Semi-arid Climate Zones Research Articles

Enhancing the Energy Efficiency of Buildings by Shading with PV Panels in Semi-Arid Climate Zone

Solar energy is one of the most abundant and available forms of renewable energy. Reliance on the electricity network can be decreased and net-zero energy achieved by mounting photovoltaic power on the tops of houses. Photovoltaic arrays can also change how the roof’s surface reacts to its environment. The influence of the structural system of a roof and weather on the energy consumption of a building is important. This research is concerned with focusing on the indirect effect of solar photovoltaic rooftop panels (shading effect) on the roof surface to see whether this effect is worth studying and calculating the total electrical load in the residential sector. Photovoltaic panels were modeled as a shading device, and the Integrated Environmental Solution-Virtual Environment Software was used to anticipate the monthly decline and growth in heating and cooling loads associated with the roof level. The influence of a photovoltaic system on a building’s roof-related energy load was measured concerning low-rise residential buildings in Mafraq city, which belongs to a mild dry-warm temperature zone. The findings indicated that a solar roof structure decreased heat loss by 4.85% in the summer and boosted heat transfer by 5.54% in the winter. The results highlight that renewable energy is very important in our times due to climate change and the increased demand for electricity by the residential sector, which is stimulated to find multiple ways to decrease and adapt to this change, and the aim of this paper helps to encourage to use solar energy by identifying the indirect effect of solar panels on building’s rooftops. This investigation also focuses on the value of offering essential instructions to who is concerned to the utilization of alternative energy to heat and cool structures, also will educate the public on a building’s total energy requirements, which is critical for future green structure design.

Geographic and seasonal variation in δ13C values of C3 plant arabidopsis: Archaeological implications

Archaeologists frequently rely on carbon isotope data to infer past climates, ecosystems, diets, and mobility patterns. Scientists continue to unravel the intricacies of carbon isotope fractionation in C3 plants, and these data work to improve archaeological interpretations. An important question is how δ13C values of a single species vary with climate across sites, years, or seasons when water may not be the limiting factor, which could have important consequences for archaeological interpretation. This article examines δ13C values of one species of C3 plant, Arabidopsis thaliana, grown across five field sites in Europe over two and a half years. The five field sites (Valencia, Spain; Norwich, UK; Köln, Germany; Halle, Germany; and Oulu, Finland) were chosen to represent A. thaliana's native climate range and include both semi-arid and sub-humid climatic zones; site-specific climatic data were collected for each planting. There were significant differences in δ13C signatures of the A. thaliana plants grown at the different sites (p < 0.001) with higher δ13C values seen at lower latitudes or closer to the coast. Further, there were significant differences between years or seasons at Valencia, Spain (p = 0.001), Norwich, UK (p < 0.001) and Halle, Germany (p < 0.001). Principal component analysis of the planting-level climate data illustrates the interconnectedness of the environmental factors at play while also highlighting the importance of daylength on carbon fractionation during photosynthesis in A. thaliana at these sites.

Sorghum-Based Power Generation in Southern Ukraine: Energy and Environmental Assessment

An increase in energy demand, fossil fuel reserves depletion, and environmental issues are primary reasons for renewable energy use, including power generation. Bioenergy is the primary alternative to conventional hydrocarbon fuels. Biomass-based power generation is increasing due to some reasons, including a gradual decrease in the levelized cost of electricity and a reduction of carbon dioxide emissions. Sorghum is a promising energy crop for semi-arid climate zones, including southern Ukraine. It can be used for both biofuel production and power generation. However, there is a lack of methodology for energy and environmental assessments of sorghum-based power generation. Some possible technologies were analyzed. The novelty of this study is the accounting of energy consumed and carbon dioxide emissions during crop cultivation. We have determined that sorghum-based power plants can generate from 2 to 12 MWh per hectare. Their operation significantly reduces carbon dioxide emissions (from 613 to 3652 kg of carbon dioxide per hectare of sorghum silage cultivation). Sorghum-based biogas plants have energy and environmental advantages if they use co-generation technologies and utilize digestate as a biofertilizer. The utilization of digestate (obtained from silage production per hectare) substitutes up to 12.8 MWh of indirect energy. The results obtained can be used by farmers and authorities for bioenergy development.

