Changes
On May 15, 2023 at 9:02:12 AM UTC, Klaus Ecker:
-
Updated description of R script and input data for "ALL-EMA sampling design" from
License: GPL-v2 The R script illustrates an avanced sampling approach for monitoring biodiversity on agricultural land by combining multiple objectives and integrating environmental and geographic space for optimal estimation efficiency. In doing so, the R script demonstrates the first-stage selection of squares (km2) in the ALL-EMA sampling design using modern sampling techniques such as unequal probability sampling with fixed sample size, balanced sampling, stratified balancing and geographic spreading. Sampling is done with unequal probabilities and weights defined by power allocation to give equal weight to extrapolations to the total agricultural area of Switzerland and two stratifications of predefined interest (regions and agricultural production zones). Calibration is used to limit the distribution of the sampling weights. The sample sizes are almost fixed within the strata and evenly distibuted across the years of a temporal rotation plan, which is favourable for the organisation of the field survey. Sampling also ensures an optimal (annual) distribution across geographic space, including altitude. Despite the complexity of the sampling, estimation based on probability theory is straightforward. Ecker, K., Meier, E. & Tillé, Y. review. Integrating spatial and ecological information into comprehensive biodiversity monitoring on agricultural land. Environmental Monitoring and Assessment.
toLicense: GPL-v2 The R script presents an advanced sampling approach for monitoring biodiversity on agricultural land by combining multiple objectives and integrating environmental and geographic space. The example demonstrates the first-stage selection of squares (km2) in the ALL-EMA sampling design using modern sampling techniques such as unequal probability sampling with fixed sample size, balanced sampling, stratified balancing and geographic spreading. Sampling is done with unequal probabilities and weights defined by power allocation to give equal weight to extrapolations to the total agricultural area of Switzerland and two stratifications of predefined interest (regions and agricultural production zones). Calibration is used to limit the distribution of the sampling weights. The sample sizes are almost fixed within the strata and evenly distributed across the years of a temporal rotation plan, which is favourable for the organisation of the field survey. Sampling also ensures an optimal (annual) distribution across geographic space, including altitude. Despite the complexity of the sampling, estimation based on probability theory is straightforward. Ecker, K., Meier, E. & Tillé, Y. review. Integrating spatial and ecological information into comprehensive biodiversity monitoring on agricultural land. Environmental Monitoring and Assessment.
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2 | "author": "[{\"affiliation\": \"WSL\", \"affiliation_02\": \"\", | 2 | "author": "[{\"affiliation\": \"WSL\", \"affiliation_02\": \"\", | ||
3 | \"affiliation_03\": \"\", \"data_credit\": [\"software\", | 3 | \"affiliation_03\": \"\", \"data_credit\": [\"software\", | ||
4 | \"publication\"], \"email\": \"klaus.ecker@wsl.ch\", \"given_name\": | 4 | \"publication\"], \"email\": \"klaus.ecker@wsl.ch\", \"given_name\": | ||
5 | \"Klaus\", \"identifier\": \"0000-0003-3388-1353\", \"name\": | 5 | \"Klaus\", \"identifier\": \"0000-0003-3388-1353\", \"name\": | ||
6 | \"Ecker\"}, {\"affiliation\": \"Institute of Statistics, University of | 6 | \"Ecker\"}, {\"affiliation\": \"Institute of Statistics, University of | ||
7 | Neuchatel\", \"affiliation_02\": \"\", \"affiliation_03\": \"\", | 7 | Neuchatel\", \"affiliation_02\": \"\", \"affiliation_03\": \"\", | ||
8 | \"data_credit\": [\"software\", \"publication\", \"supervision\"], | 8 | \"data_credit\": [\"software\", \"publication\", \"supervision\"], | ||
9 | \"email\": \"yves.tille@unine.ch\", \"given_name\": \"Yves\", | 9 | \"email\": \"yves.tille@unine.ch\", \"given_name\": \"Yves\", | ||
10 | \"identifier\": \"0000-0003-0904-5523\", \"name\": \"Till\\u00e9\"}]", | 10 | \"identifier\": \"0000-0003-0904-5523\", \"name\": \"Till\\u00e9\"}]", | ||
11 | "author_email": null, | 11 | "author_email": null, | ||
