Regression Techniques for Examining Land Use/Cover Change: A Case Study of a Mediterranean Landscape

In many areas of the northern Mediterranean Basin the abundance of forest and scrubland vegetation is increasing, commensurate with decreases in agricultural land use(s). Much of the land use/cover change (LUCC) in this region is associated with the marginalization of traditional agricultural practices due to ongoing socioeconomic shifts and subsequent ecological change. Regression-based models of LUCC have two purposes: (i) to aid explanation of the processes driving change and/or (ii) spatial projection of the changes themselves. The independent variables contained in the single ‘best’ regression model (that is, that which minimizes variation in the dependent variable) cannot be inferred as providing the strongest causal relationship with the dependent variable. Here, we examine the utility of hierarchical partitioning and multinomial regression models for, respectively, explanation and prediction of LUCC in EU Special Protection Area 56, ‘Encinares del río Alberche y Cofio’ (SPA 56) near Madrid, Spain. Hierarchical partitioning estimates the contribution of regression model variables, both independently and in conjunction with other variables in a model, to the total variance explained by that model and is a tool to isolate important causal variables. By using hierarchical partitioning we find that the combined effects of factors driving land cover transitions varies with land cover classification, with a coarser classification reducing explained variance in LUCC. We use multinomial logistic regression models solely for projecting change, finding that accuracies of maps produced vary by land cover classification and are influenced by differing spatial resolutions of socioeconomic and biophysical data. When examining LUCC in human-dominated landscapes such as those of the Mediterranean Basin, the availability and analysis of spatial data at scales that match causal processes is vital to the performance of the statistical modelling techniques used here.     

Temporal Beta Diversity of Bird Assemblages in Agricultural Landscapes: Land Cover Change vs. Stochastic Processes

Temporal variation in the composition of species assemblages could be the result of deterministic processes driven by environmental change and/or stochastic processes of colonization and local extinction. Here, we analyzed the relative roles of deterministic and stochastic processes on bird assemblages in an agricultural landscape of southwestern France. We first assessed the impact of land cover change that occurred between 1982 and 2007 on (i) the species composition (presence/absence) of bird assemblages and (ii) the spatial pattern of taxonomic beta diversity. We also compared the observed temporal change of bird assemblages with a null model accounting for the effect of stochastic dynamics on temporal beta diversity. Temporal assemblage dissimilarity was partitioned into two separate components, accounting for the replacement of species (i.e. turnover) and for the nested species losses (or gains) from one time to the other (i.e. nestedness-resultant dissimilarity), respectively. Neither the turnover nor the nestedness-resultant components of temporal variation were accurately explained by any of the measured variables accounting for land cover change (r²<0.06 in all cases). Additionally, the amount of spatial assemblage heterogeneity in the region did not significantly change between 1982 and 2007, and site-specific observed temporal dissimilarities were larger than null expectations in only 1% of sites for temporal turnover and 13% of sites for nestedness-resultant dissimilarity. Taken together, our results suggest that land cover change in this agricultural landscape had little impact on temporal beta diversity of bird assemblages. Although other unmeasured deterministic process could be driving the observed patterns, it is also possible that the observed changes in presence/absence species composition of local bird assemblages might be the consequence of stochastic processes in which species populations appeared and disappeared from specific localities in a random-like way. Our results might be case-specific, but if stochastic dynamics are generally dominant, the ability of correlative and mechanistic models to predict land cover change effects on species composition would be compromised.     