Dynamics of Vegetation Productivity in Relation to Surface Meteorological Factors in the Altay Mountains in Northwest China

Vegetation productivity, as the basis of the material cycle and energy flow in an ecosystem, directly reflects the information of vegetation change. At the ecosystem level, the gross primary productivity (GPP) refers to the amount of organic carbon fixed by plant bodies. How to accurately estimate the spatiotemporal variation of vegetation productivity of the forest ecosystem in the Altay Mountains in northwest China has become a critical issue to be addressed. The Altay Mountains, with rich forest resources, are located in a semi-arid climate zone and are sensitive to global climate changes, which will inevitably have serious impacts on the function and structure of forest ecosystems in northwest China. In this paper, to reveal the variation trends of vegetation gross primary productivity (GPP) and its response to surface meteorological factors in the Altay Mountains in northwest China, daily temperature and precipitation data from the period of 2000–2017 were collected from seven meteorological stations in Altay prefecture and its surrounding areas; the data were analyzed by using the MODIS GPP model, moving average trend analysis, linear regression analysis and the climate tendency rate method. The results show that: (1) The spatial distribution pattern of GPP in the whole year was almost the same as that in the growing season of vegetation in the Altay Mountains. In the whole mountain range, the proportion of the area which had a GPP value of 400–600 g c/m2 had the highest value; the proportion of the annual and growing season of this area was 41.10% and 40.88%, respectively, which was mainly distributed in the middle and west alpine areas of the Altay Mountains. (2) There was a big gap in the GPP value in the different stages of the vegetation growing season (April to September), which reached the highest value in July, the area with a GPP of 100–150 g c/m2 was the highest, with 36.15%. (3) The GPP of the Altay Mountains showed an overall increasing trend, but the annual fluctuation was relatively large. In 2003, 2008, 2009 and 2014, the GPP showed lower values, which were 385.18 g c/m2, 384.90 g c/m2, 384.49 g c/m2 and 393.10 g c/m2, respectively. In 2007, 2011 and 2016, the GPP showed higher values, which were 428.49 g c/m2, 428.18 g c/m2 and 446.61 g c/m2. (4) In 64.85% of the area of the Altay Mountains, the GPP was positively correlated with annual average temperature, and in 36.56% of the area, the correlation coefficient between temperature and GPP ranged from −0.2 to 0. In 71.61% of the area of the Altay Mountains, the GPP was positively correlated with annual accumulated precipitation, and in 28.39% of the area, the GPP was negatively correlated with annual accumulated precipitation. Under the scenario of global climate change, our study has quantitatively analyzed the long-term dynamics of vegetation GPP and its responses to meteorological factors in the Altay Mountains, which would be helpful for evaluating and estimating the variation trends of forest ecosystems in China, and has important guiding significance for policy formulation to protect forest resources and improve the local ecological environment.

Vegetation Productivity and Precipitation Use Efficiency across the Yellow River Basin: Spatial Patterns and Controls

