Predicting the distributions of plant species at the regional scale: a hierarchical matrix model

This paper describes a model which links four levels in an ecological hierarchy using a series of matrices. The four levels are landscape, land cover type, community and species. Each matrix quantifies the probabilistic associations between entities in two adjacent levels in the hierarchy. A landscape classification (1 km resolution) provides a spatial element to the model enabling the distributions of species to be predicted and presented as maps within a geographical information system (GIS). Implementation of the model in Northern England is described. The distributions of 579 species of plants were predicted and compared with data from independent field surveys. The predicted distributions were found to be accurate for 59 % of species. The distributions of rare and non-native (introduced) species of plant were relatively poorly predicted. The potential of this approach to model plant species distributions is discussed.     

福建武平米槠种群生态空间分布规律的研究

本文应用Ｒ尺度法对福建武平米槠种群空间分布进行分析，结果表明米槠种群分布格局及其动态均为聚集分布；种群分布格局动态随立木级增大聚集度越来越低．     

The influence of scale and the spatial characteristics of landscapes on land-cover mapping using remote sensing

Statistical analyses provide a means for assessing relationships between landscape spatial pattern and errors in the estimates of cover-type proportions as land-cover data are aggregated to coarser scales. Results from a multiple-linear regression model suggest that as patch sizes, variance/mean ratio, and initial proportions of cover types increase, the proportion error moves in a positive direction and is governed by the interaction of the spatial characteristics and the scale of aggregation. However, the standard linear model does not account for the different directions of scale-dependent proportion error since some classes become larger and others become smaller as the scene is aggregated. Addition of indicator variables representing class-type significantly improves the performance by allowing the model to respond differently to different classes. A regression tree model provides a much simpler fit to the complex scaling behavior through an interaction between patch size and aggregation scale. An understanding of the relationships between landscape pattern, scale, and proportion error may advance methods for correcting land-cover area estimates. Such methods could also facilitate high-resolution calibration and validation of coarse-scale remote-sensing-based land-cover mapping algorithms. Ongoing initiatives to produce global land-cover datasets from remote sensing, such as efforts within the IGBP and the EOS MODIS Land-Team, include significant emphasis on high level calibration and validation activities of this nature.     

Movement rules for herbivores in spatially heterogeneous environments: responses to small scale pattern

Foraging herbivores respond to the spatial pattern of resources at a variety of scales. At small scales of space and time, existing models capture the essence of the feeding process and successfully predict intake rates. Models that operate over larger scales have not exhibited a similar success, in part because we have a limited understanding of the rules used by animals to make decisions in spatially complex environments, or of the consequences of departing from these rules. To evaluate the rules that large herbivores use when navigating between forages, we examined movements of bighorn sheep foraging on apparent prey (alfalfa plants) in hand-constructed patches of plants. Observations of movements and path lengths were compared to simulations that used a variety of different rules-of-thumb to determine a search path. Rules used in simulations ranged from a random walk with various detection distances, to more complicated rules that solved a variant of the travelling salesman problem. Simulations of a random walk yielded movement lengths that exceeded observations by a factor of 3 for long detection distances, and by 30-fold for short detection distances. Observed move distances were most closely approximated by simulations based on a nearest-neighbor ruleover 75 % of all moves by bighorn sheep were to the closest available plant. Movement rules based on random walks are clearly inappropriate for many herbivores that typically consume visually apparent plants, and we suggest the use of a nearest-neighbor rule for modelling foraging by large herbivores.     

用拓扑变换对空间连杆机构按极限位置和行程速比的综合

空间两轴垂直交叉的RSSR曲柄摇杆机构和RSSP曲柄滑块机构,是空间连杆机构中应用最广泛的四连杆机构。本文运用拓扑变换原理,对RSSR和RSSP这两种机构,按极限位置和行程速比的综合进行了分析研究。导出了其尺寸参数的计算公式,并提出了电子计算机辅助设计和绘图的程序框图,以定量的方法分析设计机构的可动性,这一方法具有图文并茂,形数结合,结论准确,容易理解等特点,编成软件后,使用极其方便。因而,是一种较为理想的方法。可供有条件的单位应用。     

The spatial distribution of diversity between disparate taxa: Spatial correspondence between mammals and ants across South Florida,USA

