Representation of Land-Atmosphere Coupling Processes Over Africa in CMIP6 Models

Climate models are useful tools that aid in short to long term prediction of the evolution of climate. In this study we assess how CMIP6 models represent coupling between processes over the land and atmosphere, based on terrestrial and atmospheric indices, to show the nature and strength of the coupling relative to the ERA5 datasets over Africa, with a particular focus on the March-May season. Characterization of the annual cycle indicates that model biases are highest during the peak of the rainfall season, and least during the dry season, while soil moisture biases correspond with rainfall amounts. Models show appreciable sensitivity to regional characteristics; there was model consensus in representing East Africa as a limited soil moisture regime, while major differences were noted in the wet regime over Central Africa. Most CMIP6 models tend to over-estimate the strength of the terrestrial and atmospheric pathways over East and Southern Africa. Inter-model differences in coupling indices could be traced to their inter-annual variability rather than to the mean biases of the variables considered. These results are good indicators towards scientific advancement of land surface schemes in the next generation of climate models for better applications in Africa.

Response of yam varieties to soil moisture regime in Southwestern Nigeria

A field experiment was conducted on varietal response of white yam to moisture regime in Abeokuta. The experiment comprised three varieties of yam (Efuru, Ise-osi and Oniyere), three mulching options (grass, polythene and unmulched), and two planting dates (early and late). Treatments were replicated three times using RCBD lay-out. Model for selecting planting date involved relating potential evapotranspiration (PE) to precipitation (P) in the form of 0.1PE<P < 0.5PE, partitioned for attaining optimal planting date into early {T1= Σ(P-0.1PE) ≤ 0} and late {T2 = Σ(P-0.5PE) ≤ 0}, respectively. For humid period defined by P> PE, the physiological parameters and moisture agro-climatic indices measured during phenological stages of yam grown were analyzed with respect to treatments. Result showed that T1 defined as Σ(P-0.1PE) ≤ 10 mm appeared as the best model that significantly (P < 0.05) influenced emergence rate, phenological growth and tuber yield. All yam varieties evaluated were suitable for planting with respect to yield. Efuru and Ise-osi synchronized perfectly with Actual Water Availability and produced good vegetative growth with LAI of 1.08 and 0.91 leading to higher tuber yield of 12 and 11.64 tonnes ha-1, respectively. Grass mulch had tuber yield, 4-6 tonnes ha-1greater than the polythene and unmulched plots in all varieties. Mulching significantly (P< 0.05) increased tuber yield, 6-8 tonnes ha-1than the unmulched. Conclusively, early planting with grass mulch increased tuber yield.

Model Prediction of the Soil Moisture Regime and Soil Nutrient Regime Based on DEM-Derived Topo-Hydrologic Variables for Mapping Ecosites

Ecosites are required for stand-level forest management and can be determined within a two-dimensional edatopic grid with soil nutrient regimes (SNRs) and soil moisture regimes (SMRs) as coordinates. A new modeling method is introduced in this study to map high-resolution SNR and SMR and then to design ecosites in Nova Scotia, Canada. Using coarse-resolution soil maps and nine topo-hydrologic variables derived from high-resolution digital elevation model (DEM) data as model inputs, 511 artificial neural network (ANN) models were developed by a 10-fold cross-validation with 1507 field samples to estimate 10 m resolution SNR and SMR maps. The results showed that the optimal models for mapping SNR and SMR engaged eight and seven topo-hydrologic variables, together with three coarse-resolution soil maps, as model inputs, respectively; 82% of model-estimated SNRs were identical to field assessments, while this value was 61% for SMRs, and the produced ecosite maps had 67–68% correctness. According to the error matrix, the predicted SNR and SMR maps greatly alleviated poor prediction in the areas of extreme nutrient or moisture conditions (e.g., very poor or very rich, wet, or very dry). Thus, the new method for modeling high-resolution SNR and SMR could be used to produce ecosite maps in sites where accessibility is hard.

Influence of drip irrigation on the formation of seedlings raspberries in the Non-Black earth zone

Due to the lack of scientifically grounded technologies for the cultivation of red raspberries in the gardens and nurseries of the Non-Chernozem zone of the Russian Federation, aimed at the minimum use of resources and funds, it is relevant research to establish the effect of different moisture availability on the growth, development and productivity of raspberries, as well as the development of an optimal soil moisture regime in the Non-Chernozemregion. Field research is carried out on the territory of the training and experimental farm, the fruit-growing laboratory «Michurinsky Garden». Russian State Agrarian University – Moscow Agricultural Academy named after K.A. Timiryazev. The experiment is two-factor, aimed at studying the different pre-irrigation moisture thresholds for the development of two varieties of raspberries, was laid in the fall of 2018.

Growth sensitivity to climate varies with soil moisture regime in spruce–fir forests in central British Columbia

Key message Growth sensitivity to climate varies with soil moisture regime in spruce–fir forests in central British Columbia. Stands growing at their dry edaphic limits displayed especially strong and unique climatic sensitivities. Abstract Soil moisture regime is an important influence of productivity, process, and structure in forested ecosystems. In western North America, projected warming trends may result in decreasing available soil moisture; however, the potential effects on forest growth remain unclear. This study aimed to determine the influence of stand-level soil moisture regime on the climatic sensitivity of mature hybrid white spruce (Picea glauca (Moensch) Voss x Picea engelmannii Parry) and subalpine fir (Abies lasiocarpa (Hook.) Nutt.) forests in central British Columbia, Canada. We collected and analyzed tree-ring data from 51 stands spanning a range of soil moisture regimes. Dendroecological analyses of climate–growth relationships indicated that warm summer temperatures and drought limit growth for both species across all soil moisture regimes; however, responses were strongest on the driest sites. Spruce populations across the gradient of soil moisture regimes displayed unique climate-growth relationships; growth in populations on wetter sites was more correlated with summer climate from the year prior to growth. Radial growth responses to prior summer temperatures strengthened over the past ca. 80 years in both species and across most sites, suggesting that climate–growth relationships are shifting in this region. This study presents evidence of the importance of considering site-level ecological factors such as soil moisture regime when studying forest growth responses to climate.