DOI: 10.5061/dryad.8w9ghx3h8
title: The rescue effect and inference from isolation-extinction relationships

description: The rescue effect in metapopulations hypothesizes that less isolated
 patches are unlikely to go extinct because recolonization may occur
 between breeding seasons (“recolonization rescue”), or immigrants may
 sufficiently bolster population size to prevent extinction altogether
 (“demographic rescue”). These mechanisms have rarely been demonstrated
 directly, and most evidence of the rescue effect is from relationships
 between isolation and extinction. We determined the frequency of
 recolonization rescue for metapopulations of black rails (Laterallus
 jamaicensis) and Virginia rails (Rallus limicola) from occupancy surveys
 conducted during and between breeding seasons, and assessed the
 reliability of inferences about the occurrence of rescue drawn from
 isolation-extinction relationships, including autologistic isolation
 measures that corrected for unsurveyed patches and imperfect detection.
 Recolonization rescue occurred at expected rates, but was elevated during
 periods of disturbance that resulted in nonequilibrium metapopulation
 dynamics. Inferences from extinction-isolation relationships were
 unreliable, particularly for autologistic measures and for the more vagile
 Virginia rail.
description: This dataset contains files for (1) estimating the frequency of
 recolonization rescues corrected for imperfect detection of species’
 occupancy state and (2) conducting the Bayesian explicit recolonization
 rescue model published in Van Schmidt & Beissinger (2020)
 "The rescue effect and inference from isolation-extinction
 relationships." Black rail and Virginia rail occupancy data was
 gathered by surveying 273 wetlands in the foothills of the California
 Sierra Nevada mountains annually. The study area was the zone III Sierra
 Nevada Foothills ecoregion (US Environmental Protection Agency 2013) in
 Nevada, Yuba, and southern Butte counties, plus a 1 km buffer to quantify
 isolation for sites near the study area boundary.
 Surveys were conducted from 2002–2016 during the breeding season
 (late May to early August). Wetlands were surveyed with call broadcast
 methods, with up to 3 visits each summer (5 in 2002) to estimate detection
 probability. Surveyors entered the wetland and conducted playback at
 points spaced every 50 m throughout the wetland. The playback sequence
 included two sets of <em>kic-kic-kerr </em>calls and two sets
 of <em>grr</em> calls for black rails, and two sets of a mix
 of <em>grunt</em> and <em>tick-it</em> calls for
 Virginia rails. Each call sequence was 30 seconds and followed by 30
 seconds of silence for listening for responses. Once a species was
 detected in that wetland, calls were stopped for that species for the
 remainder of the visit. If both species were detected at a wetland, we did
 not revisit it for the remainder of that season. We used the same
 methodology to resurvey 125 wetlands during the non-breeding season
 (January 8<sup>th</sup>–29<sup>th</sup>) of
 2014–2016 to determine the frequency of recolonization rescue.
 Wetland habitat covariates were gathered using a mix of field
 data collection and manual interpretation of summer 2013 GeoEye-1 0.4 m
 imagery. We mapped all emergent wetlands &gt; 5×5 m within the study
 area in in Google Earth 7.1.5). Areas covered by hydrophytes
 (<i>Typha</i> spp., <i>Scirpus</i> spp.,
 <i>Juncus effusus</i>, <i>Leersia oryzoides</i>,
 or various sedges) were considered wetland, including those that appeared
 seasonally dried. Any green vegetation inside a 5-m buffer along these
 hydrophytes was included as a wetland-upland transition zone, but open
 water and rice fields were excluded. Each wetland’s geomorphology was
 classified as slope (shallow hillside flow), pond fringe, fluvial, rice
 fringe, irrigation ditch, or waterfowl impoundment. We combined historic
 imagery, field data, and talks with local landowners to determine the
 water sources of wetlands. Occupancy was estimated using an autogressive
 model as described in detail in the paper.
description: Missing values in occupancy data are the result of some sites not
 being surveyed for each visit in each year, due to either site access
 restrictions or because we had already detected both species. Standardized
 site covariates are provided for use with the Bayesian JAGS script
 published in Van Schmidt & Beissinger (2020). Continuous
 covariates were standardized across sites and, when appropriate, across
 years (e.g., area when used as a covariate for colonization and
 extinction). A description of each dataset
 follows.
