Assessment of Lowland Grassy Woodland, Brogo Wet Vine Forest And Dry Rainforests of The South East Forests TECs on NSW Crown Forest Estate

Indicative map for Lowland Grassy Woodland:\r\n\r\nThe indicative map for Lowland Grassy Woodland was constructed to resolve long-standing issues surrounding its identification, location and extent within the NSW State Forest estate covered by the eastern Regional Forest Agreements. The determination of Lowland Grassy Woodland was reviewed by the project’s Threatened Ecological Community (TEC) Reference Panel (the Panel), and a set of diagnostic parameters for the identifying the Lowland Grassy Woodland TEC was agreed upon.\r\nUsing these diagnostic parameters, we sampled candidate areas from existing vegetation maps to identify potential areas of Lowland Grassy Woodland occurrence in 296 000 hectares of State Forest and undertook additional mapping work using two independent mapping methods. Random Forest models (predictive habitat models) were generated using plot data and a selection of environmental variables. Aerial photo interpretation targeted stands of forests dominated by Eucalyptus tereticornis to refine the potential boundaries of Lowland Grassy Woodland.\r\nWe tested whether Lowland Grassy Woodland was present in State Forest by completing systematic plot surveys within mapped areas indicating potential presence. We compared our collected data to a large regional pool of plot data that contained a subset of plots assigned to vegetation map units cited in the determination for the Lowland Grassy Woodland TEC (see Gellie 2005, Tozer et al 2006, and Keith and Bedward 1999). Our analysis of data confidently assigned only a few plots in State Forest to Lowland Grassy Woodland (2/43).\r\nFrom these results, we were unable to construct an operational map for Lowland Grassy Woodland. The relationship between the existing mapping cited in the determination and the plot data on State Forest was not strong enough to be a reliable basis for mapping the TEC. We also found that Eucalyptus tereticornis could not reliably be used as an indicator of Lowland Grassy Woodland in State forests. As a result, we were unable to map this TEC from the few confirmed sampling points without including a significant area of forest that was highly unlikely to be Lowland Grassy Woodland. However, we created indicative maps of Lowland Grassy Woodland by merging our predictive and API maps to provide an indication of the likely extent of Lowland Grassy Woodland in State Forests.\r\n\r\nOperational map for Brogo Wet Vine Forest:\r\n\r\nThe operational map for Brogo Wet Wine Forest (BWVF) was constructed to resolve long-standing issues surrounding its identification, location and extent within the NSW State Forest estate covered by the eastern Regional Forest Agreements. We assessed whether BWVF was likely to be present in more than 296 000 hectares of State Forest in the South-east Corner Bioregion.\r\nThe project’s Threatened Ecological Community (TEC) Reference Panel (the Panel) preceded the assessment process by reviewing the determination for BWVF and reaching an agreed interpretation of floristic, environmental and distributional characteristics. The Panel found that BWVF is primarily defined by a source vegetation community derived from quantitative floristic plot data (Keith and Bedward, 1999), with additional defining characteristics relating to bioregion and elevation.\r\nThe Panel’s interpretation resulted in the identification of all State Forests located below an elevation threshold of 550 metres within the South East Corner Bioregion as potentially containing BWVF. We identified other potential areas of BWVF by overlaying the cited vegetation maps and any State Forest mapping where vegetation was dominated by or includes Eucalyptus tereticornis (a defining species of BWVF).\r\nWithin these state forests, we used aerial photo interpretation (API) to identify and delineate potential areas of BWVF based on structural characteristics and overstorey and understorey attributes, namely dominance or inclusion of Eucalyptus tereticornis. \r\nWe then compiled floristic plot data for all State Forest areas within our study area. The floristic plot data was sourced from both existing flora surveys held in the OEH VIS database and from targeted flora surveys conducted specifically for this project. We used multivariate analysis to compare plots assigned to vegetation communities identified as BWVF in the determination to all other plots in the study area. We used explicit membership thresholds to identify whether plots in State forests and elsewhere belonged to one or more of the communities listed in the BWVF determination.\r\nWe used the plot assignments to candidate BWVF to develop a predictive presence and absence Random Forest statistical model. The model generates a probability of occurrence of BWVF for each grid cell using plot data and a selection of environmental and remote-sensing variables. \r\nWe constructed our operational map using the API line work in combination with the floristic plot data and our predictive habitat models to identify and map the locations and extent of BWVF. Our mapping identified six small areas of Brogo Wet Vine Forest totalling 17.5 hectares. All areas were within Bodalla State Forest and were located on the exposed lower slopes of Mount Dromedary.\r\n\r\nOperational map for Dry Rainforest of the South East Forests:\r\n\r\nThe operational map for Dry Rainforest of the South East Forests (Dry Rainforest) was constructed to resolve long-standing issues surrounding its identification, location and extent within the NSW State Forest estate covered by the eastern Regional Forest Agreements. The determination of Dry Rainforest was reviewed by the project’s Threatened Ecological Community (TEC) Reference Panel (the Panel), and a set of diagnostic parameters for the identifying the Dry Rainforest TEC was agreed upon.\r\nUsing these diagnostic parameters, we sampled candidate areas from existing vegetation maps to identify potential areas of Dry Rainforest occurrence in 296 000 hectares of State Forest and undertook additional mapping work using two independent mapping methods. Random Forest models (predictive habitat models) were generated using plot data and a selection of environmental variables. Aerial photo interpretation targeted stands of forests dominated by Ficus rubiginosa to refine the potential boundaries of Dry Rainforest.\r\nWe tested whether Dry Rainforest was present in State Forest by completing systematic plot surveys within mapped areas indicating potential presence. We compared our collected data to a large regional pool of plot data that contained a subset of plots assigned to vegetation map units cited in the determination for the Dry Rainforests TEC (see Keith and Bedward 1999). Our analysis of data confidently assigned only a few plots in State Forest to Dry Rainforest (2/21).\r\nFrom these results, we were able to construct an operational map for Dry Rainforest. We identified six small patches of Dry Rainforest but only one patch was located within the study area. This patch was located in Towamba State Forest and was 0.53 hectares.\r\n\r\nOperational TEC Mapping have been derived by API at a viewing scale between 1-4000 using ADS40 50 cm pixel imagery and 1 m derived LIDAR DEM grids for floodplain EECs.\r\n\r\nIndicative TEC Mapping have been generated from best available composite environmental data layers - standardised to 30 m pixels.\r\n

