The multiple communities of low-carbon transition: an assessment of communities involved in forest carbon measurement

In recent writing on sociotechnical transitions theory communities are mostly conceived of as being local and place-based (“grassroots”). In this paper the implications for sociotechnical transitions theory of having multiple communities operating at different geographical scales, and with different objectives, are examined through a case study of low-carbon innovation in forests. The focus of analysis is the communities promoting sociotechnical innovations in the measurement of forest carbon. Innovation is being driven by the international United Nations climate policy initiative “Reducing Emissions from Deforestation and forest Degradation” (REDD+). The rise of REDD+ policy has prompted a flurry of activity in related scientific research, especially in the field of remote sensing. But other types of community are also actively positioning themselves as experts in forest carbon measurement: there are multiple communities at work, each with varying claims to innovation and expertise, from local (place-based) forest communities to international communities of foresters and forest ecologists. Recognition of the multiple communities operating within sociotechnical systems usefully draws our attention to the politics of innovation.     

Streamside Management Zones Compromised by Stream Crossings,Legacy Gullies,and Over‐Harvest in the Piedmont

Streamside management zone (SMZ) breakthroughs were identified and characterized to determine frequency and potential causes, in order to provide enhanced guidance for future water quality protection. Ten kilometers of SMZs were carefully examined for partial or complete breakthroughs. With partial breakthroughs the SMZ trapped sediment before it reached the stream, while complete breakthroughs appeared to have allowed sediment to have passed through with minimal restriction. A total of 41 breakthroughs occurred (33 complete, 8 partial) across 16 sites, averaging 1 complete breakthrough per 0.3 km of SMZ length. The most common complete breakthroughs were caused by stream crossings (42%), reactivation of legacy agricultural gullies (27%), and harvest related soil disturbances near/within SMZs (24%). Pearson correlations of site characteristics at breakthroughs indicated no strong relationships between breakthrough sites, representing the variable nature of these unique circumstances. Stream crossings are an intentional breakthrough for access purposes, but resulting environmental impacts can be reduced with best management practice implementation. Current recommendations for SMZs tend to work in most situations, yet further research is needed to identify causal factors and quantify breakthrough severity.     

华西雨屏区典型人工林对降雨过程中NH_4~+-N和NO_3~--N的过滤作用

氮沉降已成为河流、湖泊及城市等生态系统的主要污染威胁因素之一,森林生态系统能从林冠、地被和土壤自上而下截留过滤大气降雨中的NH+4-N和NO-3-N,是区域大气环境污染生态防治的重要途径.选取华西雨屏区几种典型人工林森林生态系统为研究对象,采用定位监测与室内分析相结合的研究方法,于2011年4—12月对大气降水、穿透雨、树干茎流、地表径流和地下渗滤NH+4-N和NO-3-N的含量与分配进行了研究.结果表明:观测期内40次降雨总雨量为492.72 mm,NH+4-N和NO-3-N的总沉降量分别为13.248 kg·hm-2和16.320 kg·hm-2;3种人工林林冠层对NH+4-N和NO-3-N的过滤能力表现为香樟林混交林柳杉林,而地表和土壤层均表现为混交林香樟林柳杉林;无林地、香樟林、柳杉林和混交林生态系统无机氮截留过滤净输入量分别为19.557、44.079、42.331、64.896 kg·hm-2,对无机氮的综合过滤作用表现为混交林香樟林柳杉林无林地.这些结果说明华西雨屏区合理配置混交林能更加有效地降低大气氮沉降对生态系统的影响.     

龙山县生态公益林建设与管理现状及对策

简述了龙山县生态公益林建设与管理的现状,剖析了新时期发挥生态公益林的生态、社会效益与提高林农收入矛盾,分析了龙山县生态公益林建设与管理中存在的问题,提出了龙山县实现生态公益林生态、社会效益与提高林农收入的措施.参4.     

A fungal perspective on conservation biology

Hitherto fungi have rarely been considered in conservation biology, but this is changing as the field moves from addressing single species issues to an integrative ecosystem‐based approach. The current emphasis on biodiversity as a provider of ecosystem services throws the spotlight on the vast diversity of fungi, their crucial roles in terrestrial ecosystems, and the benefits of considering fungi in concert with animals and plants. We reviewed the role of fungi in ecosystems and composed an overview of the current state of conservation of fungi. There are 5 areas in which fungi can be readily integrated into conservation: as providers of habitats and processes important for other organisms; as indicators of desired or undesired trends in ecosystem functioning; as indicators of habitats of conservation value; as providers of powerful links between human societies and the natural world because of their value as food, medicine, and biotechnological tools; and as sources of novel tools and approaches for conservation of megadiverse organism groups. We hope conservation professionals will value the potential of fungi, engage mycologists in their work, and appreciate the crucial role of fungi in nature. Una Perspectiva Micótica de la Biología de la Conservación     

