Dry Sub-humid Regions Research Articles

Dynamics of CO2 fluxes and controlling environmental factors in sugarcane (C4)-wheat (C3) ecosystem of dry sub-humid region in India.

In this study, CO2 exchange over sugarcane and wheat growing season was quantified by continuous measurement of CO2 fluxes using eddy covariance (EC) system from January 2014 to June 2015. We also elaborated on the response of CO2 fluxes to environmental variables. The results show that the ecosystem has seasonal and diurnal dynamics of CO2 with a distinctive U-shaped curve in both growing seasons with maximal CO2 absorption reaching up to -8.94 g C m-2 day-1 and -6.08 g C m-2 day-1 over sugarcane and wheat crop, respectively. The ecosystem as a whole acted as a carbon sink during the active growing season while it exhibits a carbon source prior to sowing and post-harvesting of crops. The cumulative net ecosystem exchange (NEE), gross primary productivity (GPP), and ecosystem respiration (Reco) were -923.04, 3316.65, and 2433.18 g C m-2 over the sugarcane growing season while the values were -192.30, 621.47, and 488.34 g C m-2 over the wheat growing season. The sesbania (green manure) appeared to be a carbon source once it is incorporated into soil. The response of day-time NEE to photosynthetically active radiation (PAR) under two vapor pressure deficit (VPD) sections (0-20 h Pa and 20-40 h Pa) seems more effective over sugarcane (R2 = 0.41-0.61) as compared to the wheat crop (R2 = 0.25-0.40). A decrease in net CO2 uptake was observed under higher VPD conditions. Similarly, night-time NEE was exponentially related to temperature at different soil moisture conditions and showed higher response to optimum soil moisture conditions for sugarcane (R2 = 0.87, 0.33 ≤ SWC < 0.42 m3 m-3) and wheat (R2 = 0.75, 0.31 ≤ SWC < 0.37 m3 m-3) crop seasons. The response of daily averaged NEE to environmental variables through path analysis indicates that PAR was the dominant predictor with the direct path coefficient of -0.65 and -0.74 over sugarcane and wheat growing season, respectively. Satellite-based GPP products from Moderate Resolution Imaging Spectroradiometer (GPPMOD) and Vegetation Photosynthetic model (GPPVPM) were also compared with the GPP obtained from EC (GPPEC) technique. The seasonal dynamics of GPPEC and GPPVPM agreed well with each other. This study covers the broad aspects ranging from micro-meteorology to remote sensing over C4-C3 cropping system.

Distinct vegetation response to drying and wetting trends across an aridity threshold

Aridity regulates the terrestrial ecosystem productivity in water-limited regions. The aridity index (AI) is often defined as the ratio of annual precipitation to annual potential evapotranspiration. However, how the drying and wetting influence the vegetation response and its characteristic along aridity gradient remains unclear. Here, we examined trends of the AI and normalized difference vegetation index (NDVI) in the drylands of East Asia from 1982 to 2015, which denoted the drying and wetting trends and vegetation response, respectively. The results show that the variability in land area and AI from 1982–2015 was lower in the whole dryland than its subtypes including hyper-arid, arid, semi-arid, and dry sub-humid regions. Drying and wetting trends were observed in each AI interval along a spatial aridity gradient. Wetting trends are prevalent owing to their area and magnitude were twice those of drying trends. Spatial variation of aridity shaped the pattern of trends in vegetation response to drying and wetting trends; drier regions had smaller and narrower ranges of variation in NDVI trends relative to wetter regions. A shift in AI trends and NDVI trends along the spatial aridity gradient occurred at 0.4 of AI. Distinct patterns of vegetation response to aridity change were observed across the aridity threshold, and the transition region was identified in the studied drylands. The results suggest that changes in the subtypes might be masked by the entire drylands and then leading to failure in recognizing the transformation of the subtypes. This implies that terrestrial carbon storage variability prediction should consider the spatial aridity changes to avoid the uncertainties due to the divergent vegetation response to AI trends at different aridity levels.

