Socio-demographic determinants of place attachment in Gauteng,South Africa,using partial proportional odds models

GeoJournal - Determinants of place attachment have been extensively explored in the world now characterised by increased globalisation and mobility. Apart from some studies analysing attachment to...     

Meteorological drought analysis using copula theory for the case of upper Tekeze river basin,Northern Ethiopia

Theoretical and Applied Climatology - Meteorological drought is among the key climate-related risks affecting Ethiopia. It indicates a shortage of precipitation over a long period, usually for a...     

Biome-level relationships between vegetation indices and climate variables using time-series analysis of remotely-sensed data

ABSTRACT

Climatic factors such as rainfall and temperature play a vital role in the growth characteristics of vegetation. While the relationship between climate and vegetation growth can be accurately predicted in instances where vegetation is homogenous, this becomes complex to determine in heterogeneous vegetation environments. The aim of this paper was to study the relationship between remotely-sensed monthly vegetation indices (i.e. Normalized Difference Vegetation Index and Enhanced Vegetation Index) and climatic variables (temperature and precipitation) using time-series analysis at the biome-level. Specifically, the autoregressive distributed lag model (ARDL1 and ARDL2, corresponding respectively to one month and two month lags) and the Koyck-transformed distributed lag model were used to build regression models. All three models estimated NDVI and EVI fairly accurately in all biomes (Relative Root-Mean-Squared-Error (RMSE): 12.0–26.4%). Biomes characterized by relative homogeneity (Grassland, Savanna, Indian Ocean Coastal Belt and Forest Biomes) achieved the most accurate estimates due to the dominance of a few species. Comparisons of lag size (one month compared to two months) generally showed similarities (Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC) and log-likelihood) with quite high comparability in certain biomes – this indicates the utility of the ARDL1 and ARDL2 model, depending on the availability of appropriate data. These findings demonstrate the variation in estimation linked to the biome, and thus the validity of biome-level correlation of climatic data and vegetation indices.     

Soil temperature in an open site and below two plantation forest canopies in a tropical highland area,southern Ethiopia

This paper examines soil temperature (Ts) in two different plantation forests relative to an adjacent open land area in a tropical highland environment. To achieve the objectives, Ts in a Juniperus procera (JP) plantation, a Grevillea robusta (GR) plantation, and in the adjacent open land (OL) area were measured. One-way ANOVA and Pearson’s correlation were used for the data analysis. The result indicated that the mean daily Ts in the OL area at 10-cm depth of the soil was greater than the mean daily Ts recorded in the JP and GR plantations by 5 °C and 6 °C, respectively. The OL area Ts recorded at different soil depths (10 cm and 20 cm) was significantly different (p < 0.05). Rainfall (RF) and air temperature (Ta) of the study area have a direct relationship with the Ts in the plantation forests. The RF and Ta do not have a significant relationship with the Ts in the OL area at 10-cm soil depth. Overall, the study indicated that the Ts in the open land area was highly fluctuating monotonically, while it is relatively constant in the plantation forests.