In arid and semi-arid climate zones, understanding the spatial patterns and biogeographical mechanisms of net primary production (NPP) and precipitation use efficiency (PUE) is crucial for assessing the function and stability of ecosystem services, as well as directing ecological restoration. Although the vegetation coverage has changed dramatically after the construction of several ecological restoration projects, due to limited observation data, fewer studies have provided a thorough understanding of NPP and PUE’s recent spatial patterns and the controlling factors of different vegetation types in the Yellow River Basin (YRB). To narrow this gap, we integrated remote-sensing land-cover maps with long-term MODIS NPP and meteorological datasets to comprehend NPP and PUE spatial patterns in YRB. Furthermore, we applied structural equation models (SEM) to estimate the effect intensity of NPP and PUE controlling factors. The results showed that along geographical coordinates NPP and PUE decreased from southeast to northwest and trends were roughly consistent along latitude, longitude, and elevation gradients with segmented patterns of increasing and decreasing trends. As for climate gradients, NPP showed significant linear positive and negative trends across the mean annual precipitation (MAP) and the arid index (AI), while segmented changes for PUE. However, the mean annual average temperature (MAT) showed a positive slope for below zero temperature and no change above zero temperature for both NPP and PUE. SEM results suggested that AI determined the spatial pattern of NPP, whereas PUE was controlled by MAP and NPP. As the AI becomes higher in the further, vegetation tends to have decreased NPP with higher sensitivity to water availability. While artificial vegetation had a substantially lower NPP than original vegetation but increased water competition between the ecosystem and human society. Hence further optimization of artificial vegetation is needed to satisfy both ecological and economic needs. This study advanced our understanding of spatial patterns and biogeographic mechanisms of NPP and PUE at YRB, therefore giving theoretical guidance for ecological restoration and ecosystem function evaluation in the face of further climate change.

Spatiotemporal evolutionary and mechanism analysis of grassland GPP in China

At the ecosystem level, Gross Primary Productivity (GPP) was defined as the organic compounds formed by plants that absorb atmospheric CO2 through photosynthesis and sequester carbon in plant bodies. How to accurately assess the spatiotemporal evolution of ecosystem carbon indicators has become a critical issue to be addressed. Chinese grasslands are located in a typical arid and semi-arid climate zone and are sensitive to global changes, which will inevitably have serious impacts on the function and structure of Chinese grasslands. Based on this, our paper takes Chinese grassland ecosystems as the research area, and used multi-source GPP dataset from terrestrial ecosystem model simulations and remote sensing satellite observations to quantitatively analyze the spatiotemporal evolution patterns of GPP in Chinese grasslands over the past 40 years. We combined trend analysis and breakpoint test, and then to analyze the mechanism components of GPP space–time variability. The main results are as follows: (1) The model and remote sensing estimated GPP results showed that more than 80% of Chinese grasslands show a significant increasing trend over the past 40 years, with growth rates ranging from 0.68 to 3.13 g C/m−2 year−1. (2) GPPmax also shows that more than 80% of Chinese grasslands are growing rapidly, with an overall growth rate of more than 0.1 g C/m−2 year−1 in each region. The overall long-term trends and interannual variability of multi-source GPP and GPPmax are generally consistent, yet vegetation dynamics in local areas are still uncertain. (3) The breakpoint test showed that ‘monotonically increasing’ was the largest breakpoint type of GPP in Chinese grasslands (33.09%), and the direction of change of GPP in Chinese grasslands before and after the breakpoint was also increasing. (4) GPPmax × CUP explained 91% of the temporal variability of annual-scale GPP in Chinese grasslands from a mechanistic view, and we found that the peak photosynthetic growth and the length of the phenological period synergistically controlled the interannual variability of GPP in Chinese grasslands. Under the scenario of rapid global change, our study accurately assessed the long-term dynamics of GPP and its mechanism-driven of grassland ecosystems in China, which is helpful for estimating and predicting the carbon budget of grassland ecosystems in China, and has important guiding significance for policy formulation to mitigate climate change.