Effects of Land Cover on Stream Ecosystems: Roles of Empirical Models and Scaling Issues

We built empirical models to estimate the effects of land cover on stream ecosystems in the mid-Atlantic region (USA) and to evaluate the spatial scales over which such models are most effective. Predictive variables included land cover in the watershed, in the streamside corridor, and near the study site, and the number and location of dams and point sources in the watershed. Response variables were annual nitrate flux; species richness of fish, benthic macroinvertebrates, and aquatic plants; and cover of aquatic plants and riparian vegetation. All data were taken from publicly available databases, mostly over the Internet. Land cover was significantly correlated with all ecological response variables. Modeled R² ranged from 0.07 to 0.5, but large data sets often allowed us to estimate with acceptable precision the regression coefficients that express the change in ecological conditions associated with a unit change in land cover. Dam- and point-source variables were ineffective at predicting ecological conditions in streams and rivers, probably because of inadequacies in the data sets. The spatial perspective (whole watershed, streamside corridor, or local) most effective at predicting ecological response variables varied across response variables, apparently in concord with the mechanisms that control each of these variables. We found some evidence that predictive power fell in very small watersheds (less than 1–10 km²), suggesting that the spatial arrangement of landscape patches may become critical at these small scales. Empirical models can replace, constrain, or be combined with more mechanistic models to understand the effects of land-cover change on stream ecosystems. Present address for L.C. Thompson: Wildlife, Fish and Conservation Biology Department, University of California, Davis, CA 95616.     

Extreme land-cover and biodiversity change as an outcome of land abandonment on a Mediterranean island (eastern Adriatic)

Understanding land abandonment and the resulting changes in land cover provides data for suitable reaction to habitat and species losses this process brings. This study aimed to define land-cover types and their biodiversity, record spatio-temporal changes and detect the trajectories and magnitude of these changes. The study was conducted on the island of Molat in the eastern Adriatic Sea. Land cover was defined for different years (1910, 1959, 1986, 2006) using remote sensing and recent vegetation sampling. The obtained land-cover maps were used for spatio-temporal analysis of land-cover change. Open vegetation units of rocky grassland, mesophilous grasslands and farm land dominated in 1910, covering 90% of the island. The observed changes occurred in trajectories through semi-open towards closed vegetation. In 2006, closed vegetation dominated, covering approximately 70% of the island area. The overall land-cover change was extreme, occurring over 90% of the island surface. Biodiversity analysis was related to the present land-cover types and change trajectories, and showed a considerable decline of species richness towards closed vegetation types. All observed changes were correlated to island depopulation and land abandonment. Re-population and encouragement of agro-pastoral activities should reduce habitat and species loss in the process of secondary succession.     

Prediction of biodiversity hotspots in the Anthropocene: The case of veteran oaks

Over the past centuries, humans have transformed large parts of the biosphere, and there is a growing need to understand and predict the distribution of biodiversity hotspots influenced by the presence of humans. Our basic hypothesis is that human influence in the Anthropocene is ubiquitous, and we predict that biodiversity hot spot modeling can be improved by addressing three challenges raised by the increasing ecological influence of humans: (i) anthropogenically modified responses to individual ecological factors, (ii) fundamentally different processes and predictors in landscape types shaped by different land use histories and (iii) a multitude and complexity of natural and anthropogenic processes that may require many predictors and even multiple models in different landscape types. We modeled the occurrence of veteran oaks in Norway, and found, in accordance with our basic hypothesis and predictions, that humans influence the distribution of veteran oaks throughout its range, but in different ways in forests and open landscapes. In forests, geographical and topographic variables related to the oak niche are still important, but the occurrence of veteran oaks is shifted toward steeper slopes, where logging is difficult. In open landscapes, land cover variables are more important, and veteran oaks are more common toward the north than expected from the fundamental oak niche. In both landscape types, multiple predictor variables representing ecological and human‐influenced processes were needed to build a good model, and several models performed almost equally well. Models accounting for the different anthropogenic influences on landscape structure and processes consistently performed better than models based exclusively on natural biogeographical and ecological predictors. Thus, our results for veteran oaks clearly illustrate the challenges to distribution modeling raised by the ubiquitous influence of humans, even in a moderately populated region, but also show that predictions can be improved by explicitly addressing these anthropogenic complexities.     

Land Cover Change in Colombia: Surprising Forest Recovery Trends between 2001 and 2010

Background

Monitoring land change at multiple spatial scales is essential for identifying hotspots of change, and for developing and implementing policies for conserving biodiversity and habitats. In the high diversity country of Colombia, these types of analyses are difficult because there is no consistent wall-to-wall, multi-temporal dataset for land-use and land-cover change.

