Study on spatial pattern of land-use change in China during 1995-2000

It is more and more acknowledged that land-use/cover dynamic change has become a key subject urgently to be dealt with in the study of global environmental change. Supported by the Landsat TM digital images, spatial patterns and temporal variation of land-use change during 1995 -2000 are studied in the paper. According to the land-use dynamic degree model, supported by the 1km GRID data of land-use change and the comprehensive characters of physical, economic and social features, a dynamic regionalization of land-use change is designed to disclose the spatial pattern of land-use change processes. Generally speaking, in the traditional agricultural zones, e.g., Huang-Huai-Hai Plains, Yangtze River Delta and Sichuan Basin, the built-up and residential areas occupy a great proportion of arable land, and in the interlock area of farming and pasturing of northern China and the oases agricultural zones, the reclamation I of arable land is conspicuously driven by changes of production conditions, economic benefits and climatic conditions. The implementation of "returning arable land into woodland or grassland" policies has won initial success in some areas, but it is too early to say that the trend of deforestation has been effectively reversed across China. In this paper, the division of dynamic regionalization of land-use change is designed, for the sake of revealing the temporal and spatial features of land-use change and laying the foundation for the study of regional scale land-use changes. Moreover, an integrated study, including studies of spatial pattern and temporal process of land-use change, is carried out in this paper, which is an interesting try on the comparative studies of spatial pattern on change process and the change process of spatial pattern of land-use change.

NDVI spatial pattern and its differentiation on the Mongolian Plateau

GIMMS NDVI database and geo-statistics were used to depict the spatial distribution and temporal stability of NDVI on the Mongolian Plateau. The results demonstrated that: (1) Regions of interest with high NDVI indices were distributed primarily in forested mountainous regions of the east and the north, areas with low NDVI indices were primarily distributed in the Gobi desert regions of the west and the southwest, and areas with moderate NDVI values were mainly distributed in a middle steppe strap from northwest to southeast. (2) The maximum NDVI values maintained for the past 22 years showed little variation. The average NDVI variance coefficient for the 22-year period was 15.2%. (3) NDVI distribution and vegetation cover showed spatial autocorrelations on a global scale. NDVI patterns from the vegetation cover also demonstrated anisotropy; a higher positive spatial correlation was indicated in a NW-SE direction, which suggested that vegetation cover in a NW-SE direction maintained increased integrity, and vegetation assemblage was mainly distributed in the same specific direction. (4) The NDVI spatial distribution was mainly controlled by structural factors, 88.7% of the total spatial variation was influenced by structural and 11.3% by random factors. And the global autocorrelation distance was 1178 km, and the average vegetation patch length (NW-SE) to width (NE-SW) ratio was approximately 2.4:1.0.

A Distributed Outstar Network for Spatial Pattern Learning

The distributed outstar, a generalization of the outstar neural network for spatial pattern learning, is introduced. In the outstar, signals from a source node cause weights to learn and recall arbitrary patterns across a target field of nodes. The distributed outstar replaces the outstar source node with a source field of arbitrarily many nodes, whose activity pattern may be arbitrarily distributed or compressed. Learning proceeds according to a principle of atrophy due to disuse, whereby a path weight decreases in joint proportion to the transmitted path signal and the degree of disuse of the target node. During learning, the total signal to a target node converges toward that node's activity level. Weight changes at a node are apportioned according to the distributed pattern of converging signals. Three synaptic transmission functions, by a product rule, a capacity rule, and a threshold rule, are examined for this system. The three rules are computationally equivalent when source field activity is maximally compressed, or winner-take-all. When source field activity is distributed, catastrophic forgetting may occur. Only the threshold rule solves this problem. Analysis of spatial pattern learning by distributed codes thereby leads to the conjecture that the unit of long-term memory in such a system is an adaptive threshold, rather than the multiplicative path weight widely used in neural models.

Spatial Pattern Learning, Catastophic Forgetting and Optimal Rules of Synaptic Transmission

It is a neural network truth universally acknowledged, that the signal transmitted to a target node must be equal to the product of the path signal times a weight. Analysis of catastrophic forgetting by distributed codes leads to the unexpected conclusion that this universal synaptic transmission rule may not be optimal in certain neural networks. The distributed outstar, a network designed to support stable codes with fast or slow learning, generalizes the outstar network for spatial pattern learning. In the outstar, signals from a source node cause weights to learn and recall arbitrary patterns across a target field of nodes. The distributed outstar replaces the outstar source node with a source field, of arbitrarily many nodes, where the activity pattern may be arbitrarily distributed or compressed. Learning proceeds according to a principle of atrophy due to disuse whereby a path weight decreases in joint proportion to the transmittcd path signal and the degree of disuse of the target node. During learning, the total signal to a target node converges toward that node's activity level. Weight changes at a node are apportioned according to the distributed pattern of converging signals three types of synaptic transmission, a product rule, a capacity rule, and a threshold rule, are examined for this system. The three rules are computationally equivalent when source field activity is maximally compressed, or winner-take-all when source field activity is distributed, catastrophic forgetting may occur. Only the threshold rule solves this problem. Analysis of spatial pattern learning by distributed codes thereby leads to the conjecture that the optimal unit of long-term memory in such a system is a subtractive threshold, rather than a multiplicative weight.