Impact of tropical convective conditions on solar irradiance forecasting based on cloud motion vectors

Intra-day forecasts of global horizontal solar irradiance (GHI) are widely produced by displacing existing clouds on a geo-stationary satellite image to their future locations with cloud motion vectors (CMVs) derived from preceding images. The CMV estimation methods assume rigid cloud bodies with advective motion, which performs reasonably well in mid-latitudes but can be strained for tropical and sub-tropical climatic zones during prolonged periods of seasonal convection. We study the impact of the South Asian monsoon time convection on the accuracy of CMV based forecasts by analysing 2 years of forecasts from three commonly used CMV methods—Block-match, Farnebäck (Optical flow) and TV-L1 (Optical flow). Forecasted cloud index (CI) maps of the entire image section are validated against analysis CI maps for the period 2018–2019 for forecast lead times from 0 to 5.5 h. Site-level GHI forecasts are validated against ground measured data from two Baseline Surface Radiation Network stations—Gurgaon (GUR) and Tiruvallur (TIR), located in hot semi-arid and tropical savanna climatic zones respectively. The inter-seasonal variation of forecast accuracy is prominent and a clear link is found between the increase in convection, represented by a decrease in outgoing longwave radiation (OLR), and the decrease in forecast accuracy. The GUR site shows the highest forecast error in the southwest monsoon period and exhibits a steep rise of forecast error with the increase in convection. The highest forecast error occurs in the northeast monsoon period of December in TIR. The impact of convection on the number of erroneous time blocks of predicted photovoltaic production is also studied. Our results provide insights into the contribution of convection to errors in CMV based forecasts and shows that OLR can be used as a feature in future forecasting methods to consider the impact of convection on forecast accuracy.

Water mining and landscape: a study on three blocks (Gangajalghati, Mejhia and Saltora) of Bankura, West Bengal, India

Groundwater depletion occurs when the rate of groundwater extraction is higher than the rate of replenishment. It is unequivocal that the demand for fresh water is ever increasing. The study area lies in the semi-arid climatic zone and it's a solely agrarian society. The water scarcity leads to an impact on soil moisture and soil becomes drier during the dry months. The study is based on the changes in the regional water table which exhibit a relatively rapid response to acute scarcity of water. To specify the soil dryness gravimetric method has been used to study the selected soil samples. The groundwater withdrawal without estimating the water requirement at the regional level leads to soil dryness, and water stress situation to the agrarian economy, and it leaves a direct impact on the land. The perception of the farm owner, that ownership of farmland is synonymous with water mining right from their land leads to stress on the water table.

Computational modeling of a PV-PCM passive cooling system during a day–night cycle at arid and semi-arid climate zones

This work investigates the use of phase change materials (PCMs) as a passive cooling system to increase the electric power generation of photovoltaic panels (PV) by a reduction of the temperature of the panels. This study aims to evaluate different configurations of PV-PCM cooling systems, by changing the phase change material, to achieve a high efficiency in a silicon PV. Each configuration is studied for three day–night cycles under seasonal variable atmospheric conditions. Two Chilean cities with a semi-arid climate and arid climate – Vicuña and Calama, respectively – were selected as the study locations. The development of the PV-PCM improved system is carried out by solving the unsteady thermal energy equation with computational simulations using the finite volume method (FVM). An Enhanced Conduction Model (ECM) was used to include the convective heat transfer in the melted PCM. The ECM was validated against numerical values of a PV-PCM system finding a maximum deviation for the PV frontal temperature of 1.23 °C. The numerical model was validated with experimental and numerical results of a PV-PCM system during a 24-hour cycle with time-varying atmospheric conditions. The results obtained indicate that the use of phase change materials as a cooling system decreases up to 17.5 °C the temperature at the PV, diminishing the losses of efficiency and increasing the generation of electricity. The electrical production in one year increases by 5.8% for Vicuña and 4.5% for Calama when a layer of CaCl2–6H2O with a thickness of 40 mm is used.

