Spatial Distribution Of Net Primary Productivity Research Articles

Spatial and temporal variation of vegetation NPP and analysis of influencing factors in Heilongjiang Province, China

Vegetation net primary productivity (NPP) plays an important role in investigating carbon cycle and NPP provided by forest constitutes the main component of terrestrial vegetation NPP. Since late 1990s, a series of policies for protecting forest have been implemented in Heilongjiang Province, China, directly leading to the continuous change of forest area and growth environment. As a result, analysis of spatiotemporal characteristics of NPP after the implementation of protection policies was conducted in this study, and influencing factors leading to the distribution and spatiotemporal heterogeneity of NPP was also compared quantitatively, aiming to reveal the changing characteristics and influencing factors of NPP in a large area over a longer time span. In this study, multi-source data including MOD17A3 NPP product, meteorological data, topographic data and land-use data was selected, and then the spatiotemporal characteristics of NPP from 2001 to 2020 were analyzed through commonly-used spatiotemporal analysis indices and methods. Finally, influencing factors leading to the distribution and spatiotemporal heterogeneity of NPP in the study area were quantitatively compared and analyzed. Results show that the total amount of NPP in Heilongjiang Province has a fluctuating trend with an increasing rate of 23.47% over the past twenty years, and the increase/decrease scenarios of NPP usually can be found in forest regions with high forest coverage and urban regions experiencing dramatic urbanization processes, respectively. Meanwhile, this study also finds that there is no absolute dominant factor can be responsible for the difference in spatial distribution of NPP, but the conversion between forest and other land-use types are the main factors leading to the spatiotemporal heterogeneity of NPP in the study area. The conclusions in this study may provide guiding significance for formulating forestry protection policies in forest regions and designing land-use plans in the future, aiming to achieve the balance between ecological protection and urban development.

Impacts of climate, phenology, elevation and their interactions on the net primary productivity of vegetation in Yunnan, China under global warming

Both net primary productivity (NPP) and vegetation phenology play essential roles in influencing the carbon sequestration of terrestrial ecosystems. However, the relationship between vegetation phenology and NPP remains unclear under the effects of global warming. This study used Geodetector to analyze the interaction mechanisms between climate, phenology, elevation, and NPP in Yunnan, China. The results are as follows. (1) NPP is positively correlated with NDVI, LOS, EOS, TEMP, PREC and SRAD, and negatively correlated with ELEV, NDBI and SOS. However, the main influencing factors leading to the variation of NPP differ with the region. (2) The spatial distribution of NPP and LOS in Yunnan Province is mainly influenced by the monsoon, showing a pattern of high in the southwest and low in the northeast, and the interaction between PREC and LOS is the main reason for the variation of NPP. (3) In the high-altitude region of northwest Yunnan, the interaction between altitude and PREC is the primary factor affecting NPP variation. (4) In the tropical monsoon forest region of southern Yunnan, the interaction between SRAD and PREC is the main cause of NPP changes. (5) Despite having a small effect on NPP, SOS was the only phenological factor that showed a significant linear relationship with NPP. This study reveals the complex and diverse interactions between climate, phenology, elevation, and NPP in different regions of Yunnan, and provides a new perspective for understanding the carbon cycle and ecological processes of terrestrial ecosystems under global warming.

Effects of climate changes on net primary productivity variation in the marsh area of the Sanjiang Plain

The Sanjiang Plain includes the largest freshwater marsh in China, playing an important role in regional carbon cycle. As an important indicator of carbon cycle, the net primary productivity (NPP) is a crucial index for estimating the carbon storage of marshy wetlands. Investigating the association between climate factors and NPP variation quantitatively is of great significance for estimating carbon sequestration of marsh. Based on NPP data and climatic data from 1954 to 2014, the spatiotemporal change of NPP in marsh area was analyzed and its association with climate factors was investigated in the Sanjiang Plain in this study. The results indicated that the NPP showed an increase trend in the marsh area of the Sanjiang Plain in the past six decades. Temperate growth made the largest contribution to the NPP increase among the main climate factors in the last six decades, followed by CO2concentration. Solar Radiation had the largest explanatory power on the spatial distribution of NPP among three climate factors before 1985. After 1985, temperature played an important role in leading the NPP distribution. Results also showed that the explanatory power of interactions between climate factors was stronger than that of single factor. Our results highlight the asymmetric effects of interactions between climate factors on marsh vegetation, which should be adequately considered in estimating carbon sequestration in marsh area in the Sanjiang Plain.

