Consequences of Landscape Heterogeneity on Grassland Diversity and Productivity in the Espinal Agroforestry System of Central Chile

The current land use system in the anthropogenic savannas (Espinales) of the Mediterranean climate region of Chile, has resulted in considerable heterogeneity at the landscape level which is associated with different covers of the legume tree, Acacia caven. The effects of landscape heterogeneity on the diversity and productivity of herbaceous plant communities were studied in 29 plots of 1000 m², with a wide range of woody cover. A detrended correspondence analysis of the species × plots matrix explained 73% of the total variation and revealed the existence of two trends of variation in floristic composition: one associated with physiographic position (hillsides and flatlands) and the other related to the number of years since the last cutting, or coppicing, of A. caven. Despite the great majority of the original herbaceous species having disappeared as a result of the prevailing land use system, some native species have been able to survive especially on hillside areas with low grazing intensity. Woody cover was a good indicator of spatial heterogeneity and land use history. It was also correlated with stocking rate, above-ground biomass of herbaceous vegetation, and soil fertility (organic matter, nitrogen and phosphorus concentration), both on hillsides and flatlands. The relationship between woody cover and herbaceous plant species richness was significant and unimodal in flat land areas, and linear, and marginally significant, on hillsides. The consequences of land use changes on the conservation of the ecological and productive values of grasslands are analyzed.     

Evaluating the potential for urban heat-island mitigation by greening parking lots

Artificial urban land uses such as commercial and residential buildings, roads, and parking lots covered by impervious surfaces can contribute to the formation of urban heat islands (UHIs), whereas vegetation such as trees, grass, and shrubs can mitigate UHIs. Considering the increasing area of parking lots with little vegetation cover in Nagoya, Japan, this study evaluated the potential for UHI mitigation of greening parking lots in Nagoya. The relationships between land surface temperature (LST) and land use/land cover (LULC) in different seasons were analyzed using multivariate linear regression models. Potential UHI mitigation was then simulated for two scenarios: (1) grass is planted on the surface of each parking lot with coverage from 10 to 100% at an interval of 10% and (2) parking lots are covered by 30% trees and 70% grass. The results show that different LULC types play different roles in different seasons and times. On average, both scenarios slightly reduced the LST for the whole study area in spring or summer. However, for an individual parking lot, the maximum LST decrease was 7.26 °C in summer. This research can help us understand the roles of vegetation cover and provide practical guidelines for planning parking lots to mitigate UHIs.     

Homogenization of northern U.S. Great Lakes forests due to land use

Human land use of forested regions has intensified worldwide in recent decades, threatening long-term sustainability. Primary effects include conversion of land cover or reversion to an earlier stage of successional development. Both types of change can have cascading effects through ecosystems; however, the long-term effects where forests are allowed to regrow are poorly understood. We quantify the regional-scale consequences of a century of Euro-American land use in the northern U.S. Great Lakes region using a combination of historical Public Land Survey records and current forest inventory and land cover data. Our analysis shows a distinct and rapid trajectory of vegetation change toward historically unprecedented and simplified conditions. In addition to overall loss of forestland, current forests are marked by lower species diversity, functional diversity, and structural complexity compared to pre-Euro-American forests. Today’s forest is marked by dominance of broadleaf deciduous species—all 55 ecoregions that comprise the region exhibit a lower relative dominance of conifers in comparison to the pre-Euro-American period. Aspen (Populus grandidentata and P. tremuloides) and maple (Acer saccharum and A. rubrum) species comprise the primary deciduous species that have replaced conifers. These changes reflect the cumulative effects of local forest alterations over the region and they affect future ecosystem conditions as well as the ecosystem services they provide. Electronic Supplementary Material The online version of this article (doi:) contains supplementary material, which is available to authorized users. An erratum to this article can be found at     

