Our aim was to quantify the effects of forest plantation and management (clear cut or 30% partial harvest) in relation to pasture, on catchment discharge in southeast Rio Grande do Sul state, Brazil. A paired-catchment approach was implemented in two regions (Eldorado do Sul and Sao Gabriel municipalities) where discharge was measured for 4 years at three catchments in each region, two of which were predominantly eucalypt plantation (mainly Eucalyptus saligna, rotation of approximately 7-9 years) with native forest and grass in streamside zones. The third catchment was covered with grazed pasture. Weather, soils, canopy interception, groundwater level, tree growth, and leaf area index were also measured. The 3-PG process-based forest productivity model was adapted to predict spatial daily plantation and pasture water balance including precipitation interception, soil evaporation, transpiration, soil moisture, drainage, discharge, and monthly plantation growth. The TOPMODEL framework was used to simulate water pools and fluxes in the catchments. Discharge was higher under pasture than pre-harvesting plantation and increased for 1-2 years after complete plantation harvest; this change was less pronounced in the catchments under partial harvest. The ratio of discharge to precipitation before harvesting varied from 7% to 13% in the eucalypt catchments and 28% to 29% under pasture. The ratio increases to 23-24% after total harvest, and to 17% after partial harvesting. The ratio under pasture also increases during this period (to 32-44%) owing to increased precipitation. The baseflow, in relation to total discharge, varied from 28% to 62% under Eucalyptus and from 38% to 43% in the pasture catchments. Hence, eucalypt plantations in these regions can be expected to influence discharge regimes when compared with pasture land use, and modelling suggests that partial harvesting would moderate the magnitude of discharge variation compared with a full catchment plantation harvesting. The model efficiency coefficient (Nash-Sutcliffe model efficiency coefficient) varied from 0.665 to 0.799 for the total period of the study. Simulation of alternative harvesting scenarios suggested that at least 20% of the catchment planted area must be harvested to increase discharge. This model could be a useful practical tool in various plantation forestry contexts around the world. Copyright (C) 2016 John Wiley & Sons, Ltd.

In recent years CSIRO has been trialling field data collection using mobile devices such as phones and tablets. Two recent tools that have been developed by CSIRO are the CSIRO Surveyor (Post Bushfire House Surveyor) and DroidFarmer. Challenges tackled include mapping field documents to mobile data through QR (Quick Response) codes, rapid input of survey data, accurate capture of GPS locations and offline operation. Throughout this paper we detail the design choices made for these systems. We give details of how well field data collection was performed and discuss our planned future developments in this space.

Models of radiant heat flux (RHF) are critical for understanding wildfire behaviour and the effect a fire may have on homes and people. Various models have been presented in the literature for wildfire RHF, many being based on the Stephan–Boltzmann equation for radiative heat transfer. Most models simplify the fire and receiver interaction by considering a single fuel type at a given separation distance from a receiving point (e.g. on a building requiring protection). However, wildfire is an inherently spatial phenomenon, in that a fire may progress across the landscape towards a building across complex terrain and through spatially varying fuel types. This spatial variation influences the fire behaviour as well as the level of RHF incident on the building. In this study, we present methods for incorporating spatially varying topography and fuels into existing RHF modelling equations. In this way, we achieve a time-dependent profile of the RHF incident on homes, while accounting for attenuation due to fuels and topography that lie between the building and the fire front. The model is applied to the prediction of damage in a fire that occurred in South Australia in 2005. Although only coarse spatial information was available for determining the spatial distribution of fuels, modelled RHF was a significant indicator of house damage. Attenuation due to vegetation between homes and the fire was shown to reduce the modelled RHF exposure of homes. However, this was not shown to increase the significance of predicted house damage in the case of this fire event.