Assessing Spatial and Temporal Changes of Natural Capital in a Typical Semi-Arid Protected Area Based on an Ecological Footprint Model

Exploring spatial and temporal changes in protected areas (PAs) is essential for protecting natural capital and creating a harmonious relationship between humans and nature. This study has assessed land use/land cover (LULC) changes in the Jajrud, a Protected Area with a semi-arid climate zone in Iran (covers an area of 18,814 km2), to assess the sustainability of the use of natural resources using Landsat imagery from 1989 to 2018. Likewise, Ecological Footprint accounts (including the sum of biological, freshwater, energy, and pollution) and changes in the per-capita Ecological Carrying Capacity were investigated to uncover Ecological Deficits. The Ecological Pressure Index was used to explore driving factors of natural capital utilization in each of the various identified zones. Between 1989 and 2018, high-density pastures decreased the most in Jajrud, while built-up land increased the most. Likewise, the Ecological Footprint increased while the Ecological Carrying Capacity decreased, increasing Ecological Deficit quantities. Driving factors for the use of natural capital differs among the various zones due to differing management goals, type of uses, and human activity development. As supply and demand for natural resources were clearly out of an imbalance between the supply and demand of natural resources and exceeded the maximum tolerable limits in Jajrud, a change in production and consumption patterns is necessary. This case study has practical importance for establishing mathematical models to reveal the patterns of LULC, ecological footprint, ecological deficit, and ecological pressure indices in a typical PA in a semi-arid region of Iran. Our approach is advisable for semi-arid PAs in Iran and regions with similar attributes in other countries.

Changes in soil C–N–P stoichiometry after 20 years of typical artificial vegetation restoration in semiarid continental climate zones

Vegetation restoration is one of the principal strategies for ecosystem recovery in degraded land of fragile regions, which is an important driving factor for soil fertility and elemental circulation. While the relationship between revegetation and soil C–N–P stoichiometry remains unclear. To evaluate the relationships between vegetation restoration and soil C–N–P stoichiometry, the distribution of soil C, N, and P within 0–30 cm soil depth under five typical artificial restored vegetation types on the Loess Plateau was analyzed and the influencing factors were evaluated. The results showed that soil C, N, and P contents were relatively lower at the study site than the mean values for topsoil in China. Compared with other vegetation types (Populus simonii Carr., Pinus tabuliformis Carr., and Caragana korshinskii Kom.), Medicago Sativa L. and Stipa bungeana Trin. helped improve soil fertility better; the soil organic carbon (SOC), total nitrogen (TN), and total phosphorus (TP) contents within the 0–30 cm soil layer respectively maximized under Stipa bungeana Trin. (3.30 g kg−1), Medicago Sativa L. (0.34 g kg−1), and Medicago Sativa L. (0.41 g kg−1). The values of soil C/N, C/P, and N/P for the five vegetation types were 9.50–11.85, 15.36–21.47, and 1.29–1.90, respectively. The contents of SOC and TN under the five vegetation types were significantly (P < 0.001) affected by soil depth and vegetation type (P < 0.001) and decreased with increasing soil depth. However, the TP content was significantly (P < 0.001) affected by vegetation type and not by soil depth. Considering the better adaptability of native species, native herb vegetation types should be considered first for ecological restoration in semiarid continental climate zones.

Quantification of water requirement of some major crops under semi-arid climate in Turkey.

The Southeastern Anatolian Region of Turkey is located in semi arid climate zone and therefore requires an efficient water use. Well-planned irrigation with optimum water required by the crops is essential for the limited water resources of the region. The numerical tool CROPWAT of the Food and Agriculture Organization (FAO) was used for modelling efficient irrigation of local crops pistachio, olive, almond and grape without reducing the yield. Local climatic, soil, plant and rainfall information were used as inputs to CROPWAT model to predict the reference evapotranspiration (ETo) values. The crop water requirement (CWR) for pistachio, olive, almond, and grape was calculated as 1,294.0 mm, 659.4 mm, 790.2 mm, and 752.0 mm, respectively, The number of irrigation needed during growth stages was determined as eight for pistachio, three for olive, six for almond and five for grape.

