Digital interpretation and management of land cover - a case study of Cyprus

Knowledge based methods using Geographic Information System and Remote Sensing for land cover classification and future land allocation in Cyprus are presented. Land cover was categorized combining statistical classification and expert rules, using multi-temporal Landsat TM and MSS data, and digitized maps of elevation and geology. Land needed for future infrastructure was allocated using multi-criteria evaluation. Reforestation area were identified for Pinus brutia and P. nigra comparing expert rules and multi-criteria evaluation.     

Comparison of land use/land cover change and landscape patterns in Honghe National Nature Reserve and the surrounding Jiansanjiang Region,China

Land use and land cover change (LUCC) determines landscape patterns and affects the ability of ecosystems to provide the services and biodiversity on which humans ultimately depend. The Honghe National Nature Reserve is a biodiversity-rich area in the Jiansanjiang region of northeast China. In this study, the LUCC and landscape patterns were compared between the reserve and the Jiansanjiang region. With remote sensing (RS) and geographic information system (GIS) procedures, satellite images from 1989, 2001 and 2010 were used to calculate dynamics of LUCC amplitudes, landscape pattern index, transition matrix. The influence of LUCC on the wetland landscape of the nature reserve was discussed in the context of broader LUCC analyses. The results showed that land uses in the studied regions changed remarkedly over the time period; swamp area declined significantly as arable land increased. The ecological landscape index showed that distinct landscape patches were small, scattered and highly fragmented, moving toward a more monotonous landscape. Anthropogenic activities such as farming directly decreased the wetland landscape diversity. Furthermore, anthropogenic factors diminished wetland areas indirectly through climatic factors, namely air temperature and precipitation levels. National and regional policies on agriculture and water use have been highly influential, and the Honghe National Nature Reserve is highly susceptible to land use changes in the surrounding Jiansanjiang region.     

Combining land cover mapping of coastal dunes with vegetation analysis

Question: Coastal dune systems are characterized by a natural mosaic that promotes species diversity. This heterogeneity often represents a severe problem for traditional mapping or ground survey techniques. The work presented here proposes to apply a very detailed CORINE land cover map as baseline information for plant community sampling and analysis in a coastal dune landscape. Location: Molise coast, Central Italy. Method: We analysed through an error matrix the coherence between land cover classes and vegetation types identified through a field survey. The CORINE land cover map (scale 1: 5000) of the Molise coast was used with the CORINE legend expanded to a fourth level of detail for natural and semi‐natural areas. Vegetation data were collected following a random stratified sampling design using the CORINE land cover classes as strata. An error matrix was used to compare, on a category‐by‐category basis, the relationship between vegetation types (obtained by cluster analyses of sampling plots) and land cover classes of the same area. Results: The coincidence between both classification approaches is quite good. Only one land cover class shows a very weak agreement with its corresponding vegetation type; this result was interpreted as being related to human disturbance. Conclusions: Since it is based on a standard land cover classification, the proposal has a potential for application to most European coastal systems. This method could represent a first step in the environmental planning of coastal systems.     

Comparison of biometrical models for joint linkage association mapping

Joint linkage association mapping (JLAM) combines the advantages of linkage mapping and association mapping, and is a powerful tool to dissect the genetic architecture of complex traits. The main goal of this study was to use a cross-validation strategy, resample model averaging and empirical data analyses to compare seven different biometrical models for JLAM with regard to the correction for population structure and the quantitative trait loci (QTL) detection power. Three linear models and four linear mixed models with different approaches to control for population stratification were evaluated. Models A, B and C were linear models with either cofactors (Model-A), or cofactors and a population effect (Model-B), or a model in which the cofactors and the single-nucleotide polymorphism effect were modeled as nested within population (Model-C). The mixed models, D, E, F and G, included a random population effect (Model-D), or a random population effect with defined variance structure (Model-E), a kinship matrix defining the degree of relatedness among the genotypes (Model-F), or a kinship matrix and principal coordinates (Model-G). The tested models were conceptually different and were also found to differ in terms of power to detect QTL. Model-B with the cofactors and a population effect, effectively controlled population structure and possessed a high predictive power. The varying allele substitution effects in different populations suggest as a promising strategy for JLAM to use Model-B for the detection of QTL and then to estimate their effects by applying Model-C.     

