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ESM
Simulations connecting metacommunity characteristics and biodiversity patterns
Eric
Sokol
sokole@gmail.com
http://sokole.blogspot.com/
https://orcid.org/0000-0001-5952-0917
McMurdo Dry Valleys LTER
http://mcmlter.org/
John "Jeb"
Barrett
jebarre@vt.edu
https://www.biol.vt.edu/faculty/barrett/index.html
https://orcid.org/0000-0002-7610-0505
associated researcher
Bryan
Brown
associated researcher
2016-10-21
English
The data and model described here with the purpose of understanding controls over biodiversity. A multi-scale approach to understand how local and regional factors affect the community assembly processes that drive emergent patterns. These data allows us to examin a wide range of parameter settings representing ecologically relevant scenarios. We used artificial neural networks (ANNs) to assess the sensitivity of diversity and variation partitioning metrics (calculated from simulation outcomes) to metacommunity parameter settings. Here you will find metadata details, dor detailed information about the simulations results and conclusions, please visit the associated publication at http://onlinelibrary.wiley.com/doi/10.1111/oik.03690/abstract;jsessionid...
dispersal
dispersion
diversity
simulation
LTER Controlled Vocabulary
distribution
Station Keywords
population dynamics
LTER Core Areas
This simulation is atemporal and non-localized. There is no physical geo-location or calendar time frame or specific season. However, simulations were performed in Aug 2016.
Data Policies
This data package is released under the Creative Commons Attribution 4.0 International License (CC BY 4.0; http://creativecommons.org/licenses/by/4.0/), which allows consumers (hereinafter referred to as “Data Users”) to freely reuse, redistribute, transform, or build on this work (even commercially) so long as appropriate credit is provided. Accordingly, Data Users are required to properly cite this data package in any publications or in the metadata of any derived products that result from its use (in whole or in part). A recommended citation is provided on the summary metadata page associated with this data package in the McMurdo Dry Valleys LTER Data Catalog (https://mcmlter.org/data), and a generic citation may be found on the summary metadata page in the repository where this data package was obtained. When these data contribute significantly to the contents of a publication, Data Users must also acknowledge that data were provided by the NSF-supported McMurdo Dry Valleys Long Term Ecological Research program (OPP-1637708). This data package has been released in the spirit of open scientific collaboration. Hence, Data Users are strongly encouraged to consider consultation, collaboration, and/or co-authorship (as appropriate) with the data package creator(s). Data Users should be aware these data may be actively used by others for ongoing research; thus, coordination may be necessary to prevent duplicate publication. Data Users should also recognize that misinterpretation of data may occur if they are used outside the context of the original study. Hence, Data Users are urged to contact the data package creator(s) if they have any questions regarding methodology or results. While substantial efforts are made to ensure the accuracy of this data package (with all its components), complete accuracy cannot be guaranteed. Periodic updates to this data package may occur, and it is the responsibility of Data Users to check for new versions. This data package is made available “as is” and comes with no warranty of accuracy or fitness for use. The creator(s) of this data package and the repository where these data were obtained shall not be liable for any damages resulting from misinterpretation, use, or misuse of these data. Finally, as a professional courtesy, we kindly request Data Users notify the primary contact referenced in the metadata when these data are used in the production of any derivative work or publication. Notification should include an explanation of how the data were used, along with a digital copy of the derived product(s). Thank you.
https://mcm.lternet.edu/content/simulations-connecting-metacommunity-characteristics-and-biodiversity-patterns
2015-08-01
McMurdo Dry Valleys LTER
http://mcmlter.org/
McMurdo Dry Valleys LTER
http://mcmlter.org/
McMurdo Dry Valleys LTER
Methods, code description and heuristics are posted in the appendix of the associated publication at http://onlinelibrary.wiley.com/doi/10.1111/oik.03690/abstract;jsessionid... The Metacommunities simulation code used is posted at http://doi.org/10.5281/zenodo.153999
ESM_SIM_DATA_INPUT
ESM_sim_data parameter settings used in metacommunity simulation (MCSim), definitions and labels.
