Relative Importance Of Climatic Factors Research Articles

Elevational shift in seed plant distributions in China's mountains over the last 70 years

AbstractAimSignificant changes in species elevational ranges in mountains have been repeatedly documented, yet the direction, magnitude and drivers of these shifts remain controversial. Presently, there is still lacking evidence about the general nature of species elevational range shifts in eastern Eurasia in response to anthropogenic climate change. By using historical specimen records and recent field observations for 735 seed plant species across 29 China's mountains, we assessed changes in species' elevational centroids and their drivers.LocationChina.Time Period1950–2018.Major Taxa StudiedSeed plant species.MethodsThe elevation records of all sampled occurrences in each mountain during the two time periods were estimated, and the null models were developed to test the sampling bias. Ecological niche models (ENMs) were used to evaluate the relative importance of climate factors in constraining each species distribution. Generalized linear models (GLMs) to test the relationships between the centroid elevational range shifts of species and different divers.ResultsWe found that 54% of the species shifting upward and 46% downhill. However, species' elevational shifts significantly differed among species and mountains. Herbaceous and lowland species moved upward faster than woody and high‐elevation species. Species in temperate mountains and in mountains with taller elevational gradients moved upward, while species in subtropical mountains and in mountains with shorter elevational gradients moved downward. Precipitation changes experienced by species, species' climatic adaptations, several species' functional traits and mountain size all contributed to explain the magnitude of species' centroid elevational range shifts.Main ConclusionsOur results highlight complex biodiversity redistribution of seed plants across Chinese mountains, not necessarily conforming to the trend of species upward shifts in elevation. Changes in precipitation regimes may blur the simplistic assumption of isotherm tracking. This study fills an important geographic shortfall for our understanding of biodiversity redistribution under anthropogenic climate change.

Multiple factors induce temporal shifts in herbaceous plant leaf senescence dates on the Qinghai–Tibetan Plateau

Plant autumn phenology affects ecosystem carbon and water cycles. However, autumn phenological shifts of herbaceous plants and their primary regulators on the Qinghai–Tibetan Plateau (QTP) remain uncertain because previous studies were mainly based on remote sensing data. Studies using ground autumn phenological data observed at many stations are very few. This study explored the primary drivers of temporal shifts in leaf senescence date (LSD) and assessed the relative importance of climatic factors and spring phenophases to LSD shifts using correlation analysis, general linear regression, and partial least squares regression based on 1685 phenological records at 27 stations on the QTP. Results showed that, preseason total precipitation (PRE) and minimum air temperature (Tmin) had higher correlation coefficients with LSD and displayed more extensive importance in predicting LSD than other factors. Despite larger influences, contributions of PRE and Tmin to LSD inter-annual variations were only 14.9% and 14.2%, respectively. In total, PRE and air temperatures (TEMs) just explained 38.0% of LSD temporal shifts. These results indicate that although PRE and TEMs are the major regulators of LSD, temporal shifts in LSD are controlled by multiple factors. Overall, climatic factors and spring phenology contributed 53.7% and 15.6% to LSD variations, respectively, which means that climate change obviously outweighed spring phenology in driving LSD shifts. Our study revealed a critical role of PRE in regulating LSD shifts directly or indirectly by enhancing the sensitivity of LSD to TEMs. Moreover, we found that the impacts of precipitation change were more prominent on LSD of sedges than those of grasses and forbs. Therefore, we suggest that accurate autumn phenological models for plants on the QTP should include multiple factors and incorporate the influences of precipitation. This study can also provide insight into QTP grassland management from the perspective of phenological responses to climate change.