Calculation of rainwater harvest in greenhouses for semi-arid and continental climate zones

In this study, it is aimed to determine the irrigation water required due to solar radiation in high technology greenhouses where soilless cultivation is carried out according to TS825 standards, and to determine the annual water consumption and storage capacity with the harvested rainwater. As a result of the calculations made for Turkey Mediterranean region, it has been determined that if 90% of the rainfall in the western Mediterranean region is harvested, 72% of the annual water consumption can be met, and 45% in the eastern Mediterranean region. In the inner regions where the terrestrial climate is dominant, 22%–32% of the annual water consumption can be met with 90% of the rain harvested depending on the amount of rainfall. The required storage volume in the western Mediterranean is 0.420 m3 .m-2, while it is 0.096 m3.m-2 in the eastern Mediterranean and 0.044 m3.m-2 in Kırşehir, where the continental climate prevails.

A 30,000-km journey by Apus apus pekinensis tracks arid lands between northern China and south-western Africa

BackgroundAs a widely distributed and aerial migratory bird, the Common Swift (Apus apus) flies over a wide geographic range in Eurasia and Africa during migration. Although some studies have revealed the migration routes and phenology of European populations, A. a. apus (from hereon the nominate apus), the route used by its East Asian counterpart A. a. pekinensis (from hereon pekinensis) remained a mystery.MethodsUsing light level geolocators, we studied the migration of adult pekinensis breeding in Beijing from 2014 to 2018, and analysed full annual tracks obtained from 25 individuals. In addition, we used the mean monthly precipitation to assess the seasonal variations in humidity for the distribution ranges of the nominate apus and pekinensis. This environmental variable is considered to be critically relevant to their migratory phenology and food resource abundance.ResultsOur results show that the swifts perform a round-trip journey of ca 30,000 km each year, representing a detour of 26% in autumn and 15% in spring compared to the shortest route between the breeding site in Beijing and wintering areas in semi-arid south-western Africa. Compared to the nominate apus, pekinensis experiences drier conditions for longer periods of time. Remarkably, individuals from our study population tracked arid habitat along the entire migration corridor leading from a breeding site in Beijing to at least central Africa. In Africa, they explored more arid habitats during non-breeding than the nominate apus.ConclusionsThe migration route followed by pekinensis breeding in Beijing might suggest an adaptation to semi-arid habitat and dry climatic zones during non-breeding periods, and provides a piece of correlative evidence indicating the historical range expansion of the subspecies. This study highlights that the Common Swift may prove invaluable as a model species for studies of migration route formation and population divergence.

Spatial and temporal variations of rainfall erosivity in the middle Yellow River Basin based on hourly rainfall data

Understanding spatial and temporal variations in rainfall erosivity is essential for estimating the variability in soil erosion. However, rainfall erosivity in the middle Yellow River Basin is usually calculated based on daily rainfall data, which fails to consider the impact of the changing rainfall intensity at the subdaily scale. In this study, we collected hourly rainfall data from 355 meteorological stations within and around the region to calculate rainfall erosivity during 1960–2017. We found that the rainfall erosivity calculated based on hourly data had much larger variability than that calculated based on daily data, and the calculated spatial and temporal variability were substantially different in periods when the rainfall intensity was highly variable. Based on our new estimation, we found that the spatial distribution of rainfall erosivity was highly heterogeneous, with high erosivity values in the Loess Regions and Rocky Mountain Regions with high soil erodibility and low erosivity values in the Aeolian Regions and Soft Sandstone Regions with low soil erodibility. This heterogeneity was mainly due to the distinct spatial distribution patterns of rainfall amount and rainfall intensity. Although the long-term increasing trend of rainfall erosivity was statistically insignificant from 1960 to 2017, its rate of increase was higher than that of the annual rainfall amount. Decadal changes showed a slight decrease from the 1960 s to the 1980 s and an increase since the 1990 s, which was substantially different from the decadal changes in the annual rainfall amount. These differences in temporal variability were mainly caused by the contribution of changing rainfall intensity, which was greater in the Aeolian Regions and Soft Sandstone Regions than in the other subregions. Our study highlighted the importance of considering the changing rainfall intensity at a subdaily scale in semiarid and semihumid climate zones and provided the first estimation of the long-term variability in rainfall erosivity based on hourly rainfall data in this region.

