Details
Original language | English |
---|---|
Article number | e0305731 |
Journal | PLOS ONE |
Volume | 19 |
Issue number | 9 |
Publication status | Published - 27 Sept 2024 |
Abstract
The habitat suitability for pollinators is an important factor for biodiversity and crop-based ecosystem services. Most flowering plants, including wild plants, rely on pollination ecosystem services for fructification and reproduction. Suitable nesting sites and accessible floral food resources are crucial to the abundance of pollinator insects. Therefore, the suitability for pollinators and the pollination service itself are influenced by the type of land use, the composition of the land cover and structures in the landscape. One way to estimate pollinator habitat suitability is to use computer models such as ESTIMAP and InVEST. Both models calculate the habitat suitability based on spatial land use data and their suitability as nesting and feeding habitats. Besides the decision for a model, the selected spatial dataset also has important effects on the modelling results. In Germany, a large number of Land Use and Land Cover (LULC) datasets is available, such as the European CORINE Land Cover, CORINE Urban Atlas, Biotope types, ATKIS or Open Street Map. These datasets differ in terms of spatial and thematic resolutions, LULC types, and abundance of structural elements, which are crucial input factors for modelling with ESTIMAP and InVEST. We applied and tested both models on the basis of two different datasets in the study area Hannover region in central Germany. A literature-based estimation and expert-based questionnaire determined the biophysical properties required for modelling with ESTIMAP and InVEST. The differences between the results based on two different spatial datasets and the differences between the models were estimated and the results that can be obtained by using freely available data were investigated and compared with the results based on non-publicly available data. The comparison of the results shows that the proportion of near-natural structures in the landscape are a decisive factor for modelling results. The comparison of the models shows that ESTIMAP estimates a higher influence of small structures in the landscape than InVEST, resulting in a higher pollinator habitat suitability. The median similarity index of the two models is between 0.68 to 0.93 for the highly detailed biotope type dataset and 0.40 to 0.79 for the less detailed Corine dataset. The results provide a guidance on how to choose the appropriate model and data to assess pollination ecosystem services.
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In: PLOS ONE, Vol. 19, No. 9, e0305731, 27.09.2024.
Research output: Contribution to journal › Article › Research › peer review
}
TY - JOUR
T1 - The influence of model choice and input data on pollinator habitat suitability in the Hannover region
AU - Hinsch, Malte
AU - Groß, Jens
AU - Burkhard, Benjamin
N1 - Publisher Copyright: © 2024 Hinsch et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
PY - 2024/9/27
Y1 - 2024/9/27
N2 - The habitat suitability for pollinators is an important factor for biodiversity and crop-based ecosystem services. Most flowering plants, including wild plants, rely on pollination ecosystem services for fructification and reproduction. Suitable nesting sites and accessible floral food resources are crucial to the abundance of pollinator insects. Therefore, the suitability for pollinators and the pollination service itself are influenced by the type of land use, the composition of the land cover and structures in the landscape. One way to estimate pollinator habitat suitability is to use computer models such as ESTIMAP and InVEST. Both models calculate the habitat suitability based on spatial land use data and their suitability as nesting and feeding habitats. Besides the decision for a model, the selected spatial dataset also has important effects on the modelling results. In Germany, a large number of Land Use and Land Cover (LULC) datasets is available, such as the European CORINE Land Cover, CORINE Urban Atlas, Biotope types, ATKIS or Open Street Map. These datasets differ in terms of spatial and thematic resolutions, LULC types, and abundance of structural elements, which are crucial input factors for modelling with ESTIMAP and InVEST. We applied and tested both models on the basis of two different datasets in the study area Hannover region in central Germany. A literature-based estimation and expert-based questionnaire determined the biophysical properties required for modelling with ESTIMAP and InVEST. The differences between the results based on two different spatial datasets and the differences between the models were estimated and the results that can be obtained by using freely available data were investigated and compared with the results based on non-publicly available data. The comparison of the results shows that the proportion of near-natural structures in the landscape are a decisive factor for modelling results. The comparison of the models shows that ESTIMAP estimates a higher influence of small structures in the landscape than InVEST, resulting in a higher pollinator habitat suitability. The median similarity index of the two models is between 0.68 to 0.93 for the highly detailed biotope type dataset and 0.40 to 0.79 for the less detailed Corine dataset. The results provide a guidance on how to choose the appropriate model and data to assess pollination ecosystem services.
AB - The habitat suitability for pollinators is an important factor for biodiversity and crop-based ecosystem services. Most flowering plants, including wild plants, rely on pollination ecosystem services for fructification and reproduction. Suitable nesting sites and accessible floral food resources are crucial to the abundance of pollinator insects. Therefore, the suitability for pollinators and the pollination service itself are influenced by the type of land use, the composition of the land cover and structures in the landscape. One way to estimate pollinator habitat suitability is to use computer models such as ESTIMAP and InVEST. Both models calculate the habitat suitability based on spatial land use data and their suitability as nesting and feeding habitats. Besides the decision for a model, the selected spatial dataset also has important effects on the modelling results. In Germany, a large number of Land Use and Land Cover (LULC) datasets is available, such as the European CORINE Land Cover, CORINE Urban Atlas, Biotope types, ATKIS or Open Street Map. These datasets differ in terms of spatial and thematic resolutions, LULC types, and abundance of structural elements, which are crucial input factors for modelling with ESTIMAP and InVEST. We applied and tested both models on the basis of two different datasets in the study area Hannover region in central Germany. A literature-based estimation and expert-based questionnaire determined the biophysical properties required for modelling with ESTIMAP and InVEST. The differences between the results based on two different spatial datasets and the differences between the models were estimated and the results that can be obtained by using freely available data were investigated and compared with the results based on non-publicly available data. The comparison of the results shows that the proportion of near-natural structures in the landscape are a decisive factor for modelling results. The comparison of the models shows that ESTIMAP estimates a higher influence of small structures in the landscape than InVEST, resulting in a higher pollinator habitat suitability. The median similarity index of the two models is between 0.68 to 0.93 for the highly detailed biotope type dataset and 0.40 to 0.79 for the less detailed Corine dataset. The results provide a guidance on how to choose the appropriate model and data to assess pollination ecosystem services.
UR - http://www.scopus.com/inward/record.url?scp=85205275556&partnerID=8YFLogxK
U2 - 10.1371/journal.pone.0305731
DO - 10.1371/journal.pone.0305731
M3 - Article
C2 - 39331684
AN - SCOPUS:85205275556
VL - 19
JO - PLOS ONE
JF - PLOS ONE
SN - 1932-6203
IS - 9
M1 - e0305731
ER -