Evidence map›Paper›PMID 40316569›Full record

ArticleScientific reports2025

Spatial risk patches of the Indian crested porcupine crop damage in southeastern Iran.

Kamran Almasieh, Alireza Mohammadi

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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.

Kamran AlmasiehDepartment of Nature Engineering, Agricultural Sciences and Natural Resources University of Khuzestan, Mollasani, Iran. almasieh@asnrukh.ac.ir.
Alireza MohammadiDepartment of Environment Science and Engineering, Faculty of Natural Resources, University of Jiroft, Jiroft, Iran.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Human-wildlife conflict (HWC) represent a significant global issue, leading to economic losses for humans due to the destruction of agricultural products and livestock. This study was conducted in southeastern Iran with two primary objectives: to identify the major environmental variables influencing spatial risk modeling and to pinpoint spatial risk patches and hotspots of agricultural damage caused by the Indian crested porcupine (ICP) in this region. An ensemble modeling technique was used to evaluate the spatial risk of agricultural damage caused by the ICP, drawing on 111 independent conflict records and nine environmental factors. The findings indicated that the distance to villages, orchard density, cropland density, and Normalized Difference Vegetation Index emerged as the most significant variables in modeling the spatial risk of crop damage from the ICP in the study region. Nine spatial risk patches, comprising approximately 8% of the study area, were identified for crop damage attributed to the ICP. The three largest spatial risk patches, located in the west of the study area, accounted for 80% of all predicted crop damage patches caused by the ICP. Additionally, hotspots of agricultural damage were clustered in the western part of the study area. Conservation areas covered about 8% of the predicted spatial risk patches and 2.4% of the hotspots of agricultural damage, respectively. Urgent attention is needed to reduce human-ICP conflicts in the identified risk patches. We strongly recommend implementing fencing around cultivated lands and individual tree trunks, as well as enhancing local knowledge and insurance for agricultural products, to mitigate human-ICP conflicts in the study area.

Indexed as

Crops, AgriculturalPorcupinesAgricultureAnimalsConservation of Natural ResourcesHumansIranCrop damageHuman-wildlife conflictsIndian crested PorcupineIranSpatial risk modeling

Identifiers

PMID40316569
PMCPMC12048679

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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.