Methodology/Principal Findings

To address this problem, we mapped annual land-use and land-cover from 2001 to 2010 in Colombia using MODIS (250 m) products coupled with reference data from high spatial resolution imagery (QuickBird) in Google Earth. We used QuickBird imagery to visually interpret percent cover of eight land cover classes used for classifier training and accuracy assessment. Based on these maps we evaluated land cover change at four spatial scales country, biome, ecoregion, and municipality. Of the 1,117 municipalities, 820 had a net gain in woody vegetation (28,092 km²) while 264 had a net loss (11,129 km²), which resulted in a net gain of 16,963 km² in woody vegetation at the national scale. Woody regrowth mainly occurred in areas previously classified as mixed woody/plantation rather than agriculture/herbaceous. The majority of this gain occurred in the Moist Forest biome, within the montane forest ecoregions, while the greatest loss of woody vegetation occurred in the Llanos and Apure-Villavicencio ecoregions.

Conclusions

The unexpected forest recovery trend, particularly in the Andes, provides an opportunity to expand current protected areas and to promote habitat connectivity. Furthermore, ecoregions with intense land conversion (e.g. Northern Andean Páramo) and ecoregions under-represented in the protected area network (e.g. Llanos, Apure-Villavicencio Dry forest, and Magdalena-Urabá Moist forest ecoregions) should be considered for new protected areas.     

Quantifying the biophysical and socioeconomic drivers of changes in forest and agricultural land in South and Southeast Asia

South and Southeast Asia (SSEA) has been a hotspot for land use and land cover change (LULCC) in the past few decades. The identification and quantification of the drivers of LULCC are crucial for improving our understanding of LULCC trends. So far, the biophysical and socioeconomic drivers of forest change have not been quantified at the regional scale, particularly for SSEA. In this study, we quantify the biophysical and socioeconomic drivers of forest change on a country‐by‐country basis in SSEA using an integrated quantitative methodology, which systematically accounts for previously published driver information and regional datasets. We synthesize more than 200 publications to identify the drivers of the forest change at different spatial scales in SSEA. Subsequently, we collect spatially explicit proxy data to represent the identified drivers. We quantify the dynamics of forest and agricultural land from 1992 to 2015 using the Climate Change Initiative (CCI) land cover data developed by the European Space Agency (ESA). A geographically weighted regression method is employed to quantify the spatially heterogeneous drivers of forest change. Our results show that socioeconomic drivers are more important than biophysical drivers for the conversion of forest to agricultural land in South Asia and maritime Southeast Asia. In contrast, biophysical drivers are more important than socioeconomic drivers for the conversion of agricultural land to forest in maritime Southeast Asia and less important in South Asia. Both biophysical and socioeconomic drivers contribute approximately equally to both changes in the mainland Southeast Asia region. By quantifying the dynamics of forest and agricultural land and the spatially explicit drivers of their changes in SSEA, this study provides a solid foundation for LULCC modeling and projection.     

Agricultural Legacies in the Great Basin Alter Vegetation Cover, Composition, and Response to Precipitation

The land-use history of an ecosystem influences current structure and possibly response to modern disturbances and stresses. In semiarid systems the nature of land-use legacies is poorly understood, confounding efforts to establish sustainable management approaches. We compare previously cultivated and non-cultivated lands in Owens Valley, California, where cultivation once extended to 34% of the valley floor but was largely discontinued by 1940, to measure the influence of past disturbance on modern vegetation. We combined historic maps of cultivated and non-cultivated land with an extensive vegetation survey, historic aerial photographs, and satellite measurements of vegetation response to precipitation variability to examine the importance of land-use history in determining the sensitivity of vegetation to annual variations in precipitation. Remote sensing analysis showed that total plant cover on previously cultivated lands was lower and fluctuations in cover were marginally more dependent on precipitation compared with plant cover on non-cultivated lands. We then compared modern plant assemblages within cultivated and non-cultivated land to determine if compositional differences could explain the current patterns of vegetation cover. We found lower species richness on previously cultivated parcels, and higher frequency and cover of perennial grasses on non-cultivated lands. Therefore, we showed differences in land-cover patterns, isolated a mechanism that could account for the differences (species differences), and developed a method for remotely analyzing land regions that have experienced historic anthropogenic disturbance.     