This paper describes the development of vulnerability assessment methods using a new approach to estimate radiant heat flux (RHF) exposure and consequent house response at a landscape scale. The model uses a three dimensional representation of the landscape, house location, vegetation structure based on LiDar data and the landscape scale gridded fire arrival conditions as inputs. The report presents the exploratory implementation of the approach on the Pine Ridge Road region affected by the 7th of February 2009 bushfire in Victoria. The 3D RHF ray tracing model provides a more robust prediction of house loss through bushfire, provided the approach direction can be determined.

The theoretical potential for carbon forests to off-set greenhouse gas emissions may be high but the achievable rate is influenced by a range of economic and social factors. Economic returns (net present value, NPV) were calculated spatially across the cleared land area in Australia for ‘environmental carbon plantings’. A total of 105 scenarios were run by varying discount rate, carbon price, rate of carbon sequestration and costs for plantation establishment licenses for water interception. The area for which NPV was positive ranged from zero ha for tightly constrained scenarios to almost the whole of the cleared land (104 M ha) for lower discount rate and highest carbon price. For the most plausible assumptions for cost of establishment and commercial discount rate, no areas were identified as profitable until a carbon price of AUD$40 t CO2 −1 was reached. The many practical constraints to plantation establishment mean that it will likely take decades to have significant impact on emission reductions. Every 1 M ha of carbon forests established would offset about 1.4 % of Australia’s year 2000 emissions (or 7.4 Mt CO2 year−1) when an average rate of sequestration per ha was reached. All studies that predict large areas of potentially profitable land for carbon forestry need to be tempered by the realities that constrain land use change. In Australia and globally, carbon plantings can be a useful activity to help mitigate emissions and restore landscapes but it should be viewed as a long-term project in which co-benefits such as biodiversity enhancement can be realised.

Wildland and wilderness refer to areas of land which have been subject to little or no modification by human activity. These areas are important due to their role as wildlife habitats, the contributions they make to air and water quality and for human recreation. However, the intermingling of wildland and homes also increases the risk to life and property through wildfires. Management of this risk requires current and detailed knowledge of the spatial extent of wildland. What constitutes wildland vegetation is often difficult to define and may be influenced by both the horizontal continuity and vertical structure. We present a method to map wildland vegetation based on a combination of a vertically stratified cover threshold and spatial morphology. To test its practical application, the method was applied to airborne lidar data collected prior to a major wildfire that occurred in Australia in 2009. Distance between the lidar defined wildland extent and homes impacted by the fire was assessed and compared to previously published data using manual delineation of wildland extent. Results showed that the proportion of homes destroyed at the wildland boundary was greater than reported in previous fires and that there was an exponential decline in the proportion of homes destroyed as a function of distances to wildland. Although the method is objective the extent of wildland depends on the parameters which define thresholds of cover and lateral extent and connectivity. This highlights the need for a clear definition of wildland that can be used to determine extent using objective methods such as those described, whether this is in the context of quantifying wildfire vulnerability or other related applications such as ecological assessment and monitoring.

Light detection and ranging (LiDAR) from terrestrial platforms provides unprecedented detail about the three-dimensional structure of forest canopies. Although airborne laser scanning is designed to yield a relatively homogeneous distribution of returns, the radial perspective of terrestrial laser scanning (TLS) results in a rapid decrease of number of returns with increasing distance from the instrument. Additionally, when used in forested environments, significant parts of the area under investigation may be obscured by tree trunks and understorey. A possible approach to mitigate this effect is to combine TLS observations acquired at different locations to obtain multiple perspectives of an area under investigation. The denser and more evenly distributed observations then allow a spatially explicit and more comprehensive study of forest characteristics. This study demonstrates a simple approach to combine TLS observations made at multiple locations using bright reference targets as tie-points. Results show this technique was able to accurately combine the different TLS data sets (root mean square error (RMSE): 0.04–0.7 m, coefficient of determination (R 2): 0.70–0.99). Terrain elevations from TLS system were highly correlated with field-measured terrain heights (R 2: 0.70–0.98).

