Cooperative Research Centre

About: Cooperative Research Centre is a based out in . It is known for research contribution in the topics: Population & Sea ice. The organization has 7633 authors who have published 8607 publications receiving 429721 citations.

Learning to predict large-scale coral bleaching from past events: A Bayesian approach using remotely sensed data, in-situ data, and environmental proxies

Abstract: Ocean warming and coral bleaching are patchy phenomena over a wide range of scales. This paper is part of a larger study that aims to understand the relationship between heat stress and ecological impact caused by the 2002-bleaching event in the Great Barrier Reef (GBR). We used a Bayesian belief network (BBN) as a framework to refine our prior beliefs and investigate dependencies among a series of proxies that attempt to characterize potential drivers and responses: the remotely sensed environmental stress (sea surface temperature — SST); the geographic setting; and topographic and ecological attributes of reef sites for which we had field data on bleaching impact. Sensitivity analyses helped us to refine and update our beliefs in a manner that improved our capacity to hindcast areas of high and low bleaching impact. Our best predictive capacity came by combining proxies for a site’s heat stress in 2002 (remotely sensed), acclimatization temperatures (remote sensed), the ease with which it could be cooled by tidal mixing (modeled), and type of coral community present at a sample of survey sites (field data). The potential for the outlined methodology to deliver a transparent decision support tool to aid in the process of identifying a series of locations whose inclusion in a network of protected areas would help to spread the risk of bleaching is discussed.

Predicting Extractives, Lignin, and Cellulose Contents Using Near Infrared Spectroscopy on Solid Wood in Eucalyptus globulus

Abstract: Near infrared reflectance (NIR) spectroscopy can be used to reliably predict both the physical and chemical wood properties of Eucalyptus. However, studies have been based on ground wood, which is costly and time‐consuming to obtain. Predicting wood traits from NIR spectral data taken from solid wood would greatly increase the speed and cost‐effectiveness of this procedure. Existing ground wood calibrations were evaluated for the prediction of wood chemistry from NIR spectral data taken from solid wood. Extractives, acid‐soluble lignin, and Klason lignin contents were poorly predicted. Total lignin and cellulose contents showed moderate relationships between laboratory values and the NIR predicted values. NIR calibrations were further developed specifically for predicting wood chemistry from solid wood. All calibrations had high R2 values from 0.72 to 0.88, and standard errors of calibration were less than 1.37%. Calibration validation produced high correlation coefficients between predicted and ...

Frequent fires reduce tree growth in northern Australian savannas: implications for tree demography and carbon sequestration

Abstract: Tropical savannas are typically highly productive yet fire-prone ecosystems, and it has been suggested that reducing fire frequency in savannas could substantially increase the size of the global carbon sink. However, the long-term demographic consequences of modifying fire regimes in savannas are difficult to predict, with the effects of fire on many parameters, such as tree growth rates, poorly understood. Over 10 years, we examined the effects of fire frequency on the growth rates (annual increment of diameter at breast height) of 3075 tagged trees, at 137 locations throughout the mesic savannas of Kakadu, Nitmiluk and Litchfield National Parks, in northern Australia. Frequent fires substantially reduced tree growth rates, with the magnitude of the effect markedly increasing with fire severity. The highest observed frequencies of mild, moderate and severe fires (1.0, 0.8 and 0.4 fires yr1, respectively) reduced tree growth by 24%, 40% and 66% respectively, relative to unburnt areas. These reductions in tree growth imply reductions in the net primary productivity of trees by between 0.19 tCha1 yr1, in the case of mild fires, and 0.51 tCha1 yr1, in the case of severe fires. Such reductions are relatively large, given that net biome productivity (carbon sequestration potential) of these savannas is estimated to be just 1–2 tCha1 yr1. Our results suggest that current models of savanna tree demography, that do not account for a relationship between severe fire frequency and tree growth rate, are likely to underestimate the long-term negative effects of frequent severe fires on tree populations. Additionally, the negative impact of frequent severe fires on carbon sequestration rates may have been underestimated; reducing fire frequencies in savannas may increase carbon sequestration to a greater extent than previously thought.