The Definition of British Water Beetle Species Pools (Coleoptera) and their Relationship to Altitude, Temperature, Precipitation and Land Cover Variables

Pooled water beetle species lists from 1826 British national grid 10-km squares were analysed using multivariate ordination and classification methods. The relationships of pool groups to the climate, altitude and land cover variables were assessed using constrained and partial ordinations. Ordination of the species pool data indicated a major trend between squares in the north-west of Scotland and those in southern England, illustrating differences in acid and basic water standing water. Secondary variation was from acid standing water to fast-flowing streams and rivers. Classification generated nine species pool groups. These showed a distinct north-west to south-east trend but there was no obvious coastal or brackish water effect on distribution. The climatic and land cover variables were all significantly related to each other, and to north-south variation in grid square location, but the constrained ordination results indicated that that the most important influence on water beetle species pool distribution was mean summer temperature. Although the amount of variation explained by the environmental variables was low, spatial variation in the environmental predictors was almost as important as the environmental variables themselves in determining species pool composition. Mean annual temperature was also strongly correlated with species pool distribution with two land cover variables slightly less important. Altitude and precipitation had the least influence. The water beetle national recording scheme database appears to be of sufficiently high quality for environmental investigations at the British scale. There is considerable potential for the synthesis of invertebrate species distribution, land cover and climate change predictions in the assessment of environmental change. The results, together with previous work on other invertebrate species, indicate that changing summer temperatures may have a considerable influence on the distribution British invertebrate species.     

黄河三角洲自然保护区1992～2010年土地覆被变化分析

基于黄河三角洲自然保护区1992年、2000年和2010年三期遥感图像,分析近20年黄河三角洲自然保护区土地利用/覆被变化(LUCC)情况。结果表明,在1992～2010年间,黄河三角洲自然保护区内同种土地覆被类型的空间分布较一致,均以海域、滩涂和旱地为主,但同种土地覆盖类型的比重均发生不同程度的变化。总体上,旱地、河渠、水库、居民地和其他用地类型的变化程度不明显,但年际间有波动变化;草地面积虽持续减少,但总体变化不明显;灌木面积总体变化也不明显,但年际间波动较大;芦苇面积呈减少趋势,尤其是1992～2000年间,大量芦苇覆被地转化为旱地类型;养殖塘面积增加明显,近20年间增加约6.24×103 hm2,主要由滩涂、柽柳、碱蓬等开发形成;海域面积变化剧烈,海域转化为滩涂是造成海域面积减少的主要原因。黄河三角洲自然保护区LUCC改变了自然保护区的生态系统结构,降低了自然保护区的生态服务功能。造成黄河三角洲LUCC的原因既有自然因素,也有人为因素,但在该区LUCC的驱动力主要为人类活动。     

Land use change has stronger effects on functional diversity than taxonomic diversity in tropical Andean hummingbirds

Land use change modifies the environment at multiple spatial scales, and is a main driver of species declines and deterioration of ecosystem services. However, most of the research on the effects of land use change has focused on taxonomic diversity, while functional diversity, an important predictor of ecosystem services, is often neglected. We explored how local and landscape scale characteristics influence functional and taxonomic diversity of hummingbirds in the Andes Mountains in southern Ecuador. Data was collected in six landscapes along a land use gradient, from an almost intact landscape to one dominated by cattle pastures. We used point counts to sample hummingbirds from 2011 to 2012 to assessed how local factors (i.e., vegetation structure, flowering plants richness, nectar availability) and landscape factors (i.e., landscape heterogeneity, native vegetation cover) influenced taxonomic and functional diversity. Then, we analyzed environment – trait relationships (RLQ test) to explore how different hummingbird functional traits influenced species responses to these factors. Taxonomic and functional diversity of hummingbirds were positively associated with landscape heterogeneity but only functional diversity was positively related to native vegetation coverage. We found a weak response of taxonomic and functional diversity to land use change at the local scale. Environment‐trait associations showed that body mass of hummingbirds likely influenced species sensitivity to land use change. In conclusion, landscape heterogeneity created by land use change can positively influence hummingbird taxonomic and functional diversity; however, a reduction of native vegetation cover could decrease functional diversity. Given that functional diversity can mediate ecosystem services, the conservation of native vegetation cover could play a key role in the maintenance of hummingbird pollination services in the tropical Andes. Moreover, there are particular functional traits, such as body mass, that increase a species sensitivity to land use change.     

