Land Area Of China Research Articles

Optimizing protected areas to boost the conservation of key protected wildlife in China

To meet the challenge of biodiversity loss and reach the targets of the proposed Post-2020 Global Biodiversity Framework, the Chinese government updated the list of national key protected wildlife in 2021 and has been continually expanding the protected areas (PAs). However, the status of protected wildlife in PAs remains unclear. In this study, we conducted a national assessment of the status of protected wildlife and suggested an optimization plan to overcome these shortcomings. From 1988 to 2021, the number of protected species almost doubled, and the area of PAs increased by 2.4 times, covering over 92.8% of the protected species. Nonetheless, 70.8% of the protected species are still not effectively protected by PAs, with some having less than 10% of their habitat included in PAs. Despite the significant addition of amphibians and reptiles to the latest protection list, they are the fewest species and are the least covered by PAs compared with birds and mammals. To fix these gaps, we systematically optimized the current PAsnetwork by adding another 10.0% of China's land area as PAs, which resulted in 37.6% coverage of protected species' habitats in PAs. In addition,26 priority areas were identified. Our research aimed to identify gapsin current conservation policies and suggest optimization solutions to facilitate wildlife conservation planning in China. In general, updating the list of key protected wildlife species and systematically optimizing PA networks are essential and applicable to other countries facing biodiversity loss.

An increasing trend of inorganic nitrogen deposition across montane regions of China

China has experienced a dramatic increase in the total inorganic nitrogen (TIN) deposition rate over the past three decades and has become one of the hotspots of N deposition worldwide. However, the status and trends of TIN deposition across Chinese mountain regions, which occupy over 60% of the land area of China, are still unclear. Here, we established a time series dataset of TIN deposition across Chinese mountains by data collection to evaluate the status and tendency of TIN deposition in mountain regions. The average TIN deposition flux in the mountains was approximately 9.62 kg N/ha/yr, with a maximum value of 23.49 kg N/ha/yr found in northern montane regions. There was a significant increasing trend of TIN deposition during the last two decades across China's montane regions (p < 0.05), different from the decreasing temporal trend from cropland/city sites. The temporal pattern of TIN deposition in montane areas was spatial and elevation dependent, showing an obvious increasing trend in both Southwest and Northeast Chinese montane areas and in the montane areas with lower (<1000 m. asl) and middle (1000–3000 m. asl) elevations. Our results highlighted the different temporal trends of TIN deposition in China's mountain regions from cropland/city areas, which should be considered in earth system models and environmental policy-making.

Predicting the current and future distributions of Pennisetum alopecuroides (L.) in China under climate change based on the MaxEnt model.

Pennisetum alopecuroides (L.), one of the important exotic plants, gives great economic value to animal husbandry in China. In order to study the distribution of Pennisetum alopecuroides (L.) in China and its response to climate change, based on the distribution records of Pennisetum alopecuroides (L.), our study used the Maximum Entropy (MaxEnt) model and geographic information system (GIS) methods, combined with environmental factors such as climate and terrain, to predict the potential distribution areas suitable for Pennisetum alopecuroides (L.) under current and future climate scenarios. The results showed that annual precipitation was the most important factor affecting the distribution of Pennisetum alopecuroides (L.). In current climate scenario, the total area of suitable for Pennisetum alopecuroides (L.) growth was about 576.5 km2, accounting for about 60.5% of the total land area of China. Among all the suitable areas, the area of low, middle and high fitness areas accounted for 5.69%, 20.55% and 33.81% of the total area respectively. In future climate scenarios (RCP4.5), the suitable area of Pennisetum alopecuroides (L.) would decrease with climate change, showing a clear trend of northward expansion in China. A concentrated and contiguous distribution region for Pennisetum alopecuroides (L.) would appear in northeast China. The model was tested by the receiver operating characteristic curve (ROC), and the average area under the curve of ROC of the training set was 0.985, which was reliable. This work provided an important reference and theoretical basis for the efficient utilization and plant regionalization of Pennisetum alopecuroides (L.) in future.

