Data Package Metadata View Summary

Data for Context-dependent biotic interactions control plant abundance across altitudinal environmental gradients, 2014, 2016, Colorado, USA

General Information

Data Package:
Local Identifier:	edi.391.2
Title:	Data for Context-dependent biotic interactions control plant abundance across altitudinal environmental gradients, 2014, 2016, Colorado, USA
Abstract:	Many biotic interactions influence community structure, yet most distribution models for plants have focused on plant competition or used only abiotic variables to predict plant abundance. Furthermore, biotic interactions are commonly context-dependent across abiotic gradients. For example, plant-plant interactions can grade from competition to facilitation over temperature gradients. We used a hierarchical Bayesian framework to predict the abundances of 12 plant species across a mountain landscape and test hypotheses on the context-dependency of biotic interactions over abiotic gradients. We combined field-based estimates of six biotic interactions (foliar herbivory and pathogen damage, fungal root colonization, fossorial mammal disturbance, plant cover, and plant diversity) with abiotic data on climate and soil depth, nutrients, and moisture. All biotic interactions were significantly context-dependent along temperature gradients. Results supported the stress gradient hypothesis: As abiotic stress increased, the strength or direction of the relationship between biotic variables and plant abundance generally switched from negative (suggesting suppressed plant abundance) to positive (suggesting facilitation/mutualism). For half of the species, plant cover was the best predictor of abundance, suggesting that the prior focus on plant-plant interactions is well-justified. Explicitly incorporating the context-dependency of biotic interactions generated novel hypotheses about drivers of plant abundance across abiotic gradients and may improve the accuracy of niche models.
Publication Date:	2019-06-06

Time Period

Begin:

2014-06-01

End:

2016-07-31

People and Organizations
Contact:	Lynn, Joshua S (University of New Mexico; Rocky Mountain Biological Laboratory) [ email ]
Contact:	Rudgers, Jennifer A (University of New Mexico; Rocky Mountain Biological Laboratory) [ email ]
Creator:	Lynn, Joshua S (University of New Mexico; Rocky Mountain Biological Laboratory)
Creator:	Kazenel, Melanie R (University of New Mexico; Rocky Mountain Biological Laboratory)
Creator:	Kivlin, Stephanie N (University of New Mexico; Rocky Mountain Biological Laboratory; The University of Tennessee, Knoxville)
Creator:	Rudgers, Jennifer A (University of New Mexico; Rocky Mountain Biological Laboratory)
Associate:	Brown, Wendy (Rocky Mountain Biological Laboratory, Assisted In Data Collection)
Associate:	Canfield, Samuel (Rocky Mountain Biological Laboratory, Assisted In Data Collection)
Associate:	Forrester, Chiara (Rocky Mountain Biological Laboratory, Assisted In Data Collection)
Associate:	Spellman, Ian (Rocky Mountain Biological Laboratory, Assisted In Data Collection)

Data Entities
Data Table Name:	LynnETAL2019_Ecography_ContDep
Description:	Grass abundance was estimated along three parallel 20 m transects placed perpendicular to the mountain slope.

Detailed Metadata

Data Entities

Data Table


Data:	https://pasta-s.lternet.edu/package/data/eml/edi/391/2/d2c61bf3e2d71503a9f68bf0d8281d37
Name:	LynnETAL2019_Ecography_ContDep
Description:	Grass abundance was estimated along three parallel 20 m transects placed perpendicular to the mountain slope.
Number of Records:	840
Number of Columns:	26

Table Structure

Object Name:

LynnETAL2019_Ecography_ContDep.csv

Size:

141336 byte

Authentication:

dafebf7d33384bd53cdbe91886214e36 Calculated By MD5

Text Format:

Number of Header Lines:

Record Delimiter:

\r\n

Orientation:

column

Simple Delimited:

Field Delimiter:	,
Quote Character:	"

Table Column Descriptions

Column Name:

peak

site

spp

year

abund

Latitude

Longitude

Elevation_m

Avg_VWC1

Avg_VWC2

Avg_Soil_Depth

p1MAT

tot_N

nitrate

ammon

phos

goph

cov

Hdiv

richness

SimpDiv

InvSimpDiv

w_herb

w_fung

AVG_amf

Definition:

Name of the peak associated with a mountain transect

Number designation for a unique site within a transect that is loosely based on 100m elevation bands. Sites with x refer to extra sites sampled in 2016.