云南澜沧江流域土地利用和覆盖变化

由人类活动引起的土地利用和地被覆盖的变化是地球上环境变化的主要原因。上世纪90年代是云南省经济发展和环境变化的活跃时期。本文通过现代卫星遥感技术、地理信息系统和其它多学科手段相结合 ,系统调查评估了云南澜沧江流域 1990年至 1998年间土地利用和地被覆盖的变化 ,结果显示流域中林业用地面积从 1990年的 6 4 9%增长到 1998年的6 6 4 % ,但是森林有林地 (郁闭度 >30 %的天然林和人工林 )从 1990年的 5 2 6 %减少到 1998年的 35 3%。并且分析大规模商业性森林砍伐、基础建设、经济作物的种植、刀耕火种、薪材过度采集和砍伐建筑用材等引起了森林的结构的显著变化和退化 ,从而导致了生物多样性的下降。     

测量的区域土地覆盖格局研基于多尺度遥感究

利用1km、4km和8km 3种空间分辨率的NOAA/AVHRR数字影像,对中国NECT样带西部地区进行了土地覆盖分类及其景观特征的比较研究。重点比较了几种空间分辨率遥感数据分类结果边界的一致性和空间差异,以及影像所记录的景观格局的差异。为进一步在不同尺度上研究景观变化过程以及尺度转换研究奠定了基础。研究表明：3种空间分辨率的遥感影像所反映的区域土地覆盖的宏观空间格局是一致的,但类型的边界、每一类型斑块的形状和数量均产生较大的差异;经过对反映景观空间结构的4种指标（分维数、破碎度、多样性、优势度）的比较显示出随着遥感影像空间分辨率的变化,影像所反映的景观结构发生了较大的变化。其中,各覆盖类型的分维数表现出最大差异,表征着空间分辨率的变化对斑块复杂程度的影响最大。     

Impact of land use intensity on sandy desertification: An evidence from Horqin Sandy Land,China

It has been widely accepted that high land use intensity contributes to sandy desertification in Northern China. However, it is surprising that it is even not easy to find an explicit definition and proper indicator for the term “land use intensity” in the sandy desertification related literatures. To better understand the association between sandy desertification and its driving factors, especially in the context of the synergistic roles of both climatic and anthropogenic variables, an indicator for land use intensity was developed in this paper for quantifying the relative role of land use output on different kinds of vegetation cover. The results indicated land use intensity increased rapidly from 1980 to 1995, obviously decreased from 1995 to 2000, and increased slowly after 2000 as a result of the continued increase of socioeconomic pressures and the fluctuating changes in vegetative cover.An ARDL model was established and applied to analyze the correlation between the area of bare sand land and land use intensity with the influence of annual precipitation in temporal dimension. The area of bare sand land was significantly affected by land use intensity in the long run. However, in the short run, the area of bare sand land was mainly impacted by the auto-correlation effect of itself in temporal dimension and by the annual precipitation. The improvement of the sand dunes obviously reduced the risk of sandy desertification under the condition of specific land use intensity.Before analyzing the correlation between land use intensity and sandy desertification, specific skills were applied to improve the model, including data interpolation and regression verification, since there would be regression biases resulting from the acquisition and processing of time-series data of different sources. Results showed that the area of bare sand land (S_t)and the land use intensity (LI_t) were time-independent. Lag terms of these two variables were added to improve original model.Changes in socioeconomic pressures and ecological restoration projects had obvious influences on land use intensity. Along with the steady increase of socioecological pressures on land and the changes in vegetative cover resulting from various ecological protection strategies and ecological restoration projects, shifts in land use intensity followed a different trend with the population and the social-economic demands. Nonetheless, the continuous increase of socioeconomic demands will increase land use intensity in the long run, so that the risk of sandy desertification remains high.     

