Changes
On September 15, 2021 at 11:54:40 AM UTC, Alexander Skeels:
-
Updated description of Data from: Earth history events shaped the evolution of uneven biodiversity across tropical moist forests from
Datasets and R scripts Datasets Dataset_S1.csv includes species diversity counts for 237 clades in tropical moist forests (TMF) in the Neotropics (NeotropicalTMF), Indomalaya (IndomalayanTMF), Afrotropics (AfrotropicalTMF), All three TMF regions together (AllTMF), all non-TMF regions (NonTMF), and in total (Total). As well as whether the clade is pantropical (Pantropical_clade) and shows the pantropical diversity disparity (PDD_clade). Dataset_S2.csv: environmental and species richness data. Longitude (x), latitude (y), potential evapotranspiration (PET), mean annual temperature (MAT), mean annual precipitation), amphibian, bird, mammal, and reptile species richness, PC1 and PC2 of environmental PCA and the region. Environmental data (from CHELSA and ENVIREM) and species richness summarised from published data (vertLife, MOL, IUCN, GARD). Dataset_S3.csv: - Paleoenvironmental reconstructions (details in the associated SI appendix) including latitude (y), longitude (x), and temperature data across 200 myrs at 170 kyr intervals. Dataset_S4.csv: simulation model parameters and diversity summary statistics. Including rate of temperature niche evolution (Tev), temperature niche width (TW), divergence threshold (S), Dispersal probability distribution shape (WeibullShape) and information on number of extinct species, number of extant species, total species, Spearman correlation coefficient between absolute latitude and species richness (latitude_richness_cor), and diversity in the Neotropics, Indomalaya, Afrotropics. Also, whether the simulation generated pantropical distribution of species (pantropicality_index), or the pantropical diversity disparity (PDD_index). Finally what time step the simulation exited at (0 for complete simulations). Dataset_S5.csv: Net relatedness index (NRI) in three tropical moist forest regions and associated p-values for pantropically distributed taxa. Scripts Gen3sis_config_creator.R and Gen3sis_config_template.R scripts generate the configurations files to run the simulation experiment. GLS.R R script to replicate the linear modelling analyses.
toDatasets and R scripts ~~~~~Datasets Dataset_S1.csv includes species diversity counts for 237 clades in tropical moist forests (TMF) in the Neotropics (NeotropicalTMF), Indomalaya (IndomalayanTMF), Afrotropics (AfrotropicalTMF), All three TMF regions together (AllTMF), all non-TMF regions (NonTMF), and in total (Total). As well as whether the clade is pantropical (Pantropical_clade) and shows the pantropical diversity disparity (PDD_clade). Dataset_S2.csv: environmental and species richness data. Longitude (x), latitude (y), potential evapotranspiration (PET), mean annual temperature (MAT), mean annual precipitation), amphibian, bird, mammal, and reptile species richness, PC1 and PC2 of environmental PCA and the region. Environmental data (from CHELSA and ENVIREM) and species richness summarised from published data (vertLife, MOL, IUCN, GARD). Dataset_S3.csv: - Paleoenvironmental reconstructions (details in the associated SI appendix) including latitude (y), longitude (x), and temperature data across 200 myrs at 170 kyr intervals. Dataset_S4.csv: simulation model parameters and diversity summary statistics. Including rate of temperature niche evolution (Tev), temperature niche width (TW), divergence threshold (S), Dispersal probability distribution shape (WeibullShape) and information on number of extinct species, number of extant species, total species, Spearman correlation coefficient between absolute latitude and species richness (latitude_richness_cor), and diversity in the Neotropics, Indomalaya, Afrotropics. Also, whether the simulation generated pantropical distribution of species (pantropicality_index), or the pantropical diversity disparity (PDD_index). Finally what time step the simulation exited at (0 for complete simulations). Dataset_S5.csv: Net relatedness index (NRI) in three tropical moist forest regions and associated p-values for pantropically distributed taxa. ~~~~~Scripts Gen3sis_config_creator.R and Gen3sis_config_template.R scripts generate the configurations files to run the simulation experiment. GLS.R R script to replicate the linear modelling analyses.
