InsectChange: Comment
The InsectChange database (van Klink et al. 2021) underlying the meta-analysis by van Klink et al. (2020a) compiles worldwide time series of the abundance and biomass of invertebrates reported as insects and arachnids, as well as ecological data likely to have influenced the observed trends. On the...
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| Format: | Article |
| Language: | English |
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2024-10-01
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| Series: | Peer Community Journal |
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| Online Access: | https://peercommunityjournal.org/articles/10.24072/pcjournal.469/ |
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| author | Gaume, Laurence Desquilbet, Marion |
| author_facet | Gaume, Laurence Desquilbet, Marion |
| author_sort | Gaume, Laurence |
| collection | DOAJ |
| description | The InsectChange database (van Klink et al. 2021) underlying the meta-analysis by van Klink et al. (2020a) compiles worldwide time series of the abundance and biomass of invertebrates reported as insects and arachnids, as well as ecological data likely to have influenced the observed trends. On the basis of a comprehensive review of the original studies, we highlight numerous issues in this database, such as errors in insect counts, sampling biases, inclusion of noninsects driving assemblage trends, omission of drivers investigated in original studies and inaccurate assessment of local cropland cover. We show that in more than half of the original studies, the factors investigated were experimentally manipulated or were strong -often not natural- disturbances. These internal drivers created situations more frequently favouring an increase than a decrease in insects and were unlikely to be representative of habitat conditions worldwide. We demonstrate that when both groups were available in original freshwater studies, selecting all invertebrates rather than only insects led to an overestimation of the “insect” trend. We argue that the disparate and non-standardised units of measurement of insect density among studies may have detrimental consequences for users, as was the case for van Klink et al. (2020a, 2022) who log10(x+1)-transformed these heterogeneous data, compromising the comparison of temporal trends between datasets and the estimation of the overall trend. We show that geographical coordinates assigned by InsectChange to insect sampling areas are inadequate for the analysis of the local influence of agriculture, urbanisation and climate on insect change for 68% of the datasets. In terrestrial data, the local cropland cover is strongly overestimated, which may incorrectly dismiss agriculture as a driving force behind the decline in insects. Therefore, in its current state, this database enables the study of neither the temporal trends of insects worldwide nor their drivers. The supplementary information accompanying our paper presents in detail each problem identified and makes numerous suggestions that can be used as a basis for improvement. |
| format | Article |
| id | doaj-art-07d33b7ea7b1456a81ba6617223dd5bb |
| institution | Kabale University |
| issn | 2804-3871 |
| language | English |
| publishDate | 2024-10-01 |
| publisher | Peer Community In |
| record_format | Article |
| series | Peer Community Journal |
| spelling | doaj-art-07d33b7ea7b1456a81ba6617223dd5bb2025-02-07T10:17:17ZengPeer Community InPeer Community Journal2804-38712024-10-01410.24072/pcjournal.46910.24072/pcjournal.469InsectChange: Comment Gaume, Laurence0https://orcid.org/0000-0001-7647-7321Desquilbet, Marion1https://orcid.org/0000-0003-2514-4353AMAP, University of Montpellier, CNRS, CIRAD, INRAE, IRD, Montpellier, FranceToulouse School of Economics, INRAE, University of Toulouse Capitole, Toulouse, FranceThe InsectChange database (van Klink et al. 2021) underlying the meta-analysis by van Klink et al. (2020a) compiles worldwide time series of the abundance and biomass of invertebrates reported as insects and arachnids, as well as ecological data likely to have influenced the observed trends. On the basis of a comprehensive review of the original studies, we highlight numerous issues in this database, such as errors in insect counts, sampling biases, inclusion of noninsects driving assemblage trends, omission of drivers investigated in original studies and inaccurate assessment of local cropland cover. We show that in more than half of the original studies, the factors investigated were experimentally manipulated or were strong -often not natural- disturbances. These internal drivers created situations more frequently favouring an increase than a decrease in insects and were unlikely to be representative of habitat conditions worldwide. We demonstrate that when both groups were available in original freshwater studies, selecting all invertebrates rather than only insects led to an overestimation of the “insect” trend. We argue that the disparate and non-standardised units of measurement of insect density among studies may have detrimental consequences for users, as was the case for van Klink et al. (2020a, 2022) who log10(x+1)-transformed these heterogeneous data, compromising the comparison of temporal trends between datasets and the estimation of the overall trend. We show that geographical coordinates assigned by InsectChange to insect sampling areas are inadequate for the analysis of the local influence of agriculture, urbanisation and climate on insect change for 68% of the datasets. In terrestrial data, the local cropland cover is strongly overestimated, which may incorrectly dismiss agriculture as a driving force behind the decline in insects. Therefore, in its current state, this database enables the study of neither the temporal trends of insects worldwide nor their drivers. The supplementary information accompanying our paper presents in detail each problem identified and makes numerous suggestions that can be used as a basis for improvement.https://peercommunityjournal.org/articles/10.24072/pcjournal.469/Insects, Terrestrial invertebrates, Freshwater invertebrates, Insect abundance trends, Insect decline, Time series meta-analysis, Methodological biases, Agriculture, Landcover analysis, Ecological data, Database quality assessment |
| spellingShingle | Gaume, Laurence Desquilbet, Marion InsectChange: Comment Peer Community Journal Insects, Terrestrial invertebrates, Freshwater invertebrates, Insect abundance trends, Insect decline, Time series meta-analysis, Methodological biases, Agriculture, Landcover analysis, Ecological data, Database quality assessment |
| title | InsectChange: Comment
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| title_full | InsectChange: Comment
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| title_fullStr | InsectChange: Comment
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| title_full_unstemmed | InsectChange: Comment
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| title_short | InsectChange: Comment
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| title_sort | insectchange comment |
| topic | Insects, Terrestrial invertebrates, Freshwater invertebrates, Insect abundance trends, Insect decline, Time series meta-analysis, Methodological biases, Agriculture, Landcover analysis, Ecological data, Database quality assessment |
| url | https://peercommunityjournal.org/articles/10.24072/pcjournal.469/ |
| work_keys_str_mv | AT gaumelaurence insectchangecomment AT desquilbetmarion insectchangecomment |