The Impact of Water Utilization on the Dynamic Total Efficiency of China’s Agricultural Production

Water resources are very important to agricultural production. In recent years, the change rate of agricultural cultivated land area in China has been very low, so it is not easy to increase its area and improve production capacity. To measure the impact of China’s water resources on agricultural efficiency from 2012 to 2016, this research applies the dynamic SBM model, conceives agricultural water as an external input, and uses the cultivated land area as an immutable intertemporal variable. The empirical results show that (1) the agricultural efficiency of Beijing, Heilongjiang, Shanghai, Jiangsu, Zhejiang, Fujian, Shandong, Sichuan, Qinghai, and Xinjiang are not affected by agricultural water. (2) The average value of China’s overall agricultural efficiency increased from 0.834 to 0.910, indicating that agricultural water is a positive efficiency factor. (3) Jilin, Chongqing, Inner Mongolia, Shaanxi, and Hubei are the five administrative regions with the most improvement in agricultural efficiency. (4) Insufficient agricultural productivity is the main factor affecting agricultural efficiency.

Transmission Risk Predicting for Schistosomiasis in Mainland China by Exploring Ensemble Ecological Niche Modeling

Schistosomiasis caused by Schistosoma japonicum is one of the major neglected tropical diseases worldwide. The snail Oncomelania hupensis is the only intermediate host of S. japonicum, which is recognized as an indicator of the schistosomias occurrence. In order to evaluate the risk of schistosomiasis in China, this work investigate the potential geographical distribution of host snail habitus by developing an ensemble ecological niche model with reference to the suitable environmental factors. The historical records of snail habitus were collected form the national schistosomiasis surveillance program from the year of 2005 to 2014. A total of 25 environmental factors in terms of the climate, geographic, and socioeconomic determinants of snail habitats were collected and geographically coded with reference to the snail data. Based on the correlations among snail habitats and the geographically associated environmental factors, an ensemble ecological niche model was developed by integrating ten standard models, aiming for improving the predictive accuracy. Three indexes are used for model performance evaluation, including receiver operating characteristic curves, kappa statistics, and true skill statistics. The model was used for mapping the risk of schistosomiasis in the middle and lower reaches of the Yangtze River. The results have shown that the predicted risk areas were classified into low risk (4.55%), medium risk (2.01%), and high risk areas (4.40%), accounting for 10.96% of the land area of China. This study demonstrated that the developed ensemble ecological niche models was an effective tool for evaluating the risk of schistosomiasis, particularly for the endemic regions, which were not covered by the national schistosomiasis control program.

Agricultural Greenhouse Crop Information System based on Big Data and Cloud Computing Technology

With the further promotion of urbanization in China, the arable land area in China is decreasing year by year, and it is very important to make full use of the existing land resources. At present, most areas in northern China have greenhouses. Since temperature, humidity, light, and CO2 concentration directly affect the yield of crops, how to provide a suitable environment for crops to grow in greenhouses is a topic worth investigating.

Climate change affects Galliformes taxonomic, phylogenetic and functional diversity indexes, shifting conservation priority areas in China

AbstractAimComprehensive biodiversity protection necessitates the consideration of multiple indexes of diversity, and how the distribution patterns of priority areas may shift under climate change. Galliformes is a globally endangered avian order vulnerable to climate change that provide an important indicator for wildlife conservation effectiveness. Here, we identified priority areas for conserving Galliformes taxonomic, phylogenetic, and functional diversity in China and their spatial dynamics subject to climate change, and examined how well existing protected areas align with current and future priority areas.LocationChina.MethodsWe applied species distribution modelling and Zonation algorithms to identify conservation priority area dynamics for 47 galliform species across three biodiversity indexes subject to three future climate change scenarios to 2050s and 2070s. We overlaid these identified priority areas onto existing national nature reserves and national parks to assess and project their effectiveness.ResultsCurrent priority areas proved spatially incongruent between indexes, with an optimal area overlap comprising just 10.3% of China's land area, lying largely outside of existing protected areas. Furthermore, over 80% of modelled optimal priority areas currently lacked formal conservation status. Future priority areas will shift substantially under climate change, to an extent dependent on greenhouse gas emission scenarios. Nevertheless, we identified five large regions where optimal Galliformes diversity indexes should remain stable under all scenarios, thus providing potential climatic refugia, if protected from human encroachment.Main ConclusionsThe current deficits we identified for Galliformes protection in China resonate with a broader need for hierarchical conservation strategic planning across regions and ecosystems to ensure long‐term biodiversity protection, accommodating for climate change.