f | 1 | { | f | 1 | { |
2 | "author": "[{\"affiliation\": \"Swiss Federal Research Institute for | 2 | "author": "[{\"affiliation\": \"Swiss Federal Research Institute for | ||
3 | Forest, Snow and Landscape (WSL)\", \"affiliation_02\": \"ETH | 3 | Forest, Snow and Landscape (WSL)\", \"affiliation_02\": \"ETH | ||
4 | Zurich\", \"affiliation_03\": \"\", \"data_credit\": [\"collection\", | 4 | Zurich\", \"affiliation_03\": \"\", \"data_credit\": [\"collection\", | ||
5 | \"validation\", \"curation\", \"software\", \"publication\"], | 5 | \"validation\", \"curation\", \"software\", \"publication\"], | ||
6 | \"email\": \"alexander.skeels@usys.ethz.ch\", \"given_name\": | 6 | \"email\": \"alexander.skeels@usys.ethz.ch\", \"given_name\": | ||
7 | \"Alexander\", \"identifier\": \"\", \"name\": \"Skeels\"}, | 7 | \"Alexander\", \"identifier\": \"\", \"name\": \"Skeels\"}, | ||
8 | {\"affiliation\": \"German Centre for Integrative Biodiversity | 8 | {\"affiliation\": \"German Centre for Integrative Biodiversity | ||
9 | Research Halle\\u2013Jena\\u2013Leipzig\", \"affiliation_02\": \"ETH | 9 | Research Halle\\u2013Jena\\u2013Leipzig\", \"affiliation_02\": \"ETH | ||
10 | Zurich\", \"affiliation_03\": \"\", \"data_credit\": [\"collection\", | 10 | Zurich\", \"affiliation_03\": \"\", \"data_credit\": [\"collection\", | ||
11 | \"validation\", \"curation\", \"software\", \"publication\"], | 11 | \"validation\", \"curation\", \"software\", \"publication\"], | ||
12 | \"email\": \"oskar@hagen.bio\", \"given_name\": \"Oskar\", | 12 | \"email\": \"oskar@hagen.bio\", \"given_name\": \"Oskar\", | ||
13 | \"identifier\": \"0000-0002-7931-6571\", \"name\": \"Hagen\"}, | 13 | \"identifier\": \"0000-0002-7931-6571\", \"name\": \"Hagen\"}, | ||
14 | {\"affiliation\": \"ETH Zurich\", \"affiliation_02\": \"Swiss Federal | 14 | {\"affiliation\": \"ETH Zurich\", \"affiliation_02\": \"Swiss Federal | ||
15 | Research Institute for Forest, Snow and Landscape (WSL)\", | 15 | Research Institute for Forest, Snow and Landscape (WSL)\", | ||
16 | \"affiliation_03\": \"\", \"data_credit\": [\"collection\", | 16 | \"affiliation_03\": \"\", \"data_credit\": [\"collection\", | ||
17 | \"validation\", \"curation\", \"software\", \"publication\", | 17 | \"validation\", \"curation\", \"software\", \"publication\", | ||
18 | \"supervision\"], \"email\": \"loic.pellissier@usys.ethz.ch\", | 18 | \"supervision\"], \"email\": \"loic.pellissier@usys.ethz.ch\", | ||
19 | \"given_name\": \"Loic\", \"identifier\": \"\", \"name\": | 19 | \"given_name\": \"Loic\", \"identifier\": \"\", \"name\": | ||
20 | \"Pellissier\"}, {\"affiliation\": \"German Centre for Integrative | 20 | \"Pellissier\"}, {\"affiliation\": \"German Centre for Integrative | ||
21 | Biodiversity Research Halle\\u2013Jena\\u2013Leipzig\", | 21 | Biodiversity Research Halle\\u2013Jena\\u2013Leipzig\", | ||
22 | \"affiliation_02\": \"\", \"affiliation_03\": \"\", \"data_credit\": | 22 | \"affiliation_02\": \"\", \"affiliation_03\": \"\", \"data_credit\": | ||
23 | [\"collection\", \"publication\"], \"email\": | 23 | [\"collection\", \"publication\"], \"email\": | ||
24 | \"renske.onstein@idiv.de\", \"given_name\": \"Renske\", | 24 | \"renske.onstein@idiv.de\", \"given_name\": \"Renske\", | ||
25 | \"identifier\": \"0000-0002-2295-3510\", \"name\": \"Onstein\"}, | 25 | \"identifier\": \"0000-0002-2295-3510\", \"name\": \"Onstein\"}, | ||
26 | {\"affiliation\": \"Department of Ecology and Evolutionary Biology, | 26 | {\"affiliation\": \"Department of Ecology and Evolutionary Biology, | ||
27 | Yale University\", \"affiliation_02\": \"\", \"affiliation_03\": \"\", | 27 | Yale University\", \"affiliation_02\": \"\", \"affiliation_03\": \"\", | ||