Eco-biophysical indicators to ascertain the sustainability aspect of world's primitive hills range using time-series MODIS data products

In India's semi-arid climatic zone, the Aravalli hills range is an ecotone between the Thar Desert and the Gangetic plain, covering about 10% of the forest cover of Western India. Notably, the upper range of the hills has a high population density; this range has encountered substantial areal transformation in the last five decades. However, we believe that the enhancement of green cover within this range has occurred primarily due to discontinuous degradation within the entire range, without geographical alteration. We use MODIS products to compare and contrast spatiotemporal ecological dynamics between different sub-ranges (upper, middle, and lower) of Aravalli between 2000 and 2019. Specifically, we adopt seven eco-biophysical parameters that include EVI, LAI, PTC, PNTV, ET, NPP, and LST. Pixel-based time-series trend evaluation for MODIS imagery composite within the GEE platform, using the Ordinary Least Square (OLS) regression method identified that forest enhancement is experienced in some parts of different ranges. We also observed some human-induced factors and natural stressors that could possibly be responsible for forest health dynamics. Thus, we suggest sustainable planning and policy changes for people who are under anthropocentric stress; this we believe, would help management practices.

Associations between temperature and Ross river virus infection: A systematic review and meta-analysis of epidemiological evidence

Ross River virus (RRV) infection is one of the emerging and prevalent arboviral diseases in Australia and the Pacific Islands. Although many studies have been conducted to establish the relationship between temperature and RRV infection, there has been no comprehensive review of the association so far. In this study, we performed a systematic review and meta-analysis to assess the effect of temperature on RRV transmission. We searched PubMed, Scopus, Embase, and Web of Science with additional lateral searches from references. The quality and strength of evidence from the included studies were evaluated following the Navigation Guide framework. We have qualitatively synthesized the evidence and conducted a meta-analysis to pool the relative risks (RRs) of RRV infection per 1 °C increase in temperature. Subgroup analyses were performed by climate zones, temperature metrics, and lag periods. A total of 17 studies met the inclusion criteria, of which six were included in the meta-analysis The meta-analysis revealed that the overall RR for the association between temperature and the risk of RRV infection was 1.09 (95% confidence interval (CI): 1.02, 1.17). Subgroup analyses by climate zones showed an increase in RRV infection per 1 °C increase in temperature in humid subtropical and cold semi-arid climate zones. The overall quality of evidence was "moderate" and we rated the strength of evidence to be "limited", warranting additional evidence to reduce uncertainty. The results showed that the risk of RRV infection is positively associated with temperature. However, the risk varies across different climate zones, temperature metrics and lag periods. These findings indicate that future studies on the association between temperature and RRV infection should consider local and regional climate, socio-demographic, and environmental factors to explore vulnerability at local and regional levels.

Response of Potential Evapotranspiration to Warming and Wetting in Northwest China