Spatial Change of the Farming–Pastoral Ecotone in Northern China from 1985 to 2021

Identifying the spatial changes in farming–pastoral ecotone (FPE) is of utmost importance for the development of strategies for ecological protection in ecologically fragile areas. This study employed spatial autocorrelation and spatial clustering techniques to map FPE at the pixel scale using CLCD data with a spatial resolution of 30 × 30 m in the years 1985, 2000, and 2021, and then analyzed the changes of the FPE in northern China. The results showed that the FPE is mainly located at the border between the Inner Mongolia Autonomous Region and the adjacent provinces, which is along the Hu-line and the 400-mm isohyetal line. The area of the FPE was 63.94 × 104 km2, 62.90 × 104 km2, and 53.81 × 104 km2 in 1985, 2000, and 2021, respectively, accounting for 6.7%, 6.6%, 5.6% of the total land area in China. The FPE boundary moved northwestward during 1985–2021, demonstrating retreating, fragmenting, and shrinking tendencies. The decreased areas and the moving distances of the gravity center are six times and four times greater during 2000–2021 than that during 1985–2000, respectively. Moreover, the discontinuous change in FPE was mainly due to the increase in forest land, especially for the conversion of grassland to forest land. Our findings provide guidance for the construction of ecological civilization and the optimization of ecosystem structure in the farming–pastoral ecotone.

Ecological Response to Climate Change Across China From Combined Soil Temperature and Moisture Changes

AbstractA coupled soil temperature (ST) and moisture (SM) balance reflects a synthetic climate regime, having huge ecological impacts. This paper used ST and SM data from the European Center for Medium‐Range Weather Forecasts climate reanalysis‐Land and the Coupled Model Intercomparison Project Phase 6 and leaf area index (LAI) data from the Global Land Surface Satellite Product Suite. The focus was on understanding joint ST‐SM changes and the resulting ecological response across China. The results show that during 2000–2020, 24.5% of the land area in China experienced a warming‐drying trend resulting in a 9.7% LAI decrease, while 6.4% of the area experienced a warming‐wetting trend leading to an 8.6% LAI increase. During 2015–2100, 30.6% of the land area in China will be warmer and drier, while 55.2% of the area will be warmer but wetter across three shared socioeconomic pathways (SSP126, 245, and 585). Superimposed on the long‐term trends, there are also significant spatiotemporal variabilities in ST and SM on annual to decadal timescales. The LAI also showed substantial short‐term fluctuations in both typical regions and ecosystems despite consistent long‐term increases. Our findings suggest that ecosystems could be impaired on annual to decadal scales by adverse soil conditions in the twenty‐first century, but in terms of long‐term trends, ecosystems may be resilient partly because of the compensating effects of global warming and regional hydrological changes. Impact studies should thus focus more on annual to decadal soil‐ecosystem anomalous events.

Planting Cyperus esculentus augments soil microbial biomass and diversity, but not enzymatic activities.

The planting of Cyperus esculentus, a member of the grass family Cyperaceae which includes nut sedge weeds, is being increasingly promoted in northern China’s semi-arid and arid regions. Yet the effects of planting C. esculentus upon soil quality and soil microbial characteristics of sandy land remain unclear. This study examined the short-term (1 year) impact of this grass species on soil microbial biomass indices, enzymatic activities, and microbiome characteristics in the Horqin Sandy Land area of China. The results show that planting C. esculentus could increase microbial biomass in the form of carbon (MBC), nitrogen (MBN), and phosphorus (MBP), but it negligibly influenced the enzymatic activities of soil β-1,4-glucosidase (BG), cellobiohydrolase (CBH), leucine aminopeptidase (LAP), and β-1,4-N-acetaminoglycosidase (NAG). Over 1 year, we found that planting C. esculentus significantly increased the soil bacterial richness and diversity of sandy land, yet also altered community composition of soil bacteria and eukaryotes in way that could promote their homogenization. In this respect, the relative abundances of Acidobacteria and Proteobacteria significantly decreased and increased, respectively; hence, they may be considered for use as important indicators of soil nutrient-rich conditions. Overall, the results could be explained by greater soil organic carbon (SOC) and total nitrogen (TN), mainly derived from cumulative plant litter input to soils, which then increased the sandy soil’s C:N ratio. Future research should focus on exploring the long-term effects of planting C. esculentus on soil quality and soil microbial characteristics of sandy lands in China and abroad.