 <strong>blra/vira_ocep.csv</strong> – “OCEP” file
 containing occupancy parameters on the real (probability) scale, taken
 from the output of summer-winter-summer occupancy model run in Program
 PRESENCE v12.19 (Hines 2013). These are used to calculate
 Ψ<i><sup>c</sup></i> (see Hall <i>et
 al.</i> 2018). Variables are as follows:
 <i>    parameter</i> – The multi-season occupancy
 parameter estimated by PRESENCE (either Ψ, γ, ε, or
 <i>p</i>). <i>    season </i>–
 indicates which season the variable was estimated for (e.g., 1 = first
 summer, 2 = first winter, 3 = second summer, etc.). Decimal places for
 <i>p</i> indicate the visit. <i>   
 site</i> – a categorical variable indicating which site the variable
 was estimated for. Must not contain duplicate site names per value of
 <i>season</i>. <i>    estimate –
 </i>the expected value of the parameter for that site and
 season/visit as estimated by PRESENCE.
 <strong>blra/vira_detection_history_##to##.csv</strong> – a set of four comma-separated tables containing the per-visit detection histories (detected = 1, not detected = 0, not surveyed = NA) for black rails (blra) and Virginia rails (vira) for the preliminary, equilibrium period (2002 or 2004 to 2006) or the main, nonequilibrium period of this study (2013 to 2016). The latter are read directly by the R script; these would require reformatting to be read into PRESENCE for occupancy modeling. <strong>blra/vira_isolation_measures_##to##.csv</strong> – a set of four comma-separated tables containing the standardized isolation measures used in this study, obtained via the autoregressive model of Hall <i>et al.</i> (2018). Note that because these measured dispersal affecting colonization and extinction the following year, they were entered with a one-year lag (e.g., DTN.13 was a covariate for colonization and extinction in 2014). Variables are as follows: <i>    IFα.yy</i> – log<sub>10</sub> +1 incidence function measure for mean dispersal distance α in year <i>yy</i>.     <i>LBr.yy</i> – log<sub>10</sub> +1 buffer radius measure for radius <i>r</i> in year <i>yy</i>. <i>    DTN.yy</i> – log<sub>10</sub> +1 geometric mean distance to nearest 3 sites with detections in year <i>yy</i>. <strong>site_covariates.csv</strong> – Comma-separated table of site habitat covariates used in occupancy models. Variables are as follows:    <i>G_SLOPE</i> – a geomorphology dummy variable indicating whether the wetland was a shallow slope wetland lacking a central body of open water <i>   G_FRINGE </i>– a geomorphology dummy variable indicating whether the wetland was a pond or lake fringe. <i>   G_FLUVIAL </i>– a geomorphology dummy variable indicating whether the wetland was a creek fringe. <i>   G_IMPOUNDMENT </i>– a geomorphology dummy variable indicating whether the wetland was an artificial impoundment for waterfowl hunting. <i>   S_NATURAL </i>– a water source dummy variable indicating whether the wetland was fed only by natural water sources. <i>   S_IRRIGATED </i>– a water source dummy variable indicating whether the wetland was fed only by irrigation water. <i>   S_BOTH </i>– a water source dummy variable indicating whether the wetland was fed by both natural and irrigation water. <i>   ELEVATION</i> – elevation of the wetland patch in 100s of meters. <i>   AREA.yy </i>– the wetland patch area in log<sub>10</sub>(ha + 1) in year <i>yy</i>. <strong>site_covariates_standardized.csv</strong> – Comma-separated table of site habitat covariates used in occupancy models. Variables are the same as in the above datasets, but standardized. Continuous covariates were standardized across sites and, when appropriate, across years (e.g., area when used as a covariate for colonization and extinction).