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。     

Can trail spatial attributes predict trail use level in urban forest park? An examination integrating GPS data and space syntax theory

Understanding users’ spatial distribution in forest park is crucial for providing visitors with quality recreation experiences and for park planning and management. Utilizing users’ spatial distribution data, this study aims at investigating associations between trail use level and trail spatial attributes, through examining two large urban forest parks (Gongqing forest park and Paotaiwan forest park) in Shanghai, China. Users’ spatial distribution was measured utilizing GPS trackers with the interval of 10 seconds. This study conceptualizes trail spatial attributes as trail metric attributes and trail configurational attributes. Trail metric attributes include trail mean distance to gates, length, width and level of enclosure, which are calculated based on park map and on-site observation. We computed trail configurational attributes utilizing space syntax theory, which comprise measures of global integration, control, and connectivity. Trail connection with features/facilities, visual connection with water and shading are included as covariate variables. In total, we obtained 134 valid samples in Gongqing forest park and 210 valid samples in Paotaiwan forest park for analysis. Multivariate regression analyses indicate that when involving covariate variables, consistently in both parks, a greater trail usage is significantly related to trail shorter mean distance to park gate, trail width wider than 3 meters, higher global integration and higher control values. Collectively, these four trail spatial attributes explained 31.7 % (p < 0.001) and 27.3 % (p < 0.001) of the variances in trail use level in Gongqing forest park and Paotaiwan forest park. These findings provide direct implications to park designers and managers for providing visitors with different desirable social conditions, and ultimately improve users’ experiences and satisfactions.     

牧场土壤含水率与坚实度空间变异与相关性分

利用土壤水分/圆锥指数复合测量装置,应用精细农作技术体系网格定点测量与GPS定位,在一块面积约1.27 hm2的草地上获取了土壤含水率与坚实度空间分布基础数据,并针对采样过程中出现的数据缺失,用偏最小二乘法对数据进行修补.然后运用克里格插值法进行数字化成图,并在此基础上分别对含水率与坚实度的空间变异性及两者的相关性做了分析.     

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.     

Spatial epidemiology of the Asian honey bee mite (Varroa destructor) in the North Island of New Zealand

We describe the spatial epidemiology of Varroa destructor infestation among honey bee apiaries in the greater Auckland area of the North Island of New Zealand. The study population was comprised of 641 apiaries located within the boundaries of the study area on 11 April 2000. Cases were those members of the study population declared Varroa-infested on the basis of testing conducted between April and June 2000. The odds of Varroa was highest in apiaries in the area surrounding transport and storage facilities in the vicinity of Auckland International Airport. A mixed-effects geostatistical model, accounting for spatial extra-binomial variation in Varroa prevalence, showed a 17% reduction in the odds of an apiary being Varroa infested for each kilometre increase in the squared distance from the likely site of incursion (95% Bayesian credible interval 7–28%). The pattern of spatially autocorrelated risk that remained after controlling for the effect of distance from the likely incursion site identified areas thought to be ‘secondary’ foci of Varroa infestation initiated by beekeeper-assisted movement of infested bees. Targeted investigations within these identified areas indicated that the maximum rate of local spread of Varroa was in the order of 12 km/year (interquartile range 10–15 km/year).     

The influence of sampling scheme and interpolation method on the power to detect spatial effects of forest birds in Ontario (Canada)

Spatial ecology is becoming an increasingly important component of resource management, and the general monitoring of how human activities affect the distribution and abundance of wildlife. Yet most work on the reliability of sampling strategies is based on a non-spatial analysis of variance paradigm, and little work has been done assessing the power of alternative spatial methods for creating reliable maps of animal abundance. Such a map forms a critical response variable for multiple scale studies relating landscape structure to biotic function. The power to reconstruct patterns of distribution and abundance is influenced by sample placement strategy and density, the nature of spatial auto-correlation among points, and by the technique used to extrapolate points into an animal abundance map. Faced with uncertainty concerning the influence of these factors, we chose to first synthesize a model reference system of known properties and then evaluate the relative performance of alternative sampling and mapping procedures using it. We used published habitat associations of tree nesting boreal neo-tropical birds, a classified habitat map from the Manitou Lakes area of northwestern Ontario, and point count means and variances determined from field studies in boreal Canada to create 4 simulated models of avian abundance to function as reference maps. Four point sampling strategies were evaluated by 4 spatial mapping methods. We found mixed-cluster sampling to be an effective point sampling strategy, particularly when high habitat fragmentation was avoided by restricting samples to habitat patches >10 ha in size. We also found that of the 4 mapping methods, only stratified ordinary point kriging (OPK) was able to generate maps that reproduced an embedded landscape-scale spatial effect that reduced nesting bird abundance in areas of higher forest age-class fragmentation. Global OPK was effective only for detecting broader, regional-scale differences. This revised version was published online in July 2006 with corrections to the Cover Date.     