Daily Spatial Distribution of Apparent Temperature Comfort Zone in China Based on Heat Index

Apparent temperature (AT) is used to evaluate human comfort and is of great importance for studies on the effects of environmental factors on human health. This study used the daytime heat index (HI) calculated by national surface meteorological stations in China as the AT dependent variable, with August 2020 employed as an example. The daytime fifth generation European Centre for Medium-Range Weather Forecasts (ECMWF) atmospheric reanalysis of the global climate (ERA5) data and multi-source data extracted from the stations were used as the independent variables. Due to the presence of multicollinearity among the independent variables, we implemented a multiple stepwise regression model and developed a daily near-surface 1 km HI estimation model. The correlation analysis using the model showed that the coefficient of determination (R2) was 0.89; the mean absolute error (MAE) was 1.49 °C, and the root mean square error (RMSE) was 2.08 °C. We also used 10-fold cross-validation to calculate the error between the parameter and predicted values. The R2 of the model was 0.96; the MAE was 1.80 °C, and the RMSE was 2.40 °C. In this month, the mean daily daytime HI was 20.51 °C. According to the Universal Thermal Climate Index (UTCI), the areas with more than 20 days of heat stress for one month were largely distributed in the desert areas of northwest China and the coastal areas in southeast China, accounting for 29.98% of the total land area of China. This study improves the spatial resolution and accuracy of HI prediction, thus providing a scientific reference for studying residential environments and the urban heat island effect.

A framework for identifying bird conservation priority areas in croplands at national level

Global biodiversity is declining at an unprecedented rate, and the Post-2020 Global Biodiversity Framework requires each country to fulfill the conservation targets in biodiversity-inclusive spatial planning. Croplands provide habitat and food for many species, making them crucial for biodiversity conservation in addition to food production. Assessing conservation priorities in cropland is a prerequisite to allocate conservation resources and plan actions for better conservation outcomes. Yet quantitative methods to assess cropland conservation priority for biodiversity conservation at a national scale are still lacking. We proposed a framework for identifying the conservation priority in cropland for bird species at a national scale and applied the framework in China. We calculated the suitable habitat for each species and used a complementarity-based approach to designate the irreplaceable conservation priority areas considering richness, threatened level, and conservation percentage targets. We identified cropland taking up 6.76% of China's land area as a bird conservation priority, partially covering the suitable habitat of all the study species. By analyzing the landscape pattern of the priority areas and species' foraging traits, we provided policy-making suggestions according to area-specific characteristics. This framework can be used to identify priority areas for large-scale biodiversity conservation for different countries.

A comprehensive evaluation of flowering plant diversity and conservation priority for national park planning in China

Establishment of a national park protection system in China, including the latest target proposed to protect at least 30% of the land area, calls for a comprehensive exploration of conservation priorities incorporating multiple diversity facets. We herein evaluate the spatial distribution of Chinese flowering plants from the perspectives of richness, uniqueness, vulnerability, and evolutionary history, by integrating three mega-phylogenies and comprehensive distribution data. We detect significantly high consistency among hotspots of different diversity measures for Chinese flowering plants, suggesting that multiple facets of evolutionary diversity are concentrically distributed in China. Affording legal protection to these areas is expected to maximize positive conservation outcomes. We propose two integrative diversity indices by incorporating three richness-based and three phylogeny-based measures, respectively. Both methods identify areas with high species richness, but the integrative phylogeny-based index also locates key areas with ancient and unique evolutionary histories (e.g., Ailao-Wuliang Mts, Dabie Mts, Hainan rainforest, Karst area of Yunnan-Guizhou-Guangxi, Nanling Mts, and southeast coastal regions). Of all the diversity indices explored, phylogenetic endemism maximizes the incidental protection of other indices in most cases, emphasizing its significance for conservation planning. Finally, 42 priority areas are identified by combining the 5%-criterion hotspots of two integrative indices and the minimum area to protect all threatened species analyzed. These priorities cover only 13.3% of China's land area, but host 97.1% of species richness (23,394/24,095), 96.5% of endemic species (11,841/12,274), 100% of threatened species (2,613/2,613), and 99.3% of phylogenetic diversity for flowering plants involved in this study. These frameworks provide a solid scientific basis for national park planning in China.

