Land Library
Welcome to the Land Portal Library. Explore our vast collection of open-access resources (over 74,000) including reports, journal articles, research papers, peer-reviewed publications, legal documents, videos and much more.
/ library resources
Showing items 1 through 9 of 779.
We studied landscape dynamics for three time periods (
In this study we analysed: (1) the biodiversity conservation capacity of Agroforestry Systems (AFS) in temperate highlands of the Tehuacán–Cuicatlán Valley, Central Mexico, (2) human cultural motives and actions for conserving such diversity and (3) problems endangering that capacity.
As public land management agencies pursue region-specific resource management plans, with meaningful consideration of public attitudes and values, there is a need to characterize the complex mix of environmental attitudes in a diverse population.
An investigation was done to determine the occurrence and composition of avian fauna community in the urbanizing city of Nairobi, Kenya. We conducted bird counts in sample sites randomly distributed over the Nairobi landscape within a two-year period.
Agroecosystems are increasingly recognized as both sources and sinks of non‐native weedy plant species as well as of native plant species, thus management of these systems has important implications for the composition of plant communities and landscape diversity.
Changes in total soil carbon (C), nitrogen (N) and natural-abundance N isotopes (δ15N) were measured along three forest-to-pasture chronosequences on pumice soils in the Central North Island of New Zealand.
The status of grazinglands in the USA is increasingly dynamic with large areas being converted to cropland in response to demands for increased crop production. Here we focus on two types of grazinglands: rangelands and pasturelands.
Tree and shrub abundance has increased in many grasslands, causing changes in ecosystem carbon and nitrogen pools that are related to patterns of woody plant distribution.
Traditional approaches to ecological land classification (ELC) can be enhanced by integrating, a priori, data describing disturbances (natural and human), in addition to the usual vegetation, climate, and physical environment data.