Emerging Negative Warming Impacts on Tibetan Crop Yield

Preserving Tibet’s unique history and cultural heritage relies on the sustainability of the Tibetan croplands,which are characterized by highland barley,the only cereal crop cultivated over 4000 m above sea level.Yet it is unknown how these croplands will respond to climate change.Here,using yield statistics from 1985 to 2015,we found that the impact of temperature anomalies on the Tibetan crop yield shifted from nonsignificant(P>0.10)in the 1980s and 1990s to significantly negative(P<0.05)in recent years.Meanwhile,the apparent sensitivity of the crop yield to temperature anomalies almost doubled,from(–0.13±0.20)to(–0.22±0.14)t·ha^(-1)℃^(–1).The emerging negative impacts of higher temperatures suggest an increasing vulnerability of Tibetan croplands to warmer climate.With global warming scenarios of+1.5 or+2.0℃above the pre-industry level,the temperature sensitivities of crop yield may further increase to(–0.33±0.10)and(–0.51±0.18)t·ha^(-1)℃^(–1),respectively,making the crops 2–3 times more vulnerable to warmer temperatures than they are today.

Comparing community birdwatching and professional bird monitoring with implications for avian diversity research: a case study of Suzhou, China

Background:In the past decades,birdwatching as a hobby developed rapidly and produced ample scientific records that have aided conservation efforts.Therefore,it is increasingly attractive to promote avian research by providing data from birdwatching.Methods:We compared records from 16 years of community birdwatching and a 1-year formalized bird monitoring in Suzhou,China to study the similarities and differences between the two monitoring methods.Results:We showed that within the 325 bird species recorded by the two methods,an annual average of 108 species were documented by community science and 223 bird species were recorded by 1-year formalized monitoring.Measured by the number of bird species recorded per survey trip,the bird monitoring activity of community birdwatchers was significantly lower.Furthermore,the monitoring intensity of community birdwatching measured as the average survey trips per site each survey year was also lower than that of formalized bird monitoring.In addition,community birdwatchers preferred urban landscapes to rural areas.Conclusions:Community birdwatching could record the majority of local birds and complements the professional surveys in avian research.Well designed and coordinated community science can be used to expand the knowledge about avian distribution and population dynamics.These findings are critical for the development of conservation science with regard to community involvement.

Spatiotemporal dynamics of ecosystem fires and biomass burning-induced carbon emissions in China over the past two decades

Fire is a major type of disturbance that has important influences on ecosystem dynamics and carbon cycles.Yet our understanding of ecosystem fires and their carbon cycle consequences is still limited,largely due to the difficulty of large-scale fire monitoring and the complex interactions between fire,vegetation,climate,and anthropogenic factors.Here,using data from satellite-derived fire observations and ecosystem model simulations,we performed a comprehensive investigation of the spatial and temporal dynamics of China’s ecosystem fire disturbances and their carbon emissions over the past two decades(1997–2016).Satellite-derived results showed that on average about 3.47-4.53×10^(4) km^(2) of the land was burned annually during the past two decades,among which annual burned forest area was about 0.81-1.25×10^(4) km^(2),accounting for 0.33-0.51%of the forest area in China.Biomass burning emitted about 23.02 TgC per year.Compared to satellite products,simulations from the Energy Exascale Earth System Land Model(ELM)strongly overestimated China’s burned area and fire-induced carbon emissions.Annual burned area and fire-induced carbon emissions were high for boreal forest in Northeast China’s Daxing’anling region and subtropical dry forest in South Yunnan,as revealed by both the satellite product and the model simulations.Our results suggest that climate and anthropogenic factors play critical roles in controlling the spatial and seasonal distribution of China’s ecosystem fire disturbances.Our findings highlight the importance of multiple complementary approaches in assessing ecosystem fire disturbance and its carbon consequences.Further studies are required to improve the methods of observing and modelling China’s ecosystem fire disturbances,which will provide valuable information for fire management and ecosystem sustainability in an era when both human activities and the natural environment are rapidly changing.