Species code

Year that the site was sampled

Abundance of a given species at a site expressed as counts over 60m of transects

Latitude of the site in WGS 84

Longitude of the site in WGS 84

Elevation of the site above sea level

Average soil volumetric water content for a site at first sample between 12-24 July 2014 (Water L/Soil L)*100

Average soil volumetric water content for a site at first sample between 23 Sept-8 Oct 2014 (Water L/Soil L)*100

Average soil depth for a site

Soil pH of the site

Mean annual temperature (MAT) of the site measured

Total nitrogen ion exchange rate for a site determined by the addition of ammonium (ammon) and nitrate

Nitrate exchange rate for a site

Ammonium exchange rate for a site

Phosphate exchange rate for a site

Average gopher disturbance counts across three 40m transects at a site (Lynn et al. 2018 for details)

Total vegetative % cover for a site summed across 33 20x20cm plots (maximum 3300)

Shannon diversity for plants at a site based on vegetation surveys. Calculated in R with the vegan package.

Species richness of plants for a site calculated by summing the number of unique species found at a site in the vegetation surveys.

Simpsons diversity for plants at a site based on vegetation surveys. Calculated in R with the vegan package.

Inverse Simpsons diversity for plants at a site based on vegetation surveys. Calculated in R with the vegan package.

Percent leaf area damaged by herbivory. Measure is for a site by weighted averaging (by abundance) across the grass species present at a site

Percent leaf area damaged by leaf pathogens. Measure is for a site by weighted averaging (by abundance) across the grass species present at a site

Percent microscope views of roots that contained aseptate fungi (candidate arbuscular mycorrhizal fungi). Measure is for a site by weighted averaging (by abundance) across the grass species present at a site

Storage Type:

string

float

Measurement Type:

nominal

ratio

Measurement Values Domain:

Allowed Values and Definitions

Enumerated Domain

Code Definition

Code	A
Definition	Avery
Source

Code Definition

Code	C
Definition	Cinnamon
Source

Code Definition

Code	HH
Definition	Hunters Hill
Source

Code Definition

Code	R
Definition	Ruby
Source

Code Definition

Code	Teo
Definition	Teocalli
Source

Code Definition

Code	TR
Definition	Treasury
Source

Definition

Number designation for a unique site within a transect that is loosely based on 100m elevation bands. Sites with x refer to extra sites sampled in 2016.