Lowland Grassy Woodland指示图：

Lowland Grassy Woodland指示图的构建旨在解决东部区域森林协议覆盖的新南威尔士州国有林区内，该群落识别、定位及范围界定方面长期存在的问题。项目的濒危生态群落（Threatened Ecological Community，TEC）参考小组（以下简称“小组”）对Lowland Grassy Woodland的界定标准进行了审核，并商定了一套用于识别该TEC的诊断参数。
基于这些诊断参数，我们从现有植被图中选取候选区域，以识别296,000公顷国有林区内Lowland Grassy Woodland的潜在分布区，并采用两种独立制图方法开展补充制图工作。研究利用样地数据及选定的环境变量构建了随机森林模型（预测生境模型）；同时，针对以细柄桉（Eucalyptus tereticornis）为主的林分进行航空照片解译（Aerial Photo Interpretation，API），以细化Lowland Grassy Woodland的潜在边界。
我们通过在潜在分布区开展系统性样地调查，验证了Lowland Grassy Woodland在国有林区的存在性。将收集到的数据与区域大型样地数据集进行对比——该数据集包含界定中引用的Lowland Grassy Woodland TEC植被图单元对应的样地子集（参见Gellie 2005、Tozer et al 2006及Keith and Bedward 1999）。数据分析结果显示，仅2/43的国有林区样地可明确归为Lowland Grassy Woodland。
基于上述结果，我们无法构建Lowland Grassy Woodland的操作型地图。界定中引用的现有制图与国有林区样地数据间的关联性不足，难以作为TEC制图的可靠依据；同时发现细柄桉无法作为国有林区Lowland Grassy Woodland的可靠指示物种。因此，若仅基于少量确认样点制图，必然会纳入大量极不可能属于Lowland Grassy Woodland的森林区域。不过，我们通过融合预测模型与API制图结果，生成了Lowland Grassy Woodland指示图，以标示其在国有林区的可能分布范围。