The impacts of climate extremes on the terrestrial carbon cycle:A review

The increased frequency of climate extremes in recent years has profoundly affected terrestrial ecosystem functions and the welfare of human society. The carbon cycle is a key process of terrestrial ecosystem changes. Therefore, a better understanding and assessment of the impacts of climate extremes on the terrestrial carbon cycle could provide an important scientific basis to facilitate the mitigation and adaption of our society to climate change. In this paper, we systematically review the impacts of climate extremes(e.g. drought, extreme precipitation, extreme hot and extreme cold) on terrestrial ecosystems and their mechanisms. Existing studies have suggested that drought is one of the most important stressors on the terrestrial carbon sink, and that it can inhibit both ecosystem productivity and respiration. Because ecosystem productivity is usually more sensitive to drought than respiration, drought can significantly reduce the strength of terrestrial ecosystem carbon sinks and even turn them into carbon sources. Large inter-model variations have been found in the simulations of drought-induced changes in the carbon cycle, suggesting the existence of a large gap in current understanding of the mechanisms behind the responses of ecosystem carbon balance to drought, especially for tropical vegetation. The effects of extreme precipitation on the carbon cycle vary across different regions. In general, extreme precipitation enhances carbon accumulation in arid ecosystems, but restrains carbon sequestration in moist ecosystems. However, current knowledge on the indirect effects of extreme precipitation on the carbon cycle through regulating processes such as soil carbon lateral transportation and nutrient loss is still limited. This knowledge gap has caused large uncertainties in assessing the total carbon cycle impact of extreme precipitation. Extreme hot and extreme cold can affect the terrestrial carbon cycle through various ecosystem processes. Note that the severity of such climate extremes depends greatly on their timing, which needs to be investigated thoroughly in future studies. In light of current knowledge and gaps in the understanding of how extreme climates affect the terrestrial carbon cycle, we strongly recommend that future studies should place more attention on the long-term impacts and on the driving mechanisms at different time scales.Studies based on multi-source data, methods and across multiple spatial-temporal scales, are also necessary to better characterize the response of terrestrial ecosystems to climate extremes.

Mapping global forest biomass and its changes over the first decade of the 21st century

Forests played an important role in carbon sequestration during the past two decades. Using a model tree ensemble method(MTE) to regress the seven reflectance bands of EOS-Terra-MODIS satellite data against country level forest biomass carbon density(BCD) of 2001–2005 provided by United Nations' s Forest Resource Assessment(FRA), we developed a global map of forest BCD at 1 km×1 km resolution for both 2001–2005 and 2006–2010. For 2006–2010, the total global forest biomass carbon stock is estimated as 279.6±7.1 Pg C, and the tropical forest biomass carbon stock is estimated as 174.4±5.4 Pg C. During the first decade of the 21 st century, we estimated an increase of global forest biomass of 0.28±0.75 Pg C yr^(-1). Tropical forest biomass carbon stock slightly decreased(-0.31±0.60 Pg C yr^(-1)); by contrast, temperate and boreal forest biomass increased(0.58±0.28 Pg C yr^(-1)) during the same period. Our estimation of the global forest biomass carbon stock and its changes is subject to uncertainties due to lack of extensive ground measurements in the tropics, spatial heterogeneity in large countries, and different definitions of forest. The continuously monitoring of forest biomass carbon stock with MODIS satellite data will provide useful information for detecting forest changes.

Spring and autumn phenology across the Tibetan Plateau inferred from normalized difference vegetation index and solar-induced chlorophyll fluorescence

Plant phenology is a key parameter for accurately modeling ecosystem dynamics.Limited by scarce ground observations and benefiting from the rapid growth of satellite-based Earth observations,satellite data have been widely used for broad-scale phenology studies.Commonly used reflectance vegetation indices represent the emergence and senescence of photosynthetic structures(leaves),but not necessarily that of photosynthetic activities.Leveraging data of the recently emerging solar-induced chlorophyll fluorescence(SIF)that is directly related to photosynthesis,and the traditional MODIS Normalized Difference Vegetation Index(NDVI),we investigated the similarities and differences on the start and end of the growing season(SOS and EOS,respectively)of the Tibetan Plateau.We found similar spatiotemporal patterns in SIF-based SOS(SOS_(SIF))and NDVI-based SOS(SOS_(NDV)I).These spatial patterns were mainly driven by temperature in the east and by precipitation in the west.Yet the two satellite products produced different spatial patterns in EOS,likely due to their different climate dependencies.Our work demonstrates the value of big Earth data for discovering broad-scale spatiotemporal patterns,especially on regions with scarce field data.This study provides insights into extending the definition of phenology and fosters a deeper understanding of ecosystem dynamics from big data.