Visualizing certainty of extrapolations from models of land change

This article presents a method to estimate and to visualize the certainty of land change models as they extrapolate beyond the time interval for which empirical data exist. The method to project the certainty relies on measurements of model performance during a validation run with historic data and on the assumption that the model’s accuracy approaches randomness as it predicts farther into the future. A land change model typically predicts each pixel as exactly one category for each year. This article presents a technique to convert those predictions into conditional probabilities. As an example, we use the model Geomod to extrapolate forest change over a century for the Plum Island Ecosystems, which is a Long Term Ecological Research site of the United States’ National Science Foundation. Geomod uses calibration information between 1971 and 1985 in order to predict the changes from 1985 to 1999, at which point the validation procedure measures the model’s predictive accuracy. Then the model is re-calibrated with information from 1985 to 1999 in order to extrapolate into the future, assuming a business as usual scenario. As time progresses, the expected accuracy approaches 0.5, which is the probability at which the model’s prediction is as accurate as a random prediction, since the application involves two categories. The extrapolated accuracy of the prediction for the entire study area in the year 2097 is 68%. The method is designed to work with any number of categories so it can be used with a variety of land change models.     

Regional patterns of riparian characteristics in the interior Columbia River basin, Northwestern USA: applications for restoration planning

Recent declines in anadromous Pacific salmonids (Oncorhynchus spp.) have been attributed, in part, to degradation of freshwater habitat. Because riparian areas directly affect instream habitat, assessing riparian characteristics is essential for predicting salmon habitat quality and for prioritizing restoration projects. We quantified land use modification of anadromous fish-bearing streams in the interior Columbia River basin at multiple resolutions. We identified riparian areas in several land use and land cover classes using remotely sensed data. We then interpreted aerial photographs at random locations within each class to quantify riparian modifications at a local (stream reach) scale. Riparian areas in agricultural and urban areas were significantly narrower (~30 m, median) than those in forested or shrub/grass areas (~70 m). The largest proportion of modified riparian areas occurred in low-gradient streams with floodplains in semi-arid ecoregions. Riparian vegetation in these areas is unlikely to provide adequate in-stream functions, making these areas a natural starting point for restoration prioritization. We investigated how existing riparian restoration projects were spatially related to riparian land use and found that restoration effort varied among subwatersheds. Effective strategies for restoring high quality salmon habitat will be watershed-specific and must restore natural watershed processes. By using a hierarchical analysis to identify regional strategies, restoration or conservation activity can be focused in specific basins and thereby increase the likelihood that efforts will significantly improve habitat conditions for listed salmonids.     

Models to distinguish effects of landscape patterns and human population pressures associated with species loss in Canadian national parks

It is widely accepted that large protected areas are required to effectively conserve historical species composition. However, recent analyses of mammal species loss in Canadian and African national parks contradict earlier conclusions that extent of local extinctions (i.e., extirpations) is strongly inversely related to park size, suggesting that park size alone is inadequate to predict reserve designs that may sustain biodiversity. To plan protected areas that will meet conservation goals, reserve-design models that incorporate other landscape-scale factors in addition to reserve area are needed; potential factors include the types and intensity of land use and habitat change, together with land cover types, in and around parks. Additionally, human population size around parks, and visitor density in parks may affect species loss. We quantified land use, land cover, and human population in and around 24 Canadian national parks to model effects of human disturbance and changes in natural habitats on known mammal extirpations.Multiple regression models were compared using the Akaike Information Criterion (AIC_c). The most parsimonious model (AIC_c weighting w _i = 0.5391) emphasized effective habitat area in and around parks and not visitor numbers nor human population size around parks. Our model suggests that parks with as little as 3140 km² of effective habitat area inside may be large enough to conserve historical mammal species composition if they are also surrounded by at least 18 000 km² of effective habitat within 50 km of park boundaries.     

On the accuracy of landscape pattern analysis using remote sensing data

Advances in remote sensing technologies have provided practical means for land use and land cover mapping which is critically important for landscape ecological studies. However, all classifications of remote sensing data are subject to different kinds of errors, and these errors can be carried over or propagated in subsequent landscape pattern analysis. When these uncertainties go unreported, as they do commonly in the literature, they become hidden errors. While this is apparently an important issue in the study of landscapes from either a biophysical or socioeconomic perspective, limited progress has been made in resolving this problem. Here we discuss how errors of mapped data can affect landscape metrics and possible strategies which can help improve the reliability of landscape pattern analysis.     