Attribution of the spatial pattern of CO2-forced sea level change to ocean surface flux changes

Climate models taking part in the coupled model intercomparison project phase 5 (CMIP5) all predict a global mean sea level rise for the 21st century. Yet the sea level change is not spatially uniform and differs among models. Here we evaluate the role of air–sea fluxes of heat, water and momentum (windstress) to find the spatial pattern associated to each of them as well as the spread they can account for. Using one AOGCM to which we apply the surface flux changes from other AOGCMs, we show that the heat flux and windstress changes dominate both the pattern and the spread, but taking the freshwater flux into account as well yields a sea level change pattern in better agreement with the CMIP5 ensemble mean. Differences among the CMIP5 control ocean temperature fields have a smaller impact on the sea level change pattern.

Spatial ecology of a root parasite : from pattern to process

Occurrence patterns of parasitic plants are constrained by the distribution of suitable hosts and movement patterns of seed vectors and, accordingly, represent a simplified system to study many aspects of spatial ecology and determinants of distribution. Previous work has focused on the aerially hemiparasitic mistletoes, and it is unclear whether root parasites are affected by similar factors. Here, we evaluate spatial patterns in the root parasitic Santalum lanceolatum in an arid shrubland in north-western New South Wales, central Australia. In this region, the principal host is a long-lived nitrogen fixing shrub Acacia tetragonophylla closely associated with ephemeral creek-lines. The location of 765 individuals of both species was mapped along a 250-m section of creek-line using a total survey station, and occurrence patterns of the root parasite related to host distribution and landscape context. We used Ripley's K-function and the O-ring statistic to determine whether the distribution of S. lanceolatum was random, aggregated or regular; the spatial scales at which these patterns occurred; and to quantify any spatial associations between the parasite and its host, A. tetragonophylla. While acacias were closely associated with the creek-line, S. lanceolatum plants were more tightly clustered, displaying significant clustering at two spatial scales (1.2 m and 8.8 m). We suggest that host quality may act as an important constraint, with only those acacias growing in or near the creek-line being physiologically capable of supporting a parasite to maturity. Insights gained from spatial analysis are used to guide ongoing research in this system, and highlight the utility of the O-ring statistic for understanding patterns of distribution affected by multiple processes operating at critical scales.

The spatial pattern of natural selection when selection depends upon experience

Apostatic (frequency‐ or density‐dependent) selection, aposematic signals, and mate choice behavior generally require that the mean prey or potential mate density m value be high enough (above a threshold T) to result in sufficient encounter rates for the searcher to learn or retain the association between conspicuous signals and prey unprofitability, to forage apostatically, or to choose among mates. This assumes that all searchers experience , which implicitly assumes an even dispersion of targets among searcher territories. Uneven dispersion generates new phenomena. If , then only territories with local density x values that are greater than T favor experience‐based behavior, leading to spatially variable frequency‐ or density‐dependent selection intensity. As aggregation increases, the increase in percentage of targets in favorable territories ( ) is greater than the increase in the percentage of territories that are favorable. The relationship is reversed when . In both cases, because as few as 10% of the territories can contain 80% of the targets, only a few territory holders may account for most of the selection on most of the target population; accidents of experience in only a few searchers can have unexpectedly large effects on the target population. This also provides an explanation for high searcher behavior variation (personalities) : individuals from favorable territories will behave differently in behavioral experiments than those from unfavorable territories, at least with respect to similar kinds of targets. These effects will generate spatial heterogeneity in natural and sexual selection in what are otherwise uniform environments.

Checked baggage: spatial negotiations in contemporary air travel

This paper examines the act of undertaking international air travel and analyses how it forces individuals to consider a range of ideas as a result of dislocation and attempts to re-align themselves within spatial, material and biological structures. In order to balance the shifts between spatial and material experiences, travellers employ imaginative and perceptive procedures, gaining knowledge through experience. At the intersection of participatory and spatial boundaries through the lens of multi-disciplinary literature, this paper explores how practices of individuals within international air travel provides alternative modes of thinking and navigating through personal, cultural and globalised public spaces.

