Spatio-temporal distribution of net primary productivity along the northeast China transect and its response to climatic change

An improved Carnegie Ames Stanford Approach model （CASA model） was used to estimate the net primary productivity （NPP） of the Northeast China Transect （NECT） every month from 1982 to 2000. The spatial-temporal distribution of NPP along NECT and its response to climatic change were also analyzed. Results showed that the change tendency of NPP spatial distribution in NECT is quite similar to that of precipitation and their spatial correlation coefficient is up to 0.84 （P 〈 0.01）. The inter-annual variation of NPP in NECT is mainly affected by the change of the aestival NPP every year, which accounts for 67.6% of the inter-annual increase in NPP and their spatial correlation coefficient is 0.95 （P 〈 0.01）. The NPP in NECT is mainly cumulated between May and September, which accounts for 89.8% of the annual NPP. The NPP in summer （June to August） accounts for 65.9% of the annual NPP and is the lowest in winter. Recent climate changes have enhanced plant growth in NECT. The mean NPP increased 14.3% from 1980s to 1990s. The inter-annual linear trend of NPP is 4.6 gC·m^-2·a^-1, and the relative trend is 1.17%, which owns mainly to the increasing temperature.

Assessing the Dynamics of Grassland Net Primary Productivity in Response to Climate Change at the Global Scale

Understanding the net primary productivity(NPP) of grassland is crucial to evaluate the terrestrial carbon cycle. In this study, we investigated the spatial distribution and the area of global grassland across the globe. Then, we used the Carnegie-Ames-Stanford Approach(CASA) model to estimate global grassland NPP and explore the spatio-temporal variations of grassland NPP in response to climate change from 1982 to 2008. Results showed that the largest area of grassland distribution during the study period was in Asia(1737.23 × 104 km^2), while the grassland area in Europe was relatively small(202.83 × 10~4 km^2). Temporally, the total NPP increased with fluctuations from 1982 to 2008, with an annual increase rate of 0.03 Pg C/yr. The total NPP experienced a significant increasing trend from 1982 to 1995, while a decreasing trend was observed from 1996 to 2008. Spatially, the grassland NPP in South America and Africa were higher than the other regions, largely as a result of these regions are under warm and wet climatic conditions. The highest mean NPP was recorded for savannas(560.10 g C/(m^2·yr)), whereas the lowest was observed in open shrublands with an average NPP of 162.53 g C/(m^2·yr). The relationship between grassland NPP and annual mean temperature and annual precipitation(AMT, AP, respectively) varies with changes in AP, which indicates that, grassland NPP is more sensitive to precipitation than temperature.

The net primary productivity of Mid-Jurassic peatland and its control factors: Evidenced by the Ordos Basin

Using the large-scale thick 4# coal seam from the Mid-Jurassic in the southern Ordos Basin as an example, this paper studied the net primary productivity(NPP) level of the Mid-Jurassic peatland, and discussed its control factors. Geophysical logging signals were used for a spectrum analysis to obtain the Milankovitch cycle parameters in coal seam. These were then used to calculate the accumulation rate of the residual carbon in 4# coal seam. The carbon loss can be calculated according to the density and residual carbon content of 4# coal seam. Then, the total carbon accumulation rate of the peatland was further derived, and the NPP of peatland was determined. The results show that the NPP of MidJurassic peatland is higher than that of Holocene at the same latitude. Comprehensive analysis indicates that the temperature, carbon dioxide and oxygen levels in atmosphere are the main control factors of the NPP of Mid-Jurassic peatland.

Variation of net primary productivity and its drivers in China’s forests during 2000-2018

Background:Net primary productivity(NPP)in forests plays an important role in the global carbon cycle.However,it is not well known about the increase rate of China’s forest NPP,and there are different opinions about the key factors controlling the variability of forest NPP.Methods:This paper established a statistics-based multiple regression model to estimate forest NPP,using the observed NPP,meteorological and remote sensing data in five major forest ecosystems.The fluctuation values of NPP and environment variables were extracted to identify the key variables influencing the variation of forest NPP by correlation analysis.Results:The long-term trends and annual fluctuations of forest NPP between 2000 and 2018 were examined.The results showed a significant increase in forest NPP for all five forest ecosystems,with an average rise of 5.2 gC·m-2·year-1 over China.Over 90%of the forest area had an increasing NPP range of 0-161 gC·m-2·year-1.Forest NPP had an interannual fluctuation of 50-269 gC.m-2·year-1 for the five major forest ecosystems.The evergreen broadleaf forest had the largest fluctuation.The variability in forest NPP was caused mainly by variations in precipitation,then by temperature fluctuations.Conclusions:All five forest ecosystems in China exhibited a significant increasing NPP along with annual fluctuations evidently during 2000-2018.The variations in China’s forest NPP were controlled mainly by changes in precipitation.