Conservation of wildlife populations: factoring in incremental disturbance

Progressive anthropogenic disturbance can alter ecosystem organization potentially causing shifts from one stable state to another. This potential for ecosystem shifts must be considered when establishing targets and objectives for conservation. We ask whether a predator–prey system response to incremental anthropogenic disturbance might shift along a disturbance gradient and, if it does, whether any disturbance thresholds are evident for this system. Development of linear corridors in forested areas increases wolf predation effectiveness, while high density of development provides a safe‐haven for their prey. If wolves limit moose population growth, then wolves and moose should respond inversely to land cover disturbance. Using general linear model analysis, we test how the rate of change in moose (Alces alces) density and wolf (Canis lupus) harvest density are influenced by the rate of change in land cover and proportion of land cover disturbed within a 300,000 km² area in the boreal forest of Alberta, Canada. Using logistic regression, we test how the direction of change in moose density is influenced by measures of land cover change. In response to incremental land cover disturbance, moose declines occurred where <43% of land cover was disturbed; in such landscapes, there were high rates of increase in linear disturbance and wolf density increased. By contrast, moose increases occurred where >43% of land cover was disturbed and wolf density declined. Wolves and moose appeared to respond inversely to incremental disturbance with the balance between moose decline and wolf increase shifting at about 43% of land cover disturbed. Conservation decisions require quantification of disturbance rates and their relationships to predator–prey systems because ecosystem responses to anthropogenic disturbance shift across disturbance gradients.     

Consequences of the Armed Conflict, Forced Human Displacement, and Land Abandonment on Forest Cover Change in Colombia: A Multi-scaled Analysis

Most studies of land change have focused on patterns, rates, and drivers of deforestation, but much less is known about the dynamics associated with agricultural abandonment and ecosystem recovery. Furthermore, most studies are conducted at a single spatial scale, and few have included variables related with internal socio-political conflicts. Here we evaluated the effect of environmental, demographic, and socio-economic variables on woody cover change in Colombia between 2001 and 2010 at the country, biome, and ecoregion scales. We also incorporated factors that reflect the unique history of Colombia such as the presence of illegal-armed groups and forced human displacement. Environmental variables explained the patterns of deforestation and forest regrowth at all scales because they can restrict or encourage different land uses across multiple spatial scales. Demographic variables were important at the biome and ecoregion scales and appear to be a consequence of the armed conflict, particularly through forced human displacement (for example, rural–urban migration), which in some areas has resulted in forest regrowth. In other areas, the impact of illegal armed groups has reduced forest cover, particularly in areas rich in gold and lands appropriate for cattle grazing. This multi-scale and multivariate approach provides a new insight into the complex relationship between woody cover change and land abandonment triggered mainly by armed conflict.     

Spatial–Temporal Dynamics in Barrier Island Upland Vegetation: The Overlooked Coastal Landscape

Barrier islands provide the first line of defense against storms for millions of people living in coastal areas. Upland vegetation (that is, grassland, shrubland, and maritime forest) has received little attention, even though this land surface is most strongly affected by development pressures. We use remote-sensing analysis to assess state change on seven undeveloped Virginia barrier islands over 27 years (1984–2011) that are free from direct human influence. Our analysis highlights the spatial–temporally dynamic nature of barrier island upland land area and vegetation, with rapidly changing ecosystem states. Over the time period, upland vegetation was dramatically reduced by 29% whereas woody vegetation cover increased 40% across all islands. Although conversions between sand, grassland, and woody vegetation were variable within each island, three major patterns of vegetative land-cover change were apparent: overall loss of vegetative cover, frequent transitions between grass and woody cover, and gain in woody cover. These patterns are valuable for understanding natural evolution of barrier islands in response to sea-level rise. Evaluation of temporal dynamics in barrier upland is needed to characterize underlying processes including island resilience or chronic stress, and is a prerequisite to sustainable coastal management- and resilience-based planning, especially when implementing ecosystem-based solutions.     