28 | \"data_credit\": [\"collection\", \"validation\", \"publication\"], | 28 | \"data_credit\": [\"collection\", \"validation\", \"publication\"], | ||
29 | \"email\": \"walter.jetz@yale.edu\", \"given_name\": \"Walter\", | 29 | \"email\": \"walter.jetz@yale.edu\", \"given_name\": \"Walter\", | ||
30 | \"identifier\": \"0000-0002-1971-7277\", \"name\": \"Jetz\"}]", | 30 | \"identifier\": \"0000-0002-1971-7277\", \"name\": \"Jetz\"}]", | ||
31 | "author_email": null, | 31 | "author_email": null, | ||
32 | "creator_user_id": "93fd6aa4-4bae-4c26-9561-c54eb9142d42", | 32 | "creator_user_id": "93fd6aa4-4bae-4c26-9561-c54eb9142d42", | ||
33 | "date": "[{\"date\": \"2020-04-15\", \"date_type\": \"collected\", | 33 | "date": "[{\"date\": \"2020-04-15\", \"date_type\": \"collected\", | ||
34 | \"end_date\": \"2021-09-15\"}]", | 34 | \"end_date\": \"2021-09-15\"}]", | ||
35 | "doi": "", | 35 | "doi": "", | ||
36 | "funding": "[{\"grant_number\": \"310030-188550\", \"institution\": | 36 | "funding": "[{\"grant_number\": \"310030-188550\", \"institution\": | ||
37 | \"Schweizerischer Nationalfonds zur F\u00f6rderung der | 37 | \"Schweizerischer Nationalfonds zur F\u00f6rderung der | ||
38 | Wissenschaftlichen Forschung\", \"institution_url\": \"\"}]", | 38 | Wissenschaftlichen Forschung\", \"institution_url\": \"\"}]", | ||
39 | "groups": [], | 39 | "groups": [], | ||
40 | "id": "b7783edd-a5bc-4854-8e7d-1698afc875b9", | 40 | "id": "b7783edd-a5bc-4854-8e7d-1698afc875b9", | ||
41 | "isopen": false, | 41 | "isopen": false, | ||
42 | "language": "en", | 42 | "language": "en", | ||
43 | "license_id": "wsl-data", | 43 | "license_id": "wsl-data", | ||
44 | "license_title": "WSL Data Policy", | 44 | "license_title": "WSL Data Policy", | ||
45 | "license_url": | 45 | "license_url": | ||
46 | ps://www.wsl.ch/en/about-wsl/programmes-and-initiatives/envidat.html", | 46 | ps://www.wsl.ch/en/about-wsl/programmes-and-initiatives/envidat.html", | ||
47 | "maintainer": "{\"affiliation\": \"WSL / ETH\", \"email\": | 47 | "maintainer": "{\"affiliation\": \"WSL / ETH\", \"email\": | ||
48 | \"loic.pellissier@usys.ethz.ch\", \"given_name\": \"Loic\", | 48 | \"loic.pellissier@usys.ethz.ch\", \"given_name\": \"Loic\", | ||
49 | \"identifier\": \"\", \"name\": \"Pellissier\"}", | 49 | \"identifier\": \"\", \"name\": \"Pellissier\"}", | ||
50 | "maintainer_email": null, | 50 | "maintainer_email": null, | ||
51 | "metadata_created": "2021-09-15T11:44:16.660831", | 51 | "metadata_created": "2021-09-15T11:44:16.660831", | ||
n | 52 | "metadata_modified": "2021-09-15T11:53:49.158807", | n | 52 | "metadata_modified": "2021-09-15T11:54:40.691818", |
53 | "name": "data-from-hagen_etal_pnas", | 53 | "name": "data-from-hagen_etal_pnas", | ||
54 | "notes": "Datasets and R scripts | 54 | "notes": "Datasets and R scripts | ||
n | 55 | \r\n\r\nDatasets\r\n\r\nDataset_S1.csv includes species diversity | n | 55 | \r\n\r\n~~~~~Datasets\r\n\r\nDataset_S1.csv includes species diversity |
56 | counts for 237 clades in tropical moist forests (TMF) in the | 56 | counts for 237 clades in tropical moist forests (TMF) in the | ||
57 | Neotropics (NeotropicalTMF), Indomalaya (IndomalayanTMF), Afrotropics | 57 | Neotropics (NeotropicalTMF), Indomalaya (IndomalayanTMF), Afrotropics | ||
58 | (AfrotropicalTMF), All three TMF regions together (AllTMF), all | 58 | (AfrotropicalTMF), All three TMF regions together (AllTMF), all | ||
59 | non-TMF regions (NonTMF), and in total (Total). As well as whether the | 59 | non-TMF regions (NonTMF), and in total (Total). As well as whether the | ||
60 | clade is pantropical (Pantropical_clade) and shows the pantropical | 60 | clade is pantropical (Pantropical_clade) and shows the pantropical | ||
