Models Model Simplification Model Criticism Analysing Count Data: Poisson Errors Analysing Proportion Data: Binomial Errors Binary Response Variables Data with Gamma Errors Survival Data Ecological Techniques What GLIM Doesn't Do Programming in GLIM Technical Appendices Statistical Tables Library of GLIM Programmes and Macros (on disk)

2,385 citations

Journal ArticleDOI
TL;DR: This book presents a meta-modelling framework for estimating the probability of detection on the line or point in the context of tuna vessel observer data to assess trends in abundance of dolphins in the North Atlantic.
Abstract: 1 Introductory concepts.- 1.1 Introduction.- 1.2 Range of applications.- 1.3 Types of data.- 1.4 Known constants and parameters.- 1.5 Assumptions.- 1.6 Fundamental concept.- 1.7 Detection.- 1.8 History of methods.- 1.9 Program DISTANCE.- 2 Assumptions and modelling philosophy.- 2.1 Assumptions.- 2.2 Fundamental models.- 2.3 Philosophy and strategy.- 2.4 Robust models.- 2.5 Some analysis guidelines.- 3 Statistical theory.- 3.1 General formula.- 3.2 Hazard-rate modelling of the detection process.- 3.3 The key function formulation for distance data.- 3.4 Maximum likelihood methods.- 3.5 Choice of model.- 3.6 Estimation for clustered populations.- 3.7 Density, variance and interval estimation.- 3.8 Stratification and covariates.- 4 Line transects.- 4.1 Introduction.- 4.2 Example data.- 4.3 Truncation.- 4.4 Estimating the variance in sample size.- 4.5 Analysis of grouped or ungrouped data.- 4.6 Model selection.- 4.7 Estimation of density and measures of precision.- 4.8 Estimation when the objects are in clusters.- 4.9 Assumptions.- 4.10 Summary.- 5 Point transects.- 5.1 Introduction.- 5.2 Example data.- 5.3 Truncation.- 5.4 Estimating the variance in sample size.- 5.5 Analysis of grouped or ungrouped data.- 5.6 Model selection.- 5.7 Estimation of density and measures of precision.- 5.8 Estimation when the objects are in clusters.- 5.9 Assumptions.- 5.10 Summary.- 6 Extensions and related work.- 6.1 Introduction.- 6.2 Other models.- 6.3 Modelling variation in encounter rate and cluster size.- 6.4 Estimation of the probability of detection on the line or point.- 6.5 On the concept of detection search effort.- 6.6 Fixed versus random sample size.- 6.7 Efficient simulation of distance data.- 6.8 Thoughts about a full likelihood approach.- 6.9 Distance sampling in three dimensions.- 6.10 Cue counting.- 6.11 Trapping webs.- 6.12 Migration counts.- 6.13 Point-to-object and nearest neighbour methods.- 7 Study design and field methods.- 7.1 Introduction.- 7.2 Survey design.- 7.3 Searching behaviour.- 7.4 Measurements.- 7.5 Training observers.- 7.6 Field methods for mobile objects.- 7.7 Field methods when detection on the centerline is not certain.- 7.8 Field comparisons between line transects, point transects and mapping censuses.- 7.9 Summary.- 8 Illustrative examples.- 8.1 Introduction.- 8.2 Lake Huron brick data.- 8.3 Wooden stake data.- 8.4 Studies of nest density.- 8.5 Fin whale abundance in the North Atlantic.- 8.6 Use of tuna vessel observer data to assess trends in abundance of dolphins.- 8.7 House wren densities in South Platte River bottomland.- 8.8 Songbird surveys in Arapaho National Wildlife Refuge.- 8.9 Assessing the effects of habitat on density.- Appendix A List of common and scientific names cited.- Appendix B Notation and abbreviations, and their definitions.

1,629 citations

Journal ArticleDOI
TL;DR: Interspecific patterns of defense mechanisms are discussed in terms of current theories of plant apparency, and an alternative model for the evolution of plant defenses is presented.
Abstract: Rates of herbivory and defensive characteristics of young and mature leaves were measured for saplings of 46 canopy tree species in a lowland tropical rain forest (Barro Colorado Island, Panama). Grazing rates were determined in the field for sample periods in the early wet, late wet, and dry seasons. Leaf properties such as pubescence, toughness, water, protein, fiber, and phenolic contents explained over 70W% of the variation among plant species in the rates of herbivory on mature leaves. Leaf toughness was most highly correlated with levels of herbivory, followed by fiber content and nutritive value. Phenol content and phenol: protein ratios were not significantly correlated with damage. Mature leaves of gap-colonizing species were grazed six times more rapidly than leaves of shade- tolerant species. Gap-colonizers have less tough leaves, lower concentrations of fiber and phenolics, higher levels of nitrogen and water, shorter leaf lifetimes, and faster growth rates than do shade- tolerant species. Gap-colonizers did not escape discovery by herbivores to any greater extent than shade-tolerant species, as measured by the spatial distribution of plants or by the intraspecific dis- tribution of herbivore damage under natural or experimentally manipulated conditions. In 70W% of the species, young leaves suffered higher damage levels than mature leaves. Although young leaves are more nutritious and less tough and fibrous, they have two to three times the con- centrations of phenols. The temporal appearance of young leaves was not correlated with the distri- bution of herbivory among individuals of a species. Interspecific patterns of defense mechanisms are discussed in terms of current theories of plant apparency, and an alternative model for the evolution of plant defenses is presented.

