School of Agriculture, Food and Ecosystem Sciences - Research Publications
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ItemEvaluation of Spectral Indices for Assessing Fire Severity in Australian Temperate Forests(MDPI AG, 2018)Spectral indices derived from optical remote sensing data have been widely used for fire-severity classification in forests from local to global scales. However, comparative analyses of multiple indices across diverse forest types are few. This represents an information gap for fire management agencies in areas like temperate south-eastern Australia, which is characterised by a diversity of natural forests that vary in structure, and in the fire-regeneration strategies of the dominant trees. We evaluate 10 spectral indices across eight areas burnt by wildfires in 1998, 2006, 2007, and 2009 in south-eastern Australia. These wildfire areas encompass 13 forest types, which represent 86% of the 7.9M ha region’s forest area. Forest types were aggregated into six forest groups based on their fire-regeneration strategies (seeders, resprouters) and structure (tree height and canopy cover). Index performance was evaluated for each forest type and forest group by examining its sensitivity to four fire-severity classes (unburnt, low, moderate, high) using three independent methods (anova, separability, and optimality). For the best-performing indices, we calculated index-specific thresholds (by forest types and groups) to separate between the four severity classes, and evaluated the accuracy of fire-severity classification on independent samples. Our results indicated that the best-performing indices of fire severity varied with forest type and group. Overall accuracy for the best-performing indices ranged from 0.50 to 0.78, and kappa values ranged from 0.33 (fair agreement) to 0.77 (substantial agreement), depending on the forest group and index. Fire severity in resprouter open forests and woodlands was most accurately mapped using the delta Normalised Burnt ratio (dNBR). In contrast, dNDVI (delta Normalised difference vegetation index) performed best for open forests with mixed fire responses (resprouters and seeders), and dNDWI (delta Normalised difference water index) was the most accurate for obligate seeder closed forests. Our analysis highlighted the low sensitivity of all indices to fire impacts in Rainforest. We conclude that the optimal spectral index for quantifying fire severity varies with forest type, but that there is scope to group forests by structure and fire-regeneration strategy to simplify fire-severity classification in heterogeneous forest landscapes.
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ItemAssessing fire impacts on the carbon stability of fire-tolerant forests(WILEY, 2017-12)The carbon stability of fire-tolerant forests is often assumed but less frequently assessed, limiting the potential to anticipate threats to forest carbon posed by predicted increases in forest fire activity. Assessing the carbon stability of fire-tolerant forests requires multi-indicator approaches that recognize the myriad ways that fires influence the carbon balance, including combustion, deposition of pyrogenic material, and tree death, post-fire decomposition, recruitment, and growth. Five years after a large-scale wildfire in southeastern Australia, we assessed the impacts of low- and high-severity wildfire, with and without prescribed fire (≤10 yr before), on carbon stocks in multiple pools, and on carbon stability indicators (carbon stock percentages in live trees and in small trees, and carbon stocks in char and fuels) in fire-tolerant eucalypt forests. Relative to unburned forest, high-severity wildfire decreased short-term (five-year) carbon stability by significantly decreasing live tree carbon stocks and percentage stocks in live standing trees (reflecting elevated tree mortality), by increasing the percentage of live tree carbon in small trees (those vulnerable to the next fire), and by potentially increasing the probability of another fire through increased elevated fine fuel loads. In contrast, low-severity wildfire enhanced carbon stability by having negligible effects on aboveground stocks and indicators, and by significantly increasing carbon stocks in char and, in particular, soils, indicating pyrogenic carbon accumulation. Overall, recent preceding prescribed fire did not markedly influence wildfire effects on short-term carbon stability at stand scales. Despite wide confidence intervals around mean stock differences, indicating uncertainty about the magnitude of fire effects in these natural forests, our assessment highlights the need for active management of carbon assets in fire-tolerant eucalypt forests under contemporary fire regimes. Decreased live tree carbon and increased reliance on younger cohorts for carbon recovery after high-severity wildfire could increase vulnerabilities to imminent fires, leading to decisions about interventions to maintain the productivity of some stands. Our multi-indicator assessment also highlights the importance of considering all carbon pools, particularly pyrogenic reservoirs like soils, when evaluating the potential for prescribed fire regimes to mitigate the carbon costs of wildfires in fire-prone landscapes.
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ItemFrequent wildfires erode tree persistence and alter stand structure and initial composition of a fire-tolerant sub-alpine forest(WILEY, 2017-11)QUESTION: Frequent severe wildfires have the potential to alter the structure and composition of forests in temperate biomes. While temperate forests dominated by resprouting trees are thought to be largely invulnerable to more frequent wildfires, empirical data to support this assumption are lacking. Does frequent fire erode tree persistence by increasing mortality and reducing regeneration, and what are the broader impacts on forest structure and understorey composition? LOCATION: Sub‐alpine open Eucalyptus pauciflora forests, Australian Alps, Victoria, Australia. METHODS: We examined tree persistence and understorey composition of E. pauciflora open forests that were unburned, burned once, twice or three times by high‐severity wildfires between 2003 and 2013. At each of 20 sites (five per fire frequency class) we assessed extent of top‐kill and mortality of eucalypt clumps, spatial configuration of surviving and dead clumps, densities of new and lignotuberous eucalypt seedlings, and shrub and grass cover. RESULTS: At least 2 yr after the last wildfire, proportions of top‐killed E. pauciflora stems were significantly higher, and densities of live basal resprouts significantly lower, at sites burned two or three times compared to once burned or unburned sites. Clump death increased to 50% of individuals at sites burned by three short‐interval wildfires, which led to changes in live tree patchiness, as indicated by nearest‐neighbour indices. Increased tree mortality was not offset by seedling recruitment, which was significantly lower at the twice‐ and thrice‐burned sites relative to single‐burn sites – although seedling recruitment was also influenced by topography and coarse woody debris. In addition to changes in the tree layer, the prominence of understorey shrubs was substantially reduced, and the frequency of grasses markedly increased, after two, and particularly three wildfires. CONCLUSIONS: Our study provides strong empirical evidence of ecologically significant change in E. pauciflora forests after short‐interval severe wildfires, namely, erosion of the persistence niche of resprouting trees, and a shift in understorey dominance from shrubs to grasses. Our findings highlight the need to consider the impacts of compounded perturbation on forests under changing climates, including testing assumptions of long‐term persistence of resprouter‐dominated communities.