Allowed Values and Definitions

Enumerated Domain

Code Definition

Code	ACLE
Definition	Achnatherum lettermanii (Vasey) Barkworth
Source

Code Definition

Code	ACNE
Definition	Achnatherum nelsonii (Scribn.) Barkworth
Source

Code Definition

Code	ELSC
Definition	Elymus scribneri (Vasey) M.E. Jones
Source

Code Definition

Code	ELTR
Definition	Elymus trachycaulus (Link) Gould ex Shinners
Source

Code Definition

Code	FEBR
Definition	Festuca brachyphylla Schult. ex Schult. & Schult. f.
Source

Code Definition

Code	FERU
Definition	Festuca rubra L.
Source

Code Definition

Code	FESA
Definition	Festuca saximontana Rydb.
Source

Code Definition

Code	FETH
Definition	Festuca thurberi Vasey
Source

Code Definition

Code	POAL
Definition	Poa alpina L.
Source

Code Definition

Code	POPR
Definition	Poa pratensis L.
Source

Code Definition

Code	POST
Definition	Poa stenantha Trin.
Source

Code Definition

Code	TRSP
Definition	Trisetum spicatum (L.) K. Richt.
Source

Unit	nominalYear
Type	natural
Min	2014
Max	2016

Unit	number
Type	whole
Min	0
Max	173

Unit	degree
Type	real
Min	38.85
Max	39.01

Unit	degree
Type	real
Min	106.78
Max	107.13

Unit	meter
Type	real
Min	2710.5
Max	4023.25

Unit	dimensionless
Type	real
Min	2.55
Max	26.02

Unit	dimensionless
Type	real
Min	6.9
Max	31.01

Unit	millimeter
Type	real
Min	83.2
Max	1362.7

Unit	dimensionless
Type	real
Min	4.6
Max	7.7

Unit	celsius
Type	real
Min	-1.59
Max	3.32

Unit	microGramsNitrogenPerTenCentimeterSquareExchangeResinPerTenWeeks
Type	real
Min	2
Max	316

Unit	microGramsNitratePerTenCentimeterSquareExchangeResinPerTenWeeks
Type	real
Min	0
Max	309

Unit	microGramsAmmoniumPerTenCentimeterSquareExchangeResinPerTenWeeks
Type	real
Min	2
Max	8

Unit	microGramsPhosphorusPerTenCentimeterSquareExchangeResinPerTenWeeks
Type	real
Min	0
Max	24

Unit	number
Type	real
Min	0
Max	63

Unit	dimensionless
Type	real
Min	405
Max	3222

Unit	dimensionless
Type	real
Min	1.16
Max	3.01

Unit	number
Type	real
Min	7
Max	38

Unit	dimensionless
Type	real
Min	0.44
Max	0.93

Unit	dimensionless
Type	real
Min	1.8
Max	14.79

Unit	dimensionless
Type	real
Min	0.7
Max	26.68

Unit	dimensionless
Type	real
Min	0
Max	11.36

Unit	dimensionless
Type	real
Min	34
Max	85

Missing Value Code:

Code	NA
Expl	not available

Code	NA
Expl	not available

Code	NA
Expl	not available

Code	NA
Expl	not available

Code	NA
Expl	not available

Code	NA
Expl	not available

Code	NA
Expl	not available

Code	NA
Expl	not available

Code	NA
Expl	not available

Code	NA
Expl	not available

Code	NA
Expl	not available

Code	NA
Expl	not available

Code	NA
Expl	not available

Code	NA
Expl	not available

Code	NA
Expl	not available

Code	NA
Expl	not available

Code	NA
Expl	not available

Code	NA
Expl	not available

Code	NA
Expl	not available

Code	NA
Expl	not available

Code	NA
Expl	not available

Code	NA
Expl	not available

Code	NA
Expl	not available

Accuracy Report:

Accuracy Assessment:

Coverage:

Methods:

Data Package Usage Rights

This information is released under the Creative Commons license - Attribution - CC BY (https://creativecommons.org/licenses/by/4.0/). The consumer of these data ("Data User" herein) is required to cite it appropriately in any publication that results from its use. The Data User should realize that these data may be actively used by others for ongoing research and that coordination may be necessary to prevent duplicate publication. The Data User is urged to contact the authors of these data if any questions about methodology or results occur. Where appropriate, the Data User is encouraged to consider collaboration or co-authorship with the authors. The Data User should realize that misinterpretation of data may occur if used out of context of the original study. While substantial efforts are made to ensure the accuracy of data and associated documentation, complete accuracy of data sets cannot be guaranteed. All data are made available "as is." The Data User should be aware, however, that data are updated periodically and it is the responsibility of the Data User to check for new versions of the data. The data authors and the repository where these data were obtained shall not be liable for damages resulting from any use or misinterpretation of the data. Thank you.

