In the Neotropics the predominant pathway to intensify productivity is generally thought to be to convert grasslands to sown pastures, mostly in monoculture. This article examines how above-ground net primary productivity (ANPP) in semi-natural grasslands and sown pastures in Central America respond to rainfall by: (i) assessing the relationships between ANPP and accumulated rainfall and indices of rainfall distribution, (ii) evaluating the variability of ANPP between and within seasons, and (iii) estimating the temporal stability of ANPP.

It is critical to assess the effectiveness of the tools used to protect endangered species. The main tools enabled under the U.S. Endangered Species Act (ESA) to promote species recovery are funding, recovery plan development and critical habitat designation. Earlier studies sometimes found that statistically significant effects of these tools could be detected, but they have not answered the question of whether the effects were large enough to be biologically meaningful.

Inspite of loss of many native flora from National Capital Territory (NCT) region, due to rapid urban growth, seven plant species that had not been hitherto known from this region, have been recorded.

Light detection and ranging (LiDAR) remote sensing offers new and improved capabilities for vertical and structural characterization of objects, such as plant height and different growth stages/strata, etc. Climate change will change tree and plant growth conditions and thus will change forest structure and distribution, which can potentially be studied using LiDAR remote sensing.

Human-driven land-use and land-cover change (LULCC) is one of the most important causes for depletion of biodiversity. Few studies have been undertaken to spatially identify the natural areas prone to LULCC and hence biodiversity loss. This article describes a geospatial modelling technique using a combination of drivers of LULCC, spatial distribution
of LULCC and topographic impedances for change in hotspot. A study has been carried out to establish the model. The model has shown that the natural areas having high population density in the vicinity are highly prone to LULCC.