Within-site drivers for soil nutrient variability in plantation forests: A case study from dry sub-humid New Zealand

Precise spatial information on soil properties in plantation forests is needed to improve soil nutrient management and to sustain productivity. Soil nitrogen, phosphorus, potassium, organic matter, carbon and boron are important determinants and indicators of soil fertility and quality. Particularly in forests, these soil properties are highly variable in space and time. In this study, soils were sampled from three plantation forest sites in a dry sub-humid region near Blenheim, New Zealand. Thirty sampling points were selected, and samples were collected from the three sites across a range of slope and aspect strata. Soil samples were analysed for total carbon (totC), total nitrogen (totN), total phosphorus (totP), extractable potassium (exK) and hot-water extractable boron (exB). All examined soil properties varied significantly (p < 0.05) within sites. A set of fine-scale (5 m resolution) topographic surfaces, that might explain this variability, were then interpolated or derived in geographic information system software. Topographic surfaces included elevation, aspect, slope, profile and plan curvature, topographic position index (TPI), topographic wetness index (TWI), wind exposition index (WEI), and morphometric protection index (MPI). A generalised linear mixed-effect model was applied to develop predictive models. The study found all soil properties were positively correlated with MPI and negatively correlated with the WEI. This indicated that soil properties were correlated with shelter from surrounding relief and wind. Interestingly, within-site boron levels were correlated with both profile curvature (PrCurv) and topographic wetness index, indicating boron movement through the surface with the movement of soil moisture. The modelling approach in this study has potential for application to sustainable management of plantation forests using spatially-precise estimates of soil fertility.

An improved method to estimate actual vapor pressure without relative humidity data

Estimating actual vapor pressure (ea) without relative humidity (RH) data continues to draw research attention. One of the accurate ways to estimate ea is through estimation of dew point temperature (Tdew) from minimum (Tmin) or mean temperature (Tmean). Two existing methods have been largely used to estimate ea. The first method (method I) assumes that Tdew is close to Tmin. The other one (method II) adjusts Tdew from Tmin with piecewise correction factors (aT) from sub-humid to hyper arid regions, and from Tmean with a fixed correction factor, aD, in humid regions. Here, two methods are proposed to estimate ea. The first method (method III) adjusts Tdew from Tmin with dynamic aT based on the correlation function between aT and aridity index (AI) regardless of climate zones. The second method (method IV) adjusts Tdew from Tmin with dynamic aT when AI < 1.00 and from Tmean with aD when AI ≥ 1.00. The performance of four methods was evaluated based on data from 886 meteorological stations distributed from hyper-arid to humid regions. Results showed that there was a significant logarithmic correlation function between aT and AI, but no significant correlation between aD and AI. Daily values of ea estimated by method I were greatly overestimated in semi-arid to hyper-arid regions, but were reasonably estimated in humid regions. The accuracy of method II was improved in hyper-arid to dry sub-humid regions but decreased in humid regions, compared to method I. The proposed methods (III and IV) further improved the accuracy and produced reasonable estimation of daily ea in hyper-arid to humid regions, and method III produced a slightly better performance than method IV. Similar results were also observed for estimation of monthly ea. Therefore, the proposed method III is highly recommended to estimate daily and monthly ea when RH data are unavailable.

Alternating wide ridges and narrow furrows with film mulching improves soil hydrothermal conditions and maize water use efficiency in dry sub-humid regions

The ridge-furrow mulching system (RFMS) is widely used to improve crop yields and water use efficiency in arid and semi-arid rainfed agricultural regions. However, the effects of RFMS on hydrothermal states and maize (Zea mays L.) yields in dry sub-humid regions remain unclear. The objective of this study was to determine the influence of ridge-furrow construction and plastic film mulching on soil moisture and temperature, evapotranspiration (ET), maize growth and yield, water use efficiency (WUE), and thermal time use efficiency (TUE) in dry sub-humid regions of the Loess Plateau. A three-year field study was conducted in which four different planting practices were evaluated: (1) alternating wide ridges and narrow furrows with film mulching (WRM), (2) alternating equal-width ridges and furrows with film mulching (ERM), (3) equal row spacing in flat plot with half film mulching (EFM), and (4) conventional flat plot without mulching (CK). The results demonstrated that at early maize growth stages, soil water storage within the 0–200 cm soil profile and soil temperatures were increased for mulching treatments compared with CK. RFMS utilized soil water efficiently by increasing rainwater harvesting efficiency and transpiration while decreasing soil evaporation. RFMS significantly increased soil temperature in the ridges by 4.0–4.4 °C and reduced diurnal soil temperature amplitude in the furrows, thereby increasing soil thermal time. These positive effects of RFMS compared with CK improved maize growth and crop yields because of adequate absorption and utilization of water and thermal resources. RFMS increased average maize yield by 24.9–32.8%, WUE by 34.1–45.7%, and TUE by 15.9–21.1%. The highest grain yield, WUE, and TUE were observed with WRM due to its favorable soil hydrothermal conditions. The WRM treatment is a promising water-saving and high-yielding maize cultivation practice to improve grain yields and resource use efficiency in dry sub-humid regions.