Gap Analysis takes a proactive landscape-level approach to conserving native species by identifying nodes of high biological diversity. It uses vertebrate species richness as an index of overall biological diversity. However, it remains unknown whether or not the spatial distribution of vertebrate diversity corresponds with the diversity of other taxa. We tested whether landscape-level diversity patterns corresponded between a vertebrate and an invertebrate taxon, mammals and ants, across the southern half of the Florida peninsula, USA. Composite digital maps with a 30-m spatial resolution were produced for each taxon. Spatial correspondence between the taxa was determined by normalizing and then subtracting the composite maps. There were large areas of spatial correspondence – indicating that richness between mammals and ants was similar over much of southern Florida. However, spatial correspondence occurred where the richness of both taxa was low or moderate, and areas with the highest species richness (highest 20%) for each taxon, the explicit focus of Gap Analyses, corresponded over only 8752 ha. Gap Analysis provides a much needed assessment of landscape-level diversity patterns and proactive reserve design, but it must be explicit that the results are applicable for vertebrate diversity, which does not necessarily correspond with diversity patterns of other taxa. The two taxa investigated differ by orders of magnitude in the scale that they perceive their environment, and it is likely that diversity hotspots vary as the scale of investigation – and the taxa mapped – vary.     

Does kriging predict weed distributions accurately enough for site‐specific weed control?

Numerous studies have demonstrated the patchy distribution of weeds within fields. The majority of these studies have used discrete sampling, recording weed densities at the intersections of regular grids. In this study, Avena spp. seedlings were recorded on square grids at four sites. The data were then divided into test and real data sets using the whole, two-thirds and one-half of the data to evaluate the consistency of global variogram models and accuracy of ordinary kriging estimates. Kriging provided poor weed density estimates at both very low and high densities, i.e. data were smoothed when compared with true values. Grid sampling took considerable time and, therefore, money to complete, whereas continuous sampling with multispectral imagery (performed at one site) was much quicker and at a finer resolution. It is suggested that sampling systems that collect continuous rather than discrete data are currently more appropriate for site-specific weed management.     

Changes in landscape patterns in Georgia,USA

The objectives of this study were to determine how landscape patterns in Georgia, USA have changed through time and whether the spatial patterns varied by physiographic region. Historical aerial photography was used to analyze spatial patterns of land use from the 1930's to the 1980's. Land use patterns were quantified by: (1) mean number and size of patches; (2) fractal dimension of patches; (3) amount of edge between land uses; and (4) indices of diversity, dominance, and contagion. Forest cover increased in aerial extent and in mean patch size. The mean size of agricultural patches increased in the coastal plain and decreased in the mountains and piedmont. Edges between land uses decreased through time, indicating less dissection of the landscape. Fractal dimensions also decreased, indicating simpler patch shapes. Indices of diversity and dominance differed through time but not among regions; the contagion index differed among regions but not through time. A geographic trend of decreasing diversity and increasing dominance and contagion was observed from the mountains to the lower coastal plain. Landscape patterns exhibited the greatest changes in the piedmont region. Overall, the Georgia landscape has become less fragmented and more connected during the past 50 years. Changing patterns in the landscape may have implications for many ecological processes and resources.     

Spatial distribution of weeds in arable crops: are current sampling and analytical methods appropriate?

This paper reviews the literature concerning the spatial distribution of weeds; highlighting the limitations of our current sampling and analytical methodologies, and suggesting how these inadequacies can be addressed. Most research studies have used discrete sampling, i.e. weeds are counted within a quadrat, on a grid basis. Few have mapped weeds at a whole-field scale, either with a resolution appropriate to spraying operations or key ecological processes. Statistical analyses used to describe the data can be divided into two main types, spatially implicit (also at the scale of the sampling unit) or spatially explicit, in which the location of individuals is included in the analyses. Spatially implicit methods can be strongly affected by quadrat size and mean density and are of doubtful benefit. More attention is required to address sampling resolution issues for spatially explicit methods. Our understanding of the formation and dynamics of spatial pattern, as well as predicting the consequences of site-specific management, can be improved with models. Unfortunately, most models consider only newly expanding patches and appear incapable of predicting spatial distributions when an area has been fully invaded. More detailed biological information is required if models are to become more realistic and informative. We also need to ensure that we understand the spatial processes in the context of the whole field environment, to optimize the success of site-specific weed management in the longer term.     

油松毛虫卵（块）和蛹种群简单随机抽样最适样方大小的确定方法

在种群空间格局的研究的基础上，采用７种方法对同松毛虫卵（块）和蛹种群简单随机抽样技术中最适样方大小的确定问题进行了研究，结果表明，无论是卵（块）抑或蛹种群，都是在ｕ＝１时抽样误差最低，即以单株油松为样方时最为适宜，此外，文中还列出了考虑抽样花费时确定最适样方式大小的各种方法，并讨论了有关问题。