This dataset contains the dissimilarity matrices used to determine differences in spatial similarity between all reserve solutions produced with changes in levels of each investigated factor (planning-unit size, thematic resolution of habitats, socioeconomic cost). For individual reserve solutions, there are pair-wise comparisons between each of the 2000 solutions produced (100 for each of 20 total scenarios). For selection frequencies of each scenario, there are pair-wise comparisons between each of the 20 selection frequency outputs. These data matrices were Hellinger-transformed to allow meaningful use of parametric ordination methods.
There are several datasets associated with the study described in the related publication. The study quantifies the individual and interacting effects of three factors - planning-unit size, thematic resolution of habitat maps, and spatial variability of socioeconomic costs - on spatial priorities for conservation, by creating 20 unique prioritisation scenarios involving different levels of each factor. Prioritisations were run using the reserve selection tool Marxan. Because output data from these scenarios are analogous to ecological data, ecological statistics were applied to determine spatial similarities between reserve designs. The other datasets for this study can be found at the Related Data links below.
This dataset is available as 2 comma-separated values (.csv) files and may be downloaded from the Additional identifiers URL in the Data section of this record. The files exceed row and character limits respectively for opening in Microsoft Excel or importing into a Microsoft Access database. They may be opened in a text editor and saved as several (estimate 15-16) smaller files in Excel or opened in the 'R' software environment by using the "read.csv" function.
Coral-reef habitats in Fiji and Micronesia (consisting of the Mariana Islands, Marshall Islands, Palau, Guam, and the Federated States of Micronesia) were used as case studies. Although analyses are grounded in real data, they are demonstration exercises and not intended to inform real-world conservation action in the study regions.
Data time period: 04 10 2015 to 09 10 2015
Data time period:
179.43695,-18.15586 179.81398,-17.40972 179.93042,-16.58563 179.77487,-15.76396 179.36255,-15.02583 178.73383,-14.44488 177.95024,-14.07947 177.0885,-13.9665 176.23296,-14.1174 175.46736,-14.51692 174.86664,-15.12472 174.48961,-15.87979 174.37317,-16.70691 174.52872,-17.52455 174.94104,-18.25314 175.56976,-18.82268 176.35335,-19.17917 177.21509,-19.28911 178.07063,-19.14222 178.83623,-18.75224 179.43695,-18.15586
151.13617,18.63627 140.76508,19.13522 136.37054,17.46639 136.19476,12.54429 131.27289,11.51277 126.70258,9.61203 132.32758,5.60551 139.18304,5.78042 143.75336,8.74439 150.43304,8.04881 161.50726,6.13009 167.48383,4.90534 171.52679,3.50291 175.56976,7.17766 176.62445,11.16807 167.13226,12.37264 161.1557,11.68496 153.42133,17.46639 151.13617,18.63627
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- Local : b924f38b3f53fe936177d56d73d3ab1c
- Local : https://research.jcu.edu.au/data/published/f31b365002eabdcd871ee11ff30d6068
- DOI : 10.4225/28/57983A865286D