nbs_synthesis (phase III)

An R project to compile and analyse an excel based meta-dataset of nature based solution outcomes.

The meta-dataset was produced in 2023 for a rapid assessment of the economic implications of adopting field-scale NbS practices in non-high income countries. Central to our research approach was an emphasis on profit, moving away from the often-cited gross revenue metrics. Profit, which factors in the costs, gives us an unfiltered view of the farmer's genuine earnings, thereby offering a more realistic understanding of the financial dynamics of NbS. This analysis is informed by 181 studies.

The data can be found in the ./data/NBS_extraction_table.xlsx excel file.

The analysis script is ./nbs_analysis.R.

To understand this analysis please read the working paper "Steward P, Joshi N, Kacha G, Ombewa B, Mumo E, Muller L, Youngberg B, Magnan N, and Rosenstock T. 2023. Economic benefits and costs of nature-based solutions in low- and middle-income countries". Working Paper. Alliance of Bioversity-CIAT. Rome". A copy of this paper can be found in the main project directory.

Analysis results are saved in folders ./data/TV_merged or ./data/TV_not_merged. Analyses in ./data/TV_merged have total and variable cost renamed to "Cost" and are therefore both costs are considered together. Where total and variable costs are both reported by a study, only total cost is retained. For results in the TV_not_merged folder total and variable costs are considered separately. Within the ./data/TV_merged or data/TV_not_merged folders are subfolders named to reflect the maximum percentage of negative outcomes allowed before a combination of NbS practice x economic outcome is rejected from the dataset. For example data/TV_merged/Neg_7.5perc the final subfolder means that up to 7.5% negative outcomes were allowed per NbS practice x economic outcome.

The controls for the above analysis parameters can be found in analysis script ./nbs_analysis.R on L249: max_neg<-7.5 and L250: combine_TV<-T

A further control do_combos is important (L248: do_combos<-F).
The do_combos control determines whether practices are considered:

1. "raw" where the practice names used to group data for analysis are unchanged, in this case outcomes for "raw" results are given the name "Bundles" (because individual bundles of practices are analysed, and not merged); or
2. combined; for all individual practices considered, all observations containing a specific practice are subset and the practice name set to that practice, then data are recombined. For example, if the practice is reduced tillage then we use grep("reduced tillage",practice) to search for all observations containing the practice. This fidns observations with the practice alone reduced tillage or in combination with other practices, e.g.m reduced_fertizer+reduced_tillage. The practice name for all the practices is then set to reduced tillage, so reduced_fertizer+reduced_tillage becomes reduced tillage. This process is repeated for the all the practices we consider in the analysis and the results recombined into a single table.

Output datasets include:

1. Descriptives_xxxx.csv these show the number of observations, studies, and countries by outcome or nbs practice.
2. Detailed_data_xxxx.csv this is the final processed dataset compiled by ./nbs_analysis.R used in meta-analysis.
3. Dot_plot_xxxx.png a plot of the effect size of an nbs practice vs control for a specific economic outcome.
4. raw_data_phase3_v2.csv the raw (pre-processing) dataset used in analysis
5. Studies_xxxx.csv a biblography of the studies included in the analysis
6. Summary_table_xxxx.csv the results of a meta-regression using the ERAg::ERAAnalyze function xxxx refers to the do_combos control setting.

The World Bank supported this work.