Snow depth alteration and its relation with climate variability in China

AbstractVarious climatic factors and their interactions affect China's snow depth alterations. However, a measure of the relative importance of climatic factors regarding the variance in snow depth is lacking. Here, we use a heretofore largest dataset, quality‐controlled daily observations from 1,665 meteorological stations, and statistical analyses to identify proxy drivers and their contributions regarding regional variability and trends in China's snow depth and snow depth‐climate relationships from 1951 to 2019. Results show that seasonal snow depth alterations are substantial in China and caused by various climatic drivers. In winter, observed positive trends in the northwest and northeast of China mainly respond to augmentation in solid precipitation and snow accumulation in fall. For the Tibetan Plateau, the negative snow depth anomaly seems to respond to the rising air temperature below the freezing point along with some secular changes in solid precipitation and shallower fall snowpacks. All these trends in winter snow depth over the northwest, northeast, and Tibetan Plateau of China account approximately for 30% of the total interannual variance in spring snow depth in these regions. In the milder central north and south of China, snow accumulation is not evident. Besides solid precipitation and rising air temperature below the freezing point, atmospheric humidity is also notable for its effect on the interannual variance in winter snow depth in these regions. In spring and fall, however, the negative effect of warming climate on snow depth becomes remarkably more important. It seems that about 13–33% (12–50%) of the total interannual variance in the widespread decrease (insignificant perturbation), except for some weak increases in the northeast region (decreases in the Tibetan Plateau), of China's spring (fall) snow depth are caused by the rising air temperature below the freezing point.

Assessment of Climatic Impact on Vegetation Spring Phenology in Northern China

Spring phenology is often considered the start of season (SOS) for vegetation, which can affect ecosystem photosynthesis, respiration, and evapotranspiration. However, the long-run variation of SOS remains unclear at the regional scale. In this research, the long-term variation of SOS in northern China was explored by using the updated normalized difference vegetation index and monthly climatic data during 1982–2014. Furthermore, the relative importance of climatic factors on SOS was analyzed through partial correlation and multivariate regression methods. The main results were as follows: (1) average SOS largely ranged between day 120 and 165 of the year and varied widely for different vegetation types; (2) SOS during 1982–2014 showed an advancing trend, but it appeared to be reversed after 1998; (3) preseason minimum temperature was a dominant factor controlling SOS in most pixels in northern China, followed by maximum temperature (Tmx). However, impacts of radiation and precipitation on the trend of SOS primarily depended on vegetation types; (4) impacts of climatic factors on SOS declined in the period after 1998, especially for Tmx. These findings provide important support for modeling vegetation phenology and growth in northern China.

Precipitation consistently promotes, but temperature inversely drives, biomass production in temperate vs. alpine grasslands

Comparisons of vegetation production between temperate and alpine grasslands are not well studied, and the understanding of the underlying mechanisms is still incomplete. To address this issue, we selected the Inner Mongolia and Tibet regions to conduct large-transect surveys for temperate grassland (TG) and alpine grassland (AG), respectively, in China, to reveal the universal and differential mechanisms of above- and belowground biomass production (GB, AGB and BGB) and precipitation use efficiencies (PUE) in the two grasslands. The relative importance of climatic factors on biomass and PUE is greater than that of soil and biological factors. Elevated mean annual precipitation (MAP) consistently increased GB in both TG and AG. Increased mean annual temperature (MAT) reduced GB by weakening the soil nutrient status in TG, whereas it increased GB by improving the soil nutrient status in AG. MAP promoted more AGB than BGB in TG, whereas MAT affected BGB more than AGB in AG. When the multicomponent heterogeneity of other factors in grasslands was eliminated, the effect of MAP on GB remained significant for both TG and AG. After removing the effect of multifactorial heterogeneity, however, the significant effect of MAP on PUE of the two grasslands was largely enhanced. From these results, we can conclude that climatic factors do not always exert identical effects on different grasslands. In particular, highlighting the divergent mechanisms of biomass production and precipitation use efficiency between temperate and alpine grasslands can improve the understanding of the carbon sink and hydraulic sensitivity of various grasslands.

