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Record W4401437071 · doi:10.5539/jas.v16n9p41

Modelling the Current and Future Spatial Distribution Area of Adansonia digitata L. in the Context of Climate Change in Malawi (Southern Africa)

2024· article· en· W4401437071 on OpenAlexvenueno aff
Bruno Kokouvi Kokou, Prosper Kimwanga Salumu, Issa Baldé, Joyce Nababi, Georges Alunga Lufungula, Clément Soloum Teteli, Fednand Paul Wanjala, Msiska Ulemu, Tembo Mavuto, Paul Munyenyembe, Jean-Paul Rudant

Bibliographic record

VenueJournal of Agricultural Science · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAfrican Botany and Ecology Studies
Canadian institutionsnot available
Fundersnot available
KeywordsGeographyHabitatContext (archaeology)Climate changeDistribution (mathematics)SustainabilityReforestationSpecies distributionAdansonia digitataThreatened speciesHabitat destructionAgroforestryEcologyPrioritizationForestryEnvironmental scienceBiology

Abstract

fetched live from OpenAlex

Climate change is likely to affect the distribution of species worldwide. Understanding how these changes affect species distribution is important for planning conservation strategies and sustainable management methods. Adansonia digitata L. is of major ecological and socio-economic importance in Malawi, South Africa, but is highly threatened in its habitat. This work aims to investigate the effect of climate change on the ecological niche of Baobab and to find suitable habitats for its conservation and cultivation in Malawi. The distribution of this species was modeled using a maximum entropy algorithm (MaxEnt) based on 21 environmental variables and the occurrence of 480 species. Habitat prioritization was performed using Zonation software. Our results show that the variable contributing most significantly was the warmest month (47%), followed by isotherms (13.9%) and precipitation of the coldest quarter (8.6%). Under the current model, 1.17% of Malawi’s territory is highly favorable for baobab development. A slight increase of 0.09% and 0.38% in highly favorable zones is predicted by 2055 under scenarios SSP370 and SSP 585, respectively. Southern Malawi and parts of the Central region should be prioritized in baobab reforestation policies to optimize conservation and value chain sustainability for baobab. Under the current model, 1.17% of Malawi will be highly favorable for baobab. A slight increase of 0.09 % and 0.38 % in highly favorable zones is predicted by 2055 under scenarios SSP 370 and SSP 585, respectively. Priority areas (98-100%) for conservation and cultivation of Baobab was a male located in the Southern region (34.51%) and central (7.62%), in contrast to the Northern region (0.21%). Our results suggest that climate change causes the reduction and shift of suitable habitats for species along a south-north gradient. These findings highlight the urgent need to incorporate climate change projections into conservation plans. Identifying and prioritizing suitable habitats in the southern and central regions is crucial for effective conservation and sustainability.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.779
Threshold uncertainty score0.127

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.036
GPT teacher head0.239
Teacher spread0.203 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations8
Published2024
Admission routes1
Has abstractyes

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