Landscapes of protection: forest change and fragmentation in Northern West Bengal, India.

In the tropics and sub-tropics, where high levels of biodiversity co-exist with some of the greatest levels of population density, achieving complete exclusion in protected area contexts has proved close to impossible. There is a clear need to recognize that parks are significantly impacted by human-environment interactions in the larger landscape within which they are embedded, and to move the frontier of research beyond the boundaries of protected areas in order to examine larger landscapes where multiple forms of ownership and access are embedded. This research evaluates forest change and fragmentation between 1990 and 2000, in a landscape surrounding the Mahananda Wildlife Sanctuary in the Indian state of West Bengal. This protected forest is bounded to the south by a less intensively protected area, the Baikunthapur Reserve Forest, and surrounded by a mosaic of unprotected, largely private land holdings. Results indicate differences in the extent and spatial pattern of forest cover change in these three zones, corresponding to different levels of government protection, access and monitoring. The two protected areas experience a trend toward forest regrowth, relating to the cessation of commercial logging by park management during this period. Yet, there is still substantial clearing toward peripheral areas that are well connected to illegal timber markets by transportation networks. The surrounding landscape, although experiencing some forest regrowth within less intensively cultivated tea plantations, is also becoming increasingly fragmented, with potentially critical impacts on the maintenance of effective wildlife corridors in this ecologically critical region.

Warming trends of perialpine lakes from homogenised time series of historical satellite and in-situ data.

The availability of more than thirty years of historical satellite data is a valuable source which could be used as an alternative to the sparse in-situ data. We developed a new homogenised time series of daily day time Lake Surface Water Temperature (LSWT) over the last thirty years (1986-2015) at a spatial resolution of 1km from thirteen polar orbiting satellites. The new homogenisation procedure implemented in this study corrects for the different acquisition times of the satellites standardizing the derived LSWT to 12:00 UTC. In this study, we developed new time series of LSWT for five large lakes in Italy and evaluated the product with in-situ data from the respective lakes. Furthermore, we estimated the long-term annual and summer trends, the temporal coherence of mean LSWT between the lakes, and studied the intra-annual variations and long-term trends from the newly developed LSWT time series. We found a regional warming trend at a rate of 0.017°Cyr-1 annually and 0.032°Cyr-1 during summer. Mean annual and summer LSWT temporal patterns in these lakes were found to be highly coherent. Amidst the reported rapid warming of lakes globally, it is important to understand the long-term variations of surface temperature at a regional scale. This study contributes a new method to derive long-term accurate LSWT for lakes with sparse in-situ data thereby facilitating understanding of regional level changes in lake's surface temperature.

Homogenised daily lake surface water temperature data generated from multiple satellite sensors: A long-term case study of a large sub-Alpine lake.

Availability of remotely sensed multi-spectral images since the 1980's, which cover three decades of voluminous data could help researchers to study the changing dynamics of bio-physical characteristics of land and water. In this study, we introduce a new methodology to develop homogenised Lake Surface Water Temperature (LSWT) from multiple polar orbiting satellites. Precisely, we developed homogenised 1 km daily LSWT maps covering the last 30 years (1986 to 2015) combining data from 13 satellites. We used a split-window technique to derive LSWT from brightness temperatures and a modified diurnal temperature cycle model to homogenise data which were acquired between 8:00 to 17:00 UTC. Gaps in the temporal LSWT data due to the presence of clouds were filled by applying Harmonic ANalysis of Time Series (HANTS). The satellite derived LSWT maps were validated based on long-term monthly in-situ bulk temperature measurements in Lake Garda, the largest lake in Italy. We found the satellite derived homogenised LSWT being significantly correlated to in-situ data. The new LSWT time series showed a significant annual rate of increase of 0.020 °C yr(-1) (*P < 0.05), and of 0.036 °C yr(-1) (***P < 0.001) during summer.