Habitats modulate influencing factors shaping the spatial distribution of bacterial communities along a Tibetan Plateau riverine wetland

The Tibetan Plateau riverine wetland is very sensitive to global climate change. Understanding the mechanisms that maintain the spatial patterns of bacterial communities provides insight into the dominant biogeochemical processes within the plateau riverine wetlands. Nonetheless, the spatial distribution of bacterial communities along these wetlands has rarely been explored. We investigated the spatial patterns of bacterial community within rhizosphere soil, bulk soil, and sediment samples collected along the Yarlung Tsangpo riverine wetland (YTRW), the longest plateau riverine wetland in China. Our results indicated that the diversity of bacterial communities in all three habitats increased significantly along the YTRW. The slope of the linear relationship between distance and bacterial community diversity in sediment was steeper than those for bulk and rhizosphere soils. Furthermore, bacterial communities in all three habitats showed significant distance–decay relationships. A combination of historical factors (geographical distance and climatic factors) and contemporary environmental heterogeneity (edaphic properties) controlled spatial distributions of bacterial communities in all three habitats, although climatic factors were predominant. Climatic factors affected rhizosphere bacterial communities more than those in bulk soil and sediment. Co-occurrence network analysis revealed that the potential interactions between bacterial taxa may decrease along the YTRW. This field investigation highlighted that the climatic factors strongly influenced the spatial distribution of bacterial communities along the YTRW; however, habitat differences among rhizosphere soil, bulk soil, and sediment samples affected the relative importance of climatic factors on spatial distributions of the associated bacterial communities. These findings would improve the understanding of biogeochemical processes in these typical habitats and potential alterations provoked by climate change.

Soil water retention capacity surpasses climate humidity in determining soil organic carbon content but not plant production in the steppe zone of Northern China

Soil hydraulic properties determine water transport, distribution and storage in soils, thus affect ecosystem functioning. Soil water retention parameters, such as saturation water content (SAT), water drained upper limit (DUL) and lower limit (DLL), characterize soil water-holding capacity, thus are important for plant growth and carbon and nutrient cycling in grassland ecosystem. However, we are still unclear to what a content these soil water retention parameters may regulate plant production and soil organic matter content in natural ecosystems in semi-arid grassland environment. We investigated plant species richness (SR) and aboveground biomass (AGB), soil organic carbon (SOC) and nitrogen (SON) contents, and soil water retention and other physical parameters in the steppe ecosystems along a climate transect, which spans the desert steppe, typical steppe and meadow steppe zones in Northern China. We analyzed the relative importance of climate factors, soil water retention parameters and other soil physical parameters in regulating plant AGB and SOC and SON contents using partial correlation analysis, and quantified the contribution of each separate and combined climate and soil physical parameters in predicting plant AGB and SOC and SON contents using geographic detectors method. We found that (i) plant SR and AGB, soil SAT and DUL, and SOC and SON are all significantly inter-correlated, and increased with the increase of climate humidity. (ii) Climate, but not soil physical parameters, was the most preponderant factor in predicting plant SR and AGB. (iii) Soil physical parameters were more important than climate parameters in regulating soil organic matter content; soil DUL was the best predictor to SOC content. Our results suggest that soil water retention parameters especially soil DUL, may play a greater role than climate factors in modulating SOC content, though climate is more predominant in regulating plant SR and production. Our results imply that we need to be cautious in estimating SOC content based on climate factors and vegetation biomass or remotely-sensed vegetation indices, and that soil physical properties need also to be incorporated along with vegetation parameters for improving SOC estimation at a regional scale.

