Carcass weight of Greenlandic lambs in relation to grazing area biomass

This study set out to investigate possible relationships between lamb carcass weight and quality with feed availability during the main growing season in southern Greenland where farms are sparsely distributed over a large area. In early May, ewes and new-born lambs are let out to graze permanent nature areas until slaughter towards the end of September. In our study, we used data from 157,477 lambs slaughtered between 2010 and 2017 as well as the Normalized Differentiated Vegetation Index (NDVI) as an indicator of biomass growth. Mean carcass weight of lambs ranged from 13.4 kg in 2015 to 16.5 kg in 2010 where 70.5% of all lambs scored well for conformation and fat. Both farm, year, and NDVI significantly correlated with carcass weight and quality. Lambs raised in the northern and the southern grazing areas generally were smaller than lambs raised in the central part. Finally, NDVI explained between 0 and 74% of the variation in mean carcass weight across years within each grazing area. Our work exemplifies the use of satellite-derived data to attempt an explanation of spatial variation in productivity, which in the future could be coupled with other spatial variables such as soil quality, vegetation, and topography

Identifying Land Use and Land-Use Changes (LULUC):A Global LULUC Matrix

Land use and land-use changes (LULUC) information is essential to determine the environmental impacts of anthropogenic land-use and conversion. However, existing data sets are either local-scale or they quantify land occupation per land-use type rather than providing information on land-use changes. Here we combined the strengths of the remotely sensed MODIS land cover data set and FAOSTAT land-use data to obtain a database including a collection of 231 country-specific LULUC matrixes, as suggested by the IPCC. We produced two versions of each matrix: version 1, identifying forestland based on canopy cover criteria; version 2, distinguishing primary, secondary, planted forests and permanent crops. The outcome was a first country-based, consistent set of spatially explicit LULUC matrixes. The database facilitates a more holistic assessment of land-use changes, quantifying changes that occur between land classes from 2001 to 2012, providing crucial information for assessing environmental impacts caused by LULUC. The data allow global-scale land-use change analyses, requiring a distinction between land types based not only on land cover but also on land uses. The spatially explicit data set may also serve as a starting point for further studies aiming at determining the drivers of land-use change supported by spatial statistical modeling