Keywords

By Thesaurus:
(No thesaurus)	Ecological niche model, species distribution model, stress-gradient hypothesis, Dobzhansky-MacArthur hypothesis, mountain ecosystems, biotic interactions
LTER Controlled Vocabulary	plants, abundance, soil nutrients, climate

Methods and Protocols

These methods, instrumentation and/or protocols apply to all data in this dataset:

Methods and protocols used in the collection of this data package

Description:

Methods copied from-

Lynn, J.S., M.R. Kazenel, S.N. Kivlin, and J.A. Rudgers. In press. Context-dependent biotic interactions control plant abundance across altitudinal environmental gradients. Ecography. doi: 10.1111/ecog.04421

Study site selection, focal species, and abundance estimates

We collected data in the Upper Gunnison Basin of the Colorado Rocky Mountains, USA (Figure 1). In 2014, we surveyed six independent peak-to-valley gradients spanning about 1300 m (2700 m to 4000 m a.s.l.; Figure 1). Sites were established every 100 m in elevation from peak-to-valley. This method produced 67 grassland sites, about 11 sites per gradient. To bolster data for alpine species, in 2016, we surveyed an additional 2-3 sites on five gradients (3462-3960 m a.s.l.), resulting in 79 total sites (Figure 1).

We focused on native perennial grasses. Grass abundance was estimated along three parallel 20 m transects placed perpendicular to the mountain slope and spaced 10 m apart. The focal taxa were bunch grasses (with the exception of Poa pratensis) with a maximum diameter of about 0.5 m at the ground; therefore, 20 m sufficiently captured species abundance. We estimated abundance by counting the number of individuals/species that intersected transects. This process resulted in abundance estimates for 16 species, but four were insufficiently represented (4 occurrences).

The ability to detect context-dependency may depend on spatial scale. For example, sampling the whole stress gradient occupied by a species may indicate that plant-plant interactions range from facilitation to competition, but this pattern may be obscured when only part of the species range is sampled. Therefore, we grouped species by the spatial extent of sampling effort: the whole elevation range (Elymus trachycaulus, Festuca rubra, F. saximontana, Poa stenantha, Trisetum spicatum), only the high-elevation range portion/limit (Achnatherum lettermanii, A. nelsonii, F. thurberi, P. pratensis), or only the low-elevation range portion/limit (E. scribneri, F. brachyphylla, P. alpina; summary statistics in Supplementary material Appendix 1).

Abiotic environment predictors

Abiotic variables were chosen to assess hypotheses in Table 1. At each site, two 20 m transects were placed perpendicularly, with one transect horizontal to the prevailing slope. We estimated soil volumetric water content (VWC) every 5 m along transects (10 estimates per site) using a Fieldscout TDR (10 cm probes; Spectrum Technologies, Aurora, IL, USA) at two time points over the growing season (12-24 July, 23 Sept-8 Oct, 2014), then averaged VWC within a site and sampling date. We estimated soil depth at the same points with a 1.5 m tile probe (AMS, inc., American Falls, ID, USA) inserted until it met bedrock (about 10 estimates per site). We deployed Plant Root Simulator probes (Western Ag Innovations, Saskatoon, SK, Canada) at the ends of each transect for about 10 weeks (12 July - 30 Sept, 2014). The probes were analyzed together to produce a single measure of total soil N (nitrate and ammonium) and phosphorus availability per site. We also collected and pooled soil from the four transect ends to measure soil pH (Hanna Instruments HI 9813-6 Portable; Woonsocket, RI, USA). We used regional meteorological stations to interpolate climate data for each study site based on its elevation, slope, and aspect (methods in Lynn et al. 2018). Only mean annual temperature (MAT) was used in analyses due to high collinearity among climate variables. Supplementary material Appendix 2 contains a schematic diagram of site measurements.

