Evidence map›Paper›PMID 42534499›Full record

ArticleEcology and evolution2026

Species Turnover and Environmental Filtering Structure Plant Communities in Moist Temperate Forests.

Mehreen Samad, Nadeem Ahmad, Adnan Ahmad, Abeer Al-Andal, Adam Khan, Abdul Rahman Osmani, Muhammad Waheed

Abstract read
In one paragraph

Article in Ecology and evolution, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

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0 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Mehreen SamadDepartment of Botany University of Peshawar Peshawar Pakistan.
Nadeem AhmadDepartment of Botany University of Peshawar Peshawar Pakistan.
Adnan AhmadDepartment of Forestry Shaheed Benazir Bhutto University Sheringal Pakistan.
Abeer Al-AndalDepartment of Biology, College of Science King Khalid University Abha Saudi Arabia.
Adam KhanDepartment of Botany University of Lakki Marwat Lakki Marwat Pakistan.
Abdul Rahman OsmaniDepartment of Zoology Kabul University Kabul Afghanistan.
Muhammad WaheedDepartment of Botany, Faculty of Life Sciences University of Okara Okara Pakistan.ORCID https://orcid.org/0000-0003-2773-519X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Montane moist temperate forests are structured by steep elevational and edaphic gradients that drive plant community turnover over short spatial scales. However, integrated evidence linking community structure, diversity, and species turnover to environmental gradients remains limited for the Hindu Kush-Western Himalayan region. This study aimed to characterize plant community organization, quantify alpha and beta diversity, and evaluate vegetation-environment relationships in the moist temperate forests of northern Pakistan. Vegetation was sampled during 2022-2023 across 50 representative stands selected to capture environmental heterogeneity using nested quadrats, and phytosociological attributes were recorded. Soil samples were analyzed for texture and key physicochemical properties. Plant species were grouped into communities, and alpha diversity, beta diversity, and multivariate ordination were applied to examine compositional patterns. A total of 70 plant species were recorded, with herbs and hemicryptophytes representing the dominant growth and life forms. Five distinct plant communities were identified, each defined by significant indicator species. Ordination separated communities clearly, with the first two axes explaining 72.31% of total compositional variation. Alpha diversity was highest in the BRI community and lowest, with greatest dominance, in the QCL community. Beta diversity was driven primarily by species turnover, including complete replacement between high- and low-elevation communities, whereas nestedness was minimal. Communities differed significantly in altitude and soil texture fractions and also varied in pH, electrical conductivity, organic matter, nitrogen, and phosphorus. Community composition was most strongly associated with clay, sand, and slope, while within-community diversity related mainly to soil texture and nutrient availability. These findings demonstrate that environmental filtering promotes strong species replacement across environmental gradients, underscoring the importance of conserving edaphically and topographically heterogeneous habitats.

Indexed as

community assemblydiversityenvironmental gradientsmoist temperate forestsspecies turnover

Identifiers

PMID42534499
PMCPMC13420373

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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.