Biodiversity priority areas and conservation strategies for seed plants in China.

China is known for its abundant plant resources, but biodiversity conservation faces unprecedented challenges. To provide feasible suggestions for sustainable conservation, we used the species richness algorithm and complementary algorithm to study distribution patterns of 34,082 seed plants based on 1,007,196 county-level distribution records. We reconstructed a phylogenetic tree for 95.35% of species and estimated the spatial phylogenetics, followed by correlation analyses between different distribution patterns. We identified 264 counties concentrated in southern and south-western mountainous areas as hotspots which covered 10% of the land area of China and harbored 85.22% of the Chinese seed plant species. The biodiversity conservation priorities we identified were highly representative as we have considered multiple conservation indicators. We evaluated the conservation effectiveness and gaps in the network of nature reserves and identified 31.44, 32.95, and 9.47%, respectively, of the hotspot counties as gaps in the national nature reserves, provincial nature reserves and both together, with respectively 55.77, 61.53, and 28.94% of the species. Analysis of the species composition showed there were a large number of threatened and endemic species occurring in the nature reserves’ gaps. The conservation gaps need to be filled by establishing new nature reserves or national parks, especially in south-western China, and more attentions should be paid to strengthen the conservation of specific plant taxa due to the apparent mismatches between different distribution patterns.

Collaborative monitoring network of ecologically fragile areas in China and its application in carrying capacity research

Ecologically fragile areas account for more than 60% of land area in China. Global change and human activities are aggravating ecosystem degradation and reducing the carrying capacity of resources and environment. It is important to accurately quantify the carrying capacity of resources and environment in ecologically fragile areas to deal with the risk and challenge of global change and to speed up the construction of ecological civilization. How-ever, existing methods evaluating carrying capacity of resources and environment are difficult to reflect the transmission effect of ecosystem structures, processes and functions changes among resource, environment and carrying capacity. Therefore, it is essential to establish a field observation network and obtain the comprehensive data set of resource and environment elements-ecosystem structure, function and process-ecosystem carrying capacity for develo-ping the theory and evaluation method. We introduced the collaborative monitoring networks of flux and UAV photographing, including the thoughts, practice, and preliminary results in the study of ecosystem structure, process and function in the fragile ecosystems of China. Based on the achievements and progress, we proposed the application of collaborative monitoring networks in capacity evaluation.

Foreign trade and virtual land resources: A case study of China's grain

This paper selects four grain crops of rice, wheat, soybean, and corn, analyzes their foreign trade from 2002 to 2020, and estimates the virtual land resource. The research results show that China's grain has always been in the state of net import. China mainly exports rice and imports soybeans, and the market structure has an obvious trend of simplification. The net import of virtual land resources in China's grain has grown significantly and has outstanding contribution ability. The average annual net import is 62.25 million ha, which is almost equivalent to the arable land area of China's one-cropping area. The net import contribution of soybean virtual land resources is about 101 times of its sown area, while corn, rice, and wheat account for about 10.42, 11.69, and 74.66% of its sown area. The net importers of virtual land resources are relatively concentrated, mainly in Brazil, the US, Argentina, Ukraine, and Canada.

Lightning climatology across the Chinese continent from 2010 to 2020

Understanding the lightning climatological distribution is of great significance but remains challenging which is in part due to the lack of continuous and uniform lightning observations. In this paper, for the first time, an 11-year ground-based cloud-to-cloud lightning dataset of China National Lightning Detection Network from 2010 to 2020 is used to investigate the lightning climatology over China's land area in terms of spatial distribution, seasonal, monthly and diurnal variations. Lightning activity in China's land area generally decreases from south to north and from east to west. The mean cloud-to-ground lightning density of China's land area is 0.9 fl km−2 yr−1, with the average maximums (exceeding 10 fl km−2 yr−1) are found in the south and east coastal provinces, such as Guangdong, Hainan, Fujian and Zhejiang Province. The lightning activity in spring, summer and autumn seems consistent throughout the daytime cycle, with the lightning activity is rather weak in the morning and most active in the afternoon, while winter lightning appears to be more active in the nighttime and in the very early morning produced from nocturnal thunderstorms. The cloud-to-ground lightning activity in the tropical and subtropical areas within 15–25°N is mainly concentrated in the late spring and early summer, with two weak peaks in May and August, while lightning in mid latitudes within 25–55°N mainly occurs in the summer (June–July-August). The percentage of positive cloud-to-ground lightning flashes with peak current higher than 75 kA is more than 3 times than that of negative cloud-to-ground lightning flashes. Meanwhile, the mean peak current of cloud-to-ground lightning flashes shows an inverse diurnal pattern to the cloud-to-ground lightning activity.

