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Calculate the difference in the landscape-level metric totals between a baseline landscape and one or more scenario landscapes


sum_change(dat, k = 2)



tibble; see Details


coverage factor; see Details


tibble containing fields SCENARIO_VALUE, BASELINE_VALUE, net_change, and optionally SCENARIO_SE, BASELINE_SE, net_change_se, U, lcl, ucl, and z; see Details


This function expects dat to contain the following fields:

  • scenario: a character field used to identify the name of the landscape being examined; one of these must be called 'baseline' and all others will be treated as alternate scenarios for comparison with the baseline

  • either area or SCORE_TOTAL: numeric fields representing the total landscape-level values for each metric, such as those produced by sum_landcover() or sum_metrics().

The scores for each scenario are aligned with corresponding scores for the baseline landscape based on any other common fields (e.g. ZONE, METRIC_CATEGORY) and the net difference is calculated as the scenario score minus the baseline score. The function returns the original baseline and scenario total landscape scores for each metric and scenario (renamed as BASELINE and SCENARIO), along with net_change.

If SCORE_TOTAL_SE is also provided in dat, representing the uncertainty in the SCORE_TOTAL, the uncertainty in the difference (net_change_se) is also calculated as: sqrt(BASELINE_SE^2 + SCENARIO_SE^2) where BASELINE_SE and SCENARIO_SE represent the SCORE_TOTAL_SE for the baseline and scenario landscapes, respectively. In addition, the coverage factor k is used to estimate expanded uncertainty (U), or the interval within which a large fraction of the distribution of values could be reasonably expected. The appropriate value for k depends on the level of confidence required, the number of observations on which the uncertainty is based, and any knowledge of the underlying distributions of the estimates. Where the distributions concerned are normal, and for most purposes, a value of 2 is recommended to give an interval containing approximately 95% of the distribution of values. In this case, the function also returns the original uncertainty estimates for the baseline and scenario (renamed as BASELINE_SE and SCENARIO_SE), net_change_se, the expanded uncertainty estimate U and corresponding lcl and ucl, as well as a z score equal to abs(net_change/net_change_se).


# See vignette