DOI: 10.5061/dryad.s7h44j144
title: Seeds of success: a conservation and restoration investment in the future of US lands

description: Seeds of Success (SOS) is a national seed collection program led by the
 Bureau of Land Management. SOS represents the most comprehensive native
 seed repository in the US, supporting native plant restoration,
 management, and research. Since inception in 2000, SOS has collected seeds
 from over 24,400 native plant populations from ~5,600 taxa from 43 states.
 Collections include species important to wildlife, pollinators, and
 indigenous people, and over 10,000 collections have been shared for
 restoration and research use. We asked how many SOS sites have burned
 since collection, and identified 662 fires at 631 sites. If fire continues
 at the pace observed since 2011, an estimated 14% of collection sites will
 burn by 2050 and over 24% by 2080, putting genetic diversity at risk in
 areas where fire is linked with invasion. Analysis of 14 native forb
 species from the western US found that many collections were from the
 warmest and driest portions of their range, areas at the highest risk of
 wildfire, subsequent invasion, and local extinction. SOS provides an
 opportunity to understand change in natural populations, and represents a
 critical repository of native plant genetic resources for conservation and
 future use.
description: Seeds of Success programmatic information
 SOS collection data from 2000-2018 were compiled from 24,462
 records. We tabulated the number of taxa, genera, and plant families
 collected, the number of collection interns since program inception, the
 number of US states with SOS collections, and the number of seed
 collections that have been distributed for restoration and research use,
 through 2017. We also tabulated the number of collections per year, the
 number of plants sampled for each collection, and the estimated population
 size of each collection, and compared these metrics from the first years
 of the SOS program (2000-2008) to the most recent years (2009-2017) using
 general linear models. Quantifying fires at Seeds of
 Success collection sites We obtained geospatial fire
 records for fires occurring across the United States, spanning the years
 2000-2018, from GeoMAC (Geospatial Multi-Agency Coordination - Wildland
 Fire Support accessed: 21 Nov 2018 (2000-2017), 16 May 2019 (2018),
 https://www.geomac.gov/). We used these data to determine how many of a
 subset of 18,202 populations that have been georeferenced to-date have
 been impacted by fire since the date of collection.
 Case study of western forbs We performed
 in-depth analyses on 14 focal forb species known to be specifically or
 generally important for providing resources for sagebrush obligate
 wildlife in western states (Connelly et al. 2011; Dumroese et al. 2015;
 Wood et al. 2015; Dumroese et al. 2016), and for their current and
 potential use in seed increase efforts for restoration purposes. Species
 included: <i>Amsinckia tessellata</i>, <i>Astragalus
 filipes</i>, <i>Balsamorhiza sagittata</i>,
 <i>Chaenactis douglasii</i>, <i>Cleome lutea</i>,
 <i>Crepis acuminata</i>, <i>Erigeron pumilus</i>,
 <i>Erigeron speciosus</i>, <i>Heliomeris
 multiflora</i>, <i>Lomatium dissectum</i>,
 <i>Machaeranthera canescens</i>, <i>Penstemon
 speciosus</i>, <i>Phacelia hastata</i>, and
 <i>Sphaeralcea grossulariifolia</i>.
 Estimating species distributions We created
 binary species distribution maps for each focal species using a Maxent
 modeling approach, as outlined in Barga et al. (2018). Briefly, we
 gathered occurrence points from georeferenced herbarium data and
 researcher-documented point locations, and gathered environmental
 variables that were created using a Thornwaite water balance approach,
 based on PRISM temperature and precipitation data (Daly et al. 2008).
 Next, we separated the presence data for each species into test and
 training groups and created an iterative series of Maxent models that
 varied in both feature type(s) and regularization parameter. The best
 model for predicting the suitable climate for each species was selected,
 based on Akaike’s information criterion (AIC) values created using
 ENMTools (Warren, Glor, & Turelli 2010), and used to estimate the
 geographic distribution for each species. For more information on the
 calculation of environmental variables, model background selection, model
 optimization, and model selection, see Barga et al. (2018).
 Suitable habitat, fire history, and seed collection
 locations To ask how collection locations were
 distributed across each species’ potentially suitable habitat, we used
 binary species distribution maps for each of our focal species to select
 500 random points across their estimated area of occupancy using ArcMap
 10.5 (ESRI, 2017). We then extracted values for four environmental
 variables (annual precipitation (mm), summer (June, July, August)
 precipitation (mm), annual minimum and maximum temperature (ᵒC)) from both
 the SOS collection locations for each species and at the random points
 across each species’ distribution. These variables were selected because
 previous work indicated that they were highly predictive of suitable
 climate for multiple Great Basin forbs (Barga et al. 2018). We analyzed
 differences in environmental variables between SOS collection sites and
 random points using general linear models. We also asked what proportion
 of the potential habitat of our focal species was affected by fire across
 this 18 year timeframe based on the binary species distribution
 maps. Conditions across seed collection locations vs
 areas of restoration seeding We acquired geospatial
 records for all of the implemented or planned restoration seedings on
 public lands that were available from the Land Treatment Data Library, for
 the timeframe of 2000-2017 (Pilliod & Welty 2013). We used ArcMap
 10.5 to extract values for the same four temperature and precipitation
 values (described above) from 1500 random points distributed across the
 area of the restoration seedings. We then determined significant
 differences between the environmental values found at the SOS collection
 locations and the random points across restoration seedings using general
 linear models. Analyses were conducted in Program R (R
 Development Core Team 2016) using the <i>car</i> package (Fox
 & Weisberg 2011) and <i>Agricolae</i> package (de
 Mendiburu 2016) and a P-value of 0.05 was used to determine statistical
 significance.