In the last few decades, the climate in Northwest China has exhibited a warming–wetting tendency, which has been particularly prominent since the beginning of the 21st century. In this context, we analyzed the change in potential evapotranspiration (PET)in the corresponding period and its response to warming and wetting, which revealed clear periodic changes. The most significant changes occurred in the 1970s and 1980s, when PET decreased in the humid climate zone and increased in the semi-arid climate zone. Factor effect analysis showed that PET had a positive response to temperature; the highest and lowest temperatures in the region continued to rise. Relative humidity reduced the overall PET in the region, especially in the humid zone. Sunshine duration has continued to decrease rapidly since the 1980s, especially in humid and arid zones, resulting in a corresponding decrease in PET. Similarly, corresponding to the consistent wind speed decrease, there has also been a significant decrease in PET, with the largest decrease in the arid zone, followed by the humid zone. In general, PET in the central and eastern parts of Northwest China has mainly been affected by the temperature, whereas wind speed has been the main factor in the western part of the region. Relative humidity and sunshine duration have had relatively little effect on the PET (below 20% in most places). The reasons and processes that affect PET are very complicated. Owing to the unique climate characteristics and underlying surface energy mechanisms in Northwest China, it is still difficult to offer a scientific explanation for its warming and wetting. Therefore, the extent to which PET impacts climate change in this region is currently unclear, and systematic and scientific research on this is needed.

Comparison of soil production, chemical weathering, and physical erosion rates along a climate and ecological gradient (Chile) to global observations

Abstract. Weathering of bedrock to produce regolith is essential for sustaining life on Earth and global biogeochemical cycles. The rate of this process is influenced not only by tectonics, but also by climate and biota. We present new data on soil production, chemical weathering, and physical erosion rates from the large climate and ecological gradient of the Chilean Coastal Cordillera (26 to 38∘ S). Four Chilean study areas are investigated and span (from north to south) arid (Pan de Azúcar), semi-arid (Santa Gracia), Mediterranean (La Campana), and temperate humid (Nahuelbuta) climate zones. Observed soil production rates in granitoid soil-mantled hillslopes range from ∼7 to 290 t km−2 yr−1 and are lowest in the sparsely vegetated and arid north and highest in the Mediterranean setting. Calculated chemical weathering rates range from zero in the arid north to a high of 211 t km−2 yr−1 in the Mediterranean zone. Chemical weathering rates are moderate in the semi-arid and temperate humid zones (∼20 to 50 t km−2 yr−1). Similarly, physical erosion rates are lowest in the arid zone (∼11 t km−2 yr−1) and highest in the Mediterranean climate zone (∼91 t km−2 yr−1). The contribution of chemical weathering to total denudation rates is lower in the arid north than further south. However, due to heterogeneities in lithologies and Zr concentrations, reported chemical weathering rates and chemical depletion fractions are affected by large uncertainties. Comparison of Chilean results to published global data collected from hillslope settings underlain by granitoid lithologies documents similar patterns in soil production, chemical weathering, and total denudation rates for varying mean annual precipitation and vegetation cover amounts. We discuss the Chilean and global data in the light of contending model frameworks in the literature and find that observed variations in soil production rates bear the closest resemblance to models explicitly accounting for variations in soil thickness and biomass.

Identifying Potential Planting Sites for Three Non-Native Plants to Be Used for Soil Rehabilitation in the Tula Watershed

The Tula watershed in Mexico, located in a semiarid and sub-humid climate zone, is experiencing intensive population growth, the expansion of mining concessions for construction materials, and agricultural and urban development, resulting in the degradation of soils and vegetation and a greater demand on natural resources. The aims of this study were to evaluate the survival rates and identify potential habitats within the Tula watershed for planting three non-native forage species (Atriplex canescens, Cynodon dactylon, and Leucaena collinsii) using the Kaplan-Meier estimator and the MaxEnt model with the purpose of rehabilitating degraded soils via agroforestry systems. There were 19 edaphoclimatic variables used and the occurrences of three species, obtained from the GBIF, MEXU, and SNIB databases. The models generated with MaxEnt were very accurate (area under the curve [AUC] ≥ 0.7). The species Atriplex canescens and Cynodon dactylon showed areas of potential planting sites (&gt;0.4) and high survival rates (80% and 92%, respectively). The species Leucaena collinsii presented areas with lower potential planting (&lt;0.4) but registered the greater survival rate (100%). The results provide a solid basis to evaluate the survival rates of forage species within potential planting sites in the Tula watershed using agroforestry systems to rehabilitate degraded soils.