Land use determinants of small mammals abundance and distribution in a plague endemic area of Lushoto District, Tanzania

Small mammals are considered to be involved in the transmission cycle of bubonic plague, still occurring in different parts of the world, including the Lushoto district in Tanzania. The objective of this study was to determine the relationship between land use types and practices and small mammal abundance and distribution. A field survey was used to collect data in three landscapes differing in plague incidences. Data collection was done both in the wet season (April-June 2012) and dry season (August-October 2012). Analysis of variance and Boosted Regression Trees (BRT) modelling technique were used to establish the relationship between land use and small mammal abundance and distribution. Significant variations (p ≤ 0.05) of small mammal abundance among land use types were identified. Plantation forest with farming, natural forest and fallow had higher populations of small mammals than the other aggregated land use types. The influence of individual land use types on small mammal abundance level showed that, in both dry and wet seasons, miraba and fallow tended to favour small mammals’ habitation whereas land tillage practices had the opposite effect. In addition, during the wet season crop types such as potato and maize appeared to positively influence the distribution and abundance of small mammals which was attributed to both shelter and food availability. Based on the findings from this study it is recommended that future efforts to predict and map spatial and temporal human plague infection risk at fine scale should consider the role played by land use and associated human activities on small mammal abundance and distribution

Representative Landscapes in the Forested Area of Canada

Canada is a large nation with forested ecosystems that occupy over 60% of the national land base, and knowledge of the patterns of Canada’s land cover is important to proper environmental management of this vast resource. To this end, a circa 2000 Landsat-derived land cover map of the forested ecosystems of Canada has created a new window into understanding the composition and configuration of land cover patterns in forested Canada. Strategies for summarizing such large expanses of land cover are increasingly important, as land managers work to study and preserve distinctive areas, as well as to identify representative examples of current land-cover and land-use assemblages. Meanwhile, the development of extremely efficient clustering algorithms has become increasingly important in the world of computer science, in which billions of pieces of information on the internet are continually sifted for meaning for a vast variety of applications. One recently developed clustering algorithm quickly groups large numbers of items of any type in a given data set while simultaneously selecting a representative—or “exemplar”—from each cluster. In this context, the availability of both advanced data processing methods and a nationally available set of landscape metrics presents an opportunity to identify sets of representative landscapes to better understand landscape pattern, variation, and distribution across the forested area of Canada. In this research, we first identify and provide context for a small, interpretable set of exemplar landscapes that objectively represent land cover in each of Canada’s ten forested ecozones. Then, we demonstrate how this approach can be used to identify flagship and satellite long-term study areas inside and outside protected areas in the province of Ontario. These applications aid our understanding of Canada’s forest while augmenting its management toolbox, and may signal a broad range of applications for this versatile approach

A framework for comparative landscape analysis and evaluation based on land cover data, with an application in the Madrid region (Spain)

This paper presents a diagnostic framework for evaluating landscapes. The basic premise for this framework is the existence of community values of any landscape and not only landscapes selected in terms of conservation or any other functionality. Land cover data are especially targeted as input source, since they are relatively unbiased in terms of landscape values and since they generally cover whole areas, not just target objects or conditions. The general evaluation model is based on quantifiable land cover and landscape structure characteristics. The process of landscape evaluation is an iterative improvement and refinement of indicators and reference data. Criteria and indicators have to be selected with reference to regional or local specificity and priorities. These indicators are translated into landscape metrics, which yield cartographic outputs of evaluation hypotheses of landscapes. The next step is to refine these hypotheses by adding information from complementary datasources. The importance of this study lies in a possible stimulation of the discussion of landscape values across areas, in the comparison of value perceptions between different regions, and in adding value to existing land cover data. Illustrations are given for the Madrid autonomous area. CORINE land coverdata and a vegetation map have been selected as information source. (C) 2001 Elsevier Science B.V. All rights reserved.status: publishe