The role of land cover in bioclimatic models depends on spatial resolution

Aim We explored the importance of climate and land cover in bird species distribution models on multiple spatial scales. In particular, we tested whether the integration of land cover data improves the performance of pure bioclimatic models. Location Finland, northern Europe. Methods The data of the bird atlas survey carried out in 1986–89 using a 10 × 10 km uniform grid system in Finland were employed in the analyses. Land cover and climatic variables were compiled using the same grid system. The dependent and explanatory variables were resampled to 20‐km, 40‐km and 80‐km resolutions. Generalized additive models (GAM) were constructed for each of the 88 land bird species studied in order to estimate the probability of occurrence as a function of (1) climate and (2) climate and land cover variables. Model accuracy was measured by a cross‐validation approach using the area under the curve (AUC) of a receiver operating characteristic (ROC) plot. Results In general, the accuracies of the 88 bird–climate models were good at all studied resolutions. However, the inclusion of land cover increased the performance of 79 and 78 of the 88 bioclimatic models at 10‐km and 20‐km resolutions, respectively. There was no significant improvement at the 40‐km resolution. In contrast to the finer resolutions, the inclusion of land cover variables decreased the modelling accuracy at 80km resolution. Main conclusions Our results suggest that the determinants of bird species distributions are hierarchically structured: climatic variables are large‐scale determinants, followed by land cover at finer resolutions. The majority of the land bird species in Finland are rather clearly correlated with climate, and bioclimate envelope models can provide useful tools for identifying the relationships between these species and the environment at resolutions ranging from 10 km to 80 km. However, the notable contribution of land cover to the accuracy of bioclimatic models at 10–20‐km resolutions indicates that the integration of climate and land cover information can improve our understanding and model predictions of biogeographical patterns under global change.     

Seed removal decrease by invasive Argentine ants in a high Nature Value farmland

Seed dispersal by ants is an important ecological process that maintains the structure anddiversity of natural communities, however, it is vulnerable to biological invasions. Argentine ants are one of the worst invasive ant species and cause severe changes in ecosystem processes and native ant biodiversity declines in invaded sites. Here, we studied seed removal by ants combining observations and a cafeteria experiment with seeds of four myrmecochorous plant species (Centaurea sphaerocephala, Rosmarinus officinalis, Silybum marianum, and Ulex australis) in two sites (invaded and uninvaded) located in the Mediterranean Montado ecosystem and classified as High Nature Value farmland (HNV). Significant differences in daily seed removal rates were found between the two study sites. In uninvaded sites, several native ant species were attracted to the seeds, resulting in all seeds being removed rapidly. The majority of seed removal events were carried out by two key seed disperses Pheidole pallidula (71%) and Aphaenogaster iberica (26%) with a clear preference for diaspored with larger and heavier elaiosome (i.e., C. sphaerocephala, S. marianum). By contrast, while the Argentine ant showed some interest (68% of seeds were interacted with), no seed removal events were observed. The extirpation of the local ant fauna by the Argentine ant and its inability to ensure seed dispersal services may lead to the interference and eventually to the collapse of seed dispersal of the four studied myrmecochorous plants in the invaded site in the future. We argue that these discrete but severe consequences of an invasive species on a key ecological process may strongly affect the functioning of the Montado ecosystem.     

Challenges in using land use and land cover data for global change studies

Land use and land cover data play a central role in climate change assessments. These data originate from different sources and inventory techniques. Each source of land use/cover data has its own domain of applicability and quality standards. Often data are selected without explicitly considering the suitability of the data for the specific application, the bias originating from data inventory and aggregation, and the effects of the uncertainty in the data on the results of the assessment. Uncertainties due to data selection and handling can be in the same order of magnitude as uncertainties related to the representation of the processes under investigation. While acknowledging the differences in data sources and the causes of inconsistencies, several methods have been developed to optimally extract information from the data and document the uncertainties. These methods include data integration, improved validation techniques and harmonization of classification systems. Based on the data needs of global change studies and the data availability, recommendations are formulated aimed at optimal use of current data and focused efforts for additional data collection. These include: improved documentation using classification systems for land use/cover data; careful selection of data given the specific application and the use of appropriate scaling and aggregation methods. In addition, the data availability may be improved by the combination of different data sources to optimize information content while collection of additional data must focus on validation of available data sets and improved coverage of regions and land cover types with a high level of uncertainty. Specific attention in data collection should be given to the representation of land management (systems) and mosaic landscapes.     

