中国镉超富集植物的物种、生境特征和筛选建议

植物修复作为一项绿色且有效的原位修复重金属污染土壤技术,在近20年引起了中国学者的关注并取得了一系列成果.通过检索镉超富集植物相关关键词,对过去20 a(2002～2021年)科技文献中报道的中国镉超富集植物的物种特征、野外发现地在中国各植被地带的分布、原生境特征、地质特征和镉的地球化学进行归纳总结,为镉超富集植物的筛选提供建议.结果表明,目前报道的镉超富集植物有45种.在植物物种上,隶属22科,36属,其中菊科(Compositae)植物最多,为14种.由野外调查发现的镉超富集植物有25种,主要发现于亚热带常绿阔叶林区域,其主要生长于铅锌矿周围的高浓度镉土壤上.归纳总结发现,丰富的植物物种资源、高浓度重金属土壤和长时间的驯化共同促进了超富集植物的形成.因此,具备这3点的区域可以视为超富集植物存在的高概率区域,并且超富集植物的野外筛选可以围绕此展开.最后,提出可以通过高概率区域识别和调查、富集能力验证、富集能力逆境习得筛查、生态型筛查、继代遗传检验和修复能力验证这6步,来进行超富集植物的筛选和植物超富集能力的鉴定.     

中国居民消费碳排放影响因素的时空异质性

研究我国居民消费间接碳排放的阶段性和区域性特征,对于制定社会经济新常态发展下的碳减排策略具有重要的现实意义.利用投入产出法和结构分解分析法,核算了2002~2017年中国居民消费间接碳排放水平,量化了影响因素对间接碳排放的贡献;利用地理加权回归模型定量描述了省域间接碳排放的时空分异特征.结果显示:2002~2017年中国居民消费间接碳排放呈现先增长后下降的趋势,“食品”类和“居住”类消费是其主要来源,占比42%~48%.新常态下,“直接碳排放强度”、“生产技术”和“消费倾向”因素的抑制作用显著加强,大大抵消了“收入规模”、“人口”及“消费结构”因素对碳排放的促进作用,促使碳排放降低了145MtC.省域间接碳排放从东至西呈现递减的分布特征,表现出一定的集聚性.碳排放的影响因素具有空间异质性,“生产技术”与碳排放呈现负相关关系,其他因素呈现正相关关系.其中,“人口”、“收入规模”及“直接碳排放强度”对碳排放的影响程度较为突出.     

扎龙湿地丹顶鹤繁殖栖息地的选择及扩散

景观演变对野生动物栖息地质量和连接度造成的影响,一直是威胁全球生物多样性保护的关键问题,开展扎龙湿地丹顶鹤（Grus japonensis）繁殖栖息地选择及繁殖期生境间的扩散研究,对野生丹顶鹤的保护具有重要的意义。首先利用需要“出现点”的生态位MAXENT模型,进行适宜栖息地选择研究。从水源、食物、干扰、隐蔽物四个方面选择明水面距离、土壤湿度、NDVI、道路距离和居民地距离五个环境变量作为丹顶鹤繁殖栖息地选择的影响因子,预测扎龙保护区可供丹顶鹤进行营巢繁殖的栖息地分布,并分析各影响因子的反应曲线。结果显示：丹顶鹤易于选择远离道路和居民地干扰且靠近明水面的区域作为营巢栖息地,栖息地土壤湿度较高并且植被覆盖较多。从MAXENT模型中提取了38个适宜栖息地斑块,基于电路理论模拟丹顶鹤繁殖期失去飞行能力时的多路径扩散,最大电流密度图突出了可能的“夹点”,模拟出具有一定宽度范围的连接区域,可供丹顶鹤在繁殖期间进行扩散。累积电流密度图突出了在维持网络连通性方面起到积极作用的斑块,并进行面积加权来评估适宜栖息地斑块的综合重要性。结果表明,在MAXENT模型预测出的适宜栖息地斑块基础上,考虑丹顶鹤繁殖期的迁移扩散行为,利用累积电流密度面积加权来评估适宜栖息地斑块的综合重要性,得到的适宜性等级更符合丹顶鹤真实巢址的分布。研究成果可为保护区丹顶鹤栖息繁殖生境的恢复和保护提供科学依据。     