Global detection of aridification or increasing wetness in arid regions from 2001 to 2013

Arid regions are highly vulnerable to climate change and human activity, and global warming in particular has the potential to increase the arid land area. One traditional way to evaluate the extent of climate change in dryland regions is to use the aridity index (AI), defined as the ratio of annual rainfall to annual potential evapotranspiration. However, the AI is a climatic index; it does not represent actual conditions of aridity in arid regions. In contrast, the satellite-based aridity index (SbAI), which is based on day/night land surface temperature changes, is considered to represent actual conditions of moisture availability. Arid regions during 2001–2013 were classified at global scale by comparing the SbAI with the AI, that is, within Turc space, which is based on the water balance concept. In addition, factors contributing to aridification or wetness changes detected in different global regions were examined by comparing the SbAI and AI result with the yearly maximum normalized difference vegetation index and past land use. As a result, dryland regions were newly classified into five zones. In the stable zone, land areas were classified into hyper-arid, arid, semi-arid, or dry sub-humid regions by both the SbAI and the AI. Areas in the transition zone toward dryness are moderately dry. Areas in the transition zone toward wetness include large river basins, oases, and wadis with little rainfall. In the moist zone, rainfed or irrigated farming is being successfully conducted. Many parts of the dry zone, however, are extremely dry.

Drivers of Ectomycorrhizal Fungal Community Structure Associated with Pinus sylvestris var. mongolica Differ at Regional vs. Local Spatial Scales in Northern China

Pinus sylvestris var. mongolica, a widely planted tree species, is facing long-lasting, unresolved degradation in desertified Northern China. Ectomycorrhizal fungi (EMF) are closely related to the stand status, because they substantially participate in ecological processes of terrestrial forest ecosystems. EMF may be key to solving the introduction recession. Therefore, we performed DNA sequencing of P. sylvestris root samples from plantations and natural forests as control to characterize the EMF from semi-arid and dry sub-humid regions, using ITS Illumina sequencing and conventional soil physicochemical index determination. The results indicated that (1) the dominant EMF genera were Suillus, Rhizopogon, and Wilcoxina in the Hulunbuir, Mu Us, and Horqin Sandy Lands, respectively. Their dominance retained with stand ageing. (2) Plantation EM fungal diversity differs significantly among the three sandy lands and was significantly lower than in natural forest. The diversity varied with stand age, showing distinct trends at the local scale. (3) At the regional scale, the mean annual sunshine times and the soil organic carbon content affect EMF diversity. The community composition and structure were more characterized by temperature and precipitation. At the local scale, besides the soil organic carbon content, the EM fungal community composition and structure were correlated with total nitrogen and phosphorus content (Hulunbuir), the total phosphorus content (Mu Us), and the pH and total soil porosity (Horqin). The EM fungal community composition and structure have the obvious geographical distribution variation; they were strongly correlated with the meteorological elements and soil nutrients at the regional scale. At the local scale, they were jointly driven by stand age and soil properties. This improved information contributes to increasing the understanding of the interaction between EMF and forest ecosystems and guides sustainable forest management of degraded P. sylvestris plantations.