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13 | "date": "[{\"date\": \"2023-11-05\", \"date_type\": \"created\", | 13 | "date": "[{\"date\": \"2023-11-05\", \"date_type\": \"created\", | ||
14 | \"end_date\": \"\"}]", | 14 | \"end_date\": \"\"}]", | ||
15 | "doi": "10.16904/envidat.402", | 15 | "doi": "10.16904/envidat.402", | ||
16 | "funding": "[{\"grant_number\": \"\", \"institution\": \"FOEN\", | 16 | "funding": "[{\"grant_number\": \"\", \"institution\": \"FOEN\", | ||
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22 | "license_id": "other-undefined", | 22 | "license_id": "other-undefined", | ||
23 | "license_title": "Other (Specified in the description)", | 23 | "license_title": "Other (Specified in the description)", | ||
24 | "maintainer": "{\"affiliation\": \"WSL\", \"email\": | 24 | "maintainer": "{\"affiliation\": \"WSL\", \"email\": | ||
25 | \"klaus.ecker@wsl.ch\", \"given_name\": \"Klaus\", \"identifier\": | 25 | \"klaus.ecker@wsl.ch\", \"given_name\": \"Klaus\", \"identifier\": | ||
26 | \"0000-0003-3388-1353\", \"name\": \"Ecker\"}", | 26 | \"0000-0003-3388-1353\", \"name\": \"Ecker\"}", | ||
27 | "maintainer_email": null, | 27 | "maintainer_email": null, | ||
28 | "metadata_created": "2023-05-11T14:32:34.812518", | 28 | "metadata_created": "2023-05-11T14:32:34.812518", | ||
n | 29 | "metadata_modified": "2023-05-15T08:54:42.497967", | n | 29 | "metadata_modified": "2023-05-15T09:02:12.843701", |
30 | "name": "r-script-first-stage-sampling", | 30 | "name": "r-script-first-stage-sampling", | ||
n | 31 | "notes": "License: GPL-v2\r\n\r\nThe R script illustrates an avanced | n | 31 | "notes": "License: GPL-v2\r\n\r\nThe R script presents an advanced |
32 | sampling approach for monitoring biodiversity on agricultural land by | 32 | sampling approach for monitoring biodiversity on agricultural land by | ||
33 | combining multiple objectives and integrating environmental and | 33 | combining multiple objectives and integrating environmental and | ||
t | 34 | geographic space for optimal estimation efficiency.\r\n\r\nIn doing | t | 34 | geographic space.\r\n\r\nThe example demonstrates the first-stage |
35 | so, the R script demonstrates the first-stage selection of squares | 35 | selection of squares (km2) in the ALL-EMA sampling design using modern | ||
36 | (km2) in the ALL-EMA sampling design using modern sampling techniques | 36 | sampling techniques such as unequal probability sampling with fixed | ||
37 | such as unequal probability sampling with fixed sample size, balanced | 37 | sample size, balanced sampling, stratified balancing and geographic | ||
38 | sampling, stratified balancing and geographic spreading. Sampling is | 38 | spreading. Sampling is done with unequal probabilities and weights | ||
39 | done with unequal probabilities and weights defined by power | ||||
40 | allocation to give equal weight to extrapolations to the total | 39 | defined by power allocation to give equal weight to extrapolations to | ||
41 | agricultural area of Switzerland and two stratifications of predefined | 40 | the total agricultural area of Switzerland and two stratifications of | ||
42 | interest (regions and agricultural production zones). Calibration is | 41 | predefined interest (regions and agricultural production zones). | ||
43 | used to limit the distribution of the sampling weights. The sample | 42 | Calibration is used to limit the distribution of the sampling weights. | ||
44 | sizes are almost fixed within the strata and evenly distibuted across | 43 | The sample sizes are almost fixed within the strata and evenly | ||
45 | the years of a temporal rotation plan, which is favourable for the | 44 | distributed across the years of a temporal rotation plan, which is | ||
46 | organisation of the field survey. Sampling also ensures an optimal | 45 | favourable for the organisation of the field survey. Sampling also | ||
47 | (annual) distribution across geographic space, including altitude. | 46 | ensures an optimal (annual) distribution across geographic space, | ||
48 | Despite the complexity of the sampling, estimation based on | 47 | including altitude. Despite the complexity of the sampling, estimation | ||
49 | probability theory is straightforward.\r\n\r\nEcker, K., Meier, E. & | 48 | based on probability theory is straightforward.\r\n\r\n\r\nEcker, K., | ||