河道型水库溶解甲烷浓度的空间异质性研究

以河道型水库-西北口水库为研究对象,于2021年12月采用新型快速水-气平衡装置（FaRAGE）结合温室气体分析仪对其表层水体,垂向剖面溶解甲烷（CH₄）浓度进行监测,并采集代表性河段表层水体及库底沉积物,分别测定水体CH₄氧化速率与沉积物CH₄释放速率,初步探讨了河道型水库溶解CH₄浓度的空间异质性及其影响因素.结果表明,水库表层水体溶解CH₄浓度为0.02~0.42μmol/L （平均值为0.11±0.08μmol/L）,从库首到库尾呈递增趋势;水体溶解CH₄浓度的空间异质性受水库内部CH₄产生,消耗及河道入流等多因素的综合作用,其中库尾水体因沉积物CH₄产生量大且低水深影响下CH₄消耗量较小而呈现高溶解浓度,库首水体则因为CH₄产生量相对较小且高水深影响下的CH₄消耗量较大而呈低溶解浓度;同时,河道入流可能是影响水体溶解CH₄浓度垂向分层的原因之一.     

云南边境五城市空气污染物分布特征

利用2015~2021年云南省5个边境城市6种常规大气污染物的质量浓度数据,探究其污染特征、时空变化及空间异质性。结果表明,研究区域污染物年际浓度变化起伏较大,PM₁₀、PM_2.5年均浓度分别为(42.6±8.2),(25.4±4.2)µg/m³,均低于中国《环境空气质量标准》(GB 3095-2012)二级浓度限值。PM、NO₂和O_3-8h月均浓度呈U型变化趋势,其中3月份浓度最高。5个城市PM和NO₂浓度季节变化均表现为:春季>冬季>秋季>夏季,O_3-8h表现为:春季>夏季>秋季>冬季,而CO冬季污染程度最小,SO₂无明显的季节变化规律。根据Sen-MK的逐日浓度趋势分析,污染物总体呈现下降趋势,其中PM₁₀下降速率最高达11×10^-3µg/(m³×d),而O_3-8h呈现上升趋势。变异系数(COD)表明,污染物的空间分布极不均匀,特别是SO₂的COD均大于0.2,春季O_3-8h空间分布更加均匀。Person相关分析表明,PM与NO₂、CO、O_3-8h表现出较强的相关性,且西双版纳(BN)PM与其他大气污染物相关性较其他城市强。     

不同取样尺度和数量下针阔混交林土壤呼吸的空间异质性

区域土壤呼吸通量估算大多用样地尺度的测定结果进行外推,因此对样地尺度土壤呼吸(Rs)及其影响因子的空间关系和取样尺度、取样数量对测定结果的准确性进行评价非常重要.以山西省庞泉沟自然保护区针阔混交林作为研究样地,运用传统统计分析与地统计分析相结合的方法,分析了4、2、1 m取样尺度下土壤水分(Ws)、土壤温度(T10)、凋落物量(Lw)、凋落物含水量(Lm)、土壤全碳(C)、全氮(N)和全碳/全氮(C/N)对土壤呼吸速率(Rs)空间变异的影响.结果表明3个取样间隔下,Rs的均值没有显著差异,但其变异程度随着取样尺度的增大而增加,变异系数在16%~22%之间.在4 m取样间隔下,Rs与Ws、Lw、C、C/N呈极显著正相关(P0.01),与N呈显著正相关(P0.05);在2 m取样间隔下,Rs与T10呈极显著负相关(P0.01),与其他因子相关不显著;在1 m取样间隔下,Rs与其他影响因子的相关性都不显著.随着取样尺度的减小,Rs的空间自相关性逐渐减弱,由高度自相关变为弱相关,表明随着采样距离的减小,结构因素对Rs的作用减弱,随机因素的作用逐渐增大.同一置信水平下相同取样数量随着取样尺度的减小,估计误差降低.95%置信水平下,2 m和1 m取样尺度时9个样本产生的Rs误差在±12%左右,而4 m尺度的误差为±16%;90%置信水平下,2 m和1 m取样尺度时9个样本产生的误差在±10%以内,4 m尺度则为±13%.研究结果可以为样地尺度进行Rs季节测定样点的科学布设提供依据.     