Multiple Methods in the Study of Driving Forces of Land Use and Land Cover Change: A Case Study of SE Kajiado District,Kenya

This landscape-scale study combines analysis of multitemporal satellite imagery spanning 30 years and information from field studies extending over 25 years to assess the extent and causes of land use and land cover change in the Loitokitok area, southeast Kajiado District, Kenya. Rain fed and irrigated agriculture, livestock herding, and wildlife and tourism have all experienced rapid change in their structure, extent, and interactions over the past 30 years in response to a variety of economic, cultural, political, institutional, and demographic processes. Land use patterns and processes are explored through a complementary application of interpretation of satellite imagery and case study analysis that explicitly addresses the local–national spatial scale over a time frame appropriate to the identification of fundamental causal processes. The results illustrate that this combination provides an effective basis for describing and explaining patterns of land use and land cover change and their root causes.     

Forest Restoration in Urbanizing Landscapes: Interactions Between Land Uses and Exotic Shrubs

Preventing and controlling exotic plants remains a key challenge in any ecological restoration, and most efforts are currently aimed at local scales. We combined local‐ and landscape‐scale approaches to identify factors that were most closely associated with invasion of riparian forests by exotic shrubs (Amur honeysuckle [Lonicera maackii] and Tatarian honeysuckle [L. tatarica]) in Ohio, U.S.A. Twenty sites were selected in mature riparian forests along a rural–urban gradient (<1–47% urban land cover). Within each site, we measured percent cover of Lonicera spp. and native trees and shrubs, percent canopy cover, and facing edge aspect. We then developed 10 a priori models based on local‐ and landscape‐level variables that we hypothesized would influence percent cover of Lonicera spp. within 25 m of the forest edge. To determine which of these models best fit the data, we used an information‐theoretic approach and Akaike's information criterion. Percent cover of Lonicera was best explained by the proportion of urban land cover within 1 km of riparian forests. In particular, percent cover of Lonicera was greater in forests within more urban landscapes than in forests within rural landscapes. Results suggest that surrounding land uses influence invasion by exotic shrubs, and explicit consideration of land uses may improve our ability to predict or limit invasion. Moreover, identifying land uses that increase the risk of invasion may inform restoration efforts.     

Relative importance of abiotic and land use factors in explaining variation in woody vegetation in a French rural landscape

Abstract. In a rural landscape, scale vegetation patterns of woody species are controlled by both abiotic and land use factors. The woody species composition in 126 sample plots was analysed and land use factors and some abiotic parameters were quantified using land register data. The relative importance of land use and abiotic factors was differentiated using a partial Canonical Correspondence Analysis (CCA); the influence of land use in neighbouring areas was explored by changing the scale of land use sampling. The woody species composition appears to be controlled equally by land use and abiotic factors. The fraction of floristic variation in tree species composition explained by land use variables was 33.2 % in 1980 and 30.8 % in 1992, while abiotic variables accounted for 31.2 %. Part of the 17 % of the floristic variance explained is related to the surrounding land use. Thus, when the land use of the sampled plots and the surrounding land use are considered simultaneously, up to 36.9 % of the species variation may be explained. Partial CCA enabled us to quantify the respective proportion of floristic variance which could be explained by land use (36.9 %), abiotic variables alone (20.2 %), shared variance (12.0 %) and unexplained variance (31.2 %). Our results indicated that a delayed effect of variation in land use on plant populations may exist. This delay may result either from population characteristics or from inadequate land use assessment. This study indicates the need for simultaneously examining land use and abiotic patterns in ecological studies, as many Mediterranean-type ecosystems have been shaped by these patterns.