50 | Till\u00e9, Y. review. Integrating spatial and ecological information | 49 | Meier, E. & Till\u00e9, Y. review. Integrating spatial and ecological | ||
51 | into comprehensive biodiversity monitoring on agricultural land. | 50 | information into comprehensive biodiversity monitoring on agricultural | ||
52 | Environmental Monitoring and Assessment.\r\n", | 51 | land. Environmental Monitoring and Assessment.\r\n", | ||
53 | "num_resources": 2, | 52 | "num_resources": 2, | ||
54 | "num_tags": 5, | 53 | "num_tags": 5, | ||
55 | "organization": { | 54 | "organization": { | ||
56 | "approval_status": "approved", | 55 | "approval_status": "approved", | ||
57 | "created": "2018-07-18T11:14:04.773731", | 56 | "created": "2018-07-18T11:14:04.773731", | ||
58 | "description": "We assess and analyse the state of different | 57 | "description": "We assess and analyse the state of different | ||
59 | habitat types and their ecological changes with a particular focus on | 58 | habitat types and their ecological changes with a particular focus on | ||
60 | the habitats of national importance of Switzerland. We concentrate on | 59 | the habitats of national importance of Switzerland. We concentrate on | ||
61 | ecological changes and their causes in different ecosystems and | 60 | ecological changes and their causes in different ecosystems and | ||
62 | habitat types of Switzerland. We are especially interested in the | 61 | habitat types of Switzerland. We are especially interested in the | ||
63 | effects of different management systems, nutrient input, land-use | 62 | effects of different management systems, nutrient input, land-use | ||
64 | change (e.g. intensification, abandonment), habitat fragmentation as | 63 | change (e.g. intensification, abandonment), habitat fragmentation as | ||
65 | well as climate change on ecosystem state. We base our research on | 64 | well as climate change on ecosystem state. We base our research on | ||
66 | systematically assessed floristic and faunistic biodiversity-data, | 65 | systematically assessed floristic and faunistic biodiversity-data, | ||
67 | modelling and remote sensing information.\r\n\r\nWe strongly engage in | 66 | modelling and remote sensing information.\r\n\r\nWe strongly engage in | ||
68 | the monitoring and evaluation of qualitative and quantitative changes | 67 | the monitoring and evaluation of qualitative and quantitative changes | ||
69 | in natural or semi-natural habitats of Switzerland as a basis for | 68 | in natural or semi-natural habitats of Switzerland as a basis for | ||
70 | decision-making in policy and applied nature conservation. In the | 69 | decision-making in policy and applied nature conservation. In the | ||
71 | project \"Effectiveness of Habitat Protection in Switzerland\", | 70 | project \"Effectiveness of Habitat Protection in Switzerland\", | ||
72 | commissioned by the Federal Office of Environment BAFU, we concentrate | 71 | commissioned by the Federal Office of Environment BAFU, we concentrate | ||
73 | on the habitats of national importance (raised bogs, transitional | 72 | on the habitats of national importance (raised bogs, transitional | ||
74 | mires and fens, dry meadows, alluvial zones and amphibian spawning | 73 | mires and fens, dry meadows, alluvial zones and amphibian spawning | ||
75 | areas), i.e. the \"crown jewelry\" of Swiss nature reserves. Moreover, | 74 | areas), i.e. the \"crown jewelry\" of Swiss nature reserves. Moreover, | ||
76 | we share our knowledge on mire protection through consulting | 75 | we share our knowledge on mire protection through consulting | ||
77 | activities for the national government and the cantons.", | 76 | activities for the national government and the cantons.", | ||
78 | "id": "0ee5727f-9228-464f-b4c2-a7399e702be2", | 77 | "id": "0ee5727f-9228-464f-b4c2-a7399e702be2", | ||
79 | "image_url": | 78 | "image_url": | ||
80 | "https://upload.wikimedia.org/wikipedia/de/9/94/Logo_WSL.svg", | 79 | "https://upload.wikimedia.org/wikipedia/de/9/94/Logo_WSL.svg", | ||
81 | "is_organization": true, | 80 | "is_organization": true, | ||
82 | "name": "ecosystems-dynamics", | 81 | "name": "ecosystems-dynamics", | ||
83 | "state": "active", | 82 | "state": "active", | ||