Biotic interaction predictors

We briefly describe methods for measuring biotic predictors but provide detail in Supplementary material Appendix 2. Estimates of plant cover and Shannon diversity were assessed with vegetation surveys. Herbivory and pathogen damage were visually estimated as percentage leaf area damaged on 10 individuals per focal species per site. To model consumptive interactions when a species was not present, we calculated grass community weighted means of herbivory and pathogen damage to represent the site-level herbivory and pathogen "pressure". Similar community weighted means were applied to arbuscular mycorrhizal fungi (AMF) colonization of roots, following Ranelli et al. (2015). Gopher disturbance was assessed using methods of Lynn et al. (2018).

Supplementary Material Appendix 2 methods

Biotic interaction predictors

Competition/facilitation.

We assessed plant community composition using visual cover estimates. We placed a 0.2 m x 0.2 m quadrat every 2.5 m along four 20 m transects per site. In each quadrat, we visually estimated percentage cover of every plant species or bare ground to total 100% (33 plant cover estimates per site). Specimens were collected and identified using Shaw (2008) for grasses and Weber and Wittmann (2012) for non-grasses. We corrected for current taxonomy using the USDA PLANTS Database (USDA and NRCS 2017). Unidentified species (e.g., non-flowering sedges) were morphotyped, assigned unique species codes, and matched to unknowns at other sites. Plant cover for a site was represented by the summed percentage cover estimate across the 33 quadrats (maximum of 3300 if site was 100% vegetated). We used the vegan package in R to calculate plant species diversity indices (Oksanen et al. 2017). Because diversity metrics were highly colinear, we used Shannon diversity (hereafter diversity) in all subsequent analyses, as it had the highest correlation with other diversity metrics.

Potential antagonisms.

We assessed insect herbivory and leaf pathogens via calibrated visual estimates of percentage leaf damage for 10 randomly selected individuals per focal grass species per site, with a minimum distance of two m between individuals. Insect herbivory and pathogen damage present a dilemma for niche modeling: how can one estimate a biotic interaction when a species is not present at a site? Therefore, we created a site-level metric of herbivore/pathogen pressure by calculating community weighted mean damage over all grass species present at a site. This metric estimated the expected damage that a grass individual would experience if it were present at the site.

We measured pocket gopher (Thomomys talpoides) disturbance to soil at each site along three 40 m long belt transects (methods in Lynn et al. 2018). Briefly, each belt transect was 1 m wide and each characteristic sign of gopher disturbance (e.g., mounds, eskers) were summed across the transects.

Potential mutualisms.

We assessed percentage fungal colonization of roots by pooling equal amounts of root tissue by volume from six plant individuals per species per site (methods in Ranelli et al. 2015). We scored colonization of roots by arbuscular mycorrhizal fungi (AMF; aseptate hyphae with vesicles and/or arbuscules; Glomeromycotina). We estimated site-level root colonization with community weighted means over all grass species present at a site.

QA/QC Procedures:

We performed QA/QC checks with data entry checking (entry and rechecking the entries), outlier analysis, scatterplots, and internal consistency checks.

People and Organizations

Creators:

Individual:

Joshua S Lynn

Organization:

University of New Mexico; Rocky Mountain Biological Laboratory

Email Address:

jslynn@unm.edu

Individual:

Melanie R Kazenel

Organization:

University of New Mexico; Rocky Mountain Biological Laboratory

Email Address:

mkazenel@unm.edu

Individual:

Stephanie N Kivlin

Organization:

University of New Mexico; Rocky Mountain Biological Laboratory; The University of Tennessee, Knoxville

Email Address:

skivlin@utk.edu

Individual:

Jennifer A Rudgers

Organization:

University of New Mexico; Rocky Mountain Biological Laboratory

Email Address:

jrudgers@unm.edu

Contacts:

Individual:

Joshua S Lynn

Organization:

University of New Mexico; Rocky Mountain Biological Laboratory

Email Address:

jslynn@unm.edu

Individual:

Jennifer A Rudgers

Organization:

