Assessment of River-Flat Eucalypt forest on Coastal floodplains TEC on NSW Crown Forest Estate

The operational map for River-flat Eucalypt Forest (RFEF) was constructed to resolve long-standing issues surrounding its identification, location and extent within the NSW State Forest estate covered by the coastal Integrated Forestry Operation Agreements. The map was constructed in two parts, with State Forests to the north of Sydney being mapped in a separate process to those to the south of Sydney. We did this to minimise the risk that relationships between regional vegetation communities and the TEC would be confounded or masked by geographical variation or other major ecological gradients, which might otherwise be a significant risk if we had treated the full latitudinal range of the TEC as a single study area. In total, we assessed 1,218,000 hectares of State Forest across coastal NSW. This consisted of 868,000 hectares of State Forest on the north coast and more than 350,000 hectares of State Forest on the south coast. \r\nIn both study areas, the project’s Threatened Ecological Community (TEC) Reference Panel (the Panel) preceded the assessment process by reviewing the determination for RFEF and agreeing upon a set of diagnostic parameters for its identification. The Panel found that RFEF is primarily defined by floristic plot data and that it is mostly located on coastal floodplains and associated alluvial landforms.\r\nFollowing on from these conclusions, we started the mapping process by mapping the distribution of floodplains and alluvial soils and thus identifying possible areas of RFEF. For both the north and the south coast we used an existing map of coastal landforms and geology in combination with several fine-scale models of alluvial landform features to determine the likely extent of floodplains and alluvial soils within our study areas.\r\nWe used aerial photograph interpretation (API) to assess the floristic and structural attributes of the vegetation cover found on our modelled alluvial environments, and thus delineated polygons likely to contain RFEF. We also used API to modify the boundaries of the modelled alluvial areas using a prescribed list of eucalypt, casuarina and melaleuca species in combination with the interpretation of landform elements relevant to alluvial and floodplain environments.\r\nWe then compiled floristic plot data for all State Forest areas within our modelled alluvial landforms and API polygons. For both the north and the south coast 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 compared these plots with those previously assigned to flora communities listed in the determination of RFEF. Both dissimilarity-based methods and multivariate regression methods were used for the comparison. The results of the comparison were then used to assess the likelihood that the plots in State forests belonged to one or more of the communities listed in the RFEF determination.\r\nFollowing this, we developed a predictive statistical model of the probability of occurrence of RFEF using plot data and a selection of environmental and remote-sensing variables. For the north coast, we used a Random Forest model, while for the south coast we used a Boosted Regression Tree model.\r\nTo create the operational map, we assigned every mapped API polygon to RFEF if appropriate based on the plot data, over-storey and understorey attributes, landform features and modelled probabilities underlying each API polygon. \r\nWe mapped 3819 hectares of RFEF on the south coast and 198 hectares of RFEF on the north coast.\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.

本研究构建了河岸桉树林（River-flat Eucalypt Forest, RFEF）的运营地图，旨在解决沿海综合林业运营协议覆盖的新南威尔士州（NSW）国有林领地内，该群落的识别、空间定位与分布范围长期存在的争议问题。
该地图分为两部分制作：悉尼以北的国有林与悉尼以南的国有林采用独立的制图流程。此举旨在尽可能降低区域植被群落与受威胁生态群落（Threatened Ecological Community, TEC）之间的关联因地理变异或其他重大生态梯度而被混淆或掩盖的风险——若将该TEC的完整纬度范围作为单一研究区域，此类风险将显著提升。
本次研究共评估了新南威尔士州沿海区域总计121.8万公顷的国有林，其中北海岸国有林面积达86.8万公顷，南海岸国有林面积超过35万公顷。
在两个研究区域中，本项目的受威胁生态群落（TEC）专家咨询组先于评估流程开展工作，对RFEF的划定标准进行审议，并确定了一套用于识别该群落的诊断参数。专家组认定，RFEF主要以植物区系样地数据为界定依据，且其分布区域多集中于沿海洪泛平原及相关冲积地貌之中。
基于上述结论，本研究首先绘制了洪泛平原与冲积土壤的分布范围，以此初步圈定RFEF的潜在分布区域。针对南北两岸，研究团队均采用已公开的沿海地貌与地质地图，结合多套高精度冲积地貌特征模型，以确定研究区域内洪泛平原与冲积土壤的可能范围。
研究团队通过航空影像解译（Aerial Photograph Interpretation, API），对模拟冲积环境中的植被覆盖的区系与结构特征开展评估，进而勾绘出可能包含RFEF的多边形区域。同时，研究团队还依据规定的桉属、木麻黄属与白千层属物种名录，并结合冲积与洪泛平原相关的地貌要素解译结果，对模拟冲积区域的边界进行修正。
随后，研究团队对模拟冲积地貌及航空影像解译多边形覆盖的所有国有林区域的植物区系样地数据进行整理。南北两岸的植物区系样地数据均来源于新南威尔士州环境与遗产部（OEH）VIS数据库中的现有植被调查，以及为本项目专门开展的针对性植被调查。研究团队将这些样地数据与此前在RFEF划定标准中收录的植物群落样地进行比对，比对过程同时采用了基于相异性的方法与多元回归方法。基于比对结果，研究团队进而评估国有林内的样地归属RFEF划定标准所列某一类或多类植物群落的可能性。
在此基础上，研究团队利用样地数据及筛选后的环境与遥感变量，构建了RFEF发生概率的预测统计模型。其中北海岸采用随机森林（Random Forest）模型，南海岸则采用提升回归树（Boosted Regression Tree）模型。
为最终生成运营地图，研究团队结合样地数据、乔灌层属性、地貌特征及各航空影像解译多边形对应的模拟发生概率，将符合条件的所有航空影像解译多边形划归为RFEF分布区域。
本次研究最终在南海岸勾绘出3819公顷的RFEF分布范围，北海岸则为198公顷。
本研究针对洪泛平原濒危生态群落（Endangered Ecological Community, EEC）开展的TEC运营制图，采用ADS40传感器获取的50厘米像素分辨率影像，结合1米分辨率激光雷达数字高程模型（DEM）栅格数据，通过航空影像解译完成，解译观测比例尺设定为1:4000。