ASSESSMENT AND MAPPING OF IRAN DESERTIFICATION INTENSITY USING ARCGIS ENVIRONMENT

Abstract. Desertification phenomenon is described as one of the most obvious forms of natural resources degradation in the world. This phenomenon, which occurs because of natural factors or anthropogenic factors, is accounted as the third most important global challenge after crisis of water shortage and drought in the 21st century. Awareness of desertification criteria and indicators, investigation of a regional model and determining the most important factors affecting desertification are essential for combating desertification. So in this study, IMDPA model (Iranian Model of Desertification Potential Assessment) was used in order to prepare Atlas of Iran desertification. 8 criteria and 130 indicators affecting desertification have determined for this model. Regarding to these criteria and indicators and quantifying them in arid, semi-arid and dry sub-humid region of Iran, the map of desertification intensity was prepared. The results of this study showed that 88.73% of the country surface was affected by desertification that is equal to 143365238.6 hectare. The surface more than 49425703.3 hectare equal to 30.59% of total surface of country was in low desertification class, the surface more than 935677913.6 hectare equal to 57.91% was in class II or medium and the surface about 371621.7 hectare equal to 0.23% was in class III or intense. Class IV of desertification or very intense was omitted regarding to IMDPA model and 8 criteria, and natural desert areas which their surface was equal to 15624274.3 hectare or 9.67% is beyond this class.

Decadal Change in Soil Moisture Over East Asia in Response to a Decade‐Long Warming Hiatus

AbstractEast Asia has experienced long‐term warming and drying in the twentieth century. However, a phenomenon known as the “warming hiatus” changed the trend of enhanced soil drying over East Asia. In contrast to the previous long‐term drying in the last century, time series of soil moisture showed a shift from a downtrend to uptrend around 2005, and prominent wetting was located in the northeast (semiarid and dry subhumid regions) and southeast of China (extreme humid regions). Our results illustrated that such abrupt change in soil moisture was closely related to the change of warming during hiatus. The warming hiatus played a more important role in decadal soil wetting over these semiarid and dry subhumid regions, compared to relatively limited influence of surface atmosphere temperature over humid regions. The weakened drying during the hiatus decade suggests that the response of wetting/drying to climate in drylands is closely related to decadal surface atmosphere temperature, which will deepen our understanding of the mechanism on the role of surface atmosphere temperature in the process of wetting/drying in drylands over different time scales.

Assessment of monthly global solar irradiation estimates using air temperature in different climates of the state of Rio de Janeiro, Southeastern Brazil

The number of weather stations that measure solar global irradiance (Ig) is scarce, and when it is available, it does not present long-time series, without gaps and high quality. When Ig is unavailable, it is possible to estimate its integral over time—solar global irradiation (Hg)—using empirical methods. However, for a better performance these methods need to be fitted to the local climatic conditions. The aim of this study was to assess the Hargreaves–Samani (HS) and Bristow–Campbell (BC) methods to estimate monthly average daily Hg in the state of Rio de Janeiro, Southeastern Brazil, and to propose a simple approach to determine the empirical coefficients in function of the climate. The methods are based on maximum and minimum air temperature and on extraterrestrial solar irradiation. Series of air temperature extremes and Hg from 15 automatic weather stations between 2000 until 2013 were used. The methods were evaluated by the statistical indexes: determination coefficient (r2) of the linear regression between observed and estimated monthly Hg, root mean square error (RMSE), Willmott’s index (d) and performance index (c). The methods (BC—r2 > 0.60, d > 0.85 and RMSE 0.55, d > 0.75 and RMSE 0.85) in approximately 80% of the stations analyzed, while for Hargreaves–Samani, only 55% of the stations were classified as “optimal.” The highest HS coefficients (kr) occurred in Semiarid (0.246 ± 0,023) and Dry Sub-humid (0.181 ± 0.011) climates and were associated with coastal regions (< 20 km), while the stations in Humid (0.146 ± 0.008), Sub-humid (0.1524 ± 0.003) and Dry Sub-humid (0.162 ± 0.011) climates located in interior regions presented the lowest kr. Thus, it is possible to determine the kr coefficient based only on the climatic classification of the site and distance of the coastal environment. In general, the highest atmospheric transmittance (β0—BC method) was observed in Semiarid and Dry Sub-humid climate regions. β1 and β2 coefficients did not present a distribution pattern with the local climatology and with the proximity of large water bodies. The methods presented a better performance in Dry Sub-humid and Semiarid climates, due to the lower variability of cloudiness and greater thermal amplitude.