n | 61 | diversity disparity (PDD_clade). \r\nDataset_S2.csv: environmental and | n | 61 | diversity disparity (PDD_clade). \r\n\r\nDataset_S2.csv: environmental |
62 | species richness data. Longitude (x), latitude (y), potential | 62 | and species richness data. Longitude (x), latitude (y), potential | ||
63 | evapotranspiration (PET), mean annual temperature (MAT), mean annual | 63 | evapotranspiration (PET), mean annual temperature (MAT), mean annual | ||
64 | precipitation), amphibian, bird, mammal, and reptile species richness, | 64 | precipitation), amphibian, bird, mammal, and reptile species richness, | ||
65 | PC1 and PC2 of environmental PCA and the region. Environmental data | 65 | PC1 and PC2 of environmental PCA and the region. Environmental data | ||
66 | (from CHELSA and ENVIREM) and species richness summarised from | 66 | (from CHELSA and ENVIREM) and species richness summarised from | ||
n | 67 | published data (vertLife, MOL, IUCN, GARD).\r\nDataset_S3.csv: - | n | 67 | published data (vertLife, MOL, IUCN, GARD).\r\n\r\nDataset_S3.csv: - |
68 | Paleoenvironmental reconstructions (details in the associated SI | 68 | Paleoenvironmental reconstructions (details in the associated SI | ||
69 | appendix) including latitude (y), longitude (x), and temperature data | 69 | appendix) including latitude (y), longitude (x), and temperature data | ||
n | 70 | across 200 myrs at 170 kyr intervals.\r\nDataset_S4.csv: simulation | n | 70 | across 200 myrs at 170 kyr intervals.\r\n\r\nDataset_S4.csv: |
71 | model parameters and diversity summary statistics. Including rate of | 71 | simulation model parameters and diversity summary statistics. | ||
72 | temperature niche evolution (Tev), temperature niche width (TW), | 72 | Including rate of temperature niche evolution (Tev), temperature niche | ||
73 | divergence threshold (S), Dispersal probability distribution shape | 73 | width (TW), divergence threshold (S), Dispersal probability | ||
74 | (WeibullShape) and information on number of extinct species, number of | 74 | distribution shape (WeibullShape) and information on number of extinct | ||
75 | extant species, total species, Spearman correlation coefficient | 75 | species, number of extant species, total species, Spearman correlation | ||
76 | between absolute latitude and species richness | 76 | coefficient between absolute latitude and species richness | ||
77 | (latitude_richness_cor), and diversity in the Neotropics, Indomalaya, | 77 | (latitude_richness_cor), and diversity in the Neotropics, Indomalaya, | ||
78 | Afrotropics. Also, whether the simulation generated pantropical | 78 | Afrotropics. Also, whether the simulation generated pantropical | ||
79 | distribution of species (pantropicality_index), or the pantropical | 79 | distribution of species (pantropicality_index), or the pantropical | ||
80 | diversity disparity (PDD_index). Finally what time step the simulation | 80 | diversity disparity (PDD_index). Finally what time step the simulation | ||
n | 81 | exited at (0 for complete simulations).\r\nDataset_S5.csv: Net | n | 81 | exited at (0 for complete simulations).\r\n\r\nDataset_S5.csv: Net |
82 | relatedness index (NRI) in three tropical moist forest regions and | 82 | relatedness index (NRI) in three tropical moist forest regions and | ||
83 | associated p-values for pantropically distributed | 83 | associated p-values for pantropically distributed | ||
n | 84 | taxa.\r\n\r\nScripts\r\nGen3sis_config_creator.R and | n | 84 | taxa.\r\n\r\n~~~~~Scripts\r\n\r\nGen3sis_config_creator.R and |
85 | Gen3sis_config_template.R scripts generate the configurations files to | 85 | Gen3sis_config_template.R scripts generate the configurations files to | ||