Classification and Net Primary Productivity of the Southern China's Grasslands Ecosystem Based on Improved Comprehensive and Sequential Classification System(CSCS) Approach

This research classified vegetation types and evaluated net primary productivity （NPP） of southern China＇s grasslands based on the improved comprehensive and sequential classification system （CSCS）, and proposed 5 thermal grades and 6 humidity grades. Four classes of grasslands vegetation were recognized by improved CSCS, namely, tundra grassland class, typical grassland class, mixed grassland class and alpine grassland class. At the type level, 14 types of vegetations （9 grasslands and 5 forests） were classified. The NPP had a trend to decrease from east to west and south to north, and the annual mean NPP was estimated to be 656.3 g C m-2 yr-1. The NPP value of alpine grassland class was relatively high, generally more than 1200 g C m2 yr-1. The NPP value of mixed grassland class was in a range from 1 000 to 1200 g C m-2 yr-1. Tundra grassland class was located in southeastern Tibet with high elevation, and its NPP value was the lowest （〈600 g C m＇2yrl）. The typical grassland class distributed in most of the area, and its NPP value was generally from 600 to 1000 g C m-2 yr-1. The total NPP value in the study area was 68.46 Tg C. The NPP value of typical grassland class was the highest （48.44 Tg C）, and mixed grassland class was the second （16.54 Tg C）, followed by alpine grassland class （3.22 Tg C）, with tundra grassland class being the lowest （0.25 Tg C）. For all the grasslands types, the total NPP of forest meadow was the highest （34.81 Tg C）, followed by sparse forest brush （16.54 Tg C）, and montane meadow was the lowest （0.01 Tg C）.

Examining Forest Net Primary Productivity Dynamics and Driving Forces in Northeastern China During 1982–2010

Forest net primary productivity （NPP） is a key parameter for forest monitoring and management. In this study, monthly and annual forest NPP in the northeastern China from 1982 to 2010 were simulated by using Carnegie-Ames-Stanford Approach （CASA） model with normalized difference vegetation index （NDVI） sequences derived from Advanced Very High Resolution Radiometer （AVHRR） Global Invento y Modeling and Mapping Studies （GIMMS） and Terra Moderate Resolution Imaging Spectroradiometer （MODIS） products. To address the problem of data inconsistency between AVHRR and MODIS data, a per-pixel unary linear regres- sion model based on least ~;quares method was developed to derive the monthly NDVI sequences. Results suggest that estimated forest NPP has mean relative error of 18.97% compared to observed NPP from forest inventory. Forest NPP in the northeastern China in- creased significantly during the twenty-nine years. The results of seasonal dynamic show that more clear increasing trend of forest NPP occurred in spring and awmnn. This study also examined the relationship between forest NPP and its driving forces including the climatic and anthropogenic factors. In spring and winter, temperature played the most pivotal role in forest NPR In autumn, precipitation acted as the most importanl factor affecting forest NPP, while solar radiation played the most important role in the summer. Evaportran- spiration had a close correlation with NPP for coniferous forest, mixed coniferous broadleaved forest, and broadleaved deciduous forest. Spatially, forest NPP in the Da Hinggan Mountains was more sensitive to climatic changes than in the other ecological functional re- gions. In addition to climalie change, the degradation and improvement of forests had important effects on forest NPP. Results in this study are helpful for understanding the regional carbon sequestration and can enrich the cases for the monitoring of vegetation during long time series.

