DOI: 10.5061/dryad.b5mkkwhpt
title: Data from: Seed and seedling traits suggest ontogenetic coordination in the functional recruitment niche for dryland restoration species

description: Plant recruitment is shaped by functioning across seed and seedling
 stages. Because seed morphology and germination directly influence
 seedling exposure to resources and the environment, these two stages may
 be linked through trait synergies and tradeoffs that coordinate
 functioning through early ontogeny. However, the wide range of traits
 impacting environmental response at each ontogenetic stage is rarely
 explored in tandem to understand the potential dimensionality of the
 functional recruitment niche. We explored covariation among 13 seed and
 seedling traits linked to stress tolerance, rate of germination or growth,
 light response, temperature response, and other functions for 49 species
 found in semi-arid rangelands. Using phylogenetically informed ordination
 and cluster analysis, we asked how trait covariation across multiple
 ontogenetic stages and functions shapes the dimensionality of the
 functional recruitment niche. The first two trait dimensions identified at
 separate seed and seedling stages aligned, providing some basis for
 ontogenetic coordination during recruitment. Morphological traits
 reflecting size-related stress tolerance (i.e. seed and seedling mass)
 formed the strongest foundation for coordination across stages, sharing
 ties with traits reflecting seedling light response (specific leaf area),
 growth rate (root elongation), and seed temperature response (e.g.,
 germination minimum temperature). We also observed an unexpected tradeoff
 in how seeds and seedlings may avoid risk (through dormancy) or tolerate
 risk (through root investment), respectively. In contrast, seed light
 response, seed germination rate, and seedling minimum temperature
 thresholds were not tightly linked to analogous functions at other stages.
 Their independence could expand the dimensionality of the recruitment
 niche depending on the functional significance of these traits in the
 field. Synthesis. Seed and seedling stages are characterized by multiple,
 independent dimensions of functioning, but ontogenetic coordination may
 moderate increasing dimensionality of the functional recruitment niche as
 a wider breadth of traits are explored together. At the same time,
 physiological traits linked to environmental response appear less
 connected to other traits and could complexify spatiotemporal recruitment
 dynamics. Both the independent and coordinated aspects of functioning
 observed here deserve exploration across a broader range of species,
 traits, and environments to understand the full dimensionality of the
 functional recruitment niche.
description: # Seed and seedling traits suggest ontogenetic coordination in the
 functional recruitment niche for dryland restoration species
 [https://doi.org/10.5061/dryad.b5mkkwhpt](https://doi.org/10.5061/dryad.b5mkkwhpt) ## Description of the data and file structure This study used seed germination and seedling growth experiments to estimate seed and seedling traits for 49 plant species occurring naturally in cold deserts of the Western US. ### Files and variables #### File: metadata.csv **Description:** Contains information on the variables stored in each data file associated with the study ##### Variables * file: the specific data file being described * variable: the specific column being described * description: a basic description of the variable captured by each column * type: the type of data represented by each variable (character, numeric, etc.) * units: the unit of the variable, if applicable * notes: details about how the variable was collected #### File: GerminationTime\_by\_Temp.csv **Description:** Contains data on the average time to germination for multiple seedlot subpopulations (5% to 100%) at each of three temperatures (6C, 12C, 18C), across 49 unique species. These data are used to estimate germination minimum temperature and germination thermal time -- two traits included in the paper's analyses. ##### Variables * Please see metadata.csv for a description of each variable #### File: Species\_trait\_estimates\_final.csv **Description:** Contains all seed and seedling trait estimates (species' means) used in statistical analysis. ##### Variables * Please see metadata.csv for a description of each variable #### File: Root\_Elongation\_Rates.csv **Description:** Contains data on root elongation rate for each seedling replicate at each of three temperatures (6C, 12C, 18C), across 49 unique species. These data are used to estimate minimum temperature for root elongation and thermal time for root elongation-- two traits included in the paper's analyses. ##### Variables * Please see metadata.csv for a description of each variable Missing data: mentioned as NA #### File: Script\_Germination\_Temp\_Metrics.R **Description:** This R script contains code used to generate estimates of germination minimum temperature and thermal time estimates, two seed traits used in the paper's analyses. #### File: Script\_Analysis.R **Description:**  This script contains all statistical analyses supporting the inferences described in the paper. #### File: Script\_RER\_Temp\_Metrics.R **Description:** This script contains code used to generate estimates of RER minimum temperature and RER thermal time, two seedling traits used in the paper's analyses. ## Plant Species This table shows n=49 study species included in the dataset.  * species: Six-digit species identifier used in some tables and figures in the associated manuscript * species_name: Full genus and species name of each plant species | species | species\_name | | :------ | :--------------------------------------- | | ACHMIL | Achillea millefolium | | ACHHYM | Achnatherum hymenoides | | AGOGRA | Agoseris grandiflora | | AGRCRI | Agropyron cristatum | | ARIPUR | Aristida purpurea | | ARTTRI | Artemisia tridentata subsp. wyomingensis | | ASCTUB | Asclepias tuberosa | | ATRCAN | Atriplex canescens | | BAIMUL | Baileya multiradiata | | BALSAG | Balsamorhiza sagittata | | BOUCUR | Bouteloua curtipendula | | BOUERI | Bouteloua eriopoda | | BOUGRA | Bouteloua gracilis | | BROTEC | Bromus tectorum | | CHADOU | Chaenactis douglasii | | CLELUT | Cleome lutea | | CLESER | Cleome serrulata | | CREACU | Crepis acuminata | | CREINT | Crepis intermedia | | DALCAN | Dalea candida | | DALORN | Dalea ornata | | DALSEA | Dalea searlsiae | | ELYELY | Elymus elymoides | | ELYTRA | Elymus trachycaulus | | ERIPUM | Erigeron pumilus | | ERISPE | Erigeron speciosus | | ERIUMB | Eriogonum umbellatum | | HEDBOR | Hedysarum boreale | | HELMUL | Heliomeris multiflora | | HESCOM | Hesperostipa comata | | KRALAN | Krascheninnikovia lanata | | LEYCIN | Leymus cinereus | | LEYTRI | Leymus triticoides | | LINLEW | Linum lewisii | | LOMDIS | Lomatium dissectum | | LOMMAC | Lomatium macrocarpum | | LUPARG | Lupinus argenteus | | MACCAN | Machaeranthera canescens | | PASSMI | Pascopyrum smithii | | PENPAL | Penstemon palmeri | | PHAHAS | Phacelia hastata | | PLEJAM | Pleuraphis jamesii | | POASEC | Poa secunda | | PSESPI | Pseudoroegneria spicata | | SENCOV | Senna covesii | | SPHGRO | Sphaeralcea grossulariifolia | | SPHMUN | Sphaeralcea munroana | | SPOAIR | Sporobolus airoides | | SPOCRY | Sporobolus cryptandrus | ## Code/software All analyses were performed in the free and open statistical software, R. R is required to view code (.R files) and perform analyses. ``` R Core Team (2024). _R: A Language and Environment for Statistical Computing_. R Foundation for Statistical Computing, Vienna, Austria. . ``` ## Access information Other publicly accessible locations of the data: * Summary figures and tables produced by these data and code can be found in Appendix A of the published paper (online supporting information).