基于土地利用变化的河北省坝上地区景观生态风险评价

[目的]对河北省坝上地区近40 a来的土地利用动态变化和生态风险进行分析评价并对未来趋势作出预测,为该地区生态建设和治理、可持续发展提供科学依据。[方法]基于坝上地区1980—2018年5期土地利用数据以及通过土地转移矩阵、空间相关性分析等方法揭示和预测该区1980—2026年的土地利用变化特征并评估该区生态风险水平。[结果](1)整个研究期间,坝上地区土地利用类型以耕地为主,所占比例近50%,其中,1980—2018年,耕地、林地扩张面积均超过300 km~2,草地减少近616.60 km~2,水域面积缩减36.04%,其中耕地、林地、草地之间的互相流转程度较为剧烈,空间变化上表现为各地类的重心在2000—2010年明显迁移。(2)1980—2026年,坝上地区6个时期内生态风险值全局空间自相关Moran’s I指数均在0.500左右,其空间分布表现出较高的趋同集聚性。(3)近40 a来,坝上生态风险水平升至为高风险级,其区域增加了123.22 km~2,较高风险区域分布在城镇地区,据CA-Markov模型预测,未来坝上地区中等及中等以上风险区域持续扩张,丰宁县和围场县将分别出现小规模高风险区和较高风险区。[结论](1)近40 a来坝上地区草地退化严重,水域面积显著减少,原因系安固里淖干涸所致。(2)该区生态风险水平与土地格局分布具有较强相关性,且在未来会继续升高。     

Analysis of a Long-term Experiment with Repeated-measurement Models

Long‐term experiments are a classical case of repeated measurements. Traits are measured on the same experimental unit over many years so that correlations arise between the observations made on the same plot in consecutive years. This paper describes the analysis of a three‐crop‐rotation long‐term experiment. We analysed the yields of the crops and the organic carbon content in the topsoil over 30 consecutive years. Several variance–covariance approaches are discussed and the trait‐specific best fit is interpreted. Mixed models are used to describe the structure of the experiment. Both yields and soil organic carbon show a more or less pronounced variance heterogeneity. Especially for yields, the heterogeneity of cycles and years is dominant. The consideration of correlations results in a better model fit in all cases.     

Trends in NE Atlantic landings (southern Portugal): identifying the relative importance of fisheries and environmental variables

Time series of commercial landings from the Algarve (southern Portugal) from 1982 to 1999 were analyzed using min/max autocorrelation factor analysis (MAFA) and dynamic factor analysis (DFA). These techniques were used to identify trends and explore the relationships between the response variables (annual landings of 12 species) and explanatory variables [sea surface temperature, rainfall, an upwelling index, Guadiana river (south‐east Portugal) flow, the North Atlantic oscillation, the number of licensed fishing vessels and the number of commercial fishermen]. Landings were more highly correlated with non‐lagged environmental variables and in particular with Guadiana river flow. Both techniques gave coherent results, with the most important trend being a steady decline over time. A DFA model with two explanatory variables (Guadiana river flow and number of fishermen) and three common trends (smoothing functions over time) gave good fits to 10 of the 12 species. Results of other models indicated that river flow is the more important explanatory variable in this model. Changes in the mean flow and discharge regime of the Guadiana river resulting from the construction of the Alqueva dam, completed in 2002, are therefore likely to have a significant and deleterious impact on Algarve fisheries landings.     