Impacts of Climate Change on Net Primary Productivity in Arid and Semiarid Regions of China

In recent years, with the constant change in the global climate, the effect of climate factors on net primary productivity(NPP) has become a hot research topic. However, two opposing views have been presented in this research area: global NPP increases with global warming, and global NPP decreases with global warming. The main reasons for these two opposite results are the tremendous differences among seasonal and annual climate variables, and the growth of plants in accordance with these climate variables. Therefore, it will fail to fully clarify the relation between vegetation growth and climate changes by research that relies solely on annual data. With seasonal climate variables, we may clarify the relation between vegetation growth and climate changes more accurately. Our research examined the arid and semiarid areas in China(ASAC), which account for one quarter of the total area of China. The ecological environment of these areas is fragile and easily affected by human activities. We analyzed the influence of climate changes, especially the changes in seasonal climate variables, on NPP, with Climatic Research Unit(CRU) climatic data and Moderate Resolution Imaging Spectroradiometer(MODIS) satellite remote data, for the years 2000–2010. The results indicate that: for annual climatic data, the percentage of the ASAC in which NPP is positively correlated with temperature is 66.11%, and 91.47% of the ASAC demonstrates a positive correlation between NPP and precipitation. Precipitation is more positively correlated with NPP than temperature in the ASAC. For seasonal climatic data, the correlation between NPP and spring temperature shows significant regional differences. Positive correlation areas are concentrated in the eastern portion of the ASAC, while the western section of the ASAC generally shows a negative correlation. However, in summer, most areas in the ASAC show a negative correlation between NPP and temperature. In autumn, precipitation is less important in the west, as opposed to the east, in which it is critically important. Temperatures in winter are a limiting factor for NPP throughout the region. The findings of this research not only underline the importance of seasonal climate variables for vegetation growth, but also suggest that the effects of seasonal climate variables on NPP should be explored further in related research in the future.

Spatio-temporal Pattern of Net Primary Productivity in Hengduan Mountains area, China： Impacts of Climate Change and Human Activities

Net primary productivity(NPP), a metric used to define and identify changes in plant communities, is greatly affected by climate change, human activities and other factors. Here, we used the Carnegie-Ames-Stanford Approach(CASA) model to estimate the NPP of plant communities in Hengduan Mountains area of China, and to explore the relationship between NPP and altitude in this region. We examined the mechanisms underlying vegetation growth responses to climate change and quantitatively assessed the effects of ecological protection measures by partitioning the contributions of climate change and human activities to NPP changes. The results demonstrated that: 1) the average total and annual NPP values over the years were 209.15 Tg C and 468.06 g C/(m2·yr), respectively. Their trend increasingly fluctuated, with spatial distribution strongly linked to altitude(i.e., lower and higher NPP in high altitude and low altitude areas, respectively) and 2400 m represented the marginal altitude for vegetation differentiation; 2) areas where climate was the main factor affecting NPP accounted for 18.2% of the total research area, whereas human activities were the primary factor influencing NPP in 81.8% of the total research area, which indicated that human activity was the main force driving changes in NPP. Areas where climatic factors(i.e., temperature and precipitation) were the main driving factors occupied 13.6%(temperature) and 6.0%(precipitation) of the total research area, respectively. Therefore, the effect of temperature on NPP changes was stronger than that of precipitation; and 3) the majority of NPP residuals from 2001 to 2014 were positive, with human activities playing an active role in determining regional vegetation growth, possibly due to the return of farmland back to forest and natural forest protection. However, this positive trend is decreasing. This clearly shows the periodical nature of ecological projects and a lack of long-term effectiveness.

松花江流域NPP时空演变及其对极端气候的响应机制

为探究全球气候变化条件下松花江流域陆地生态系统健康程度的变化特征,基于2000—2020年MODIS MOD17A3HGF数据集,采用趋势分析、相关性分析、M-K检验、地理探测器和相对重要性分析等方法,结合气象站点数据和土地利用数据,分析植被净初级生产力(net primary productivity,NPP)时空演变特征及其对极端气候事件的响应机制。结果表明:松花江流域年均NPP值为407.45 g/m^(2)(以C计,下同),以年均4.82 g/m的速率显著上升(p<0.01);极端降水事件对植被NPP空间分异性的影响强于极端气温事件,极端气候指数间交互作用的影响大于单一极端气候指数的影响,流域及农田和草地生态系统NPP主要受总降水量(PRCPTOT)与年平均最低气温(TMIN)交互作用的影响,森林、湿地和聚落生态系统NPP分别受中雨日数(R10 mm)与年平均最高气温(TMAX)交互作用、强降水量(R95P)与TMIN交互作用和R10 mm与暖夜日数(TN90P)交互作用的影响;时间尺度上PRCPTOT、TMAX和TMIN是植被NPP的主要影响因素,空间尺度上PRCPTOT和TMIN是多年平均NPP的主要影响因素。研究结果可为量化气候变化背景下区域生态系统健康程度和应对极端气候事件措施的制定提供科学依据。

