Evidence map›Paper›PMID 37529586›Full record

ArticleEcology and evolution2023

Nonparametric assessment of mangrove ecosystem in the context of coastal resilience in Ghana.

Daniel Aja, Michael Miyittah, Donatus Bapentire Angnuureng

Abstract read
In one paragraph

Article in Ecology and evolution, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
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

The trial behind it

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3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

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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

3 authors.

Daniel AjaAfrica Center of Excellence in Coastal Resilience, Center for Coastal Management University of Cape Coast Cape Coast Ghana.ORCID https://orcid.org/0000-0002-8849-381X
Michael MiyittahAfrica Center of Excellence in Coastal Resilience, Center for Coastal Management University of Cape Coast Cape Coast Ghana.
Donatus Bapentire AngnuurengAfrica Center of Excellence in Coastal Resilience, Center for Coastal Management University of Cape Coast Cape Coast Ghana.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cloud cover effects make it difficult to evaluate the mangrove ecosystem in tropical locations using solely optical satellite data. Therefore, it is essential to conduct a more precise evaluation using data from several sources and appropriate models in order to manage the mangrove ecosystem as effectively as feasible. In this study, the status of the mangrove ecosystem and its potential contribution to coastal resilience were evaluated using the Google Earth Engine (GEE) and the InVEST model. The GEE was used to map changes in mangrove and other land cover types for the years 2009 and 2019 by integrating both optical and radar data. The quantity allocation disagreement index (QADI) was used to assess the classification accuracy. Mangrove height and aboveground biomass density were estimated using GEE by extracting their values from radar image clipped with a digital elevation model and mangrove vector file. A universal allometric equation that relates canopy height to aboveground biomass was applied. The InVEST model was used to calculate a hazard index of every 250 m of the shoreline with and without mangrove ecosystem. Our result showed that about 16.9% and 21% of mangrove and other vegetation cover were lost between 2009 and 2019. However, water body and bare land/built-up areas increased by 7% and 45%, respectively. The overall accuracy of 2009 and 2019 classifications was 99.6% (QADI = 0.00794) and 99.1% (QADI = 0.00529), respectively. Mangrove height and aboveground biomass generally decreased from 12.7 to 6.3 m and from 105 to 88 Mg/ha on average. The vulnerability index showed that 23%, 51% and 26% of the coastal segment in the presence of mangrove fall under very low/low, moderate and high risks, respectively. Whereas in the absence of mangrove, 8%, 38%, 39% and 15% fall under low, moderate, high and very high-risk zones, respectively. This study will among other things help the stakeholders in coastal management and marine spatial planning to identify the need to focus on conservation practices.

Indexed as

complex wetlandGhanaHazard indexInVESTLULCQADI

Identifiers

PMID37529586
PMCPMC10388404

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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.