Brogo Wet Vine Forest操作图：

Brogo Wet Vine Forest（BWVF）操作图的构建旨在解决东部区域森林协议覆盖的新南威尔士州国有林区内，该群落识别、定位及范围界定方面长期存在的问题。我们评估了BWVF在东南角生物区内296,000公顷以上国有林区的潜在存在性。
项目的濒危生态群落（TEC）参考小组在评估前，对BWVF的界定标准进行了审核，并就植物区系、环境及分布特征达成了一致解读。小组认为，BWVF主要通过定量植物区系样地数据（Keith and Bedward, 1999）定义的源植被群落来识别，同时需结合生物区及海拔等附加界定特征。
基于小组的解读，东南角生物区内海拔低于550米的所有国有林区均被认定为可能包含BWVF的区域。我们通过叠加界定中引用的植被图及所有以细柄桉（BWVF的界定物种）为主或包含该物种的国有林区制图，识别了其他潜在分布区。
在这些国有林区内，我们利用航空照片解译（API），基于结构特征及乔灌层属性（即细柄桉的优势度或存在性）识别并划定了BWVF的潜在区域。
随后，我们汇编了研究区内所有国有林区的植物区系样地数据，数据来源包括新南威尔士州环境与遗产局（Office of Environment and Heritage，OEH）植被信息系统（Vegetation Information System，VIS）数据库中存档的现有植物调查数据，以及为本项目专门开展的针对性植物调查数据。我们采用多变量分析方法，将界定中被认定为BWVF的植被群落样地与研究区内所有其他样地进行对比，并通过明确的成员资格阈值识别国有林区及其他区域的样地是否属于BWVF界定中列出的群落类型。
我们利用被归为BWVF候选群落的样点，构建了随机森林统计模型以预测BWVF的存在与否。该模型通过样地数据及选定的环境与遥感变量，生成每个网格单元的BWVF出现概率。
我们结合API线划数据、植物区系样地数据及预测生境模型，构建了BWVF操作型地图。制图结果识别出6处小型BWVF区域，总面积17.5公顷，均位于Bodalla国有林区内的德罗马德里山裸露低坡。

东南森林干旱雨林操作图：

东南森林干旱雨林（Dry Rainforest）操作图的构建旨在解决东部区域森林协议覆盖的新南威尔士州国有林区内，该群落识别、定位及范围界定方面长期存在的问题。项目的濒危生态群落（TEC）参考小组对干旱雨林的界定标准进行了审核，并商定了一套用于识别该TEC的诊断参数。
基于这些诊断参数，我们从现有植被图中选取候选区域，以识别296,000公顷国有林区内干旱雨林的潜在分布区，并采用两种独立制图方法开展补充制图工作。研究利用样地数据及选定的环境变量构建了随机森林模型（预测生境模型）；同时，针对以锈叶榕（Ficus rubiginosa）为主的林分进行航空照片解译（API），以细化干旱雨林的潜在边界。
我们通过在潜在分布区开展系统性样地调查，验证了干旱雨林在国有林区的存在性。将收集到的数据与区域大型样地数据集进行对比——该数据集包含界定中引用的干旱雨林TEC植被图单元对应的样地子集（参见Keith and Bedward 1999）。数据分析结果显示，仅2/21的国有林区样地可明确归为干旱雨林。
基于上述结果，我们成功构建了干旱雨林操作型地图。识别出6处小型干旱雨林斑块，但仅1处位于研究区内，即Towamba国有林区内的0.53公顷斑块。

操作型TEC制图通过API生成，观测比例尺介于1:1至1:4000之间；洪泛区濒危生态群落（Endangered Ecological Community，EEC）制图使用了ADS40型50厘米像素分辨率影像及1米分辨率激光雷达数字高程模型（Digital Elevation Model，DEM）格网。

指示型TEC制图基于现有最优复合环境数据层生成，已标准化为30米像素分辨率。