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Data related to Using Bayesian Belief Networks to assess the influence of landscape connectivity on ecosystem service trade-offs and synergies in urban landscapes in the UK

dataset
posted on 09.08.2021, 20:50 by James Dariush Karimi
This data comprises ten file figures reported in the paper Using Bayesian Belief Networks to assess the influence of landscape connectivity on ecosystem service trade-offs and synergies in urban landscapes in the UK.


Fig1a.tif, Fig1b.tif and Fig1c.tif show the study area and land cover classification. Fig1Loc_a.jpg shows the location of the study area.


Fig2.png shows the methodological framework to assess the influence of connectivity on ES trade-offs and synergies.


Fig3.png shows an example of Bayesian Belief Network model structure for Nutrient retention and Carbon storage trade-offs. All models used a comparable structure.

Fig4a.tif, Fig4b.tif and Fig4c.tif show the modelled cumulative current maps for Bedford, Luton and Milton Keynes at 2 m resolution.


Fig5.png shows the heat maps that visually depict the conditional probabilities driving each model.


The dataset Dataset_PC_maxBA.txt was used for Bayesian modelling to assess whether connectivity affects ES trade-offs and synergies. It contains 116 cases (observations) where each case represents a point observation of counts of bird abundance (within a radius of 200 m), a point observation of bird species richness, data point cumulative current mapped values, data point principal components raster mapped values and patch area metric values found at the same location. The dataset refers to cases (observations) across the combined built-up areas of Bedford, Luton and Milton Keynes.

The data point principal component values represent nutrient retention and carbon storage trade-offs(PC 1), habitat quality and pollinator abundance trade-offs (PC 2) and potential soil erosion and water supply synergies(PC 3).

Funding

NERC Grant Number NE/M009009/1

History

Authoriser (e.g. PI/supervisor)

roncorstanje@cranfield.ac.uk