Predicting the spatial distribution of ground flora on large domains using a hierarchical Bayesian model

Accomodation of important sources of uncertainty in ecological models is essential to realistically predicting ecological processes. The purpose of this project is to develop a robust methodology for modeling natural processes on a landscape while accounting for the variability in a process by utilizing environmental and spatial random effects. A hierarchical Bayesian framework has allowed the simultaneous integration of these effects. This framework naturally assumes variables to be random and the posterior distribution of the model provides probabilistic information about the process. Two species in the genus Desmodium were used as examples to illustrate the utility of the model in Southeast Missouri, USA. In addition, two validation techniques were applied to evaluate the qualitative and quantitative characteristics of the predictions.This revised version was published online in May 2005 with corrections to the Cover Date.     

A leakiness index for assessing landscape function using remote sensing

The cover, number, size, shape, spatial arrangement and orientation of vegetation patches are attributes that have been used to indicate how well landscapes function to retain, not ‘leak’, vital system resources such as rainwater and soil. We derived and tested a directional leakiness index (DLI) for this resource retention function. We used simulated landscape maps where resource flows over map surfaces were directional and where landscape patch attributes were known. Although DLI was most strongly related to patch cover, it also logically related to patch number, size, shape, arrangement and orientation. If the direction of resource flow is multi-directional, a variant of DLI, the multi-directional leakiness index (MDLI) can be used. The utility of DLI and MDLI was demonstrated by applying these indices to three Australian savanna landscapes differing in their remotely sensed vegetation patch attributes. These leakiness indices clearly positioned these three landscapes along a function-dysfunction continuum, where dysfunctional landscapes are leaky (poorly retain resources). This revised version was published online in July 2006 with corrections to the Cover Date.     

Spatial dependence and the relationship of soil organic carbon and soil moisture in the Luquillo Experimental Forest,Puerto Rico

We used geo-spatial statistical techniques to examine the spatial variation and relationship of soil organic carbon (SOC) and soil moisture (SM) in the Luquillo Experimental Forest (LEF), Puerto Rico, in order to test the hypothesis that mountainous terrain introduces spatial autocorrelation and crosscorrelation in ecosystem and soil properties. Soil samples (n = 100) were collected from the LEF in the summer of 1998 and analyzed for SOC, SM, and bulk density (BD). A global positioning system was used to georeference the location of each sampling site. At each site, elevation, slope and aspect were recorded. We calculated the isotropic and anisotropic semivariograms of soil and topographic properties, as well as the cross-variograms between SOC and SM, and between SOC and elevation. Then we used four models (random, linear, spherical and wave/hole) to test the semi-variances of SOC, SM, BD, elevation, slope and aspect for spatial dependence. Our results indicate that all the studied properties except slope angle exhibit spatial dependence within the scale of sampling (200 – 1000 m sampling interval). The spatially structured variance (the variance due to the location of sampling sites) accounted for a large proportion of the sample variance for elevation (99%), BD (90%), SOC (68%), aspect (56%) and SM (44%). The ranges of spatial dependence (the distances within which parameters are spatially dependent) for aspect, SOC, elevation, SM, and BD were 9810 m, 3070 m, 1120 m, 930 m and 430 m, respectively. Cross correlograms indicate that SOC varies closely with elevation and SM depending on the distances between samples. The correlation can shift from positive to negative as the separation distance increases. Larger ranges of spatial dependence of SOC, aspect and elevation indicate that the distribution of SOC in the LEF is determined by a combination of biotic (e.g., litterfall) and abiotic factors (e.g., microclimate and topographic features) related to elevation and aspect. This demonstrates the importance of both elevation and topographic gradients in controlling climate, vegetation distribution and soil properties as well as the associated biogeochemical processes in the LEF.This revised version was published online in May 2005 with corrections to the Cover Date.