Supporting data for "Illegal trade network, remote sensing and genomic approaches to tropical hardwood conservation in Africa and Asia"

<p dir="ltr">This metadata contains supporting data for my PhD thesis titled "Illegal trade network, remote sensing and genomic approaches to tropical hardwood conservation in Africa and Asia".</p><p dir="ltr">In Chapter 2, I did a social network analysis on timber seizure records involving China from 2012 - 2022 to identify conservation hotspots and species. The seizure records were aggregated by myself from open accessed media, press releases and court cases, and were uploaded in this metadata.</p><p dir="ltr">Chapter 3 quantified the extent of conflict impacts, using the Anglophone crisis in Cameroon as a case study, on forest change and target tree species. I used remote sensing for a supervised random forest classification of target regions in Cameroon, and did overlap analyses between forest change and conflict events, as well as species occurrences and conflict events. The Google Earth Engine codes were used for the supervised random forest classification. The R codes and tree species list were used for obtaining tree occurrence data from GBIF. These outputs were overlapped with conflict events downloaded from ACLED at different buffering distances to understand the extent of conflict impacts.</p><p dir="ltr">Chapter 4 was a population genetics study on a tree species, <i>Microberlinia bisulcata</i>, the African Zebrawood/Zingana. It compared the genetic diversity, gene flow and population structure across (i) the wild, Ebo forest population, (ii) a nursery population and (iii) two cultivated populations. The uploaded dataset contained the species list and their corresponding sampling populations, and their inline and index barcodes for the demultiplexing of pooled sequences into individual sequences. Sequences from the three pools of ddRADseq libraries generated by Illumina Novaseq 6000 2*150 bp were uploaded.</p>