84 | "title": "Ecosystems Dynamics", | 83 | "title": "Ecosystems Dynamics", | ||
85 | "type": "organization" | 84 | "type": "organization" | ||
86 | }, | 85 | }, | ||
87 | "owner_org": "0ee5727f-9228-464f-b4c2-a7399e702be2", | 86 | "owner_org": "0ee5727f-9228-464f-b4c2-a7399e702be2", | ||
88 | "private": false, | 87 | "private": false, | ||
89 | "publication": "{\"publication_year\": \"2023\", \"publisher\": | 88 | "publication": "{\"publication_year\": \"2023\", \"publisher\": | ||
90 | \"EnviDat\"}", | 89 | \"EnviDat\"}", | ||
91 | "publication_state": "published", | 90 | "publication_state": "published", | ||
92 | "related_datasets": "", | 91 | "related_datasets": "", | ||
93 | "related_publications": "", | 92 | "related_publications": "", | ||
94 | "relationships_as_object": [], | 93 | "relationships_as_object": [], | ||
95 | "relationships_as_subject": [], | 94 | "relationships_as_subject": [], | ||
96 | "resource_type": "dataset", | 95 | "resource_type": "dataset", | ||
97 | "resource_type_general": "dataset", | 96 | "resource_type_general": "dataset", | ||
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140 | "name": "R script", | 139 | "name": "R script", | ||
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156 | "spatial": "{\"type\": \"Polygon\", \"coordinates\": [[[5.95587, | 155 | "spatial": "{\"type\": \"Polygon\", \"coordinates\": [[[5.95587, | ||
157 | 45.81802],[5.95587, 47.80838],[10.49203, 47.80838],[10.49203, | 156 | 45.81802],[5.95587, 47.80838],[10.49203, 47.80838],[10.49203, | ||
158 | 45.81802],[5.95587, 45.81802]]]}", | 157 | 45.81802],[5.95587, 45.81802]]]}", | ||
159 | "spatial_info": "Switzerland", | 158 | "spatial_info": "Switzerland", | ||
160 | "state": "active", | 159 | "state": "active", | ||
161 | "subtitle": "", | 160 | "subtitle": "", | ||
162 | "tags": [ | 161 | "tags": [ | ||
163 | { | 162 | { | ||
164 | "display_name": "BALANCED SAMPLING", | 163 | "display_name": "BALANCED SAMPLING", | ||
165 | "id": "64aaea7f-cd25-4c75-a37b-bc4c342510d6", | 164 | "id": "64aaea7f-cd25-4c75-a37b-bc4c342510d6", | ||
166 | "name": "BALANCED SAMPLING", | 165 | "name": "BALANCED SAMPLING", | ||
167 | "state": "active", | 166 | "state": "active", | ||
168 | "vocabulary_id": null | 167 | "vocabulary_id": null | ||
169 | }, | 168 | }, | ||
170 | { | 169 | { | ||
171 | "display_name": "HABITAT", | 170 | "display_name": "HABITAT", | ||
172 | "id": "af968922-763a-4f34-b156-a33745dc1852", | 171 | "id": "af968922-763a-4f34-b156-a33745dc1852", | ||
173 | "name": "HABITAT", | 172 | "name": "HABITAT", | ||
174 | "state": "active", | 173 | "state": "active", | ||
175 | "vocabulary_id": null | 174 | "vocabulary_id": null | ||
176 | }, | 175 | }, | ||
177 | { | 176 | { | ||
178 | "display_name": "MULTI-STAGE", | 177 | "display_name": "MULTI-STAGE", | ||
179 | "id": "0104f31b-7abc-425e-b5b2-e892c24113a3", | 178 | "id": "0104f31b-7abc-425e-b5b2-e892c24113a3", | ||
180 | "name": "MULTI-STAGE", | 179 | "name": "MULTI-STAGE", | ||
181 | "state": "active", | 180 | "state": "active", | ||
182 | "vocabulary_id": null | 181 | "vocabulary_id": null | ||
183 | }, | 182 | }, | ||
184 | { | 183 | { | ||
185 | "display_name": "UNEQUAL PROBABILITY", | 184 | "display_name": "UNEQUAL PROBABILITY", | ||
186 | "id": "ab7374b6-8cb8-4394-b06e-ce172c867317", | 185 | "id": "ab7374b6-8cb8-4394-b06e-ce172c867317", | ||
187 | "name": "UNEQUAL PROBABILITY", | 186 | "name": "UNEQUAL PROBABILITY", | ||
188 | "state": "active", | 187 | "state": "active", | ||
189 | "vocabulary_id": null | 188 | "vocabulary_id": null | ||
190 | }, | 189 | }, | ||
191 | { | 190 | { | ||
192 | "display_name": "VEGETATION", | 191 | "display_name": "VEGETATION", | ||
193 | "id": "d2f171f0-87f1-4e4a-aa7d-535d103ce617", | 192 | "id": "d2f171f0-87f1-4e4a-aa7d-535d103ce617", | ||
194 | "name": "VEGETATION", | 193 | "name": "VEGETATION", | ||
195 | "state": "active", | 194 | "state": "active", | ||
196 | "vocabulary_id": null | 195 | "vocabulary_id": null | ||
197 | } | 196 | } | ||
198 | ], | 197 | ], | ||
199 | "title": "R script and input data for \"ALL-EMA sampling design\"", | 198 | "title": "R script and input data for \"ALL-EMA sampling design\"", | ||
200 | "type": "dataset", | 199 | "type": "dataset", | ||
201 | "url": null, | 200 | "url": null, | ||
202 | "version": "1.0" | 201 | "version": "1.0" | ||
203 | } | 202 | } |