Characteristics and driving factors of lake level variations by climatic factors and groundwater level

Hongjiannao Lake (HL), the largest desert freshwater lake in China, has been undergoing quickly evolution of lake area during the past 30 years. The causes and driving mechanism of such changes, however, are still not well understood. The evolution process can be divided into three phases: the stationary phase, the shrinking phase, and the rising phase, which were affected by climate change and human activities, such as unreasonable utilization and water diversion. Here, wavelet coherence was used to analyze the relationship between the groundwater level and the lake level, and the results shown that groundwater levels in the lakeshore region were positively correlated to lake level within a short lag period of approximately 30 days. Then a gradient boosting decision tree-based regression model was applied to analyze the relative importance of climatic factors (model 1) and both of climatic factors and groundwater level (model 2) to the lake level. In model 1, the most important factor was the evaporation to the HL level, while in model 2, it was the groundwater level and the evaporation, which also achieved better prediction performance. Finally, using the 2021 meteorological data and groundwater level, model 2 was utilized to dynamically predict the daily water level of the HL, showing that the lake level fluctuated upward.

Phenology-based seasonal terrestrial vegetation growth response to climate variability with consideration of cumulative effect and biological carryover

Vegetation growth is influenced not only by climate variability but also by its past states. However, the differences in the degree of the climate variability and past states affecting vegetation growth over seasons are still poorly understood, particularly given the cumulative climate effects. Relying on the Normalized Difference Vegetation Index (NDVI) data from 1982 to 2014, the vegetation growing season was decomposed into three periods (sub-seasons) - green-up (GSgp), maturity (GSmp), and senescence (GSsp) - following a phenology-based definition. A distributed lag model was then utilized to analyze the time-lag effect of vegetation growth response to climatic factors including precipitation, temperature, and solar radiation during each sub-season. On this basis, the relative importance of climatic factors and vegetation growth carryover (VGC) effect on vegetation growth was quantified at the phenology-based seasonal scale. Results showed that the longest peak lag of precipitation, temperature, and solar radiation occurred in the GSmp, GSsp, and GSgp, with 1.27 (1.13 SD), 0.89 (1.02 SD), and 0.80 (1.04 SD) months, respectively. The influence of climate variability was strongest in the GSgp, and diminished over the season, while the opposite for the VGC effect. The relative influence of each climatic factor also varied between sub-seasons. Vegetation in more than 58% of areas was more affected by temperature in the GSgp, and the proportion decreased to 34.00% and 31.78% in the GSmp and GSsp, respectively. Precipitation and solar radiation acted as the dominant climatic factors in only 28.80% and 20.88% of vegetation areas in the GSgp, but they increased to 35.21%, 32.61% in the GSmp, and 38.20%, 30.02% in the GSsp, respectively. The increased regions influenced by precipitation were mainly in dry areas especially for the boreal and cool temperate climate zones, while increased regions influenced by solar radiation were primarily located in moist areas of mid-high latitudes of the Northern Hemisphere. By introducing the cumulative climate effect, our findings highlight seasonal patterns of vegetation growth affected by climate variability and the VGC effect. The results provide a more comprehensive perspective on climate-vegetation interactions, which may help us to accurately forecast future vegetation growth under accelerating global warming.

Analysis of drought events and their impacts on vegetation productivity based on the integrated surface drought index in the Hanjiang River Basin, China

Accurately monitoring the spatial-temporal distribution of drought events is helpful for reducing the meteorological risk. The monthly integrated surface drought index (mISDI) dataset of the Hanjiang River Basin (HJRB) from 2001 to 2017 was established by using the Cubist algorithm, and the Run theory was applied to identify and characterize the drought events. Two gross primary productivity (GPP) datasets, obtained from the Global Land Surface Satellite (GLASS GPP) program and the Numerical Terradynamic Simulation Group (NTSG GPP), were used to investigate the impact of drought events on GPP changes and the relative importance of climate factors in GPP changes. The results showed that (1) the mISDI had good accuracy and reliability in drought events monitoring (R = 0.95; MAE = 0.503; RMSE = 0.707). The problem of missing land surface temperature data was solved, and the filled LST dataset has good accuracy. In addition, the model accuracy was significantly improved by using the time variables; (2) Five drought events were identified by using the Run theory, and the drought event occurred from August 2013 to August 2014 had the largest drought intensity (1.309) and drought affected area (81.12%). Spatially, the western HJRB had more frequent droughts than the eastern region, but the eastern HJRB had longer average drought duration and higher mean drought intensity and severity; (3) During the drought event occurred from August 2013 to August 2014, mainly occurred in the eastern basin. The correlation between GLASS GPP anomalies and mISDI (R = 0.553, p < 0.05) was greater than that between NTSG GPP anomalies and mISDI (R = 0.324, p > 0.1). The decreased area of GLASS GPP (78.36%) was larger than that of NTSG GPP (49.08%), both were mainly distributed in the eastern HJRB. Among different climate factors, temperature was an important drought factor affecting GPP changes. This study provides a good way to understand the evolution process of drought events and the impact of drought events on vegetation productivity.