Quantitative assessment of the relative contributions of climate change and human activities to NPP changes in the Southwest Karst area of China.

Net primary production (NPP) is an essential component of the terrestrial carbon cycle and an essential factor of ecological processes. In global change research, it was the core content to study the driving forces of NPP change. In this paper, we focused on the Southwest Karst area of China and analyzed the response mechanisms of NPP to topography, land-use types, climatic change, and human activities. Our results showed that (1) changes in elevation and slope lead to significant differences in the spatial distribution of NPP. With the increase of elevation and slope, NPP first increased and then decreased, their critical values were 2000m and 15°, respectively. (2) NPP varied significantly among different land-use types. The average NPP of the forest was the highest, and the average NPP of cultivated land increased fastest. (3) Temperature and precipitation had the most substantial influence on NPP, both of them promoted the increase of NPP, and the effect of temperature was more obvious in the Southwest Karst area. (4) Ecological engineering significantly promoted the change of NPP, while animal husbandry significantly inhibited the change of NPP. (5) There were significant spatial differences in the driving effects and corresponding contributions of climatic change and human activities; both of them promoted the increase of NPP in the Southwest Karst area of China. Under climatic change and human activities, NPP increased by 1.24 gC·m-2·year-1 and 2.29 gC·m-2·year-1, respectively. The contributions rates of climatic change and human activities separately accounted for 35% and 65%. The contribution of human activities on NPP was much higher than that of climatic change in the Southwest Karst area, and the results suggested that we should focus on the role of human activities on NPP change.

Spatiotemporal changes in net primary productivity before and after the development of unused land in the hilly areas of Hebei, China.

Net primary productivity (NPP) plays an important role in the carbon cycle of an ecosystem. To explore the impact of unused land development on NPP, this study adopted an improved Carnegie Ames Stanford Approach (CASA) model to analyze the changes in NPP before and after the development of unused land in Tang County, Hebei Province, in 2000, 2007, and 2018. The results showed that, due to the changes in land use types from unused land, forestland, arable land with high NPP values to urban and rural residential land, traffic land with low NPP values, and the changes in precipitation and temperature, the NPP in the study area showed an overall trend of decreasing first and then rising from 2000 to 2018. Before the development of unused land in 2000, the total NPP was 38.45×1010 g C. After the development in 2007 and 2018, the total NPP was 36.44×1010 g C and 41.05×1010 g C, respectively. The NPP of each land type in 2018 was arable land (1046.18 g C m-2) > forestland (464.42 g C m-2) > unused land (356.34 g C m-2) > grassland (343.77 g C m-2) > waters (182.56 g C m-2) > urban and rural settlements (120.86 g C m-2) > traffic land (120.70 g C m-2). The distribution of NPP was generally high in the north and low in the south before and after development. NPP was mainly concentrated in the interval of 300 g C m-2 yr-1–400 g C m-2 yr-1, and the range of NPP change was mostly within 100 g C m-2. The influence of elevation, temperature and precipitation on the spatial distribution of NPP was significant. Elevation and precipitation were positively correlated with NPP, while temperature was negatively correlated with NPP. The increase in NPP mainly originated from the conversion of unused land to forestland and arable land. The loss of NPP was mainly due to the conversion from forestland with high vegetation productivity to a land use type with low vegetation productivity, such as the conversion from forestland to urban and rural residential land. The results can provide references for making reasonable land planning decisions and ecological environment construction.