基于缓冲区重采样的LSTM林火预测模型*

为提高林火风险预测精度,挖掘地图上隐含的空间信息、时间序列上隐含的长期趋势和循环波动,提出1种基于缓冲区重采样的长短期记忆（LSTM）林火预测模型,选取15个与林火相关的影响因素,以方差膨胀因子为评价指标对其进行多重共线性检验,方差膨胀因子大于10的因素具有共线性,并采用信息增益率验证筛选结果的合理性。考虑到火灾的空间聚集特性,采用缓冲区分析与过采样相结合方法减少样本不均衡现象的影响,最终得到176 732条样本。对12个影响因素和研究时间段的火点建立LSTM预测模型,对森林火灾发生风险进行预测。研究结果表明:基于缓冲区重采样的LSTM林火预测模型有效考虑时空上隐含的信息,预测模型准确率为87.06%,特异性为97.99%,敏感度为76.12%,阳性预测率为97.43%,阴性预测率为80.41%,ROC曲线与AUC值均优于随机森林（RF）和支持向量机（SVM）这2种基准算法。维尔克松秩和检验发现,本文提出的模型与基准算法结果具有显著性差异。研究结果可为提高林火风险预测精度提供参考。     

森林保险支付意愿及影响因素分析——基于异质性营林主体视角

基于期望效用函数理论分析了异质性营林主体的森林保险支付意愿及差异,并以传统小林农和新型林业经营主体为研究对象,以福建省382户传统小林农和88户新型林业经营主体的调研数据为基础,综合运用条件估值法、卡方检验及Cox比例风险模型,对异质性营林主体的森林保险支付意愿与差异及支付意愿影响因素进行对比与分析。研究表明：传统小林农和新型林业经营主体的森林保险意愿支付水平存在显著差异,在1000~2500元/亩保障水平下,传统小林农的意愿支付水平分别为1.911元/亩、2.941元/亩、3.532元/亩及3.979元/亩,新型林业经营主体为1.632元/亩、3.971元/亩、5.809元/亩及6.864元/亩;两类营林主体的支付意愿均随保额的提高而提高,但新型林业经营主体的提升幅度远高于小林农。异质性营林主体的森林保险支付意愿影响因素也存在明显差别,这与其在森林保险认知特征、林业生产经营特征、林业灾损特征、森林保险产品评价特征等方面存在显著差异有关。此外,林地面积对两类营林主体支付意愿均具有显著影响,规模化、集约化的林业生产经营可促进林业经营主体的森林保险愿意支付水平。     

基于变量重要性评分-随机森林的溶解氧预测模型——以深圳湾为例

运用Pearson相关性分析,变量重要性评分和随机森林方法构建了溶解氧（DO）实时预测模型,并以深圳湾为例采用浮标资料预测1,3,6和12h的溶解氧.模型预测结果表明,模型最优的输入条件为pH值,水温,叶绿素a,氧化还原电位和蓝绿藻5个水质指标,1h预报的相关系数在0.9以上,6h预报结果一定程度上可以满足工程要求,但对低溶解氧事件的预报必须在3h以内.     

极端梯度提升与随机森林融合的天然气露点预测方法

目的 解决目前水露点数据多为人工采用测量仪器测得,时效性低且成本高昂的问题。方法 建立一种基于极端梯度提升(XGBoost)和随机森林(RF)的天然气水露点预测方法。采用XGBoost方法对所有监测工艺参数进行分析,筛选出主要影响水露点的关键工艺特征参数,以排除无关特征参数对预测的干扰。建立RF预测模型,输入关键特征集参数,实现对水露点的实时预测。以重庆气矿某脱水监测系统监测数据与生产数据为例,对所提预测方法进行对比分析验证。结果 相较于XGBoost、SVM等预测方法,RF模型具有最佳的预测性能,且经过XGBoost特征选择后,RF预测结果的MAE值降低了0.016 9 ℃,RMSE值降低了0.014 6 ℃。结论 基于极端梯度提升与随机森林融合的水露点预测方法具有更优的预测精度与鲁棒性,对指导脱水现场生产具有积极作用。     

多尺度分割与特征优选下的盐碱地提取

土地盐渍化作为一种土壤灾害,严重制约着社会经济与农业的发展。对盐碱地进行实时监测,可为盐碱地的评价改良提供科学依据。由于盐碱地的信息复杂、提取精度不高,因此本文以高分六号（GF-6）卫星遥感影像为数据源,采用分形网络演化算法（fractal net evolution approach,FNEA）进行影像对象的多尺度分割,从面向对象的角度减少高分影像分类结果中的椒盐噪声问题,通过计算图像对象的局部方差和变化率来确定适宜的盐碱地分割尺度。利用基于特征选择的相关性算法（correlations-based feature selection,CFS）与Relief F算法分别对由光谱、纹理、形状、遥感指数构成的初始特征空间进行特征优选,精简特征子集,解决特征数量冗余问题,以此来优化随机森林对盐碱地提取精度。结果表明：CFS约简后的特征子集更小,精度更高,说明在盐碱地提取过程中,筛选特征数目能够减小冗余数据对提取精度的影响。CFS优化后的随机森林对盐碱地的提取效果较好,该方法总体分类精度达到83.7%。