Changes
On June 2, 2023 at 8:20:01 AM UTC, kennedysenagi:
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Changed title to Insect diversity can predict biodiversity status in Africa (previously Measuring insect-based biodiversity status in Africa)
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Updated description of Insect diversity can predict biodiversity status in Africa from
This work describes a straightforward metric to measure biodiversity status measuring insect data.Here we combine a new index on the absence of human impacts with scale appropriate (in time and space) biodiversity richness information. Our metric does not rely on expert opinions and ecosystem-based biodiversity assessments. The metric can be practically implemented and is replicable given the availability of open access Earth Observation and citizen-science-based species occurrence data.
toReliable metrics to monitor human impacts on biodiversity are essential for informing conservation policy. As insects are indicators of global change, whose declines profoundly affect ecosystems, insect diversity may predict biodiversity status. Here we present an unbiased and straightforward biodiversity status metric based on insect diversity (richness) and landscape naturalness. Insect diversity was estimated using spatially explicit earth observation data and insect species assemblages across microhabitats in two agro-ecological zones in Africa. Landscape naturalness was estimated using various human impact factors. Biodiversity status values differed considerably (p < 0.05) between protected and non-protected areas, while protected areas, regardless of agro-ecology, shared similar biodiversity status values. The metric is consistent when using richness from different indicator taxa (i.e., stingless bees, butterflies, dragonflies) and independent data for landscape naturalness. Our biodiversity status metric is applicable to data-scarce environments and practical for conservation actions and reporting the status of biodiversity targets.
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2 | "acknowledgement": "", | 2 | "acknowledgement": "", | ||
3 | "administrative_areas": "Western region Kenya, St Lucia region South | 3 | "administrative_areas": "Western region Kenya, St Lucia region South | ||
4 | Africa", | 4 | Africa", | ||
5 | "author": null, | 5 | "author": null, | ||
6 | "author_email": null, | 6 | "author_email": null, | ||
7 | "citation_narrative": "", | 7 | "citation_narrative": "", | ||
8 | "collaborators": "[{\"collaborator\": \"Tobias Landmann\"}, | 8 | "collaborators": "[{\"collaborator\": \"Tobias Landmann\"}, | ||
9 | {\"collaborator\": \"Michael Schmitt\"}, {\"collaborator\": \"Burak | 9 | {\"collaborator\": \"Michael Schmitt\"}, {\"collaborator\": \"Burak | ||
10 | Ekim\"}, {\"collaborator\": \"Jandouwe Villinger\"}, | 10 | Ekim\"}, {\"collaborator\": \"Jandouwe Villinger\"}, | ||
11 | {\"collaborator\": \"Faith Ashiono\"}, {\"collaborator\": \" Jan C. | 11 | {\"collaborator\": \"Faith Ashiono\"}, {\"collaborator\": \" Jan C. | ||
12 | Habel\"}, {\"collaborator\": \"Henri E.Z. Tonnang\"}]", | 12 | Habel\"}, {\"collaborator\": \"Henri E.Z. Tonnang\"}]", | ||
13 | "contact_person": "Tobias Landmann", | 13 | "contact_person": "Tobias Landmann", | ||
14 | "contact_person_email": "tlandmann@icipe.org", | 14 | "contact_person_email": "tlandmann@icipe.org", | ||
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25 | "maintainer": "Kennedy Senagi", | 25 | "maintainer": "Kennedy Senagi", | ||
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29 | "name": "measuring-insect-based-biodiversity-status-in-africa", | 29 | "name": "measuring-insect-based-biodiversity-status-in-africa", | ||
n | 30 | "notes": "This work describes a straightforward metric to measure | n | 30 | "notes": "Reliable metrics to monitor human impacts on biodiversity |
31 | biodiversity status measuring insect data.Here we combine a new index | 31 | are essential for informing conservation policy. As insects are | ||
32 | on the absence of human impacts with scale appropriate (in time and | 32 | indicators of global change, whose declines profoundly affect | ||
33 | space) biodiversity richness information. Our metric does not rely on | 33 | ecosystems, insect diversity may predict biodiversity status. Here we | ||
34 | expert opinions and ecosystem-based biodiversity assessments. The | 34 | present an unbiased and straightforward biodiversity status metric | ||
35 | metric can be practically implemented and is replicable given the | 35 | based on insect diversity (richness) and landscape naturalness. Insect | ||
36 | availability of open access Earth Observation and | 36 | diversity was estimated using spatially explicit earth observation | ||
37 | citizen-science-based species occurrence data.", | 37 | data and insect species assemblages across microhabitats in two | ||
38 | agro-ecological zones in Africa. Landscape naturalness was estimated | ||||
39 | using various human impact factors. Biodiversity status values | ||||
40 | differed considerably (p < 0.05) between protected and non-protected | ||||
41 | areas, while protected areas, regardless of agro-ecology, shared | ||||
42 | similar biodiversity status values. The metric is consistent when | ||||
43 | using richness from different indicator taxa (i.e., stingless bees, | ||||
44 | butterflies, dragonflies) and independent data for landscape | ||||
45 | naturalness. Our biodiversity status metric is applicable to | ||||
46 | data-scarce environments and practical for conservation actions and | ||||
47 | reporting the status of biodiversity targets.", | ||||
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487 | { | 497 | { | ||
488 | "display_name": "spectral transformation", | 498 | "display_name": "spectral transformation", | ||
489 | "id": "f36edeeb-fb38-40ff-b5da-f78da4aef7da", | 499 | "id": "f36edeeb-fb38-40ff-b5da-f78da4aef7da", | ||
490 | "name": "spectral transformation", | 500 | "name": "spectral transformation", | ||
491 | "state": "active", | 501 | "state": "active", | ||
492 | "vocabulary_id": null | 502 | "vocabulary_id": null | ||
493 | } | 503 | } | ||
494 | ], | 504 | ], | ||
495 | "third_party": "no", | 505 | "third_party": "no", | ||
t | 496 | "title": "Measuring insect-based biodiversity status in Africa", | t | 506 | "title": "Insect diversity can predict biodiversity status in |
507 | Africa", | ||||
497 | "type": "dataset", | 508 | "type": "dataset", | ||
498 | "url": null, | 509 | "url": null, | ||
499 | "version": null | 510 | "version": null | ||
500 | } | 511 | } |