Persistent changes in forest vegetation and seed bank 1,600 years after human occupation

Past land use is an important factor determining vegetation in temperate deciduous forests. Little is known about the long-term persistence of these impacts on vegetation but especially on the seed bank. This study assessed whether soil characteristics remain altered 1,600 years after human occupation and if this yielded persistent differences in forest plant communities and their seed bank in particular. Compiègne forest is located in northern-France and has a history of continuous forest cover since the end of Roman times. Twenty-four Gallo-Roman and 24 unoccupied sites were sampled and data were analysed using paired sample tests to investigate whether soil, vegetation and seed bank still differed significantly. The soil was persistently altered on the Gallo-Roman sites resulting in elevated phosphorus levels and pH (dependent on initial soil conditions) which translated into increased vegetation and seed bank species richness. Though spatially isolated, Gallo-Roman sites supported both a homogenized vegetation and seed bank. Vegetation differences were not the only driver behind seed bank differences. Similarity between vegetation and seed bank was low and the possibility existed that agricultural ruderals were introduced via the former land use. Ancient human occupation leaves a persistent trace on forest soil, vegetation and seed bank and appears to do so at least 1,600 years after the former occupation. The geochemical alterations created an entirely different habitat causing not only vegetation but also the seed bank to have altered and homogenized composition and characteristics. Seed bank differences likely persisted by the traditional forest management and altered forest environment.     

Predicting land cover change and avian community responses in rapidly urbanizing environments

We used an integrated modeling approach to simulate future land cover and predict the effects of future urban development and land cover on avian diversity in the Central Puget Sound region of Washington State, USA. We parameterized and applied a land cover change model (LCCM) that used output from a microsimulation model of urban development, UrbanSim, and biophysical site and landscape characteristics to simulate land cover 28 years into the future. We used 1991, 1995, and 1999 Landsat TM-derived land cover data and three different spatial partitions of our study area to develop six different estimations of the LCCM. We validated model simulations with 2002 land cover. We combined UrbanSim land use outputs and LCCM simulations to predict changes in avian species richness. Results indicate that landscape composition and configuration were important in explaining land cover change as well as avian species response to landscape change. Over the next 28 years, urban land cover was predicted to increase at the expense of agriculture and deciduous and mixed lowland forests. Land cover changes were predicted to reduce the total number of avian species, with losses primarily in native forest specialists and gains in common synanthropic species such as the American Crow (Corvus brachyrhynchos). The integrated modeling framework we present has potential applications in urban and natural resource planning and management and in assessing of the effects of policies on land development, land cover, and avian biodiversity.     

Projecting land use transitions at forest fringes in the Philippines at two spatial scales

This paper presents two applications of a spatially explicit model of land use change at two spatial scales: a nation-wide application for the Philippines at relatively coarse resolution and an application with high spatial resolution for one island of the Philippines: Sibuyan island, Romblon province. The model is based on integrated analysis of socio-economic and biophysical factors that determine the allocation of land use change in combination with the simulation of the temporal dynamics (path-dependence and reversibility of changes), spatial policies and land requirements. Different scenarios of near-future developments in land use pattern are simulated illustrating the effects of implementing spatial policies. Results from the coarse scale model with national extent mainly serve to identify the overall pattern of land use change and hot zones of deforestation. The detailed application provides more insight in the pattern of land use change and its consequences for ecological processes. The use of the results for environmental assessments is illustrated by calculating spatial indices to assess the impact of land use change on forest fragmentation. It is concluded that spatially explicit modeling of land use change yields important information for environmental management and land use planning. The applications illustrate that the scale of analysis is an important determinant of the model configuration, the interpretation of the results and the potential use by stakeholders. There is no single, optimal, scale for land use change assessments. Each scale enables different types of analysis and assessment: applications at multiple scales therefore give complementary information needed for environmental management.This revised version was published online in May 2005 with corrections to the Cover Date.