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ItemTesting the generality of above-ground biomass allometry across plant functional types at the continent scale(WILEY, 2016-06)Accurate ground-based estimation of the carbon stored in terrestrial ecosystems is critical to quantifying the global carbon budget. Allometric models provide cost-effective methods for biomass prediction. But do such models vary with ecoregion or plant functional type? We compiled 15 054 measurements of individual tree or shrub biomass from across Australia to examine the generality of allometric models for above-ground biomass prediction. This provided a robust case study because Australia includes ecoregions ranging from arid shrublands to tropical rainforests, and has a rich history of biomass research, particularly in planted forests. Regardless of ecoregion, for five broad categories of plant functional type (shrubs; multistemmed trees; trees of the genus Eucalyptus and closely related genera; other trees of high wood density; and other trees of low wood density), relationships between biomass and stem diameter were generic. Simple power-law models explained 84-95% of the variation in biomass, with little improvement in model performance when other plant variables (height, bole wood density), or site characteristics (climate, age, management) were included. Predictions of stand-based biomass from allometric models of varying levels of generalization (species-specific, plant functional type) were validated using whole-plot harvest data from 17 contrasting stands (range: 9-356 Mg ha(-1) ). Losses in efficiency of prediction were <1% if generalized models were used in place of species-specific models. Furthermore, application of generalized multispecies models did not introduce significant bias in biomass prediction in 92% of the 53 species tested. Further, overall efficiency of stand-level biomass prediction was 99%, with a mean absolute prediction error of only 13%. Hence, for cost-effective prediction of biomass across a wide range of stands, we recommend use of generic allometric models based on plant functional types. Development of new species-specific models is only warranted when gains in accuracy of stand-based predictions are relatively high (e.g. high-value monocultures).
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ItemPredicted consequences of increased rainfall variability on soil carbon stocks in a semiarid environment(INTER-RESEARCH, 2016)Research on the impacts of climate change on soil organic carbon (SOC) stocks has focused on the effects of changes in average climate, but the potential effects of increased climate variability, including more frequent extreme events, remain under-examined. In this study, set in a semiarid agricultural landscape in southeastern Australia, we used the Rothamsted carbon (RothC) model to isolate the effects of interannual rainfall variability on SOC stocks over a 50 yr period. We modelled SOC trends in response to 3 scenarios that had the same 50 yr average climate but different interannual rainfall distributions: non-changing average climate, historic variability (H), and increased variability due to more frequent extreme rainfall years (XH). Relative to the non-changing average climate, RothC simulations predicted net decreases in mean SOC stocks to 50 yr of 11% under the H scenario and 13% under the XH scenario. These decreases were the result of predicted SOC decreases (and increased CO2 emissions) in extreme wet years (ca. 0.26 Mg ha(-1) yr(-1)) that were not counterbalanced by SOC increases in extreme dry years (ca. 0.11 Mg ha(-1) yr(-1)). No significant difference in mean SOC stocks at 50 yr between the H and XH scenarios was likely due to an increase in both extreme wet and counterbalancing extreme dry years in the latter. Strong negative correlations were found between annual changes in SOC stocks and rainfall. Our modelled predictions indicate the potential for extreme rainfall years to influence SOC gains and losses in semiarid environments and highlight the importance of maintaining plant inputs in these environments, particularly during extreme wet years.
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ItemPsychological values and cues as a basis for developing socially relevant criteria and indicators for forest management(Elsevier BV, 2017-05-01)Criteria and indicators (C & I) have proven an essential tool for managers implementing sustainable forest management, but have been less effective for communication with the wider community. We demonstrate a new bottom-up approach to developing socially relevant C & I using social analysis and psychology-based concepts and methods. Our conceptual framework links the concepts of valued attributes and environmental cues with, respectively, criteria and indicators. We illustrate our approach using thirty-six semi-structured interviews of individual members of the general public and of stakeholder groups in Victoria, southern Australia. The interviews included a modified cognitive mapping task to identify attributes of forests valued by the interviewees, as well as cues used by them to know if a valued attribute was present or had changed. Seven broad valued attributes of forests were identified: Natural; Experiential; Productive; Setting; Social/Economic; Learning; and Cultural. Four broad categories of cues were identified: Biophysical; Social/Psychological; Economic; and Management/Planning. Cues were translated into a set of measurable ‘socially relevant’ indicators of forest management. Comparison with existing frameworks revealed some similarities, but that an important component of public evaluations, Experiential and Setting valued attributes, was largely absent from C & I used in Victoria, which are based on the Montreal Process framework. Some socially relevant indicators aligned with existing indicators, but others were poorly represented, particularly sensory indicators that are concerned with subjective experiences of forests. Our approach demonstrates a new way of developing C & I and has a strong conceptual basis that enables more explicit consideration and communication of a comprehensive range of social values and cues in environmental management systems.