t | 86 | run the simulation experiment.\r\nGLS.R R script to replicate the | t | 86 | run the simulation experiment.\r\n\r\nGLS.R R script to replicate the |
87 | linear modelling analyses.\r\n\r\n", | 87 | linear modelling analyses.\r\n\r\n", | ||
88 | "num_resources": 5, | 88 | "num_resources": 5, | ||
89 | "num_tags": 5, | 89 | "num_tags": 5, | ||
90 | "organization": { | 90 | "organization": { | ||
91 | "approval_status": "approved", | 91 | "approval_status": "approved", | ||
92 | "created": "2018-12-01T11:42:44.590217", | 92 | "created": "2018-12-01T11:42:44.590217", | ||
93 | "description": "Our laboratory aims at understanding and | 93 | "description": "Our laboratory aims at understanding and | ||
94 | forecasting the response of biodiversity to landscape changes. We | 94 | forecasting the response of biodiversity to landscape changes. We | ||
95 | investigate the historical responses of species to past changes such | 95 | investigate the historical responses of species to past changes such | ||
96 | as plate tectonics or the glaciations of the Quaternary and | 96 | as plate tectonics or the glaciations of the Quaternary and | ||
97 | contemporary responses to ongoing global changes. We develop spatial | 97 | contemporary responses to ongoing global changes. We develop spatial | ||
98 | mechanistic models of biodiversity that account for processes such as | 98 | mechanistic models of biodiversity that account for processes such as | ||
99 | dispersal and biotic interactions.", | 99 | dispersal and biotic interactions.", | ||
100 | "id": "3b0fde83-e15c-4f8b-a451-9778f5309a84", | 100 | "id": "3b0fde83-e15c-4f8b-a451-9778f5309a84", | ||
101 | "image_url": | 101 | "image_url": | ||
102 | ww.ites.ethz.ch/_jcr_content/orgLogo.imageformat.logo.1518520524.jpg", | 102 | ww.ites.ethz.ch/_jcr_content/orgLogo.imageformat.logo.1518520524.jpg", | ||
103 | "is_organization": true, | 103 | "is_organization": true, | ||
104 | "name": "landscape-ecology", | 104 | "name": "landscape-ecology", | ||
105 | "state": "active", | 105 | "state": "active", | ||
106 | "title": "Landscape Ecology", | 106 | "title": "Landscape Ecology", | ||
107 | "type": "organization" | 107 | "type": "organization" | ||
108 | }, | 108 | }, | ||
109 | "owner_org": "3b0fde83-e15c-4f8b-a451-9778f5309a84", | 109 | "owner_org": "3b0fde83-e15c-4f8b-a451-9778f5309a84", | ||
110 | "private": false, | 110 | "private": false, | ||
111 | "publication": "{\"publication_year\": \"2021\", \"publisher\": | 111 | "publication": "{\"publication_year\": \"2021\", \"publisher\": | ||
112 | \"EnviDat\"}", | 112 | \"EnviDat\"}", | ||
113 | "publication_state": "", | 113 | "publication_state": "", | ||
114 | "related_datasets": "", | 114 | "related_datasets": "", | ||
115 | "related_publications": "", | 115 | "related_publications": "", | ||
116 | "relationships_as_object": [], | 116 | "relationships_as_object": [], | ||
117 | "relationships_as_subject": [], | 117 | "relationships_as_subject": [], | ||
118 | "resource_type": "dataset", | 118 | "resource_type": "dataset", | ||
119 | "resource_type_general": "dataset", | 119 | "resource_type_general": "dataset", | ||
120 | "resources": [ | 120 | "resources": [ | ||
121 | { | 121 | { | ||
122 | "cache_last_updated": null, | 122 | "cache_last_updated": null, | ||
123 | "cache_url": null, | 123 | "cache_url": null, | ||
124 | "created": "2021-09-15T11:45:27.749059", | 124 | "created": "2021-09-15T11:45:27.749059", | ||
125 | "description": "Gen3sis_config_creator.R and | 125 | "description": "Gen3sis_config_creator.R and | ||
126 | Gen3sis_config_template.R scripts generate the configurations files to | 126 | Gen3sis_config_template.R scripts generate the configurations files to | ||
127 | run the simulation experiment.", | 127 | run the simulation experiment.", | ||