The Major Biophysical Indicators of Desertification in Arid and Semi arid regions of India

Desertification is a process of land degradation in arid, semi- arid and dry sub-humid regions due to climatic uncertainties and improper land management activities. The major desertification processes operating in arid and semi arid regions of India are soil erosion, vegetal degradation, salinization/alkalinisation, water logging, loss of soil fertility and uncontrolled mining. Identification of major biophysical indicators of desertification is necessary for periodical monitoring and preparation of strong combating plan. To investigate the biophysical indicators which are most effective in assessing the level of desertification vulnerability, a total of 17 biophysical indicators were studied in 13 sites of South India representing two different agro-ecological regions (AESR 8.3&amp;3). Principal Component Analysis was employed to identify the effective indicators based on maximum loadings and Eigen value. Linear discriminant analysis was used to identify the most important and reliable indicators for assessing degree of desertification processes. The results showed that pH and organic carbon are the most reliable indicators for assessing the degree of desertification processes in South India.

Severe wildfire exposes remnant peat carbon stocks to increased post-fire drying

The potential of high severity wildfires to increase global terrestrial carbon emissions and exacerbate future climatic warming is of international concern. Nowhere is this more prevalent than within high latitude regions where peatlands have, over millennia, accumulated legacy carbon stocks comparable to all human CO2 emissions since the beginning of the industrial revolution. Drying increases rates of peat decomposition and associated atmospheric and aquatic carbon emissions. The degree to which severe wildfires enhance drying under future climates and induce instability in peatland ecological communities and carbon stocks is unknown. Here we show that high burn severities increased post-fire evapotranspiration by 410% within a feather moss peatland by burning through the protective capping layer that restricts evaporative drying in response to low severity burns. High burn severities projected under future climates will therefore leave peatlands that dominate dry sub-humid regions across the boreal, on the edge of their climatic envelopes, more vulnerable to intense post-fire drying, inducing high rates of carbon loss to the atmosphere that amplify the direct combustion emissions.

Responses of vegetation to climatic variations in the desert region of northern China

Global climate change is expected to impact vegetation dynamics. However, differences in the responses of vegetation in desert regions remain poorly understood. We analysed trends in normalised difference vegetation index (NDVI) and its correlations with climatic factors (temperature and precipitation) for typical vegetation in dry sub-humid, semi-arid, arid, and hyper-arid regions of northern China over the past three decades (1982–2015). We also evaluated the effects of climatic variations on vegetation using the vegetation sensitivity index (VSI). Over the study period, NDVI in the dry sub-humid and semi-arid regions showed a significant increasing trend, but no marked trend was noted in the arid region. Both precipitation and temperature had positive effects on NDVI, but that of the latter on NDVI decreased with increasing aridity. The VSI of vegetation dominated by Pinus sylvestris var. mongolica, Ulmus spp., and Caragana spp. was higher than that of vegetation dominated by Artemisia desertorum, A. ordosica, Haloxylon persicum, and H. ammodendron. Our analysis provides two important insights into the responses of vegetation to climatic variations: Firstly, vegetation in the different desert regions of northern China showed diverse responses to climatic variations. Secondly, vegetation dominated by trees (P. sylvestris var. mongolica and Ulmus spp.) and tall shrubs (Caragana spp.) was more sensitive to climatic variations than that dominated by drought-tolerant dwarf shrubs (e.g. A. desertorum and A. ordosica).

Variable resolution modeling of near future mean temperature changes in the dry sub-humid region of Ghana

The study used two models from Rossby Centre Regional Atmospheric Model (RCA4) and two from Weather Research and Forecasting Model (WRF) plus the Statistical Downscaling Model—Decision Centric (SDSM-DC) at 44 km, 12 km and 2 m resolution respectively to project the impact of climate change on mean temperature in the Pra River Basin for the period 2020–2049. Results showed that the minimum temperature increased (+ 1.47 °C) faster than the increase (+ 1.11 °C) in maximum temperature for observed period 1981–2010. An evaluation of the performance of the models with time-series based metrics showed that SDSM-DC and RCA4 are better for projecting mean temperature in the study area compared to WRF despite its resolution. Analysis of variance (p < 0.05) indicated significant difference between the projected mean temperature of the five models but there was no significant difference between SDSM-DC and RCA4 models. Correlation between models was highest at R = 0.727 between SDSM-DC and RCA4. The years 2041, 2042 and 2047 were projected as hottest by minimum two different models. The mean temperature change was projected at + 1.36, + 1.42 and + 1.12 °C by SDSM-DC, RCA4 and WRF respectively. The ensemble of projection depicted same trend of February—April as the high mean temperature and July—September as the lowest as was for the observed period. However, January is projected to have the highest change in mean temperature of + 1.51 °C. The maximum temperature for observed period was found to be the mean temperature in the period 2020–2049. Future study will focus on the impact of projected temperature change on ecosystem services delivery in the region.