盐渍化灌区节水改造后土壤盐分时空变化规律研究

为探明沈乌灌域节水改造后因地下水水位变化造成的土壤盐分重分布规律,采用区域土壤信息定点监测,并结合经典统计学、空间插值、缓冲区分析和空间自相关分析方法,研究节水改造前后沈乌灌域土壤盐分空间变异、时空分布规律及不同改造年限区域土壤盐分变化差异。结果表明:节水改造后,秋浇前土壤整体含盐量平均降幅7. 30%,秋浇水量减少,秋浇后土壤盐分淋洗效果减弱9. 26%;空间上,土壤盐分高值区(大于6 g/kg)多位于地下水埋深较浅的东北和南部区域,低值区(小于2 g/kg)位于西南和东部沙区。节水改造后,秋浇前土壤盐分全局Moran’s I指数平均增幅为5%,空间相关性增强;秋浇水量减少,全局Moran’s I指数变化不显著,秋浇作用对土壤盐分空间自相关影响度减弱。由LISA集聚分析可知,改造后、秋浇前南部高-高显著区向不显著和高-低区转变,秋浇后南部集聚特征仍十分显著,存在盐渍化风险,改造后仍是盐渍化防治重点区域。针对中度耐盐作物,沈乌灌域耕层作物生长安全区和深层非盐渍土面积比例分别为49. 66%和71. 57%;改造后,秋浇前耕层作物生长安全区和深层非盐渍土分别增加4. 82、1. 85个百分点,秋浇后,耕层作物生长安全区面积增幅下降5. 02个百分点,深层变化不显著。不同距离缓冲区对平均土壤含盐量的解释能力较强,长期改造区和短期改造区受渠道影响半径分别为1. 5 km和0. 7 km,长期改造区缓冲区内平均土壤含盐量下降速率高于短期改造区,均一化程度较高。综上所述,节水改造工程实施后,土壤盐渍化程度减轻,作物生长安全区面积增加,表聚作用弱化,秋浇水量减少,土壤盐分淋洗效果减弱,土壤环境有所改善。     

常州市钟楼区耕地产能空间分布与影响因素分析

耕地产能评价对于耕地资源保护及质量提升具有重要的现实意义。通过构建耕地产能评价体系，运用空间自相关及主成分回归分析法对常州市钟楼区的耕地产能进行空间分布及影响因素分析。结果表明：基于气候、自然因素和技术水平综合指标的耕地产能评价体系具有适用性和可操作性；钟楼区耕地产能等别分为6等和7等，其中6等地占比达到97.55%，等别空间分布呈现出城区内部街道低、外围地区较高的格局；耕地产能整体空间集聚性显著，各街道（乡镇）均表现出较强的空间正相关性，正相关类型（HH型和LL型）多呈现组团式，负相关类型（LH型和HL型）则分布零散；耕地自然质量和技术水平是影响钟楼区耕地产能空间分布的主要驱动因素，其中，耕作层厚度、有机质含量、障碍层距地表深度和土壤养分元素为主导因素，pH值、灌溉保证程度和排水条件为次要因素。因此，应从增强耕地自然质量、提高耕地技术水平等方面制定提高耕地产能的针对性措施。     

基于空间自相关构建树木生长模型

2004—2008年，在日本九州地区宫崎县田野天然次生林内设置的一块100 m×100 m固定标准地中，通过每木调查，测量了固定标准地内树木的种类、空间位置、生长等数据。为了便于理解，以固定标准地中优势树种蚊母树为主要研究对象，在考虑周边所有树木的影响的同时，利用贝叶斯统计方法分析了空间自相关及树木间的对称竞争、非对称竞争对树木生长过程的影响，并比较了忽略空间自相关的情况。结果表明:在构建研究对象树种的生长模型时，树木个体间的竞争是不可缺少的参数，尤其是个体间的对称竞争。在利用空间自相关参数建模时，最终模型的决定系数R2＝0.83；而忽略空间自相关参数的模型，其决定系数R2＝0.74。通过其他主要树种的分析也表明了导入空间自相关参数的优越性，因此可以认为，考虑空间自相关的随机效应模型能更精确地预测树木的生长。本研究所采用的空间自相关模型不仅可以利用树木个体的分布信息推测其生态学特征，还为树木生长模拟提供了理论与方法上的借鉴。      

Multi-scale use of lands providing anthropogenic resources by American Crows in an urbanizing landscape

The conversion of forests and farmlands to human settlements has negative impacts on many native species, but also provides resources that some species are able to exploit. American Crows (Corvus brachyrhynchos), one such exploiter, create concern due to their impact as nest predators, disease hosts, and cultural harbingers of evil. We used various measures of crow abundance and resource use to determine crows’ response to features of anthropogenic landscapes in the Puget Sound region of the United States. We examined land cover and land use composition at three spatial scales: study sites (up to 208 ha), crow home ranges within sites (18.1 ha), and local land cover (400 m²). At the study site and within-site scales crow abundance was strongly correlated with land cover providing anthropogenic resources. In particular, crows were associated with the amount of ‘maintained forest’ cover, and were more likely to use grass and shrub cover than forest or bare soil cover. Although crows did not show a generalized response to an edge variable, they exhibited greater use of patchy habitat created by human settlements than of native forests. Radio-tagged territorial adults used resources within their home ranges relatively evenly, suggesting resource selection had occurred at a larger spatial scale. The land conversion pattern of new suburban and exurban settlements creates the mix of impervious surfaces and maintained vegetation that crows use, and in our study area crow populations are expected to continue to increase. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Spatial structure of genetic variation within populations of forest trees