128 | "doi": "", | 128 | "doi": "", | ||
129 | "format": "R", | 129 | "format": "R", | ||
130 | "hash": "", | 130 | "hash": "", | ||
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136 | "name": "Gen3sis config creator", | 136 | "name": "Gen3sis config creator", | ||
137 | "package_id": "b7783edd-a5bc-4854-8e7d-1698afc875b9", | 137 | "package_id": "b7783edd-a5bc-4854-8e7d-1698afc875b9", | ||
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154 | "created": "2021-09-15T11:48:21.670609", | 154 | "created": "2021-09-15T11:48:21.670609", | ||
155 | "description": "Zip folder containing:\r\n\r\nDataset_S1.csv: | 155 | "description": "Zip folder containing:\r\n\r\nDataset_S1.csv: | ||
156 | includes species diversity counts for 237 clades in tropical moist | 156 | includes species diversity counts for 237 clades in tropical moist | ||
157 | forests (TMF) in the Neotropics (NeotropicalTMF), Indomalaya | 157 | forests (TMF) in the Neotropics (NeotropicalTMF), Indomalaya | ||
158 | (IndomalayanTMF), Afrotropics (AfrotropicalTMF), All three TMF regions | 158 | (IndomalayanTMF), Afrotropics (AfrotropicalTMF), All three TMF regions | ||
159 | together (AllTMF), all non-TMF regions (NonTMF), and in total (Total). | 159 | together (AllTMF), all non-TMF regions (NonTMF), and in total (Total). | ||
160 | As well as whether the clade is pantropical (Pantropical_clade) and | 160 | As well as whether the clade is pantropical (Pantropical_clade) and | ||
161 | shows the pantropical diversity disparity (PDD_clade). | 161 | shows the pantropical diversity disparity (PDD_clade). | ||
162 | \r\nDataset_S2.csv: environmental and species richness data. Longitude | 162 | \r\nDataset_S2.csv: environmental and species richness data. Longitude | ||
163 | (x), latitude (y), potential evapotranspiration (PET), mean annual | 163 | (x), latitude (y), potential evapotranspiration (PET), mean annual | ||
164 | temperature (MAT), mean annual precipitation), amphibian, bird, | 164 | temperature (MAT), mean annual precipitation), amphibian, bird, | ||
165 | mammal, and reptile species richness, PC1 and PC2 of environmental PCA | 165 | mammal, and reptile species richness, PC1 and PC2 of environmental PCA | ||
166 | and the region. Environmental data (from CHELSA and ENVIREM) and | 166 | and the region. Environmental data (from CHELSA and ENVIREM) and | ||
167 | species richness summarised from published data (vertLife, MOL, IUCN, | 167 | species richness summarised from published data (vertLife, MOL, IUCN, | ||
168 | GARD).\r\nDataset_S3.csv: - Paleoenvironmental reconstructions | 168 | GARD).\r\nDataset_S3.csv: - Paleoenvironmental reconstructions | ||
169 | (details in the associated SI appendix) including latitude (y), | 169 | (details in the associated SI appendix) including latitude (y), | ||
170 | longitude (x), and temperature data across 200 myrs at 170 kyr | 170 | longitude (x), and temperature data across 200 myrs at 170 kyr | ||
171 | intervals.\r\nDataset_S4.csv: simulation model parameters and | 171 | intervals.\r\nDataset_S4.csv: simulation model parameters and | ||
172 | diversity summary statistics. Including rate of temperature niche | 172 | diversity summary statistics. Including rate of temperature niche | ||
173 | evolution (Tev), temperature niche width (TW), divergence threshold | 173 | evolution (Tev), temperature niche width (TW), divergence threshold | ||
174 | (S), Dispersal probability distribution shape (WeibullShape) and | 174 | (S), Dispersal probability distribution shape (WeibullShape) and | ||
175 | information on number of extinct species, number of extant species, | 175 | information on number of extinct species, number of extant species, | ||