ESM_SIM_DATA_INPUT.csv
84676
1
column
,
https://mcm.lternet.edu/sites/default/files/data/ESM_SIM_DATA_INPUT.csv
Scenario ID
Scenario ID
Scenario ID, an integer used as identifier to distinguish the simulation run or realization.
string
Scenario ID, an integer used as identifier to distinguish the simulation run or realization.
nu
Probability of invasion
nu - Metacommunity openness, probability of invasion by a novel taxon, a log uniform distribution
dimensionless
real
.01
.00001
m
Recruitment proportion from inmmigrants
m - Metacommunity connectivity, proportion of recruitment events drawing from immigrant pool
dimensionless
real
.001
.999
w
Dispersal Slope
w - Dispersal kernel slope, pooled from a log-uniform distribution
dimensionless
real
0
200
sigma
sigma
sigma - Niche-breadth, constant among all taxa in a simulation. Pooled from a log-uniform distribution
dimensionless
real
0.01
2
alpha_Fisher
alpha_Fisher
alpha_Fisher - determines shape of the initial rank-abundance curve. Pooed from a uniform distribution
dimensionless
real
1
50
n_sites
n_sites
n_sites - Number of patches in a metacommunity. Pooled from a log-uniform distro.
dimensionless
real
20
200
s
s
s - Scale of environmental heterogeneity, standardized rank PCNM eigenvector used to model spatial variation in E. Pooled from a uniform distribution
dimensionless
real
0
.988
JM
JM
JM Metacommunity size (no. of individuals in a metacommunity at a single point in time). Value pooled from Log-uniform distribution
dimensionless
real
400
1000000
ESM_SIM_DATA_OUTPUT
ESM_sim_data_2. Biodiversity outcomes for 100 different simulated metacommunity (MCSim) scenarios -- Definitions, ranges, labels.
ESM_SIM_DATA_OUTPUT.csv
4964745
1
column
,
https://mcm.lternet.edu/sites/default/files/data/ESM_SIM_DATA_OUTPUT.csv
Simulation ID
Simulation ID
Simulation ID - an alphanumeric identifier used to distinguish the simulation realization.
string
Simulation ID - an alphanumeric identifier used to distinguish the simulation realization.
Time Step
Time Step
Time Step used in simulation
dimensionless
real
Diversity Type
Diversity Type
Diversity Type
string
dis.sat
dissimilarity saturation
varpart
variation partitions
divpart
diversity partitions
Metric Type
Metric Type
Metric Type
string
Metric Type
Metric ID
Metric ID
Metric ID
string
Metric ID
Metric Value
Metric Value
Metric Value
dimensionless
real
ESM_SIM_DATA_ANN_UNPRUNNED
ESM_sim_data_3. Estimates of contribution of MCSim parameters to variation in biodiversity metrics based on contribution statistics from artificial neural networks (ANNs) trained and validated on simulated metacommunity outcomes.
ESM_SIM_DATA_ANN_UNPRUNNED.csv
29130
1
column
,
https://mcm.lternet.edu/sites/default/files/data/ESM_SIM_DATA_ANN_UNPRUNNED.csv
Diversity Metric ID
Diversity Metric ID
Diversity Metric ID
string
Diversity Metric ID
Predictor Variable
Predictor Variable
Predictor Variable
string
Predictor Variable
Predictor contribution to variation in response variable
Predictor contribution to variation in response variable
Predictor contribution to variation in response variable
string
Predictor contribution to variation in response variable
Contribution p value
Contribution p value
Contribution p value
string
Contribution p value
Predictor relative importance (RI) to variatino in response variable
Predictor relative importance (RI) to variatino in response variable
Predictor relative importance (RI) to variatino in response variable
string
Predictor relative importance (RI) to variatino in response variable
RI p value
RI p value
RI p value
string
RI p value
Keep predictor in pruned model?
Keep predictor in pruned model?
Keep predictor in pruned model?
string
Keep predictor in pruned model?
N permutations used to estimate p values
N permutations used to estimate p values
N permutations used to estimate p values
string
N permutations used to estimate p values