AbstractThis paper describes the procedure developed to select representative experimental catchments to quantify water use and water use efficiency of different vegetation types. We combined freely available information such as LANDSAT satellite images, digital elevation model, Google Earth images, streamflow and rainfall historical data, and soils and vegetation data to select the experimental catchments. Once these catchments were indentified, sub-catchments with different vegetation were delineated, which were used to define the distribution and installation of the instrumentation. Forty eight catchments and respective sub-catchments of Tasmania in Australia were analyzed and only two catchments were identified as ideal for the purposes of quantifying and comparing the historic and current water use by Eucalyptus plantation, native forest and pasture. We choose one catchment and created four experimental and instrumented sub-catchments with the following predominant land use: Eucalyptus nitens, native forest and pasture. ResumoO presente artigo descreve o procedimento desenvolvido para selecionar microbacias representativas para quantificar o uso de água e a eficiência do uso de água de diferentes tipos de vegetação. Foram combinadas informações disponíveis sem custo tais como: imagens de satélite LANDSAT, modelo digital do terreno, imagens de Google Earth, escoamento superficial e dados históricos de precipitação pluviométrica, tipos de solos e cobertura vegetal para a seleção de microbacias experimentais. Uma vez identificadas as microbacias, sub-microbacias com diferente tipos de vegetação foram delineadas, as quais foram usadas para definir a distribuição e instalação de instrumentação. Foram analisadas quarenta e oito microbacias e respectivas sub-microbacias na Tasmânia na Austrália e somente duas microbacias foram identificadas como ideais para o propósito de quantificar e comparar o histórico e atual uso de água por plantações de eucalipto, floresta nativa e pastagem. Ao final foi escolhida uma microbacia e quatro sub-microbacias experimentais instrumentadas com o uso de solo predominantemente de Eucalyptus nitens, floresta nativa e pastagem.

Farm forestry is an increasingly important form of diversifying farm income and helping to deal with environmental issues including dryland salinity, global warming and climate variability. Here we briefly describe the development, use and spatial application of improved versions of the plantation growth model, 3-PG, to provide estimates of productivity and carbon sequestration as well as salinity impacts. Several forestry scenarios using eucalypt species and Pinus radiata were tested with application to the Corangamite Catchment in south western Victoria, Australia.

This chapter contains sections titled: Introduction Data Capture and Elevation Modelling Flood Modelling Vegetation Mapping Conclusions References

The area of commercial Eucalyptus plantations has expanded dramatically in many countries during the last three decades, and continues to do so. This is causing concerns about the potential impacts of these plantations on water resources and uncertainty about productivity under different environmental conditions.We present a study where the effects of climate change on the spatial variation in climate are taken into account when predicting potential productivity in terms of dry mass (DM) of wood or mean annual volume of wood increment and water use efficiency (WUE) of hybrids of Eucalyptus grandis and Eucalyptus urophylla plantations across more than 32 million ha located near the Atlantic coast of Brazil. Our main objective was to estimate the effects of future climate and increasing CO2 concentration on planted forests in this region. Predictions of mean annual increment in wood production and of water use efficiency were generated with an updated spatial version of the process-based growth model 3-PG (Landsberg and Waring, 1997). The model has been modified to include the direct effects of increasing levels of atmospheric CO2 on the vegetation. We assume that light saturated assimilation rate and light use efficiency increase as atmospheric CO2 concentration increases, while maximum stomatal conductance declines.The study considered three climatic periods with different CO2 concentrations: the historical scenario has 350 ppm, while the 2030 and 2050 scenarios correspond to 450 ppm and 520 ppm, respectively. Sensitivity analyses quantified the effects of the parameters used in the model to account for the effects of atmospheric CO2 on the predicted forest productivity. Stem mass is strongly sensitive to changes in canopy quantum efficiency, and hence to the effect of CO2 on light use efficiency, but less so to changes in stomatal conductance, and hence to the effect of CO2 on conductance. WUE, defined here as DM of wood per mass of water evapotranspired, is also sensitive to these parameters.Analysis of the climatic data for the 2030 and 2050 scenarios in the study area suggests a reduction of 2% and 3% in annual precipitation and an increase of 8% and 15% in vapour pressure deficit in 2030 and 2050, respectively, compared with the period 1971 to 2000. Application of 3-PG with the 2030 and 2050 climates suggests that, averaged over the study area, forest productivity may increase by of the order of 6 m(3) ha(-1) year(-1) by 2030, and 10 m(3) ha(-1)year(-1) by 2050, corresponding to 17% and 26% increments compared with the historical period. WUE increases by an average of 1.0g DM kg(-1) H2O in 2030 and 1.7 g DM kg(-1) H2O in 2050 compared with the historical scenario, which is equivalent to increases of 29% and 51% in WUE, respectively. This shows that with increasing CO2 the trees are more efficient in using water.If these changes do occur it will increase the amount of land with higher potential productivity for Eucalyptus plantations in the study area. From the total area of 32 million hectares (Mha), 8.5 Mha currently have potential productivity above 40 m(2) ha(-1) year(-1). With increasing CO2 this area increases to 20.5 Mha in 2030 and 26.0 Mha in 2050.

