Data from: Habitat loss-biodiversity relationships are influenced by assembly processes and the spatial configuration of area loss

Habitat loss greatly threatens biodiversity worldwide. However, how different facets of biodiversity (taxonomic, phylogenetic and functional diversity) decline with habitat loss is currently poorly understood. Habitat loss-biodiversity relationships, while important to understand in their own right, have the potential to reveal the underlying mechanisms that naturally structure plant communities and can further illuminate how spatial configurations of habitat loss affect biodiversity in a given amount of habitat. In this study, we used four spatial point process models to assess the relative importance of the processes of random placement of individuals, habitat filtering, dispersal limitation and the combined effects of habitat filtering and dispersal limitation in producing habitat loss-biodiversity relationships across different biodiversity facets for plant species in a subtropical forest. We assessed this using a 50 ha fully mapped subtropical forest in southern China by applying two simulated habitat destruction patterns, namely random and aggregated habitat removal to both real and simulated forest communities. We found that the combined effects of habitat filtering and dispersal limitation provided the best fit among the four competing assembly mechanisms, to the simulated habitat loss-biodiversity relationships applied to real forest data across all three biodiversity metrics. We also found that phylogenetic and functional diversity were less sensitive to the loss of habitat area than species richness and biodiversity declined more gradually under random habitat removal than for aggregated removal for both empirical forests and the simulated communities where assembly mechanisms generated intraspecific aggregation. Overall, our study examined how different assembly processes result in differing susceptibilities to diversity loss from habitat destruction and identified the potential mechanisms underlying the spatial patterns of diversity. This study also provides guidelines for the prioritization of the conservation of different facets of biodiversity under different spatial configurations of habitat loss.GENERAL INFORMATION 1. Title of Dataset: Data from: Habitat loss-Biodiversity Relationships are Influenced by Assembly Processes and the Spatial Configuration of Area Loss 2. Author Information A. Principal Investigator Contact Information Name: Deyi Yin Institution: South China Botanical Garden Address: Xingke Road 723, Tianhe District, Guangzhou, China Email: yindeyi@scbg.ac.cn 3. Date of data collection: from 2012 to 2016 4. Geographic location of data collection: 111°52'E, 23°27'N, HSD nature reserve, Guangdong Province, China SHARING/ACCESS INFORMATION 1. Licenses/restrictions placed on the data: 2. Links to publications that cite or use the data: 3. Links to other publicly accessible locations of the data: 4. Links/relationships to ancillary data sets: 5. Was data derived from another source? yes/no A. If yes, list source(s): the former SYSU-Alberta Joint Lab for Biodiversity Conservation 6. Recommended citation for this dataset: Yin, Deyi; Ye, Qing; Cadotte, Marc (2021), Data from: Habitat loss-Biodiversity Relationships are Influenced by Assembly Processes and the Spatial Configuration of Area Loss, Dryad, Dataset, https://doi.org/10.5061/dryad.51c59zw7k DATA & FILE OVERVIEW 1. File List: hsd_distribution_use.csv HSD_soildat_2014_use.csv HSD_topgraphy_5m.csv hsd_trait_use.csv hsdtree.use.txt METHODOLOGICAL INFORMATION 1. Description of methods used for collection/generation of data: Each stem with DBH>1 cm in the HSD forest plot was mapped, identified and measured. 4 topographic factors and 6 variables of soil nutrient content have been measured across the forest plot. Species-level functional traits were measured from 5-30 individuals and then averaged the individual-level trait values. Phylogenetic tree of the HSD forest community was built based on the sequencing Gene data. All the data were collected by the former SYSU-Albert joint lab 3. Instrument- or software-specific information needed to interpret the data: R software DATA-SPECIFIC INFORMATION FOR: [FILENAME] dataset: hsd_distribution_use.csv 1. Number of variables: 3 2. Number of cases/rows: 210,595 3. Variable List: gx, gy, scientific_name 4. Missing data codes: n 5. Specialized formats or other abbreviations used: dataset: HSD_soildat_2014_use.csv 1. Number of variables: 9 2. Number of cases/rows: 1709 3. Variable List: sample, gx, gy, moisture,toc, tn, AP, AAl, AK dataset: HSD_topgraphy_5m.csv 1. Number of variables: 7 2. Number of cases/rows: 20001 3. Variable List: No, sx, sy, topo5m, slope5m, aspect5m, curvature5m hsd_trait_use.csv 1. Number of variables: 13 2. Number of cases/rows: 250 3. Variable List: scientific_name,LA,LFM,LDM,SLA,LDMC,WD,WDMC,pH,LCC,LNC,LPC,MH dataset: hsdtree.use.txt phylogenetic tree of HSD forest plot Funding provided by: National Natural Science Foundation of ChinaCrossref Funder Registry ID: http://dx.doi.org/10.13039/501100001809Award Number: 31901107Funding provided by: Natural Science Foundation of Guangdong ProvinceCrossref Funder Registry ID: http://dx.doi.org/10.13039/501100003453Award Number: 2018A030310384Funding provided by: Natural Sciences and Engineering Research Council of CanadaCrossref Funder Registry ID: http://dx.doi.org/10.13039/501100000038Award Number: 386151Each stem with DBH>1 cm in the HSD forest plot was mapped, identified and measured. 4 topographic factors and 6 variables of soil nutrient content have been measured across the forest plot. Species-level functional traits were measured from 5-30 individuals and then averaged the individual-level trait values. Phylogenetic tree of the HSD forest community was built based on the sequencing Gene data. All the data were collected by the former SYSU-Albert joint la