2000—2020年吉林省植被NPP时空演变及其与气温、降水的关系分析

探究植被净初级生产力(NPP)时空分布格局及气候因素响应特征,对全球变暖背景下吉林省生态环境保护和碳源/汇评价至关重要。对2000—2020年吉林省植被生长季NPP时空变化特征及其对气候因子的相关性逐像元分析结果表明,吉林省植被NPP具有较明显的空间分异性,总体呈西—中—东逐步递增分布态势,2000—2020年NPP呈波动上升的年际变化趋势,各生态功能区NPP表现为东部森林生态区的>中部农田生态区的>西部草原湿地生态区的。植被NPP的Hurst指数范围在0.23~0.74,未来变化趋势具有较强同向持续特征,植被生长状态整体向好。吉林省植被NPP具有显著的正向空间自相关性,冷热点分布出现了一定程度的极化现象,冷点区域相对稳定,东部热点区域范围年际变化明显。NPP年际差异的空间格局主要是H-H型和L-L型团状集聚分布。吉林省植被NPP主要受降水影响,干旱区与降水呈显著正相关,东部以南水资源丰沛区多为负相关,NPP与气温相关性较弱。去趋势后的相关性分析更能剔除气候因素外的干扰,从而更真实地探究NPP与各气候因素内部年际变化之间的关系。

Quantitative Assessment of the Relative Contributions of Climate and Human Factors to Net Primary Productivity in the Ili River Basin of China and Kazakhstan

It is necessary to quantitatively study the relationship between climate and human factors on net primary productivity(NPP)inorder to understand the driving mechanism of NPP and prevent desertification.This study investigated the spatial and temporal differentiation features of actual net primary productivity(ANPP)in the Ili River Basin,a transboundary river between China and Kazakhstan,as well as the proportional contributions of climate and human causes to ANPP variation.Additionally,we analyzed the pixel-scale relationship between ANPP and significant climatic parameters.ANPP in the Ili River Basin increased from 2001 to 2020 and was lower in the northeast and higher in the southwest;furthermore,it was distributed in a ring around the Tianshan Mountains.In the vegetation improvement zone,human activities were the dominant driving force,whereas in the degraded zone,climate change was the primary major driving force.The correlation coefficients of ANPP with precipitation and temperature were 0.322 and 0.098,respectively.In most areas,there was a positive relationship between vegetation change,temperature and precipitation.During 2001 to 2020,the basin’s climatic change trend was warm and humid,which promoted vegetation growth.One of the driving factors in the vegetation improvement area was moderate grazing by livestock.

Identification of Milankovitch Cycles and Calculation of Net Primary Productivity of Paleo-peatlands using Geophysical Logs of Coal Seams

Individual coal seams formed in paleo-peatlands represent sustained periods of terrestrial carbon accumulation and a key environmental indicator attributed to this record is the rate of carbon accumulation.Determining the rate of carbon accumulation requires a measure of time contained within the coal.This study aimed to determine this rate via the identification of Milankovitch orbital cycles in the coals.The geophysical log is an ideal paleoclimate proxy and has been widely used in the study of sedimentary records using spectral analysis.Spectral analyses of geophysical log from thick coal seams can be used to identify the Milankovitch cycles and to calculate the period of the coal deposition.By considering the carbon loss during coalification,the long-term average carbon accumulation rate and net primary productivity(NPP)of paleo-peatlands in coal seams can be obtained.This review paper presents the procedures of analysis,assessment of results and interpretation of geophysical logs in determining the NPP of paleo-peatlands.

Carbon uptake and change in net primary productivity of oasis-desert ecosystem in arid western China with remote sensing technique

Arid and semi-arid ecosystems exhibit a spatially complex biogeophysical structure. According to arid western special climate-vegetation characters, the fractional cover of photosynthetic vegetation （PV）, non-photosynthetic vegetation （NPV）, bare soil and water are unmixed, using the remote sensing spectral mixture analysis. We try the method to unmix the canopy funation structure of arid land cover in order to avoid the differentiation of regional vegetation system and the disturbance of environmental background. We developed a modified production efficiency model NPP-PEM appropriate for the arid area at regional scale based on the concept of radiation use efficiency. This model refer to the GLO-PEM and CASA model was driven with remotely sensed observations, and calculates not just the conversion efficiency of absorbed photosynthetically active radiation but also the carbon fluxes that determine net primary productivity （NPP）. We apply and validate the model in the Kaxger and Yarkant river basins in arid western China. The NPP of the study area in 1992 and 1998 was estimated based on the NPP-PEM model. The results show that the improved PEM model, considering the photosynthetical activation of heterogeneous functional vegetation, is in good agreement with field measurements and the existing literature. An accurate agreement （R2= 0.85, P〈0.001） between the estimates and the ground-based measurement was obtained. The spatial distribution of mountain-oasis-desert ecosystem shows an obvious heterogeneous carbon uptake. The results are applicable to arid ecosystem studies ranging from characterizing carbon cycle, carbon flux over arid areas to monitoring change in mountain-oasis-desert productivity, stress and management.