1996-2015年滇西北香格里拉植被净初级生产力变化

地处青藏高原东南缘的滇西北香格里拉，其植被NPP的时空格局变化，对于深入了解青藏高原区域植被对气候变化的响应具有重要的科学意义。基于地面气象数据和MODIS-NDVI等遥感数据，运用改进的CASA模型，估算了1996-2015年香格里拉区域不同植被类型NPP，分析探讨了区域植被NPP的演变特征及其对气候变化的响应规律。研究显示：1）1995-2015年间，香格里拉区域6-8月平均气温总体呈上升趋势，增速为0.037℃/a；6-8月总降水量为373.1 mm，呈微弱下降趋势；20年间辐射量基本维持波动稳定状态；2）1996-2015年，香格里拉区域6-8月最大月植被NPP平均值为176.9 gC/m²，不同植被类型的变化范围为128.9-286.9 gC/m²；空间格局上，表现为"从西北、东南及金沙江沿岸向中部递减"的特征；3）香格里拉区域植被NPP显著地受到气温变化的调控（P<0.05），20年间随着气温的持续升高，区域NPP总体呈增加趋势；4）区域植被NPP未表现出受降水变化的显著影响（P>0.05），水分条件对区域植被NPP未形成限制性的影响作用。区域内植被NPP在2005年前后的变化特征，一定程度上也表明了人类活动干扰及生态保护修复等政策措施的影响。;Studying on the spatial and temporal variation pattern of net primary productivity (NPP) in Shangri-La region in northwest Yunnan Province, which lies on the edge of southeast Qinghai-Tibet Plateau, is of scientific significance for exploring the response of vegetation to climate change. In this study, the NPPs of different vegetation types were estimated through using the improved CASA model based on surface meteorological data and remote sensing data including MODIS-NDVI and Landsat 5 TM image in Shangri-La region from 1996 to 2015. The spatial and temporal patterns of the NPP were analyzed and the responses of the NPP to major climate factors were revealed based on correlation analysis method. The results showed that:1) from 1996 to 2015, the annually average temperature from June to August in Shangri-La area indicated an overall trend of increase, with an increase rate of 0.037℃/a; the annually average precipitation of June-August was 373.1 mm, showing a slight downward trend; the annually total solar radiation basically maintained the fluctuation stable state during the period of 20 years; 2) From 1996 to 2015, the annually average NPP of vegetation in the Shangri-La area in June-August was 176.9 gC/m^2, and the variation range of different vegetation types was from 128.9-286.9 gC/m². Among them, the NPP of broad-leaved forest was significantly higher than that of other vegetation types, followed by cultivated land, grassland, shrub, and the NPP of coniferous forest was the lowest. The maximum monthly NPP of each vegetation type increased from 171.6 gC/m² to 182.3 gC/m² from the first 10 years to the second 10 years, increasing by 6.2%. In addition, the pattern of spatial distribution presented a trend of decrease from the northwest and southeast to middle of the zone; 3) The NPP of vegetation in Shangri-La region was significantly affected by annual temperature change (P<0.05), and presented an increasing trend generally with the continuous rise of temperature over 20 years; 4) The NPP of vegetation in this region was not significantly affected by precipitation change (P>0.05) which showed an nonrestrictive effect of water conditions to the NPP of vegetation. During the period from 1996 to 2005, the spatial distribution of NPP in Shangri-La was generally declining, and was obviously increasing during the period from 2005 to 2015. This change trend of NPP in the zone before and after 2005 also presented to some extent the influence of human activity disturbance and policy measures such as ecological protection and restoration on the NPP of regional vegetation.

Persistent Uncertainties in Ocean Net Primary Production Climate Change Projections at Regional Scales Raise Challenges for Assessing Impacts on Ecosystem Services