Interannual variability and climatic sensitivity of global wildfire activity

Understanding historical wildfire variations and their environmental driving mechanisms is key to predicting and mitigating wildfires. However, current knowledge of climatic responses and regional contributions to the interannual variability (IAV) of global burned area remains limited. Using recent satellite-derived wildfire products and simulations from version v1.0 of the land component of the U.S. Department of Energy's Energy Exascale Earth System Model (E3SM land model [ELM] v1) driven by three different climate forcings, we investigated the burned area IAV and its climatic sensitivity globally and across nine biomes from 1997 to 2018. We found that 1) the ELM simulations generally agreed with the satellite observations in terms of the burned area IAV magnitudes, regional contributions, and covariations with climate factors, confirming the robustness of the ELM to the usage of different climate forcing sources;2) tropical savannas, tropical forests, and semi-arid grasslands near deserts were primary contributors to the global burned area IAV, collectively accounting for 71.7%–99.7% of the global wildfire IAV estimated by both the satellite observations and ELM simulations;3) precipitation was a major fire suppressing factor and dominated the global and regional burned area IAVs, and temperature and shortwave solar radiation were mostly positively related with burned area IAVs;and 4) noticeable local discrepancies between the ELM and remote-sensing results occurred in semi-arid grasslands, croplands, boreal forests, and wetlands, likely caused by uncertainties in the current ELM fire scheme and the imperfectly derived satellite observations. Our findings revealed the spatiotemporal diversity of wildfire variations, regional contributions and climatic responses, and provided new metrics for wildfire modeling, facilitating the wildfire prediction and management.

Fertilization regulates the response of wheat yield to interannual temperature variation in North China

Aims understanding the effect of long-term fertilization on the sensitivity of grain yield to temperature changes is critical for accurately assess-ing the impact of global warming on crop production.In this study,we aim to assess the impacts of temperature changes on grain yields of winter wheat(Triticum aestivum l.)under different fertilization treatments in a long-term manipulative experiment in North China.Methods We measured grain yields of winter wheat under four fertilization treatments at the Yucheng Comprehensive Experimental station each year from 1993 to 2012.We also measured air temperature at 0200,0800,1400 and 2000 h each day since 1 January 1980.We then used the first-difference method and simple linear regres-sion models to examine the relationship of crop yield changes to mean air temperature,mean daytime and nighttime air temperature in crop growing seasons.Important Findings We found that increases in mean daily temperature,mean day-time temperature and mean nighttime temperature each had a positive impact on the grain yield of winter wheat.grain yield increased by 16.7-85.6%for winter wheat in response to a 1°C increase in growing season mean daily temperature.Winter wheat yield was more sensitive to variations of nighttime temperature than to that of daytime temperature.The observed temperature impacts also varied across different fertilization treatments.balanced fertilization significantly enhanced grain yields for winter wheat under a warming climate.Wheat plots treated with nitrogen and phosphorous balanced fertilization(NPK-and NP-treated plots)were more responsive to temperature changes than those without.This report provides direct evidence of how temperature change impacts grain yields under different fertiliza-tion treatments,which is useful for crop management in a chang-ing global climate.

China's Growth Slowdown:Labor Supply,Productivity,or What?

There has been much discussion of the sources of China's growth slowdown but little formal econometric analysis of this question.Chen and Groenewold(2019)show that the slowdown was primarily supply-driven,but they stopped short of identifying specific supply variables.This paper extends their analysis and distinguishes several potential supply components:labor supply,productivity,and capital accumulation.Our results confirm their main conclusion that supply dominates the explanation of the slowdown.A model with two supply factors(labor supply and productivity)reveals that both components contribute to the slowdown,although productivity makes the greater contribution.However,when capital stock is added to the model,the decline in the capital accumulation rate becomes an important factor in the growth slowdown,to some extent replacing the effects of both labor supply and productivity.

Improved Fine-Scale Tropical Forest Cover Mapping for Southeast Asia Using Planet-NICFI and Sentinel-1 Imagery

The accuracy of existing forest cover products typically suffers from“rounding”errors arising from classifications that estimate the fractional cover of forest in each pixel,which often exclude the presence of large,isolated trees and small or narrow forest clearings,and is primarily attributable to the moderate resolution of the imagery used to make maps.However,the degree to which such high-resolution imagery can mitigate this problem,and thereby improve large-area forest cover maps,is largely unexplored.Here,we developed an approach to map tropical forest cover at a fine scale using Planet and Sentinel-1 synthetic aperture radar(SAR)imagery in the Google Earth Engine platform and used it to map all of Southeastern Asia’s forest cover.The machine learning approach,based on the Random Forests models and trained and validated using a total of 37,345 labels collected from Planet imagery across the entire region,had an accuracy of 0.937 and an F1 score of 0.942,while a version based only on Planet imagery had an accuracy of 0.908 and F1 of 0.923.We compared the accuracy of our resulting maps with 5 existing forest cover products derived from medium-resolution optical-only or combined optical-SAR approaches at 3,000 randomly selected locations.We found that our approach overall achieved higher accuracy and helped minimize the rounding errors commonly found along small or narrow forest clearings and deforestation frontiers where isolated trees are common.However,the forest area estimates varied depending on topographic location and showed smaller differences in highlands(areas>300 m above sea level)but obvious differences in complex lowland landscapes.Overall,the proposed method shows promise for monitoring forest changes,particularly those caused by deforestation frontiers.Our study also represents one of the most extensive applications of Planet imagery to date,resulting in an open,high-resolution map of forest cover for the entire Southeastern Asia region.