Impact of Agricultural Weathering on Physicochemical Properties of Biodegradable Plastic Mulch Films: Comparison of Two Diverse Climates Over Four Successive Years

Biodegradable plastic mulch films (BDMs) are essential in the production of vegetable and specialty crops due to their promotion of increased crop yield and quality. Unlike conventional polyethylene (PE) mulches, BDMs can be tilled into the soil after crop harvest to undergo biodegradation, thereby leading to minimal environmental impact. Agricultural weathering impacts both the performance of BDMs during crop production as a barrier to weeds and biodegradability of BDMs in the soil. To better understand the relative importance of climatic factors, the change of physicochemical properties of BDMs during single-season, 3–4 month, field trials for vegetable production at two diverse climates (Knoxville, TN and Mount Vernon, WA) across four successive years (2015–2018) was evaluated. Mulch treatments consisted of four commercially available BDMs composed primarily of polybutylene co-adipate- co-terephthalate (PBAT) that differed in color and polymeric feedstock, a black experimental BDM prepared from polylactic acid/polyhydroxybutyrate (PLA/PHA) blend, and conventional PE mulch. Solar radiation, an important factor to degradation of mulches, was higher in WA than TN in most sampling years. Yet, degradation occurred more greatly for BDMs in TN, which is attributable to higher temperatures in TN. Mulch deterioration did not very extensively between years. Loss of mechanical properties and color was greater than chemical property changes. Differences in the extent of molecular weight decrease between years correlated significantly with solar radiation exposure at the two locations. A black-colored PBAT-based BDM was less susceptible to degradation than equivalent clear and white-on-black films, due to carbon black acting as a photostabilizer. The impact of weathering also differed between three commercially available PBAT-based films. The PLA/PHA mulch was more susceptible to degradation than PBAT-based BDMs, particularly in the warmer location, TN, partially due to a leaching out of PHA and lower-molecular weight polymer molecules. The extent of change for physicochemical properties of BDMs due to agricultural weathering is greatly affected by polymeric composition, and is greater in warmer climates.

Spatiotemporal Variation of Vegetation Coverage and Its Response to Climate Factors and Human Activities in Arid and Semi-Arid Areas: Case Study of the Otindag Sandy Land in China

Vegetation coverage is a key variable in terrestrial ecosystem monitoring and climate change research and is closely related to soil erosion and land desertification. In this article, we aimed to resolve two key scientific issues: (1) quantifying the spatial-temporal vegetation dynamics in the Otindag Sandy Land (OSL); and (2) identifying the relative importance of climate factors and human activities in impacting vegetation dynamics. Based on correlation analysis, simple regression analysis, and the partial derivative formula method, we examined the spatiotemporal variation of vegetation coverage in the OSL, belonging to the arid and semiarid region of northern China, and their interaction with climate-human factors. The results showed that the vegetation coverage of the area showed a downward trend with a rate of −0.0006/a during 2001–2017, and gradually decreased from east to west. Precipitation was the main climate factor controlling the overall distribution pattern of vegetation coverage, while the human factors had a more severe impact on the vegetation coverage than the climate factors in such a short period, and the overall impact was negative. Among the human factors, population pressure, urbanization, industrialization, pastoral production activities, and residents’ lifestyles had a negative impact. However, ecological restoration polices alleviated the contradiction between human development and vegetation deterioration. The results of this article provide a scientific basis for restoring grassland systems in arid and semi-arid areas