Diet and Spatial Pattern of Foraging in Ectatomma opaciventre (Hymenoptera: Formicidae) in an Anthropic Area

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Oviposition pattern and within-season spatial and temporal variation of pre-dispersal seed predation in a population of Mimosa bimucronata trees

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Spatial pattern of parasitism in Diatraea saccharalis Fab. (Lep., Crambidae) populations at two different spatial scales in sugarcane fields in Brazil

The biological control of Diatraea saccharalis is regarded as one of the best examples of successful classical biological control in Brazil. Since the introduction of the exotic parasitoid, Cotesia flavipes, the decrease in D. saccharalis infestation in sugarcane fields has been attributed to the effectiveness of this agent. Native Tachinidae fly parasitoids (Lydella minense and Paratheresia claripalpis) have also been implicated in the success. Quantitative data confirming the actual contribution of these agents to the control of D. saccharalis are, however, rather scant. The purpose of this study was to investigate the spatial pattern of parasitism of these parasitoids in D. saccharalis populations at two large spatial scales (fields and zones). To investigate this subject, a large data set comprising information collected from a sugarcane mill located in the state of São Paulo, Brazil (São João sugarcane mill) was analysed. When regressions between the proportion parasitism against host density were computed, the percentage of significant regressions with either a positive or a negative slope was very small at both spatial scales for both parasitoid species. Regressing the densities of tachinid-parasitized hosts against host densities per field showed that these parasitoids presented a 'moderate aggregative' response to host densities, as 53.33% of the regressions were positively significant. Cotesia flavipes was 'weakly aggregated' on host densities at the field level, because only 33.33% of the regressions were positively significant. At the zone level, neither aggregative nor spatial proportion parasitism responses were evident for either parasitoid species due to the small percentage of significant regressions computed.

Spatial reference of black capuchin monkeys in Brazilian Atlantic Forest: egocentric or allocentric?

Wild primates occupy large home ranges and travel long distances to reach goals. However, how primates are able to remember goal locations and travel efficiently is unclear. Few studies present consistent results regarding what reference system primates use to navigate, and what kind of spatial information they recognize. We analysed the pattern of navigation of one wild group of black capuchin monkeys, Cebus nigritus, at Atlantic Forest for 100 days in Carlos Botelho State Park (PECB), Brazil. We tested predictions based on the alternative hypotheses that black capuchin monkeys navigate using a sequence of landmarks as an egocentric reference system or an allocentric reference system, or both, depending on availability of food resources. The group location was recorded using a GPS device collecting coordinates at 5 min intervals, and route maps were generated using ArcView v9.3.1. The study group travelled through habitual routes during less than 30% of our study sample, and revisited resources from different starting points, using different paths and routes, even when prominent landmarks near feeding locations were not visible. The study group used habitual routes more frequently when high-quality foods were scarce, and navigated using different paths when revisiting food sources. Results support the hypothesis that black capuchin monkeys at PECB navigate using both egocentric and allocentric systems of reference, depending on the quality and distribution of the food resource they find. (C) 2010 The Association for the Study of Animal Behaviour. Published by Elsevier Ltd. All rights reserved.

SPATIAL PATTERN OF FOUR FOREST COMMUNITIES BY RIPLEY'S K FUNCTION IN SAO PAULO STATE

Investigating tree's spatial patterns according to their size classes and according to their more abundant species can provide evidences about the structure of the vegetal community, since the spatial pattern is a key question for forestry ecology studies. The tree spatial organization patterns on the environment depend on several ecological processes and on the specific characteristics of each environment, so that the best understanding of this frame provides important elements for the knowledge on forestry formation. This paper aimed to study tree spatial patterns, according to the diameter classes and from four most abundant species in different forests, in order to provide evidences regarding to the ecology of each vegetal community. The spatial pattern description in each forestry formation was developed using Ripley's K function. The studied forestry formations were: Ombrophilous Forest, Cerradao, Seasonal Forest and Restinga Forest. In this work, a 10.24 ha plot was installed in each forestry formation, and every tree, with a circumference at breast height (CBH) larger than 15 cm were measured, georeferenced and identified. The obtained data highlights the aggregated character in tropical forests, as observed in every studied forest. The 'Cerraddo' and 'Restinga' forest trees showed close aggregate patterns. In the Ombrophilous forest, for all distance scales, the aggregate pattern was meaningful. In the seasonal forest, a random tendency was observed, although a meaningful aggregation was observed in all short distances. The spatial pattern by diameter classes was generally aggregated for trees smaller than 10 cm of diameter and between 10 and 20 cm and random for the others, proving the existence of a tendency which in young trees is more aggregated than in old ones. The spatial pattern of the dominant species is always strongly similar to the general pattern of each forestry formation. The differences between the spatial patterns of two or three coincident species, among the forestry formations, indicate that its pattern is influenced by each different environment. This stands out the importance of its self-ecology and of its ecological processes, intrinsic of each community that can explain the observed patterns.