Ocean net primary production (NPP) results from CO2 fixation by marine phytoplankton, catalysing the transfer of organic matter and energy to marine ecosystems, supporting most marine food webs, and fisheries production as well as stimulating ocean carbon sequestration. Thus, alterations to ocean NPP in response to climate change, as quantified by Earth system model experiments conducted as part of the 5th and 6th Coupled Model Intercomparison Project (CMIP5 and CMIP6) efforts, are expected to alter key ecosystem services. Despite reductions in inter-model variability since CMIP5, the ocean components of CMIP6 models disagree roughly 2-fold in the magnitude and spatial distribution of NPP in the contemporary era, due to incomplete understanding and insufficient observational constraints. Projections of NPP change in absolute terms show large uncertainty in CMIP6, most notably in the North Atlantic and the Indo-Pacific regions, with the latter explaining over two-thirds of the total inter-model uncertainty. While the Indo-Pacific has previously been identified as a hotspot for climate impacts on biodiversity and fisheries, the increased inter-model variability of NPP projections further exacerbates the uncertainties of climate risks on ocean-dependent human communities. Drivers of uncertainty in NPP changes at regional scales integrate different physical and biogeochemical factors that require more targeted mechanistic assessment in future studies. Globally, inter-model uncertainty in the projected changes in NPP has increased since CMIP5, which amplifies the challenges associated with the management of associated ecosystem services. Notably, this increased regional uncertainty in the projected NPP change in CMIP6 has occurred despite reduced uncertainty in the regional rates of NPP for historical period. Improved constraints on the magnitude of ocean NPP and the mechanistic drivers of its spatial variability would improve confidence in future changes. It is unlikely that the CMIP6 model ensemble samples the complete uncertainty in NPP, with the inclusion of additional mechanistic realism likely to widen projections further in the future, especially at regional scales. This has important consequences for assessing ecosystem impacts. Ultimately, we need an integrated mechanistic framework that considers how NPP and marine ecosystems respond to impacts of not only climate change, but also the additional non-climate drivers.

Investigating net primary production in climate regions of central Zagros, Iran, using MODIS and meteorological data

Rangeland production is sensitive to climate conditions. In this study, we monitored actual and potential production in the climate zones of Chaharmahal and Bakhtiari province in central Zagros, Iran, from 2000-2016. Net primary production (NPP), light use efficiency (LUE) and rain use efficiency (RUE) were extracted from climatic and MODIS satellite data using the Carnegie-Ames-Stanford approach (CASA) and Miami models. The accuracy of the modeled NPP maps was assessed using regression analysis, based on field data collected at 750 sites under different rangeland conditions. The spatial distribution of NPP and RUE indicated that annual production and photosynthetic efficiency in degraded rangelands with poor and very poor conditions have decreased compared to those of moderate-good classes. The highest relationship between the field and modeled NPP was associated with the Astragalus spp.-Ferula spp. (R2 = 0.865, p &lt; 0.001) in the humid and cold climate zone with good rangeland conditions while the lowest was observed in the annual grasses-annual forbs (R2 = 0.198, p &lt; 0.001) vegetation type with very poor rangeland conditions within the semi-arid and cold climate zone. Furthermore, the highest and lowest NPP values were observed in the Daphne mucronata-Prangos ferulacea (48.38 g C m-2 yr-1) and annual grasses-annual forbs (3.42 g C m-2yr-1) vegetation types with LUE values of 0.13 and 0.02 g C MJ-1 within the humid and cold and the semi-humid and cold climate zones, respectively. According to these findings, remote sensing-based differences between actual and potential NPP can be used as a valuable tool for identification of human impacts on broad rangeland ecosystems.

Effects of precipitation and temperature on net primary productivity and precipitation use efficiency across China’s grasslands

Net primary production (NPP) is a crucial feature of ecosystem function and structure. Furthermore, precipitation use efficiency (PUE) is a critical indicator for exploring NPP in grassland ecosystem responses to variations in precipitation and temperature. In this study, we examined the spatial patterns of NPP and PUE in China’s grasslands from 2000 to 2010 and explored the effects of environmental factors on NPP and PUE at different scales. The results showed first that the spatial distribution of NPP and PUE decreased from the northeast to southwest. NPP increased in most places across China’s grasslands; however, there was no obvious change in PUE during 2000–2010. Second, in most regions across China’s grasslands, positive and negative correlations existed between precipitation and NPP and PUE, respectively. The spatial distribution of the relationship between temperature and NPP and PUE was consistent with the relationship between precipitation with NPP and PUE. Finally, for the gradients of the various environmental factors in different regional grassland ecosystems, on the Tibetan Plateau, there were unimodal correlations between precipitation with NPP and PUE and aridity with NPP and PUE, but a positive linear correlation existed for temperature with NPP and PUE. However, in the Inner Mongolian Plateau, there were positive correlations between precipitation and NPP, temperature and NPP, and aridity and both NPP and PUE and negative correlations between precipitations and PUE and temperature and PUE. Our findings improve understanding of grassland ecosystem responses to global climate change and provide a basis for the protection of grassland ecosystems in arid and semi-arid regions.