Snowpack determines relative importance of climate factors driving summer lake warming

AbstractMountain lakes experience extreme interannual climate variation as well as rapidly warming air temperatures, making them ideal systems to understand lake‐climate responses. Snowpack and water temperature are highly correlated in mountain lakes, but we lack a complete understanding of underlying mechanisms. Motivated by predicted declines in snowfall with future temperature increases, we investigated how surface heat fluxes and lake warming responded to variation in snowpack, ice‐off, and summer weather patterns in a high elevation lake in the Sierra Nevada, California. Ice‐off timing determined the phenology of lake exposure to solar radiation, and was the dominant mechanism linking snowpack to lake temperature. The relative importance of heat loss fluxes (longwave radiation, latent and sensible heat exchange) varied among wet and dry years. Declines in snowpack and ice cover in mountain systems will reduce variability in lake thermal responses and increase the responsiveness of lake warming to atmospheric forcing.

Amazonian rainforest tree mortality driven by climate and functional traits

Tree mortality appears to be increasing in moist tropical forests1, with potentially important implications for global carbon and water cycles2. Little is known about the drivers of tree mortality in these diverse forests, partly because long-term data are lacking3. The relative importance of climatic factors and species functional traits as drivers of tropical tree mortality are evaluated using a unique dataset in which the survival of over 1,000 rainforest canopy trees from over 200 species has been monitored monthly over five decades in the Central Amazon. We found that drought, as well as heat, storms and extreme rainy years, increase tree mortality for at least two years after the climatic event. Specific functional groups (pioneers, softwoods and evergreens) had especially high mortality during extreme years. These results suggest that predicted climate change will lead to higher tree mortality rates, especially for short-lived species, which may result in faster carbon sequestration but lower carbon storage of tropical forests. Fifty years of monthly observation of rainforest canopy trees in the Central Amazon reveals that drought, heat, storms and extreme rain can all increase tree mortality. Pioneers, softwoods and evergreen functional groups were particularly vulnerable.

Predicting Wetland Distribution Changes under Climate Change and Human Activities in a Mid- and High-Latitude Region

Wetlands in the mid- and high-latitudes are particularly vulnerable to environmental changes and have declined dramatically in recent decades. Climate change and human activities are arguably the most important factors driving wetland distribution changes which will have important implications for wetland ecological functions and services. We analyzed the importance of driving variables for wetland distribution and investigated the relative importance of climatic factors and human activity factors in driving historical wetland distribution changes. We predicted wetland distribution changes under climate change and human activities over the 21st century using the Random Forest model in a mid- and high-latitude region of Northeast China. Climate change scenarios included three Representative Concentration Pathways (RCPs) based on five general circulation models (GCMs) downloaded from the Coupled Model Intercomparison Project, Phase 5 (CMIP5). The three scenarios (RCP 2.6, RCP 4.5, and RCP 8.5) predicted radiative forcing to peak at 2.6, 4.5, and 8.5 W/m2 by the 2100s, respectively. Our results showed that the variables with high importance scores were agricultural population proportion, warmness index, distance to water body, coldness index, and annual mean precipitation; climatic variables were given higher importance scores than human activity variables on average. Average predicted wetland area among three emission scenarios were 340,000 ha, 123,000 ha, and 113,000 ha for the 2040s, 2070s, and 2100s, respectively. Average change percent in predicted wetland area among three periods was greatest under the RCP 8.5 emission scenario followed by RCP 4.5 and RCP 2.6 emission scenarios, which were 78%, 64%, and 55%, respectively. Losses in predicted wetland distribution were generally around agricultural lands and expanded continually from the north to the whole region over time, while the gains were mostly associated with grasslands and water in the most southern region. In conclusion, climatic factors had larger effects than human activity factors on historical wetland distribution changes and wetland distributions were predicted to decline remarkably over time under climate change scenarios. Our findings have important implications for wetland resource management and restoration because predictions of future wetland changes are needed for wetlands management planning.

