Evidence map›Paper›PMID 39336630›Full record

ArticleInsects2024

Spatial Modeling of Insect Pollination Services in Fragmented Landscapes.

Ehsan Rahimi, Chuleui Jung

Abstract read
In one paragraph

Article in Insects, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Ehsan RahimiAgricultural Science and Technology Institute, Andong National University, Andong 36729, Republic of Korea.ORCID 0000-0002-8401-472X
Chuleui JungAgricultural Science and Technology Institute, Andong National University, Andong 36729, Republic of Korea.ORCID 0000-0001-8134-9279

Funding

National Research Foundation of Korea NRF-2018R1A6A1A03024862RDA Korea RS-2023-00232847
6 · The paper itself

Abstract

Pollination mapping and modeling have opened new avenues for comprehending the intricate interactions between pollinators, their habitats, and the plants they pollinate. While the Lonsdorf model has been extensively employed in pollination mapping within previous studies, its conceptualization of bee movement in agricultural landscapes presents notable limitations. Consequently, a gap exists in exploring the effects of forest fragmentation on pollination once these constraints are addressed. In this study, our objective is to model pollination dynamics in fragmented forest landscapes using a modified version of the Lonsdorf model, which operates as a distance-based model. Initially, we generated several simulated agricultural landscapes, incorporating forested and agricultural habitats with varying forest proportions ranging from 10% to 50%, along with a range of fragmentation degrees from low to high. Subsequently, employing the modified Lonsdorf model, we evaluated the nesting suitability and consequent pollination supply capacity across these diverse scenarios. We found that as the degree of forest fragmentation increases, resulting in smaller and more isolated patches with less aggregation, the pollination services within landscapes tend to become enhanced. In conclusion, our research suggests that landscapes exhibiting fragmented forest patch patterns generally display greater nesting suitability due to increased floral resources in their vicinity. These findings highlight the importance of employing varied models for pollination mapping, as modifications to the Lonsdorf model yield distinct outcomes compared to studies using the original version.

Indexed as

forest patchesfragmented landscapesinsect pollinatorslandscape metricsLonsdorf modelpollination services

Identifiers

PMID39336630
PMCPMC11432557

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.