The spatial pattern and structure of genetic variation are important aspects of the population genetics of forest stands. Combined with limits to seed and pollen dispersal, spatial structure affects the level of inbreeding and the action of natural selection. The genetic constitution of stand regeneration, following different forestry practices, is also influenced by spatial structure. For example, natural regeneration with seed trees involves sampling seed trees from a stand that may be genetically nonhomogeneous. This paper reviews theoretical and empirical results on spatial patterns of genetic variation, produced under limited gene flow and selection, in terms of recently developed spatial statistics (e.g., spatial autocorrelation). Genetic correlations in samples from spatially structured populations are also described, as well as how spatial samples can be used to characterize the structure of genetic variation, and how inferences can be made about (spatially distributed) components of fitness and yield.     

Incorporating spatial autocorrelation into the general linear model with an application to the yellowfin tuna (Thunnus albacares) longline CPUE data

Catch-per-unit-effort (CPUE) data have often been used to obtain a relative index of the abundance of a fish stock by standardizing nominal CPUE using various statistical methods. The theory underlying most of these methods assumes the independence of the observed CPUEs. This assumption is invalid for a fish population because of their spatial autocorrelation. To overcome this problem, we incorporated spatial autocorrelation into the standard general linear model (GLM). We also incorporated into it a habitat-based model (HBM), to reflect, more effectively, the vertical distributions of tuna. As a case study, we fitted both the standard-GLM and spatial-GLM (with or without HBM) to the yellowfin tuna CPUE data of the Japanese longline fisheries in the Indian Ocean. Four distance models (Gaussian, exponential, linear and spherical) were examined for spatial autocorrelation. We found that the spatial-GLMs always produced the best goodness-of-fit to the data and gave more realistic estimates of the variances of the parameters, and that HBM-based GLMs always produced better goodness-of-fit to the data than those without. Of the four distance models, the Gaussian model performed the best. The point estimates of the relative indices of the abundance of yellowfin tuna differed slightly between standard and spatial GLMs, while their 95% confidence intervals from the spatial-GLMs were larger than those from the standard-GLM. Therefore, spatial-GLMs yield more robust estimates of the relative indices of the abundance of yellowfin tuna, especially when the nominal CPUEs are strongly spatially autocorrelated.     

1996—2020年海南岛水源涵养量时空变化及地理探测

[目的] 分析影响海南岛水源涵养量时空变化的主要驱动因素,为海南岛生态系统水源涵养功能重点区域识别及保护,水资源管理及区域可持续发展等方面提供决策依据。[方法] 基于InVEST模型产水量模块,定量分析海南岛1996—2020年水源涵养的时空变化,并对海南岛的水源涵养影响因素展开地理探测分析研究。[结果] ①1996—2020年海南岛水源涵养总量略微上升,多年平均水源涵养量为41.77 mm,水源涵养总量为1.42×10⁹ m³。空间上,海南岛水源涵养分布呈现东高西低及北高南低的特征。各地类中,林地的水源涵养能力较强,且面积占比大,对海南岛水源涵养量的贡献显著。②水源涵养量有较强的空间正相关性,呈现明显聚集特征,水源涵养重点区域主要分布于海南岛东中部、东部沿海海岸带以及海口市西部的火山熔岩湿地。③各因子对水源涵养影响力从大到小依次为降水量、土地利用类型、实际蒸散发和高程;因子交互作用,尤其是降水与土地利用的交互显著增强水源涵养分布的解释。[结论] 气候作用和人类活动主导了海南岛水源涵养量空间格局。未来既要充分考虑气候变化对水源涵养的影响,通过建立有效措施确保海南岛生态系统水源涵养功能有效适应全球变化,又要通过土地资源的合理利用与管理,确保土地生态安全。