Climate seasonality, fire and global patterns of tree cover

Vegetation systems with varying levels of tree cover are widely distributed globally, but the determinants of vegetation and tree cover still lack a consistent global framework. How these systems’ distribution responds to spatial variability of climate seasonality and associated fire regimes therefore remains unclear. &nbsp;Here, we focus on tree cover distribution at the global level. We develop a model that accounts for the role of seasonality and moisture in the dynamics that link climate, fire and tree cover. We choose predictors that have a clear link to functional processes that control tree physiology and growth, such as freezing tolerance (accounted for in the variable growing season length, GSL) and the balance between water availability and evapotranspiration (accounted for in the variables moisture index and moisture season length). The results show that the relative importance of climate factors and fire frequency as determinants of tree cover hinges on the GSL conditions. For example, significant interactions of tree cover with fire only occur in regions with GSL of 6–7 months or of 12 months. Our data also show a general relationship between maximum tree cover and moisture at the global level that is not visible when examining precipitation. Discontinuities in this relationship occur with frequent fires found under specific levels of seasonal moisture and temperature. A common climatic trait of frequent fires is moisture with a pronounced seasonality and an overall negative balance over the growing season. Frequent fires allow grassland to persist where there could be savanna/woodland as in the case of the North American grasslands. Frequent fires also allow savanna to persist where there could be forest, as found in tropical regions. This quantitative work is useful in improving large-scale land-atmosphere models as well as for identifying conditions of vulnerability for ecosystem diversity.

Relative importance of climate factors and human activities in impacting vegetation dynamics during 2000–2015 in the Otindag Sandy Land, northern China

In recent years, there has been increasing research interests in differentiating the relative importance of climate factors and human activities in impacting vegetation dynamics. In this study, based on residual trend method, we used MOD13A3 (MODIS vegetation index product), MCD12Q1 (MODIS land cover product) and meteorological datasets to differentiate the relative importance of climate factors and human activities in impacting vegetation dynamics during 2000–2015 in the Otindag Sandy Land, northern China. Results show that during the study period (2000–2015), the overall vegetation condition had improved in the Otindag Sandy Land. The driving forces of vegetation dynamics differed spatially in the whole study area over the study period. The area with vegetation degradation solely resulted from human activities accounted for 8.23% of the study area, while the area with vegetation degradation resulted from others (including climate factors and combination of climate factors and human activities) occupied 1.53%. The area with vegetation recovery benefitted from human activities occurred over 26.02% of the study area; the area benefitted from climate factors accounted for 23.69%; and the area benefitted from both climate factors and human activities occupied 37.74%. All in all, impacts of climate factors and human activities on vegetation dynamics varied at the county/city/banner scales and locality-specific measures should be adopted to protect the environments.

Assessing the relative importance of climate variables to rice yield variation using support vector machines

