Multifunctional landscapes are characterized by various functions and values that sustain directly or indirectly the quality of human life, through the provision of natural capital flow. Primary production (PP), representing a measure of the solar energy captured by the system and available to drive its functioning, is recognized as a fundamental supporting service. Several biophysical modification and conversion altering the primary production are due to land-use change.

Based on the Regional Integrated Environmental Model System (RIEMS 2.0) developed by START TEA-COM RRC and Department of Atmospheric Science of Nanjing University, a dataset of observation and remote sensing over the Heihe River Basin (HRB) was used to recalibrate the model’s parameters, including topography elevation, land cover type, saturated soil water potential, saturated soil hydraulic conductivity, field moisture capacity, wilting point moisture, soil porosity, and parameter b of soil hydraulic conductivity, to build a high-resolution regional climate model for the HRB.

Landscape management could contribute to sustainable pest control. Landscape composition, in particular, could either directly impact a pest abundance by affecting its dispersal, mortality or reproduction, or indirectly by affecting its natural enemies. We performed an analysis of the scientific literature to assess how the proportion of different land covers at the landscape level is related to the abundance of pests or to their control by natural enemies. Of 72 independent case studies, 45 reported an effect of landscape composition.

Changes in flora biodiversity are a dilemma facing managers in order to cope with challenges of extinction or endangering plant species as well as replacement by invasive species. Such problems can occur in the region as disruption of ecosystem balance. The first step of proper management of a watershed is obtaining accurate information about plant communities and their dominance and biodiversity status. Such information will help decision makers to adopt an appropriate management approach.

There is an ongoing debate on the effect different property regimes have on the use of natural resources and land conversion (i.e., deforestation or reforestation). Much of the discussion has been centered on the two main forms of tenure regime: common-pool system and private property. Case studies around the world have provided evidence on whether one is more effective at preventing deforestation than the other, but there is not a clear pattern. Part of the problem is that evidence comes from theoretical models or isolated case studies instead of comparative studies across large areas.

Relationships between land use/cover (LUC) and stream water quality have been well-documented in many environments and at a range of spatial scales. From these analyses, reduced in-stream biological integrity and habitat quality are commonly associated with increasing amounts of anthropogenic LUC. However, very few studies have examined the influence of landscape condition, relative to studies using LUC, on water quality parameters. Landscape condition indices use remote sensing-based data to quantify biophysical land surface condition.

Socioecological theory, developed through the study of urban environments, has recently led to a proliferation of research focusing on comparative analyses of cities. This research emphasis has been concentrated in the more developed countries of the Northern Hemisphere (often referred to as the “Global North”), yet urbanization is now occurring mostly in the developing world, with the fastest rates of growth in sub‐Saharan Africa.

The pastoral resources in eastern Sudan are changing under the combined impact of increasing anthropogenic activities such as clearance of natural vegetation and the effect of state policies that favour crop farming against pastoralism. Remotely sensed data are used to detect spatial and temporal changes from 1979 to 2009 in the land use/land cover (LULC) across three study sites. Areas of natural vegetation have been reduced from 26.1% in 1979 to 12.6% in 1999 and further to 9.4% in 2007. The majority of this reduction went into agricultural land.

Our view of the future of biodiversity remains limited to a restricted number of taxa, and some taxa, such as spiders, have been largely omitted. Here we provide the first assessment of effects of global change on threatened spiders using a red-listed vulnerable spider, Dolomedes plantarius (Clerck, 1757) as an example. We aim at applying this assessment to assist two conservation actions for this species, including a translocation program. We compiled all the available data on D.

Heathlands in Western Europe have shown dramatic declines over the last century and therefore have been given a high conservation priority in the Habitats Directive of the European Union (EU). Accurate surveying and monitoring of heathland habitats is essential for appropriate conservation management, but the large heterogeneity of vegetation types within habitats as well as the occurrence of similar vegetation across habitat types hinders a straightforward, automated mapping based on aerial images.

It is difficult to monitor forests in tropical regions with frequent cloud cover using optical remote-sensing data. Adequate multi-temporal, high-resolution imagery is often not available. Microwave imagery is able to penetrate cloud cover, enabling imagery of the land surface to be recorded more frequently. This study seeks to improve tropical forest mapping by combining optical and microwave imagery, with one of the main objectives being the discrimination of planted and natural forests.

Denitrification is an anaerobic respiration that reduces nitrogen (N) oxides (NO₃ ⁻, NO₂ ⁻) to N gases (N₂O, N₂). Our hypothesis suggests that this process might be an important process in depleting nitrogen in dryland soils, based on the idea that the intensity of microbial respiration following infrequent rainfall events and floods, is high enough to deplete soil O₂ concentrations and allow denitrification to occur. We tested our hypothesis by analyses of soil surface samples, collected along a rainfall gradient.