1,523 citations

Book
27 May 1993
TL;DR: In this article, the authors propose a key function formulation for distance data to estimate the probability of detection on the line or point of interest (line transects) and the variance in sample size.
Abstract: 1 Introductory concepts.- 1.1 Introduction.- 1.2 Range of applications.- 1.3 Types of data.- 1.4 Known constants and parameters.- 1.5 Assumptions.- 1.6 Fundamental concept.- 1.7 Detection.- 1.8 History of methods.- 1.9 Program DISTANCE.- 2 Assumptions and modelling philosophy.- 2.1 Assumptions.- 2.2 Fundamental models.- 2.3 Philosophy and strategy.- 2.4 Robust models.- 2.5 Some analysis guidelines.- 3 Statistical theory.- 3.1 General formula.- 3.2 Hazard-rate modelling of the detection process.- 3.3 The key function formulation for distance data.- 3.4 Maximum likelihood methods.- 3.5 Choice of model.- 3.6 Estimation for clustered populations.- 3.7 Density, variance and interval estimation.- 3.8 Stratification and covariates.- 4 Line transects.- 4.1 Introduction.- 4.2 Example data.- 4.3 Truncation.- 4.4 Estimating the variance in sample size.- 4.5 Analysis of grouped or ungrouped data.- 4.6 Model selection.- 4.7 Estimation of density and measures of precision.- 4.8 Estimation when the objects are in clusters.- 4.9 Assumptions.- 4.10 Summary.- 5 Point transects.- 5.1 Introduction.- 5.2 Example data.- 5.3 Truncation.- 5.4 Estimating the variance in sample size.- 5.5 Analysis of grouped or ungrouped data.- 5.6 Model selection.- 5.7 Estimation of density and measures of precision.- 5.8 Estimation when the objects are in clusters.- 5.9 Assumptions.- 5.10 Summary.- 6 Extensions and related work.- 6.1 Introduction.- 6.2 Other models.- 6.3 Modelling variation in encounter rate and cluster size.- 6.4 Estimation of the probability of detection on the line or point.- 6.5 On the concept of detection search effort.- 6.6 Fixed versus random sample size.- 6.7 Efficient simulation of distance data.- 6.8 Thoughts about a full likelihood approach.- 6.9 Distance sampling in three dimensions.- 6.10 Cue counting.- 6.11 Trapping webs.- 6.12 Migration counts.- 6.13 Point-to-object and nearest neighbour methods.- 7 Study design and field methods.- 7.1 Introduction.- 7.2 Survey design.- 7.3 Searching behaviour.- 7.4 Measurements.- 7.5 Training observers.- 7.6 Field methods for mobile objects.- 7.7 Field methods when detection on the centerline is not certain.- 7.8 Field comparisons between line transects, point transects and mapping censuses.- 7.9 Summary.- 8 Illustrative examples.- 8.1 Introduction.- 8.2 Lake Huron brick data.- 8.3 Wooden stake data.- 8.4 Studies of nest density.- 8.5 Fin whale abundance in the North Atlantic.- 8.6 Use of tuna vessel observer data to assess trends in abundance of dolphins.- 8.7 House wren densities in South Platte River bottomland.- 8.8 Songbird surveys in Arapaho National Wildlife Refuge.- 8.9 Assessing the effects of habitat on density.- Appendix A List of common and scientific names cited.- Appendix B Notation and abbreviations, and their definitions.

1,211 citations

Journal ArticleDOI
TL;DR: Field metabolic rates (FMRs or HF), all measured using doubly labeled water, of 23 species of eutherian mammals, 13 species of marsupial mammals, and 25 species of birds were summarized and analyzed allometrically (log10-1og10 regressions).
Abstract: Field metabolic rates (FMRs or HF), all measured using doubly labeled water, of 23 species of eutherian mammals, 13 species of marsupial mammals, and 25 species of birds were summarized and analyzed allometrically (log10-1og10 regressions). FMR is strong- ly correlated with body mass in each of these groups. FMR scales differently than does basal or standard metabolic rate in eutherians (FMR slope = 0.81) and marsupials (FMR slope = 0.58), but not in birds (FMR slope = 0.64 overall, but 0.75 in passerines and 0.75 in all other birds). Medium-sized (240-5 50 g) eutherians, marsupials, and birds have similar FMRs, and these are - 17 times as high as FMRs of like-sized ectothermic vertebrates such as iguanid lizards. For endothermic vertebrates, the energy cost of surviving in nature is enormous compared with that for ectotherms. Within the eutherians, marsupials, or birds, FMR scales differently for the following subgroups: rodents, passerine birds, her- bivorous eutherians, herbivorous marsupials, desert eutherians, desert birds, and seabirds. Equations are given for use in predicting daily and annual FMR and food requirement of a species of terrestrial vertebrate, given its body mass.

959 citations


"Ecological correlates of folivore a..." refers background in this paper

  • ...johnstoni occupying an intermediate position (Harestad and Bunnell 1979; Nagy 1987)....

    [...]