Environmental controls on wood density in tropical forests

Torello Raventos, Mireia (2014) Environmental controls on wood density in tropical forests. PhD thesis, James Cook University.

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View at Publisher Website: https://doi.org/10.25903/1803-cw81
 
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Abstract

Tropical forests store a larger amount of carbon (C) than boreal and temperate forests. However, the determination of above ground biomass and C stocks in tropical ecosystems usually relies on a combination of remote sensing data together with ground data to develop models that predict forest biomass. One of the major determinants of above ground C stocks that cannot be determined in the field is wood density (ρ) and tropical ecosystems usually contain a high diversity of tree species, with a wide range of wood densities in comparison with temperate forests.

Summary of the data chapters

This thesis aimed to understand the importance of accounting for the intra and interspecific variation of the ρ with changing environmental conditions on the calculation of the above ground C on tropical forests. Not including this variation of ρ could misestimate the C reservoirs on these ecosystems. In total, this thesis includes four data chapters. The first data chapter that is Chapter 2 comprises a novel method to study the ρ within and between tree species at different study sites in Australia, Papua New Guinea and Vanuatu across different forest types. Chapter 3 and 4 studied the variation of ρ with elevation (within and between tree species) from a low to mid montane tropical forests in Papua New Guinea and in range from lowland to montane tropical forest in Australia on respectively. Additionally, Chapter 4 also examined the variation of above ground biomass with increasing elevation. Chapter 5 investigated the importance of including ρ on the estimations of the coarse woody debris residence times. The study was conducted along an altitudinal gradient in a tropical forest in Australia to observe the variation of the decomposition of the wood with the decreasing of mean annual temperature. The aim of using altitudinal gradients as sampling design was to understand the potential effects of climate change on the forest dynamics.

Description of the data chapters

Traditional methods for both field core extraction and laboratory processing for determining the ρ of trees are generally time consuming and costly. Some trees are very hard to core and the field and the laboratory equipment required to obtain accurate numbers are expensive. There is also the risk of sample damaging during the process of collecting and transporting the core samples. Because of all of the listed inconveniences, a fast, cheap, nondestructive and efficient field method to determine wood density would help the researchers to facilitate biomass census on tropical forests and with special emphasis those located in remote areas. Chapter 2 develops a field-based method to determine ρ that relies on a non-destructive ultrasonic technique. We tested the technique on living trees, from different ecosystem types and under a range of climate conditions. The results suggest a positive relationship between ρ and ultrasonic velocity with a coefficient of variation of 0.66 for intraspecific variation of ρ and 0.81 for interspecific variation of ρ. Due to interferences with the ultrasonic pulse velocity, measurements should be conducted in dry weather when temperatures are less than 30 °C. Potential improvements of this technique would include reducing the size of the transducers of the instrument and the development of conversion factors for measurements carried out above 30°C.

Few studies have described ρ values for trees located on remote forests of Papua New Guinea. Besides, studies of the quantification of the intraspecific and interspecific variation of ρ in relation to environmental variables are scarce for tropical forests and inexistent for Papua New Guinea. Thus, in this thesis study site elevation was chosen as an environmental gradient for the study of the climatic effects on the variation of ρ. Therefore, chapter 3 reports the ρ values from the most common sun-exposed and shaded tree species in the YUS Conservation Area, Papua New Guinea over an elevation range from 1800 m to 3050 m above sea level. Besides, one key focus of this chapter is the study of intra-specific variation of ρ with elevation (temperature). The results indicate ρ was negatively related to elevation for sun-exposed trees but with a positive ρ /elevation relationship for shaded species. Both within and across species, tree size was found to be a significant covariate in models attempting to explain individual tree variations on ρ: a positive relationship between ρ with 1/DBH provided the best model fit. The results of this study have important implication for future studies on ground-based tropical forest biomass estimates for tropical montane forests.

Australian forests are located in a World Heritage Area and little is known about their role of carbon reservoirs and how they will respond to the effects of climate change. Chapter 4 presents a study along an elevational gradient from 50 m to 1500 m in North Queensland on the a) plot above ground biomass, basal area and tree diameter variation, b) the intra and interspecific variation of wood density for common species along the elevation range and c) the tree growth rates variation according to tree diameter and species. This study also included the effects of soil fertility as potential cause of ρ variability. The results indicated that tree forest strata, diameter and growth rates were related. Sun-exposed trees that had bigger average diameters presented bigger growth rates than smaller trees. In addition, results suggested a relationship between forest strata and ρ. For sun-exposed trees, wood density decreased with elevation and the inverse case was for shaded trees. A multi-level statistical analysis of the dataset explained that soil fertility in addition to site elevation were significant drivers of tree wood density variation.

The coarse woody debris (CWD) pool of a forest in composed mainly by death trees, large branches and death leaves. The nutrients that are confined on the death material return to the ecosystems to be reused by living organisms. Throughout this cycle, CWD provides food and habitat to living organisms and increases forest biodiversity. The pace that CWD might degrade can be related to environmental variables (i.e. soil fertility, forest mature stage). However, due to the imminent consequences of climate change on actual and future forest dynamics, this study has focused on the effects of mean annual temperature of the CWD residence times. Thus, Chapter 5 examines coarse woody debris residence time (τ), for different tree species (and therefore with different wood traits) - ranging from low to hard woods – along an elevation gradient from 102 m above sea level (MAT = 23.7 °C) to 1500 m above sea level (MAT = 16.7 °C) in a tropical forests in Australia. The aim was to understand the effects of elevation (temperature) on the chemical and physical decay of CWD. Results suggested that wood density together with Carbon:Nitrogen ratio enable prediction of the variation in τ within decay classes and tree species along an elevation gradient. In addition, τ decreased with increasing decay status of the wood, with temperature also playing an important role, as τ increased with increasing site elevation. The study also suggested the importance of further studies of the effects of seasonal variations in climate in short term field studies, as a single wet season reduced the observed τ of the CWD faster than two wet season and a dry season.

Item ID: 44654
Item Type: Thesis (PhD)
Keywords: above ground carbon; altitudinal gradients; Australia; biomass determination; carbon levels; carbon stocks; climate change; coarse woody debris; forest biomass; global warming; Papua New Guinea (PNG); rain forests; rainforests; tree density; tropical forest carbon; tropical forests; Vanuatu; wood density
Date Deposited: 11 Aug 2016 05:11
FoR Codes: 04 EARTH SCIENCES > 0401 Atmospheric Sciences > 040104 Climate Change Processes @ 33%
05 ENVIRONMENTAL SCIENCES > 0501 Ecological Applications > 050101 Ecological Impacts of Climate Change @ 33%
07 AGRICULTURAL AND VETERINARY SCIENCES > 0705 Forestry Sciences > 070502 Forestry Biomass and Bioproducts @ 34%
SEO Codes: 96 ENVIRONMENT > 9603 Climate and Climate Change > 960305 Ecosystem Adaptation to Climate Change @ 33%
96 ENVIRONMENT > 9609 Land and Water Management > 960906 Forest and Woodlands Land Management @ 34%
96 ENVIRONMENT > 9603 Climate and Climate Change > 960307 Effects of Climate Change and Variability on Australia (excl. Social Impacts) @ 33%
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