In the wet tropics, near the Atlantic Coast of Brazil, drought may reduce plantation yields by as much one-third over a six-to-seven-year rotation. For land owners, annual variation in production cannot be estimated with empirical models. In this paper, we examine whether the process-based growth model, 3-PG is sufficiently sensitive to climatic variation to provide a virtual record of changes in growing stock across 180,000ha eucalypt plantation estate. We first mapped variation in climate and soil properties, and then ran simulations for the current planted forest with ages varying from one to seven years. Model predictions of stand volume and mean tree diameter agreed closely with measurements acquired on 60 reference plots monitored over the test period; the prediction of mean annual increment (MAI) was less reliable. Available soil water (ASW) and leaf area index (LAI) were also measured and compared with the model estimations. Vapour pressure deficit (VPD) and ASW accounted for most of the variation in yields. We conclude that this spatial modelling approach offers a reasonable alternative to extensive ground surveys, particularly when climatic variation extends beyond the historical average for a region.

Variations in vertical and horizontal forest structure are often difficult to quantify as field-based methods are labour intensive and passive optical remote sensing techniques are limited in their capacity to distinguish structural changes occurring below the top of the canopy. In this study the capacity of small footprint (0.19 cm), discrete return, densely spaced (0.7 hits/m−2), multiple return, Light Detection and Ranging (LiDAR) technology, to measure foliage height and to estimate several stand and canopy structure attributes is investigated. The study focused on six Douglas-fir [Pseudotsuga menziesii spp. menziesii (Mirb.) Franco] and western hemlock [Tsuga heterophylla (Raf.) Sarg.] stands located on the east coast of Vancouver Island, British Columbia, Canada, with each stand representing a different structural stage of stand development for forests within this biogeoclimatic zone. Tree height, crown dimensions, cover, and vertical foliage distributions were measured in 20 m × 20 m plots and correlated to the LiDAR data. Foliage profiles were then fitted, using the Weibull probability density function, to the field measured crown dimensions, vertical foliage density distributions and the LiDAR data at each plot. A modified canopy volume approach, based on methods developed for full waveform LiDAR observations, was developed and used to examine the vertical and horizontal variation in stand structure. Results indicate that measured stand attributes such as mean stand height, and basal area were significantly correlated with LiDAR estimates (r 2 = 0.85, P < 0.001, SE = 1.8 m and r 2 = 0.65, P < 0.05, SE = 14.8 m2 ha−1, respectively). Significant relationships were also found between the LiDAR data and the field estimated vertical foliage profiles indicating that models of vertical foliage distribution may be robust and transferable between both field and LiDAR datasets. This study demonstrates that small footprint, discrete return, LiDAR observations can provide quantitative information on stand and tree height, as well as information on foliage profiles, which can be successfully modelled, providing detailed descriptions of canopy structure.