大湘西高级别景区时空分布特征及影响因素的空间异质性

旅游景区既是旅游业发展的先决条件和核心载体,也是最主要和最根本的旅游供给。基于大湘西高级别旅游景区数据,引入高级别景区发展差异指数,运用标准差椭圆分析法、核密度估计、全局空间自相关等多种空间统计方法,对2007年、2012年和2016年大湘西高级别旅游景区时空分布特征进行测度,并运用全局回归（OLS）模型和地理加权回归（GWR）模型,分析大湘西高级别景区影响因素的空间异质性。结果表明：大湘西高级别景区空间分布总体走向为东北—西南方向,且整体呈现小幅度逆时针旋转;高级别景区空间分布格局呈现出由“三核心两区县”向“一极多点”再到双核带动的“遍地开花型”空间格局的演化;高级别景区数量的空间正相关性不断减弱,且其在空间上的分布呈现一定的集聚特征;区域经济发展水平、政府政策扶持力度、交通条件、旅游资源因素对大湘西高级别景区空间分布格局影响显著,且不同影响因素呈现出一定的空间异质性。研究结论可为全域旅游背景下深化旅游景区体制机制改革提供科学依据和参考价值。     

An ecological model of the habitat mosaic in estuarine nursery areas: Part I—Interaction of dispersal theory and habitat variability in describing juvenile fish distributions

Identification of critical habitat in estuarine nursery areas is an important conservation and management objective. Habitat can be viewed as a mosaic of both temporally variable environmental features and spatially variable structural features that combine to define optimal habitat. Effective models of juvenile distributions should account for individual movement, as well as the full suite of habitat variability including both spatial and temporal components. We have extended a terrestrial model of small-scale movement patterns to describe habitat choices of an index juvenile fish in an estuarine nursery system. Movement of small juvenile fishes was found to be influenced by both spatial and temporal patterns in habitat quality, and it was a balanced mix of both that resulted in an optimal distribution. Fishes that perceive habitat on a scale much smaller than the scale of spatial heterogeneity may respond to temporal change as a movement cue allowing for more deterministic outcomes at larger scales despite perceptual limitations. These model outcomes suggest a hierarchical approach is best for describing habitat choice in juvenile fishes and this approach will be used in the future to explore individual and population responses to predictable habitat change.     

A novel method for mapping reefs and subtidal rocky habitats using artificial neural networks

Reefs and subtidal rocky habitats are sites of high biodiversity and productivity which harbour commercially important species of fish and invertebrates. Although the conservation management of reef associated species has been informed using species distribution models (SDM) and community based approaches, to date their use has been constrained to specific regions where the locality and spatial extent of reefs is well known. Much of the world's subtidal habitats remain either undiscovered or unmapped, including coasts of intense human use. Consequently, to facilitate a stronger understanding of species-environmental relationships there is an urgent need for a cost and time effective standard method to map reefs at fine spatial resolutions across broad geographical extents. We used bathymetric data (∼250 m resolution) to calculate the local slope and curvature of the seabed. We then constructed artificial neural networks (ANNs) to forecast the probability of reef occurrence within grid cells as a function of bathymetric and slope variables. Testing over an independent data set not used in training showed that ANNs were able to accurately predict the location of reefs for 86% of all grid cells (Kappa = 0.63) without over fitting. The ANN with greatest support, combining bathymetric values of the target grid cell with the slope of adjacent grid cells, was used to map inshore reef locations around the Southern Australian coastline (∼250 m resolution). Broadly, our results show that reefs are identifiable from coarse-scale bathymetry data of the seabed. We anticipate that our research technique will strengthen systematic conservation planning tools in many regions of the world, by enabling the identification of rocky substratum and mapping in localities that remain poorly surveyed due to logistics or monetary constraints.     

A spatially explicit estimate of avoided forest loss

With the potential expansion of forest conservation programs spurred by climate-change agreements, there is a need to measure the extent to which such programs achieve their intended results. Conventional methods for evaluating conservation impact tend to be biased because they do not compare like areas or account for spatial relations. We assessed the effect of a conservation initiative that combined designation of protected areas with payments for environmental services to conserve over wintering habitat for the monarch butterfly (Danaus plexippus) in Mexico. To do so, we used a spatial-matching estimator that matches covariates among polygons and their neighbors. We measured avoided forest loss (avoided disturbance and deforestation) by comparing forest cover on protected and unprotected lands that were similar in terms of accessibility, governance, and forest type. Whereas conventional estimates of avoided forest loss suggest that conservation initiatives did not protect forest cover, we found evidence that the conservation measures are preserving forest cover. We found that the conservation measures protected between 200 ha and 710 ha (3-16%) of forest that is high-quality habitat for monarch butterflies, but had a smaller effect on total forest cover, preserving between 0 ha and 200 ha (0-2.5%) of forest with canopy cover >70%. We suggest that future estimates of avoided forest loss be analyzed spatially to account for how forest loss occurs across the landscape. Given the forthcoming demand from donors and carbon financiers for estimates of avoided forest loss, we anticipate our methods and results will contribute to future studies that estimate the outcome of conservation efforts.