Identification of the potential distribution area of Cunninghamia lanceolata in China under climate change based on the MaxEnt model

Based on the distribution records of Cunninghamia lanceolata, we used the maximum Entropy (MaxEnt) model and geographic information system (GIS) methods, combined with environmental factors such as climate and terrain, to predict the potential distribution areas suitable for C. lanceolata under current and future climate scenarios. The results showed that annual precipitation was the most important factor driving the distribution of C. lanceolata. Under the current climate scenario, the total area of suitable for C. lanceolata growth was about 3.28 million km2, accounting for about 34.5% of the total land area of China. Among all the suitable areas, the lowly, intermediately, and highly suitable areas accounted for 18.3%, 29.7% and 52.0% of the total, respectively. Under future climate scenarios, the suitable area of C. lanceolata would increase, showing a clear trend of northward expansion in China. A concentrated and contiguous distribution region highly suitable for C. lanceolata would appear in the humid subtropical areas of southern China. The model was tested by the receiver operating characteristic curve (ROC). The average area under the curve of ROC of the training set was 0.91, showing high reliability.

Distribution and invasion risk assessment of Oryctes rhinoceros (L.) in China under changing climate

AbstractOryctes rhinoceros (L.) is one of the most important pests of palm plants. It has expanded rapidly and posed a serious threat to related plants in recent years. To study the impact of climatic conditions on it and its distribution under current and future climatic conditions, the maximum entropy (MaxEnt) model and ArcGIS software were used for the first time to predict the potential distribution of O. rhinoceros in China under climate change in this work. The results showed that the distribution range of O. rhinoceros was 92.42–120.81°E, 17.07–37.10°N under current climatic conditions. The highly suitable area was 58,298.61 km2, which is equal to 0.61% of China's land area. The area of highly suitable areas increased by 5.48%–39.43% under different scenarios (RCP 2.6, 4.5 and 8.5) in the future (2050s, 2090s) compared with the current distribution, which implied that the distribution of the pest will further expand. The precipitation in the wettest month (bio13), the minimum temperatures in November (tmin11), the minimum temperatures in July (tmin7) and the precipitation in September (prec9) were determined to be the key environmental variables affecting the distribution of O. rhinoceros. This work has important guiding significance for developing effective O. rhinoceros monitoring, prevention and control methods. We suggest that relevant departments take measures as soon as possible to control the spread of this pest.

Climate Rather Than Vegetation Changes Dominate Changes in Effective Vegetation Available Water Capacity

AbstractChina has experienced significant vegetation greening over recent decades. Vegetation greening may regulate the effective vegetation available water capacity (EVAWC), which determines the root zone water availability for evapotranspiration. EVAWC is one of the most important factors controlling vegetation growth and ecosystem resilience. Despite its importance, quantifying EVAWC at large scale is challenging due to limited observations of soil properties and insufficient understanding of underlying physical processes. Thus, to what extent changes in EVAWC are driven by vegetation and climate change is still unclear. Here, we establish a physics‐based, data‐driven stochastic approach to examine the spatiotemporal variability of the EVAWC and its potential drivers over China, with the consideration of vegetation and climate dynamics. The major strength of our approach is that it does not require observations related to soil properties as inputs, but only needs a few simple hydrometeorological and remotely sensed vegetation parameters that can be easily obtained. On average, we find that vegetation changes tend to increase EVAWC over 71.0 ± 3.9% of the total land area in China, while climate variabilities tend to reduce EVAWC over 73.7 ± 9.5% of the land area. More importantly, the potential increase in EVAWC resulting from vegetation changes is offset by climate variability. As a result, the changes in EVAWC over recent decades are generally dominated by climate variabilities (relative contribution of 82.7 ± 9.6%) rather than vegetation changes, especially in humid and semihumid areas. Our results suggest that vegetation greening in China has subordinate impacts on EVAWC, and ecosystem resilience is mainly dominated by the local climate.