University of New Mexico; Rocky Mountain Biological Laboratory

Email Address:

jrudgers@unm.edu

Associated Parties:

Individual:	Wendy Brown
Organization:	Rocky Mountain Biological Laboratory
Role:	Assisted In Data Collection

Individual:	Samuel Canfield
Organization:	Rocky Mountain Biological Laboratory
Role:	Assisted In Data Collection

Individual:	Chiara Forrester
Organization:	Rocky Mountain Biological Laboratory
Role:	Assisted In Data Collection

Individual:	Ian Spellman
Organization:	Rocky Mountain Biological Laboratory
Role:	Assisted In Data Collection

Temporal, Geographic and Taxonomic Coverage

Temporal, Geographic and/or Taxonomic information that applies to all data in this dataset:

Time Period

Begin:

2014-06-01

End:

2016-07-31

Geographic Region:

Description:

Bounding Coordinates:

Northern:	38.98512406	Southern:	38.86523
Western:	-106.9885206	Eastern:	-106.9123563

Geographic Region:

Description:

Bounding Coordinates:

Northern:	38.99665621	Southern:	38.88163
Western:	-107.0704268	Eastern:	-106.96172

Geographic Region:

Description:

Bounding Coordinates:

Northern:	38.94594843	Southern:	38.84758708
Western:	-106.819641	Eastern:	-106.7777649

Geographic Region:

Description:

Bounding Coordinates:

Northern:	38.90226451	Southern:	38.856165
Western:	-107.1283646	Eastern:	-107.031725

Geographic Region:

Description:

Teo

Bounding Coordinates:

Northern:	38.96006224	Southern:	38.89571492
Western:	-106.8912166	Eastern:	-106.8761911

Geographic Region:

Description:

Bounding Coordinates:

Northern:	39.0113075	Southern:	38.9186175
Western:	-107.095645	Eastern:	-107.0362825

Project

Parent Project Information:

Title:

Graduate Student Research Award

Personnel:

Individual:	Joshua Lynn
Role:	Principal Investigator

Funding:

Western Ag Innovations

Related Project:

Title:

King of the Hill? Potential for novel biotic interactions

Personnel:

Individual:	Joshua Lynn
Role:	Principal Investigator

Funding:

Botanical Society of America Graduate Student Research Award

Related Project:

Title:

Harry Wayne Springfield and Grove Scholarships

Personnel:

Individual:	Joshua Lynn
Role:	Principal Investigator

Funding:

University of New Mexico Biology Department

Related Project:

Title:

King of the hill? Climate change effects on biotic interactions in alpine plant communities

Personnel:

Individual:	Joshua Lynn
Role:	Principal Investigator

Funding:

Rocky Mountain Biological Laboratory Jean Langenheim Graduate Student Fellowship

Related Project:

Title:

King of the Hill? Predicting the population consequences of climate change altered species interactions

Personnel:

Individual:	Joshua Lynn
Role:	Principal Investigator

Funding:

American Philosophical Society Lewis and Clark Fund

Related Project:

Title:

DISSERTATION RESEARCH: King of the hill? How competitive interactions affect biogeographical pattern and species responses to environmental variability

Personnel:

Individual:	Joshua Lynn
Role:	Principal Investigator

Funding:

NSF-DEB: 1701221

Related Project:

Title:

The potential for climate-induced disruption of plant-microbe symbioses along altitudinal gradients

Personnel:

Individual:	Jennifer Rudgers
Role:	Principal Investigator

Funding:

NSF-DEB: 1354972

Maintenance

Maintenance:

Description:	completed
Frequency:

