The rescue effect and inference from isolation-extinction relationships
Van Schmidt, Nathan; Beissinger, Steven (2021), The rescue effect and inference from isolation-extinction relationships, Dryad, Dataset, https://doi.org/10.5061/dryad.8w9ghx3h8
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.
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 kic-kic-kerr calls and two sets of grr calls for black rails, and two sets of a mix of grunt and tick-it 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 8th–29th) 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 > 5×5 m within the study area in in Google Earth 7.1.5). Areas covered by hydrophytes (Typha spp., Scirpus spp., Juncus effusus, Leersia oryzoides, 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.
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.
blra/vira_ocep.csv – “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 Ψc (see Hall et al. 2018). Variables are as follows:
parameter – The multi-season occupancy parameter estimated by PRESENCE (either Ψ, γ, ε, or p).
season – indicates which season the variable was estimated for (e.g., 1 = first summer, 2 = first winter, 3 = second summer, etc.). Decimal places for p indicate the visit.
site – a categorical variable indicating which site the variable was estimated for. Must not contain duplicate site names per value of season.
estimate – the expected value of the parameter for that site and season/visit as estimated by PRESENCE.
blra/vira_detection_history_##to##.csv – 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.
blra/vira_isolation_measures_##to##.csv – a set of four comma-separated tables containing the standardized isolation measures used in this study, obtained via the autoregressive model of Hall et al. (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:
IFα.yy – log10 +1 incidence function measure for mean dispersal distance α in year yy.
LBr.yy – log10 +1 buffer radius measure for radius r in year yy.
DTN.yy – log10 +1 geometric mean distance to nearest 3 sites with detections in year yy.
site_covariates.csv – Comma-separated table of site habitat covariates used in occupancy models. Variables are as follows:
G_SLOPE – a geomorphology dummy variable indicating whether the wetland was a shallow slope wetland lacking a central body of open water
G_FRINGE – a geomorphology dummy variable indicating whether the wetland was a pond or lake fringe.
G_FLUVIAL – a geomorphology dummy variable indicating whether the wetland was a creek fringe.
G_IMPOUNDMENT – a geomorphology dummy variable indicating whether the wetland was an artificial impoundment for waterfowl hunting.
S_NATURAL – a water source dummy variable indicating whether the wetland was fed only by natural water sources.
S_IRRIGATED – a water source dummy variable indicating whether the wetland was fed only by irrigation water.
S_BOTH – a water source dummy variable indicating whether the wetland was fed by both natural and irrigation water.
ELEVATION – elevation of the wetland patch in 100s of meters.
AREA.yy – the wetland patch area in log10(ha + 1) in year yy.
site_covariates_standardized.csv – 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).
National Science Foundation, Award: DEB-1051342
National Science Foundation, Award: CNH-1115069
Sierra Foothills and Sacramento Audubon Societies