176 | total species, Spearman correlation coefficient between absolute | 176 | total species, Spearman correlation coefficient between absolute | ||
177 | latitude and species richness (latitude_richness_cor), and diversity | 177 | latitude and species richness (latitude_richness_cor), and diversity | ||
178 | in the Neotropics, Indomalaya, Afrotropics. Also, whether the | 178 | in the Neotropics, Indomalaya, Afrotropics. Also, whether the | ||
179 | simulation generated pantropical distribution of species | 179 | simulation generated pantropical distribution of species | ||
180 | (pantropicality_index), or the pantropical diversity disparity | 180 | (pantropicality_index), or the pantropical diversity disparity | ||
181 | (PDD_index). Finally what time step the simulation exited at (0 for | 181 | (PDD_index). Finally what time step the simulation exited at (0 for | ||
182 | complete simulations).\r\nDataset_S5.csv: Net relatedness index (NRI) | 182 | complete simulations).\r\nDataset_S5.csv: Net relatedness index (NRI) | ||
183 | in three tropical moist forest regions and associated p-values for | 183 | in three tropical moist forest regions and associated p-values for | ||
184 | pantropically distributed taxa.\r\nGen3sis_config_creator.R and | 184 | pantropically distributed taxa.\r\nGen3sis_config_creator.R and | ||
185 | Gen3sis_config_template.R scripts generate the configurations files to | 185 | Gen3sis_config_template.R scripts generate the configurations files to | ||
186 | run the simulation experiment.\r\nGLS.R R script to replicate the | 186 | run the simulation experiment.\r\nGLS.R R script to replicate the | ||
187 | linear modelling analyses.\r\n", | 187 | linear modelling analyses.\r\n", | ||
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242 | "description": "Gen3sis_config_creator.R and | 242 | "description": "Gen3sis_config_creator.R and | ||
243 | Gen3sis_config_template.R scripts generate the configurations files to | 243 | Gen3sis_config_template.R scripts generate the configurations files to | ||
244 | run the simulation experiment.", | 244 | run the simulation experiment.", | ||
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272 | "description": "GLS.R R script to replicate the linear modeling | 272 | "description": "GLS.R R script to replicate the linear modeling | ||
273 | analyses.", | 273 | analyses.", | ||
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301 | "spatial_info": "Switzerland", | 301 | "spatial_info": "Switzerland", | ||
302 | "state": "draft", | 302 | "state": "draft", | ||
303 | "subtitle": "", | 303 | "subtitle": "", | ||
304 | "tags": [ | 304 | "tags": [ | ||
305 | { | 305 | { | ||
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307 | "id": "7fd8733b-4feb-438b-a363-65cb5ce4b52a", | 307 | "id": "7fd8733b-4feb-438b-a363-65cb5ce4b52a", | ||
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324 | "vocabulary_id": null | 324 | "vocabulary_id": null | ||
325 | }, | 325 | }, | ||
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328 | "id": "c1a2995c-32b5-4bb6-9de7-e1f29e697791", | 328 | "id": "c1a2995c-32b5-4bb6-9de7-e1f29e697791", | ||
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338 | "vocabulary_id": null | 338 | "vocabulary_id": null | ||
339 | } | 339 | } | ||
340 | ], | 340 | ], | ||
341 | "title": "Data from: Earth history events shaped the evolution of | 341 | "title": "Data from: Earth history events shaped the evolution of | ||
342 | uneven biodiversity across tropical moist forests", | 342 | uneven biodiversity across tropical moist forests", | ||
343 | "type": "dataset", | 343 | "type": "dataset", | ||
344 | "url": null, | 344 | "url": null, | ||
345 | "version": "1.0" | 345 | "version": "1.0" | ||
346 | } | 346 | } |