Comparison and Prediction of the above Ground Carbon Storage in Croplands on the Inhabited Slopes on Mount Kilimanjaro (Tanzania) and the Taita Hills (Kenya)

Dickens Odeny, Faith Karanja, Geoffrey Mwachala, Petri Pellikka, Rob Marchant

Tutkimustuotos: ArtikkelijulkaisuArtikkeliTieteellinenvertaisarvioitu

Kuvaus

Mount Kilimanjaro and the Taita Hills are adjacent montane areas that experience similar climate and agricultural activity, but which differ in their geologic history, nature of elevation gradients and cultures. We assessed differences in cropland above ground carbon (AGC) between the two sites and
against environmental variables. One hectare sampling plots were randomly
distributed along elevational gradients stratified by cropland type; AGC was
derived from all trees with diameter ≥ 10 cm at breast height in each plot.
Predictor variables were physical and edaphic variables and human population.
A generalized linear model was used for predicting AGC with AIC used
for ranking models. AGC was spatially upscaled in 2 km buffer and visually
compared. Kilimanjaro has higher AGC in cropped and agroforestry areas
than the Taita Hills, but only significant difference in AGC variation in agroforestry areas (F = 9.36, p = 0.03). AGC in cropped land and agroforestry in
Kilimanjaro has significant difference on mean (t = 4.62, p = 0.001) and variation (F = 17.41, p = 0.007). In the Taita Hills, significant difference is observed only on the mean AGC (t = 4.86, p = 0.001). Common tree species that contribute the most to AGC in Kilimanjaro are Albizia gummifera and Persea
americana, and in the Taita Hills Grevillea robusta and Mangifera indica . Significant and univariate predictors of AGC in Mount Kilimanjaro are pH (R2 =
0.80, p = 0.00) and EVI (R2 = 0.68, p = 0.00). On Mount Kilimanjaro, the top
multivariate model contained SOC, CEC, pH and BLD (R2 = 0.90, p = 0.00), whereas in the Taita Hills, the top multivariate model contained elevation,
slope and population (R2 = 0.89, p = 0.00). Despite of the difference in land
management history of Mount Kilimanjaro and the Taita Hills, mean of AGC
in croplands does not differ significantly. Difference occurs on variation of
AGC, type of trees contributing AGC, and environmental variables that explain
AGC distribution. The research results provide reference for management
of carbon sequestration on inhabited montane areas.
Alkuperäiskielienglanti
LehtiJournal of Geographic Information System
Vuosikerta10
Sivut415-438
Sivumäärä23
ISSN2151-1950
DOI - pysyväislinkit
TilaJulkaistu - elokuuta 2018
OKM-julkaisutyyppiA1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä, vertaisarvioitu

Tieteenalat

  • 1171 Geotieteet

Lainaa tätä

@article{1e9b083acca54899a1f9b7079070c3f5,
title = "Comparison and Prediction of the above Ground Carbon Storage in Croplands on the Inhabited Slopes on Mount Kilimanjaro (Tanzania) and the Taita Hills (Kenya)",
abstract = "Mount Kilimanjaro and the Taita Hills are adjacent montane areas that experience similar climate and agricultural activity, but which differ in their geologic history, nature of elevation gradients and cultures. We assessed differences in cropland above ground carbon (AGC) between the two sites andagainst environmental variables. One hectare sampling plots were randomlydistributed along elevational gradients stratified by cropland type; AGC wasderived from all trees with diameter ≥ 10 cm at breast height in each plot.Predictor variables were physical and edaphic variables and human population.A generalized linear model was used for predicting AGC with AIC usedfor ranking models. AGC was spatially upscaled in 2 km buffer and visuallycompared. Kilimanjaro has higher AGC in cropped and agroforestry areasthan the Taita Hills, but only significant difference in AGC variation in agroforestry areas (F = 9.36, p = 0.03). AGC in cropped land and agroforestry inKilimanjaro has significant difference on mean (t = 4.62, p = 0.001) and variation (F = 17.41, p = 0.007). In the Taita Hills, significant difference is observed only on the mean AGC (t = 4.86, p = 0.001). Common tree species that contribute the most to AGC in Kilimanjaro are Albizia gummifera and Perseaamericana, and in the Taita Hills Grevillea robusta and Mangifera indica . Significant and univariate predictors of AGC in Mount Kilimanjaro are pH (R2 =0.80, p = 0.00) and EVI (R2 = 0.68, p = 0.00). On Mount Kilimanjaro, the topmultivariate model contained SOC, CEC, pH and BLD (R2 = 0.90, p = 0.00), whereas in the Taita Hills, the top multivariate model contained elevation,slope and population (R2 = 0.89, p = 0.00). Despite of the difference in landmanagement history of Mount Kilimanjaro and the Taita Hills, mean of AGCin croplands does not differ significantly. Difference occurs on variation ofAGC, type of trees contributing AGC, and environmental variables that explainAGC distribution. The research results provide reference for managementof carbon sequestration on inhabited montane areas.",
keywords = "1171 Geosciences",
author = "Dickens Odeny and Faith Karanja and Geoffrey Mwachala and Petri Pellikka and Rob Marchant",
year = "2018",
month = "8",
doi = "10.4236/jgis.2018.104022",
language = "English",
volume = "10",
pages = "415--438",
journal = "Journal of Geographic Information System",
issn = "2151-1950",
publisher = "Scientific Research Publishing",

}

Comparison and Prediction of the above Ground Carbon Storage in Croplands on the Inhabited Slopes on Mount Kilimanjaro (Tanzania) and the Taita Hills (Kenya). / Odeny, Dickens; Karanja, Faith; Mwachala, Geoffrey; Pellikka, Petri; Marchant, Rob.

julkaisussa: Journal of Geographic Information System , Vuosikerta 10, 08.2018, s. 415-438.