Climate factors have distinct impacts on crop yields. Understanding the relative importance of these factors to crop yield variation could provide valuable information about crop planting and management under climate change condition for policymakers and farmers. The current study investigated the applicability of support vector machines (SVMs) in determining the relative importance of climate factors (mean temperature, rainfall, relative humidity, sunshine hours, daily temperature range, and rainy days) to yield variation of paddy rice in southwestern China. The SVM models were compared with traditional artificial neural networks and multiple linear regression. The performance accuracy was evaluated by mean absolute error (MAE), mean relative absolute error (MRAE), root mean square error (RMSE), relative root mean square error (RRMSE), and coefficient of determination (R2). Comparative results showed that SVMs outperformed artificial neural networks and multiple linear regression. The SVM with radial basis function performed best with MAE of 0.06 t ha−1, MRAE of 0.9 %, RMSE of 0.15 t ha−1, RRMSE of 2.23 %, and R2 of 0.94. The results showed that SVMs are suitable for determining the effects of climate on crop yield variability. The relative importance of the studied climate factors to rice yield variation was in order of sunshine hours > daily temperature range > rainfall > relative humidity > mean temperature > rainy days in the current study area.

Land use and climate change impacts on soil organic carbon stocks in semi-arid Spain

The sensitivity of soil organic carbon to global change drivers, according to the depth profile, is receiving increasing attention because of its importance in the global carbon cycle and its potential feedback to climate change. A better knowledge of the vertical distribution of SOC and its controlling factors—the aim of this study—will help scientists predict the consequences of global change. The study area was the Murcia Province (S.E. Spain) under semiarid Mediterranean conditions. The database used consists of 312 soil profiles collected in a systematic grid, each 12 km2 covering a total area of 11,004 km2. Statistical analysis to study the relationships between SOC concentration and control factors in different soil use scenarios was conducted at fixed depths of 0–20, 20–40, 40–60, and 60–100 cm. SOC concentration in the top 40 cm ranged between 6.1 and 31.5 g kg−1, with significant differences according to land use, soil type and lithology, while below this depth, no differences were observed (SOC concentration 2.1–6.8 g kg−1). The ANOVA showed that land use was the most important factor controlling SOC concentration in the 0–40 cm depth. Significant differences were found in the relative importance of environmental and textural factors according to land use and soil depth. In forestland, mean annual precipitation and texture were the main predictors of SOC, while in cropland and shrubland, the main predictors were mean annual temperature and lithology. Total SOC stored in the top 1 m in the region was about 79 Tg with a low mean density of 7.18 kg Cm−3. The vertical distribution of SOC was shallower in forestland and deeper in cropland. A reduction in rainfall would lead to SOC decrease in forestland and shrubland, and an increase of mean annual temperature would adversely affect SOC in croplands and shrubland. With increasing depth, the relative importance of climatic factors decreases and texture becomes more important in controlling SOC in all land uses. Due to climate change, impacts will be much greater in surface SOC, the strategies for C sequestration should be focused on subsoil sequestration, which was hindered in forestland due to bedrock limitations to soil depth. In these conditions, sequestration in cropland through appropriate management practices is recommended.

Climate Factors Play a Limited Role for Past Adaptation Strategies in West Africa

The Sudano-Sahelian zone of West Africa has experienced recurrent droughts since the mid-1970s and today there is considerable concern for how this region will be able to adapt to future climate change. To develop well targeted adaptation strategies, the relative importance of climate factors as drivers of land use and livelihood change need to be better understood. Based on the perceptions of 1249 households in five countries across an annual rainfall gradient of 400-900 mm, we provide an estimate of the relative weight of climate factors as drivers of changes in rural households during the past 20 years. Climate factors, mainly inadequate rainfall, are perceived by 30-50% of households to be a cause of decreasing rainfed crop production, whereas a wide range of other factors explains the remaining 50-70%. Climate factors are much less important for decreasing livestock production and pasture areas. Increases in pasture are also observed and caused by improved tenure in the driest zone. Adaptation strategies to declining crop production include 'prayer' and migration in the 400-500 mm zone; reforestation, migration, and government support in the 500-700 mm zone; and soil improvement in the 700-900 mm zone. Declining livestock holdings are countered by improved fodder resources and veterinary services. It is concluded that although rainfed crop production is mainly constrained by climate factors, livestock and pasture are less climate sensitive in all rainfall zones. This needs to be reflected in national adaptation strategies in the region. (Resume d'auteur)