DOI: 10.5061/dryad.mgqnk996x
title: Of islands on islands: Natural habitat fragmentation drives microallopatric differentiation in the context of distinct biological assemblages

description: An important evolutionary hypothesis posits that much of the biodiversity
 we see today was generated by the interplay of colonization, extinction,
 adaptation, and speciation during episodes of natural habitat
 fragmentation. To interrogate the generality of this hypothesis, we
 leverage the natural experiment provided by arthropod communities in
 kīpuka—patches of Hawaiian wet forest isolated by lava flows. With DNA
 metabarcoding, we provide the first simultaneous exploration of ecological
 and evolutionary characteristics in the kīpuka system. At both species-
 and haplotype-equivalent scales, we find that diversity scales with kīpuka
 area, and that kīpuka accelerate the distance decay of similarity relative
 to continuous forest. Open lava, kīpuka edges, and the centers of the
 smallest kīpuka host lower inter- and intra-specific richness, are more
 biologically homogeneous, and have higher proportions of non-native OTUs
 than kīpuka centers for the order we could test (Araneae). Our work shows
 how natural habitat fragmentation stimulates, in tandem, ecological shifts
 in community composition and genetic differentiation. The strong
 signatures of both ecological and evolutionary processes highlight the
 importance of studying both processes simultaneously if we are to
 understand how biological communities respond to change.
description: See "Materials and methods" of the manuscript. 
description: # Of islands on islands: Natural habitat fragmentation drives
 microallopatric differentiation in the context of distinct biological
 assemblages
 [https://doi.org/10.5061/dryad.mgqnk996x](https://doi.org/10.5061/dryad.mgqnk996x) ## Key for abbreviations used below zOTU- zero-radius operational taxonomic unit OTU- operational taxonomic unit NMDS- non-metric multidimensional scaling MDS- multidimensional scaling ## Description of the data and file structure Data was collected for a study of how natural fragmentation impacts OTU richness and turnover at the zOTU and 3 % radius OTU scales.  ### Files and variables #### File: geo\_dist.csv **Description:**  A geographic distance matrix between pairs of sampling sites. Site names occur along column names and row names. Distances are in meters.  #### File: Merged\_by\_site\_2.csv **Description:** operational taxonomic unit (OTU) counts per site ##### Variables * *The  blank cells at the top left of the sheet are there on purpose, because each sampling site (rows) and zOTU (columns) is associated with a richer set of data, as described here.*  * Site identification codes occur as row names, starting in row 10.  * First 9 rows contain data pertinent to each zOTU, starting in column 14 : * ZOTU: ID of the zOTU * INVNAT: Whether OTU is native ("NAT"), non-native ("INV"), or unassigned ("NA"). * 3PercOTU: The 3% OTU pertaining to each zOTU * Kingdom, Phylum, Class, Order, Family, Genus, Species: Taxonomic information pertaining to each zOTU * The first 13 columns contain further data pertinent to each sampling site: * Name: Site name * Hoehe: elevation in meters above sea level * MDS1: first axis of MDS * MDS2: second axis of MDS * Niederschlag: Annual precipitation in millimeters * Temp: Average annual temperature in degrees Celcius * Perimeter/Length: Perimeter in meters of kipuka sites * Site: Habitat type * Area: Kipuka area in meters squared * Area log: Log of kipuka area in meters squared * Specimens: Count of specimens collected * Lat: latitude in decimal degrees * Lon: longitude in decimal degrees #### File: nmds3otu.csv **Description:** Data required for NMDS of 3% radius OTU.  ##### Variables * ID: Site name * Site: Habitat type * Hoehe: Elevation in meters above sea level * MDS1zOTU: zOTU MDS axis 1 * MDS2zOTU: zOTU MDS axis 2 * MDS1OTU: 3 % OTU MDS axis 1 * MDS2OTU: 3 % OTU MDS axis 2 * Niederschlag: Average annual precipitation (millimeters) * Temp: Average annual temperature in degrees Celcius * Perimeter/Length: Perimeter of kipuka in meters * Area: Area of kipuka in meters squared * Arealog: Log area of kipuka * SRzOTU, SROTU: Ignore these outdated data columns.  * Lat: Latitude in decimal degrees * Lon: Longitude in decimal degrees * Columns 24 forward contain count data per each 3% radius OTU named in the column names.  #### File: OTU3\_Bray.csv **Description:** Bray-Curtis dissimilarity data for 3% radius OTUs. ##### Variables * Var1:  First sampling site ID * Var2: Second sampling site ID * value: Bray-Curtis dissimilarity values for 3% radius OTUs.  #### File: OTU3\_Bray\_Order.csv **Description:** Bray-Curtis dissimilarity data for 3% radius OTUs, order-by-order ##### Variables * Var1:  First sampling site ID * Var2: Second sampling site ID * Araneae_value, Hemiptera_value, Psocoptera_value, Coleoptera_value, Lepidoptera_value, Diptera_value: Bray-Curtis dissimilarity value for that site pair for the specified order.  #### File: zOTU\_Jaccard\_Order.csv **Description:** Jaccard dissimilarities between site pairs based on zOTUs, order-by-order. ##### Variables * Var1: First site name * Var2: Second site name * Hemiptera_value, Araneae_value, Psocoptera_value, Lepidoptera_value, Coleoptera_value, Diptera_value: Jaccard dissimilarity value between the given pair of sites for the named order.  #### File: zOTU\_jaccard.csv **Description:** Jaccard dissimilarities between site pairs based on zOTUs. ##### Variables * Var1: First site name * Var2: Second site name * value: Jaccard dissimilarity value for given pair of sites. #### File: inventory.csv **Description:** Phylogenetic information per zOTU ##### Variables (rows) * Class, Order, Family, Genus, Species: taxonomic information pertinent to each zOTU * ID: zOTU ID * 3PercOTU: 3% radius OTU ID per zOTU #### File: Stainbeck\_extent, Kona\_extent, & Kipuka\_extent files (shp, prj, shx, qpj, dbf) **Description:** Spatial extent shapefile polygons for each of the sampling areas (a box surrounding the kipuka landscape, Stainback sampling sites, and Kona sampling sites).   Shapefiles can be visualized with QGIS, ArcGIS, or your favorite spatial package/module in R/Python. * shp file: stores the geometry * prj file: Spatial reference (WGS84) * shx file: spatial index file * qpj file: map projection file * dbf file: No particular attributes associated with this data * Data source: drawn by authors around study areas #### File: conthil010a (shp, prj, dbf, shx, & txt) **Description:**  Big Island contour shapefile for mapping. As per the description provided in the metadata text file by the US Geological Survey: "This map layer shows elevation contour lines for Hawaii. The map layer was derived from the 100-meter resolution elevation data set which is published by the National Atlas of the United States, and is in the same Albers Equal-area Conic projection as that source data set. Contour intervals match the steps used in the National Atlas Color-Sliced Elevation data sets. Contours were adjusted so that they are in the proper relationship to National Atlas 1:1,000,000-scale lakes, reservoirs, and wide (double-line) streams.". Shapefiles can be visualized with QGIS, ArcGIS, or your favorite spatial package/module in R/Python. * shp file: stores the geometry * prj file: Spatial reference (WGS84) * dbf file: Attribute file associated with shapefile. Attribute definitions are given in the metadata text file.  * shx file: spatial index file * txt file: Additional metadata associated with the shapefile * Data source: Published by the National Atlas of the United states at the link provided in the txt metadata file ## Code/software Programs available in the Materials and Methods of the article, and scripts available through the github linked in the Code Availability Statement.