Other Metadata

Additional Metadata

additionalMetadata
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        |___element 'metadata'
        |     |___text '\n      '
        |     |___element 'unitList'
        |     |     |___text '\n        '
        |     |     |___element 'unit'
        |     |     |     |  \___attribute 'id' = 'microGramsNitrogenPerTenCentimeterSquareExchangeResinPerTenWeeks'
        |     |     |     |  \___attribute 'multiplierToSI' = ''
        |     |     |     |  \___attribute 'name' = 'microGramsNitrogenPerTenCentimeterSquareExchangeResinPerTenWeeks'
        |     |     |     |  \___attribute 'parentSI' = ''
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        |     |     |___text '\n        '
        |     |     |___element 'unit'
        |     |     |     |  \___attribute 'id' = 'microGramsNitratePerTenCentimeterSquareExchangeResinPerTenWeeks'
        |     |     |     |  \___attribute 'multiplierToSI' = ''
        |     |     |     |  \___attribute 'name' = 'microGramsNitratePerTenCentimeterSquareExchangeResinPerTenWeeks'
        |     |     |     |  \___attribute 'parentSI' = ''
        |     |     |     |  \___attribute 'unitType' = ''
        |     |     |     |___text '\n          '
        |     |     |     |___element 'description'
        |     |     |     |     |___text 'ion exchange rate'
        |     |     |     |___text '\n        '
        |     |     |___text '\n        '
        |     |     |___element 'unit'
        |     |     |     |  \___attribute 'id' = 'microGramsAmmoniumPerTenCentimeterSquareExchangeResinPerTenWeeks'
        |     |     |     |  \___attribute 'multiplierToSI' = ''
        |     |     |     |  \___attribute 'name' = 'microGramsAmmoniumPerTenCentimeterSquareExchangeResinPerTenWeeks'
        |     |     |     |  \___attribute 'parentSI' = ''
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        |     |     |___element 'unit'
        |     |     |     |  \___attribute 'id' = 'microGramsPhosphorusPerTenCentimeterSquareExchangeResinPerTenWeeks'
        |     |     |     |  \___attribute 'multiplierToSI' = ''
        |     |     |     |  \___attribute 'name' = 'microGramsPhosphorusPerTenCentimeterSquareExchangeResinPerTenWeeks'
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Copyright 2024 Environmental Data Initiative. This material is based upon work supported by the National Science Foundation under grants #2223103 and #2223104. Any opinions, findings, conclusions, or recommendations expressed in the material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation. Please contact us with questions, comments, or for technical assistance regarding this web site or the Environmental Data Initiative. Please read our privacy policy to know what information we collect about you and to understand your privacy rights.

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Data Package Metadata View Summary

Data for Context-dependent biotic interactions control plant abundance across altitudinal environmental gradients, 2014, 2016, Colorado, USA

Data Entities

Data Table

Data Package Usage Rights

Keywords

Methods and Protocols

These methods, instrumentation and/or protocols apply to all data in this dataset:

Study site selection, focal species, and abundance estimates

Abiotic environment predictors

Biotic interaction predictors

Supplementary Material Appendix 2 methods

QA/QC Procedures:

People and Organizations

Temporal, Geographic and Taxonomic Coverage

Project

Parent Project Information:

Maintenance

Additional Metadata

Recently Added

Recently Updated

Data Package Metadata View Summary

Data for Context-dependent biotic interactions control plant abundance across altitudinal environmental gradients, 2014, 2016, Colorado, USA

+/- Data Entities

Data Table

+/- Data Package Usage Rights

+/- Keywords

+/- Methods and Protocols

These methods, instrumentation and/or protocols apply to all data in this dataset:

Study site selection, focal species, and abundance estimates

Abiotic environment predictors

Biotic interaction predictors

Supplementary Material Appendix 2 methods

QA/QC Procedures:

+/- People and Organizations

+/- Temporal, Geographic and Taxonomic Coverage

+/- Project

Parent Project Information:

+/- Maintenance

+/- Additional Metadata

Data Entities

Data Package Usage Rights

Keywords

Methods and Protocols

People and Organizations

Temporal, Geographic and Taxonomic Coverage

Project

Maintenance

Additional Metadata