Spatiotemporal variation in vegetation net primary productivity and its relationship with meteorological factors in the Tarim River Basin of China from 2001 to 2020 based on the Google Earth Engine

Vegetation growth status is an important indicator of ecological security.The Tarim River Basin is located in the inland arid region of Northwest China and has a highly fragile ecological environment.Assessing the vegetation net primary productivity(NPP)of the Tarim River Basin can provide insights into the vegetation growth variations in the region.Therefore,based on the Google Earth Engine(GEE)cloud platform,we studied the spatiotemporal variation of vegetation NPP in the Tarim River Basin(except for the eastern Gobi and Kumutag deserts)from 2001 to 2020 and analyzed the correlations between vegetation NPP and meteorological factors(air temperature and precipitation)using the Sen slope estimation method,coefficient of variation,and rescaled range analysis method.In terms of temporal characteristics,vegetation NPP in the Tarim River Basin showed an overall fluctuating upward trend from 2001 to 2020,with the smallest value of 118.99 g C/(m2•a)in 2001 and the largest value of 155.07 g C/(m2•a)in 2017.Regarding the spatial characteristics,vegetation NPP in the Tarim River Basin showed a downward trend from northwest to southeast along the outer edge of the study area.The annual average value of vegetation NPP was 133.35 g C/(m2•a),and the area with annual average vegetation NPP values greater than 100.00 g C/(m2•a)was 82,638.75 km2,accounting for 57.76%of the basin.The future trend of vegetation NPP was dominated by anti-continuity characteristic;the percentage of the area with anti-continuity characteristic was 63.57%.The area with a significant positive correlation between vegetation NPP and air temperature accounted for 53.74%of the regions that passed the significance test,while the area with a significant positive correlation between vegetation NPP and precipitation occupied 98.68%of the regions that passed the significance test.Hence,the effect of precipitation on vegetation NPP was greater than that of air temperature.The results of this study improve the understanding on the spatiotemporal variation of vegetation NPP in the Tarim River Basin and the impact of meteorological factors on vegetation NPP.

Effects of Drought on Net Primary Productivity:Roles of Temperature,Drought Intensity,and Duration

Northeast China has experienced frequent droughts over the past fifteen years. However, the effects of droughts on net primary productivity(NPP) in Northeast China remain unclear. In this paper, the droughts that occurred in Northeast China between 1999 and 2013 were identified using the Standardized Precipitation Evapotranspiration Index(SPEI). The NPP standardized anomaly index(NPP-SAI) was used to evaluate NPP anomalies. The years of 1999, 2000, 2001, and 2007 were further investigated in order to explore the influence of droughts on NPP at different time scales(3, 6, and 12 months). Based on the NPP-SAI of normal areas, we found droughts overall decreased NPP by 112.06 Tg C between 1999 and 2013. Lower temperatures at the beginning of the growing season could cause declines in NPP by shortening the length of the growing season. Mild drought or short-term drought with higher temperatures might increase NPP, and weak intensity droughts intensified the lag effects of droughts on NPP.