Impact of drought on vegetation carbon storage in arid and semi-arid regions

Drought is a common phenomenon in arid and semi-arid regions. In global carbon cycle, semi-arid ecosystem plays a crucial role in interannual variability and greening trend. The vegetation carbon storage and its relation with drought in India are not well understood. The impact of drought on vegetation carbon storage is investigated using Standardized Precipitation Evapotranspiration Index (SPEI) and CASA (Carnegie-Ames-Stanford Approach) derived Net Primary Production (NPP) during 2001–2013. A strong positive correlation is found between regional NPP and SPEI. CASA derived NPP shows good agreement (R2 = 0.57, significance > 95%) with field based observation in arid and semi-arid regions of Gujarat. A significant Increasing trend of 0.2 TgC Yr−1 (about 2 % per year) is observed during the period of 2001–2013. The highest decreased of 24% (2.79 TgC Yr−1) in NPP was found during 2002 and a notable increase of 17% (1.61 TgC Yr−1) was seen during 2013 due to consecutive drought and surplus rainfall years respectively. The study suggests that consecutive droughts have brought an immense impact on vegetation productivity. During the drought years, dry sub-humid region was the most vulnerable as it was dominated by agriculture land, while semi-arid region was less affected due to forest cover. Despite many droughts, some part of north-west and south-west regions had shown an increase in vegetation carbon storage, which indicates that these parts are not affected by the drought. The study also suggests that in addition to rainfall, heat wave also played a major limiting factor in vegetation productivity. The study will be useful in identifying the regions which are more vulnerable to drought. Present study, will also be helpful in combating the regional climate change as vegetation carbon storage is directly linked with agricultural productivity.

Spatio-temporal monitoring of vegetation phenology in the dry sub-humid region of Nigeria using time series of AVHRR NDVI and TAMSAT datasets

Abstract Time series data are of great importance for monitoring vegetation phenology in the dry sub-humid regions where change in land cover has influence on biomass productivity. However few studies have inquired into examining the impact of rainfall and land cover change on vegetation phenology. This study explores Seasonal Trend Analysis (STA) approach in order to investigate overall greenness, peak of annual greenness and timing of annual greenness in the seasonal NDVI cycle. Phenological pattern for the start of season (SOS) and end of season (EOS) was also examined across different land cover types in four selected locations. A significant increase in overall greenness (amplitude 0) and a significant decrease in other greenness trend maps (amplitude 1 and phase 1) was observed over the study period. Moreover significant positive trends in overall annual rainfall (amplitude 0) was found which follows similar pattern with vegetation trend. Variation in the timing of peak of greenness (phase 1) was seen in the four selected locations, this indicate a change in phenological trend. Additionally, strong relationship was revealed by the result of the pixel-wise regression between NDVI and rainfall. Change in vegetation phenology in the study area is attributed to climatic variability than anthropogenic activities.

Exploiting genetic and physiological variation of the native forage grass Trichloris crinita for revegetation in arid and semi‐arid regions: An integrative review

AbstractIn arid, semi‐arid and dry subhumid regions, which represent ~ 41% of the Earth's land surface, desertification and soil degradation are very frequent, leading to low soil fertility and productivity. In these regions, revegetation with locally adapted native species may aid in ameliorating desertification processes. Trichloris crinita is a C4 perennial grass native to arid and semi‐arid regions of the American continent. Its good forage quality, drought tolerance, resistance to trampling and grazing, and rapid growth and competing aggressiveness among other native species warrant its use as forage and for revegetation purposes. In the last decades, many studies have revealed broad intraspecific genetic variation for ecophysiological, morphological, biomass production, nutritional quality (as forage) and adaptive stress response‐related traits. Also, results from field trials evaluating T. crinita genotypes as forage and for restoration of degraded areas suggest great potential for—and have encouraged—its utilization under different habitats and environmental conditions. In this integrative review, we compiled and discussed the most relevant research data regarding T. crinita, focusing on aspects and traits that influence its utilization both as forage and in rehabilitation of degraded lands. Challenges and prospects towards the improvement of this species in breeding programmes with specific goals are discussed.