Changes of NPP and their relationship to climate factors based on the transformation of different scales in Gansu, China

Net primary production (NPP) is one of the important indexes of ecological change. In this study, the spatial distribution of NPP in Gansu province was simulated using an improved Carnegie-Ames-Stanford Approach (CASA) model, from 2000 to 2010, using MODIS-NDVI data at 250×250m spatial resolution. We analyzed NPP responses in forest, grassland, agricultural and desert biomes to climate change, by combining the simulated data with meteorological data. The results indicated that: (i) The spatial distribution of the annual NPP from 2000 to 2010 varied significantly over the region, with NPP high in the southeast, but low in the northwest, of Gansu. The mean annual NPP values for forest, grassland, agricultural and desert biomes were 580.12 gC m−2 yr−1, 380.12gC m−2 yr−1, 280.71gC m−2 yr−1 and 83.27gC m−2 yr−1, respectively. (ii) The annual NPP values with extremely significant increase (ESI, θslope>0 and p<0.01) and significant increase (SI, θslope>0 and 0.01≤p<0.05) from 2000 to 2010 accounted for 6.00% and 17.49% of the total area, respectively. The annual NPP values with extremely significant decrease (ESD, θslope<0 and p<0.01) and significant decrease (SD, θslope<0 and 0.01≤p<0.05) from 2000 to 2010 accounted for 12.31% and 27.07% of the total area, respectively. Overall, the NPP values displayed a decreasing trend. (iii) The forest and grassland biomes were influenced mainly by temperature, while precipitation was the main controlling factor in the desert and agricultural biomes, at the annual scale. (iv) Compared with the forest and desert biomes, the grassland and agricultural biomes showed time-lag and cumulative correlations with precipitation and temperature, respectively.

Responses of Terrestrial Ecosystems’ Net Primary Productivity to Future Regional Climate Change in China

The impact of regional climate change on net primary productivity (NPP) is an important aspect in the study of ecosystems’ response to global climate change. China’s ecosystems are very sensitive to climate change owing to the influence of the East Asian monsoon. The Lund–Potsdam–Jena Dynamic Global Vegetation Model for China (LPJ-CN), a global dynamical vegetation model developed for China’s terrestrial ecosystems, was applied in this study to simulate the NPP changes affected by future climate change. As the LPJ-CN model is based on natural vegetation, the simulation in this study did not consider the influence of anthropogenic activities. Results suggest that future climate change would have adverse effects on natural ecosystems, with NPP tending to decrease in eastern China, particularly in the temperate and warm temperate regions. NPP would increase in western China, with a concentration in the Tibetan Plateau and the northwest arid regions. The increasing trend in NPP in western China and the decreasing trend in eastern China would be further enhanced by the warming climate. The spatial distribution of NPP, which declines from the southeast coast to the northwest inland, would have minimal variation under scenarios of climate change.

Estimation of net primary productivity in China using remote sensing data

It is significant to estimate terrestrial net primary productivity (NPP) accurately not only for global change research, but also for natural resources management to achieve sustainable development. Remote sensing data can describe spatial distribution of plant resources better. So, in this paper an NPP model based on remote sensing data and climate data is developed. And 1km resolution AVHRR NDVI data are used to estimate the spatial distribution and seasonal change of NPP in China. The results show that NPP estimated using remote sensing data are more close to truth. Total annual NPP in China is 2.645X109 tC. The spatial distribution of NPP in China is mainly affected by precipitation and has the trend of decreasing from southeast to northwest.