Mapping natural capital: optimising the use of national scale datasets

Mapping and validating predictions of soil bacterial biodiversity using European and national scale datasets

“…Such approaches are commonly used in wider ecology (sometimes termed environmental-, ecological-, or species-distribution modelling: Elith et al, 2006), and can be used to predict either species or communities at unsampled locations (Chapman and Purse, 2011). These environmental correlational approaches have so far been used to predict historical change in soil bacterial biodiversity due to land use at regional scales (Fierer et al, 2013); and also to improve on the interpolated maps of bacterial biodiversity across Great Britain (Griffiths et al, 2011) by modelling the observed relationships between bacterial communities and environmental variables, and then forecasting communities in unsampled locations using remote sensed land cover information and parent material maps (Henrys et al, 2015). This paper aside there are few studies which have examined in detail the predictive performance of such maps compared to simple interpolation.…”

Biodiversity and Resilience of Ecosystem Functions

“…However, the stability of species 96 composition itself is not a necessary pre-requisite for the resilience of ecosystem functions. 97 Turnover in species communities might actually be the very thing that allows for resilient 98 functions. For example, in communities subjected to climatic warming, cold-adapted species 99 are expected to decline whilst warm-adapted species increase [30].…”

“…These proxy measures are currently used to inform on spatial and temporal trends in ecosystem function for the reporting and management of biodiversity change [4][5][6]. Such models use abiotic variables such as land cover, topography and climate data as explanatory variables in spatially-explicit statistical correlative models [96,97] or process models [98,99] in order to predict the provision of ecosystem functions and services. However, because models are parameterised and validated (where undertaken) on the current set of environmental conditions they are often only suitable for producing indicators of short-term ecosystem function flows rather than resilience under environmental perturbations (Figure 4).…”

Estimation of gross land-use change and its uncertainty using a Bayesian data assimilation approach

“…This follows the way in which the data became available chronologically; these were the only data available with which we could estimate land-use change in the UK when an inventory of carbon emissions was first attempted (Cannell et al, 1999). The uncertainty in the prior distribution of B can be relatively well quantified, because considerable effort has gone into quantifying the likely level of error in the national-scale estimates of land use (Scott, 2008;Wood et al, 2017 1970 1980 1990 2000 2010 1970 1980 1990 2000 2010 1970 1980 1990 2000 2010 1970 1980 1990 2000 2010 1970 1980 1990 2000 2010 1970 1980 1990 deviation σ of the prior distribution was most easily estimated by applying a bootstrapping approach to the CS data, but more advanced approaches have been investigated (Henrys et al, 2015). Alternative options for the prior are possible, and would be worth exploring further to examine sensitivity to the specification of the prior.…”