Tutkimustuotos: ArtikkelijulkaisuArtikkeliTieteellinenvertaisarvioitu

TY - JOUR

T1 - Comparison and Prediction of the above Ground Carbon Storage in Croplands on the Inhabited Slopes on Mount Kilimanjaro (Tanzania) and the Taita Hills (Kenya)

AU - Odeny, Dickens

AU - Karanja, Faith

AU - Mwachala, Geoffrey

AU - Pellikka, Petri

AU - Marchant, Rob

PY - 2018/8

Y1 - 2018/8

N2 - Mount Kilimanjaro and the Taita Hills are adjacent montane areas that experience similar climate and agricultural activity, but which differ in their geologic history, nature of elevation gradients and cultures. We assessed differences in cropland above ground carbon (AGC) between the two sites andagainst environmental variables. One hectare sampling plots were randomlydistributed along elevational gradients stratified by cropland type; AGC wasderived from all trees with diameter ≥ 10 cm at breast height in each plot.Predictor variables were physical and edaphic variables and human population.A generalized linear model was used for predicting AGC with AIC usedfor ranking models. AGC was spatially upscaled in 2 km buffer and visuallycompared. Kilimanjaro has higher AGC in cropped and agroforestry areasthan the Taita Hills, but only significant difference in AGC variation in agroforestry areas (F = 9.36, p = 0.03). AGC in cropped land and agroforestry inKilimanjaro has significant difference on mean (t = 4.62, p = 0.001) and variation (F = 17.41, p = 0.007). In the Taita Hills, significant difference is observed only on the mean AGC (t = 4.86, p = 0.001). Common tree species that contribute the most to AGC in Kilimanjaro are Albizia gummifera and Perseaamericana, and in the Taita Hills Grevillea robusta and Mangifera indica . Significant and univariate predictors of AGC in Mount Kilimanjaro are pH (R2 =0.80, p = 0.00) and EVI (R2 = 0.68, p = 0.00). On Mount Kilimanjaro, the topmultivariate model contained SOC, CEC, pH and BLD (R2 = 0.90, p = 0.00), whereas in the Taita Hills, the top multivariate model contained elevation,slope and population (R2 = 0.89, p = 0.00). Despite of the difference in landmanagement history of Mount Kilimanjaro and the Taita Hills, mean of AGCin croplands does not differ significantly. Difference occurs on variation ofAGC, type of trees contributing AGC, and environmental variables that explainAGC distribution. The research results provide reference for managementof carbon sequestration on inhabited montane areas.

AB - Mount Kilimanjaro and the Taita Hills are adjacent montane areas that experience similar climate and agricultural activity, but which differ in their geologic history, nature of elevation gradients and cultures. We assessed differences in cropland above ground carbon (AGC) between the two sites andagainst environmental variables. One hectare sampling plots were randomlydistributed along elevational gradients stratified by cropland type; AGC wasderived from all trees with diameter ≥ 10 cm at breast height in each plot.Predictor variables were physical and edaphic variables and human population.A generalized linear model was used for predicting AGC with AIC usedfor ranking models. AGC was spatially upscaled in 2 km buffer and visuallycompared. Kilimanjaro has higher AGC in cropped and agroforestry areasthan the Taita Hills, but only significant difference in AGC variation in agroforestry areas (F = 9.36, p = 0.03). AGC in cropped land and agroforestry inKilimanjaro has significant difference on mean (t = 4.62, p = 0.001) and variation (F = 17.41, p = 0.007). In the Taita Hills, significant difference is observed only on the mean AGC (t = 4.86, p = 0.001). Common tree species that contribute the most to AGC in Kilimanjaro are Albizia gummifera and Perseaamericana, and in the Taita Hills Grevillea robusta and Mangifera indica . Significant and univariate predictors of AGC in Mount Kilimanjaro are pH (R2 =0.80, p = 0.00) and EVI (R2 = 0.68, p = 0.00). On Mount Kilimanjaro, the topmultivariate model contained SOC, CEC, pH and BLD (R2 = 0.90, p = 0.00), whereas in the Taita Hills, the top multivariate model contained elevation,slope and population (R2 = 0.89, p = 0.00). Despite of the difference in landmanagement history of Mount Kilimanjaro and the Taita Hills, mean of AGCin croplands does not differ significantly. Difference occurs on variation ofAGC, type of trees contributing AGC, and environmental variables that explainAGC distribution. The research results provide reference for managementof carbon sequestration on inhabited montane areas.

KW - 1171 Geosciences

U2 - 10.4236/jgis.2018.104022

DO - 10.4236/jgis.2018.104022

M3 - Article

VL - 10

SP - 415

EP - 438

JO - Journal of Geographic Information System

JF - Journal of Geographic Information System

SN - 2151-1950

ER -