Assessment of status and trends of olive farming intensity in EU-Mediterranean countries using remote sensing time series and land cover data

For EU-Mediterranean olive groves (Olea europaea), mapped in CORINE, classes of olive farming intensities were derived from the outcome of a multi-temporal remote sensing vegetation dynamics analysis. The management intensity classes were developed in view of a differentiated accounting of olive groves when delineating High Nature Value Farmland areas (HNV) at pan-European level. The remote sensing input data used was the Green Vegetation Fraction (GVF), derived in 10-day intervals from a long-term time series of NOAA AVHRR data. The key physical parameters for the intensity assessment were obtained by parametrization of the observed annual growth cycle. These parameters represent two functional proportions in olive groves, a seasonally changing annual component and a permanent perennial vegetation component, which were interpreted to classify data in three olive farming intensity levels. 27% of the assessed EU-Mediterranean wide olive areas were found to be of very high intensity, 12% were classified as low intensity olive areas and 61% form an intermediate intensity class. Strong intensification was found in Spain, followed by Italy, Greece and Portugal. Most pronounced indications of management changes for the period 1990–2000 were observed for the Spanish provinces Jaèn/Cordoba and the Italian province of Bari.     

High resolution population maps for low income nations: combining land cover and census in East Africa

Background

Between 2005 and 2050, the human population is forecast to grow by 2.7 billion, with the vast majority of this growth occurring in low income countries. This growth is likely to have significant social, economic and environmental impacts, and make the achievement of international development goals more difficult. The measurement, monitoring and potential mitigation of these impacts require high resolution, contemporary data on human population distributions. In low income countries, however, where the changes will be concentrated, the least information on the distribution of population exists. In this paper we investigate whether satellite imagery in combination with land cover information and census data can be used to create inexpensive, high resolution and easily-updatable settlement and population distribution maps over large areas.

Methodology/Principal Findings

We examine various approaches for the production of maps of the East African region (Kenya, Uganda, Burundi, Rwanda and Tanzania) and where fine resolution census data exists, test the accuracies of map production approaches and existing population distribution products. The results show that combining high resolution census, settlement and land cover information is important in producing accurate population distribution maps.

Conclusions

We find that this semi-automated population distribution mapping at unprecedented spatial resolution produces more accurate results than existing products and can be undertaken for as little as $0.01 per km². The resulting population maps are a product of the Malaria Atlas Project (MAP: http://www.map.ox.ac.uk) and are freely available.     

Consequences of organic farming and landscape heterogeneity for species richness and abundance of farmland birds

It has been suggested that organic farming may benefit farmland biodiversity more in landscapes that have lost a significant part of its former landscape heterogeneity. We tested this hypothesis by comparing bird species richness and abundance during the breeding season in organic and conventional farms, matched to eliminate all differences not directly linked to the farming practice, situated in either homogeneous plains with only a little semi-natural habitat or in heterogeneous farmland landscapes with abundant field borders and semi-natural grasslands. The effect of farm management on species richness interacted with landscape structure, such that there was a positive relationship between organic farming and diversity only in homogeneous landscapes. This pattern was mainly dependent on the species richness of passerine birds, in particular those that were invertebrate feeders. Species richness of non-passerines was positively related to organic farming independent of the landscape context. Bird abundance was positively related to landscape heterogeneity but not to farm management. This was mainly because the abundance of passerines, particularly invertebrate feeders, was positively related to landscape heterogeneity. We suggest that invertebrate feeders particularly benefit from organic farming because of improved foraging conditions through increased invertebrate abundances in otherwise depauperate homogeneous landscapes. Although many seed-eaters also benefit from increased insect abundance, they may also utilize crop seed resources in homogeneous landscapes and conventional farms. The occurrence of an interactive effect of organic farming and landscape heterogeneity on bird diversity will have consequences for the optimal allocation of resources to restore the diversity of farmland birds.     

High resolution land cover data improve understanding of mechanistic linkages with stream integrity

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Evaluating changes in land cover and their importance for global change

During recent years, much progress has been made in integrating traditional natural science disciplines and in the developmnet of multidisciplinary models. This is crucial for an increased understanding of the dynamics of the Earth system. The domination of human activities in altering these dynamics is still increasing. However, few research projects have focused directly on understanding the motives for such intensification. It has only recently been acknowledged that improved understanding of human driving forces of global change is required to enable meaningful projections of plausible future states of the Earth system.     

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基于CA-Markov模型的艾比湖湿地自然保护区土地利用/覆被变化及预测

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