Can agroforestry systems thrive in the drylands? Characteristics of successful agroforestry systems in the arid and semi-arid regions of Latin America

Agroforestry systems are a strategy for rural communities to manage environmental change through contributions in agrobiodiversity, livelihood diversity and labour availability, and economic stability. The majority of research in agroforestry has focused on tropical humid and sub-humid environments and the characteristics of agroforestry systems in arid and semi-arid regions have not been extensively documented in Latin American countries. Here, we document the characteristics of replicable, widely practiced agroforestry systems in five climatic regimes across the arid and semi-arid regions of Latin America (dry sub-humid, warm semi-arid, temperate arid, cold arid, and warm arid regions). The research was conducted on 4-6 farms per region using the design and diagnosis method, highlighting that the combination of multi-purpose trees with subsistence crops and livestock is highly context-specific. The analysis was corroborated by semi-structured interviews and focus group discussions on farmers’ perceptions of the challenges and benefits of implementing agroforestry. In general farmers perceive the significant contributions to economic and ecological sustainability, including the improvement of soil fertility and resilience to climate change.

Sensitivity of potential evapotranspiration estimation to the Thornthwaite and Penman–Monteith methods in the study of global drylands

Drylands are among those regions most sensitive to climate and environmental changes and human-induced perturbations. The most widely accepted definition of the term dryland is a ratio, called the Surface Wetness Index (SWI), of annual precipitation to potential evapotranspiration (PET) being below 0.65. PET is commonly estimated using the Thornthwaite (PET Th) and Penman–Monteith equations (PET PM). The present study compared spatiotemporal characteristics of global drylands based on the SWI with PET Th and PET PM. Results showed vast differences between PET Th and PET PM; however, the SWI derived from the two kinds of PET showed broadly similar characteristics in the interdecadal variability of global and continental drylands, except in North America, with high correlation coefficients ranging from 0.58 to 0.89. It was found that, during 1901–2014, global hyper-arid and semi-arid regions expanded, arid and dry sub-humid regions contracted, and drylands underwent interdecadal fluctuation. This was because precipitation variations made major contributions, whereas PET changes contributed to a much lesser degree. However, distinct differences in the interdecadal variability of semi-arid and dry sub-humid regions were found. This indicated that the influence of PET changes was comparable to that of precipitation variations in the global dry–wet transition zone. Additionally, the contribution of PET changes to the variations in global and continental drylands gradually enhanced with global warming, and the Thornthwaite method was found to be increasingly less applicable under climate change.

Organic and inorganic carbon storage in soils along an arid to dry sub-humid climosequence in northwest of Iran

The importance of soil carbon in different biomes of the earth is well understood. Most of the studies on terrestrial carbon cycle have been focused on the surface horizon of soils, but deeper soils have rarely been considered. The effects of arid, semi-arid and dry sub-humid climates on soil organic carbon (SOC), soil inorganic carbon (SIC) and soil total carbon storage (STC) along a soil climosequence, on basaltic underlying rocks were investigated. SOC and SIC content and storage showed reverse trends with increasing soil depth. STCs increased by increasing mean annual precipitation (MAP) from 3.75 and 6.28kg m−2 in the arid and semi-arid regions, respectively to 11.32kgm−2 in the dry sub-humid. Despite lower SOC in the soils of arid region, the highest SICs/SOCs ratio was obtained in the arid climate, which indicates the importance of climate on SIC storage compared to the SOC content. The average times to store SIC in the dry sub-humid, semi-arid and arid regions were calculated as 15,400, 23,100 and 26,000years, respectively; this indicates that SIC is stored more rapidly in wetter climates due to more weathering. SICs constituted the dominant proportion of STCs which decreased by increasing MAP from in the arid region in comparison with other wetter regions (65%, 74.4% and 84.8% in the semi-arid, dry sub-humid and arid regions, respectively).