基于PIE-Engine云计算平台和CASA模型的植被NPP时空动态遥感监测:以道孚县为例

【目的】为深入了解道孚县的植被固碳水平以及其长期变化趋势,【方法】以MODIS数据、站点气象和土地覆盖等资料为基础,通过PIE-Engine遥感云计算平台建立了CASA模型,估算了2001—2016年道孚县陆地植被净初级生产力(NPP)。同时,结合Theil-Sen Median趋势分析、稳定性分析、分区统计和冷热点分析等手段,探讨了其时空分布和演变特征。【结果】结果显示:(1)基于PIE-Engine云平台模型和CASA模型估算的道孚县2001—2016年的NPP,其精度较高并与MODIS NPP数据有良好的拟合效果。(2)道孚县NPP呈持续上升趋势,其中中部和东南部NPP较高,东北部和中南部NPP较低,同时NPP的低值区正在逐年减少,反映出该地区生态状况正在逐渐改善。(3)所有乡镇的NPP在2001—2016年间均有增长,NPP的空间变化整体稳定,大部分地区NPP波动较小。(4)道孚县的NPP在2001—2016年间总体显著增长,增长区域面积占全县的93%以上。(5)高NPP值区域在空间上形成聚类,“热点”现象明显,这为进一步研究和理解NPP的空间分布和变化规律提供了依据。【结论】研究成果为道孚县的生态环境改善和持续发展提供了科学依据,并提出了一种基于云平台的快速、高效的区域植被NPP评估方法,这对于全面评估可持续发展目标和推动生态文明建设具有积极意义。

Response of vegetation net primary productivity to climate change scenarios in the Loess Plateau of China--A case study of the Yangou watershed

Vegetation net primary productivity(NPP)is a sensitive indicator to characterize the response of terrestrial ecosystems to the climate change.Projections of the NPP changes of the Loess Plateau under future climate scenarios have great significances in revealing the interactions among terrestrial ecosystems and climatic systems,as well as instructing future vegetation construction of this region.Here,we carried out a case study on the Yangou watershed in the Loess Plateau.Using the vegetation-producing process model(VPP)established for such small watersheds,we simulated the NPP of the Yangou watershed under different scenarios of climate changes.The results showed that the NPP significandy increased with the precipitation increasing and evidently decreased with the temperature increasing where the climate change occurred in the whole year or in the summer half year.However,where the climate change occurred in the winter half year,the increased precipitation had little effect on the NPP,and the increased temperature significantly reduced the NPP.There were clear differences among the response sensitivities of different vegetation types with trees and shrubs were more sensitive to the changes in temperature and precipitation than crops and grasses.Currently,the most favourable climate change scenario to the NPP in the Yangou watershed was T0P15 under which the precipitation increased by 15%and the temperature did not changed,in the whole year;in the meantime,the most unfavourable climate change scenarios was T2P-15 under which the precipitation declined by 15%and the temperature increased by 2℃,in the whole year.

The study of productivity in the Bohai Sea-Ⅱ. Primary productivity and estimation of potential fish catch

-On the basis of the data obtained from the surveys in the Bohai Sea during 1982-1983, this paper analysed and discussed the distribution and seasonal variation of primary productivity in the Bohai Sea, and the correlations between the primary productivity and environmental factors. The organic carbon production and prospect of fishery production in the waters of this sea are estimated. It is shown that, there exists production patential in the Bohai Sea, the primary production is 112 gC/ (m2 ?a)the production of organic carbon being 10 million ton per year, the fishery yields 1 million ton and the maximum catch of sea products 0. 5 million ton. The results of the investigation can serve as the basic data for the exploitation, utilization and management of the fishery resources in the Bohai Sea.

Distribution of chlorophyU a and estimation of primary productivity in the eastern waters of Balingtang Channel in summer

Oceanographical features on both sides of Balingtang Channel (17°55′-20°06′N, 122°55′-126°57′E) were comprehensively investigated on board of R/V "Experiment 3" in June. 1984. The pre-sent paper reports the chlorophyll data collected and primary productivity estimated there. Water sam-ples were taken with a glass bottle of Model HQMat the depth of 0, 10. 25, 50, 75, 100 and 150m, separately. Chlorophyll was determined according to the spectrophotometry proposed by UNESCO(1966) and calculated with the trichromatic equations of Jeffrey-Humphrey(1975). Estimations ofprimary productivity were carried out using a simplified equation (Q = 1.5) given by Cadee(1975).

Responses of Net Primary Productivity to Climatic Factors in Youyang County

Based on monthly data of precipitation,temperature,sunshine duration,wind speed,relative humidity and other climatic factors in Youyang County during 1956-2013,net primary productivity(NPP)in the county was calculated by using a climate productivity model,and effects of changes in climatic factors on NPP in the county were studied.The results show that annual average NPP in Youyang County during 1956-2013was 11.137 t/(hm^2·a),but there were no significant changes over the past 58 years.There was a significantly positive correlation between NPP and annual precipitation or annual mean relative humidity.Under the background of global warming,NPP in Youyang County will face greater pressure,thereby putting pressure on local ecological environment.The research can provide scientific reference for the construction of Youyang County and ecological protection zones in the southeast of Chongqing.