Quantifying the response of forest carbon balance to future climate change in Northeastern China: Model validation and prediction

In this study, we report on the validation of process-based forest growth and carbon and nitrogen model of TRIPLEX against observed data, and the use of the model to investigate the potential impacts and interaction of climate change and increasing atmospheric CO₂ on forest net primary productivity (NPP) and carbon budgets in northeast of China. The model validation results show that the simulated tree total volume, NPP, total biomass and soil carbon are consistent with observed data across the Northeast of China, demonstrating that the improved TRIPLEX model is able to simulate forest growth and carbon dynamics of the boreal and temperate forest ecosystems at regional scale. The climate change would increase forest NPP and biomass carbon but decrease overall soil carbon under all three climate change scenarios. The combined effects of climate change and CO₂ fertilization on the increase of NPP were estimated to be 10–12% for 2030s and 28–37% in 2090s. The simulated effects of CO₂ fertilization significantly offset the soil carbon loss due to climate change alone. Overall, future climate change and increasing atmospheric CO₂ would have a significant impact on the forest ecosystems of Northeastern China.     

The possible response of life zones in China under global climate change

The response of natural vegetation to climate change is of global concern. In this research, an aggregated Holdridge Life Zone System was used to study the possible response of life zones in China under doubled atmospheric CO₂ concentration with the input climatic parameters at 0.5×0.5° resolution of longitude and latitude from NCAR regional climate model 2 (RegCM2) coupled with the CSIRO global climate model. The results indicate that the latitudinal distribution of life zones would become irregular because of the complicated climate change. In particular, new life zones, such as subtropical desert (SD), tropical desert (TDE) and tropical thorn woodland (TTW), would appear. Subtropical evergreen broadleaved forest (SEBF), tropical rainforest and monsoon forest (TRF), SD, TDE and TTW zones would appear in the northeastern China. Cool-temperate mixed coniferous and broadleaved forest (CMC) and warm-temperate deciduous broadleaved forest (WDBF) zones would appear at latitudes 25–35°N. The temperate desert (TD) in the western China would become Tibetan high-cold plateau (THP), SEBF, WDBF and temperate steppe (TS), and a large part of THP would be replaced by TRF, TDE, SEBF, TS and TTW. The relative area (distribution area/total terrestrial area) of CMC, TRF, TDE and TTW zone would increase about 3%, 21%, 3% and 6%, respectively. However, the relative area of SEBF, TS, TD and THP would decrease about 5%, 3%, 19% and 4%, respectively. In all, the relative area of forests (CCF, CMC, WDBF, SEBF, TRF) would increase about 15%, but the relative area of desert (TD, SD, TDE, and TTW) and THP would decrease about 9% and 4%, respectively. Therefore, responses of different life zones in China to climate change would be dramatic, and nationwide corridors should be considered for the conservation of migrating species under climate change.     

Numerical modeling of the response of alluvial rivers to Quaternary climate change

A numerical model, which simulates the dynamics of alluvial river channels on geological (Quaternary) time scales, is presented. The model includes water flow, channel dimensions, sediment transport and channel planform type. A number of numerical experiments, which investigate the response of an alluvial river to imposed sequences of water and sediment supply, with special emphasis on the time lags between these controlling variables, as well as a downstream discharge increase, are presented. It is found that the influence of the time lags can be substantial, having major implications for the reconstructions of palaeo climate based on river channel behavior documented in the geological record. The model is further applied to both a conceptual warm–cold–warm cycle and a reconstructed evolution of the river Meuse, the Netherlands, during the Late Glacial–Holocene warming. Results show that the model is capable of explaining the response of this river, although better validation against palaeoenvironmental data remains necessary.     

Multi-model Bayesian assessment of climate change in the northern annular mode

A typical question in climate change analysis is whether a certain observed climate characteristic, like a pronounced anomaly or an interdecadal trend, is an indicator of anthropogenic climate change or still in the range of natural variability. Many climatic features are described by one-dimensional index time series, like for instance the global mean temperature or circulation indices. Here, we present a Bayesian classification approach applied to the time series of the northern annular mode (NAM), which is the leading mode of Northern Hemisphere climate variability. After a pronounced negative phase during the 1950s and 1960s, the observed NAM index reveals a distinct positive trend, which is also simulated by various climate model simulations under enhanced greenhouse conditions. The objective of this study is to decide whether the observed temporal evolution of the NAM may be an indicator of global warming. Given a set of prior probabilities for disturbed and undisturbed climate scenarios, the Bayesian decision theorem decides whether the observed NAM trend is classified in a control climate, a greenhouse-gas plus sulphate aerosol climate or a purely greenhouse-gas induced climate as derived from multi-model ensemble simulations.The three climate scenarios are well separated from each other in terms of the 30-year NAM trends. The multi-model ensembles contain a weak but statistically significant climate change signal in the form of an intensification of the NAM. The Bayesian classification suggests that the greenhouse-gas scenario is the most probable explanation for the observed NAM trend since 1960, even if a high prior probability is assigned to the control climate. However, there are still large uncertainties in this classification result because some periods at the end of the 19th century and during the “warm” 1920s are also classified in an anthropogenic climate, although natural forcings are likely responsible for this early NAM intensification. This demonstrates a basic shortcoming of the Bayesian decision theorem when it is based on one-dimensional index time series like the NAM index.     

An empirical assessment of the impact of climate change on smallholder agriculture in Cameroon

Rainfed tropical agriculture provides important avenue to ascertain the consequences of climate change. This is because reliability of rainfall accounts for much of the variation in agriculture in the region. In addition, the region is already hot and vulnerable from further warming. This study shows from a climate change experiment using Ricardian method in Cameroon that a 7% decrease in precipitation would cause net revenues from crops to fall US$2.86 billion and a 14% decrease in precipitation would cause net revenue from crops to fall US$3.48 billion. Increases in precipitation would have the opposite effect on net revenues. For a 2.5 °C warming, net revenues would fall by US$0.79 billion, and a 5 °C warming would cause net revenues to fall US$1.94 billion. This highlights that agriculture is not only limited by seasonality and magnitude of moisture availability, but also it is significantly impacted by climate change.     

Glacier retreat and climatic variability in the eastern Terskey–Alatoo, inner Tien Shan between the middle of the 19th century and beginning of the 21st century

Changes in the extent of glaciers and rates of glacier termini retreat in the eastern Terskey–Alatoo Range, the Tien Shan Mountains, Central Asia have been evaluated using the remote sensing techniques. Changes in the extent of 335 glaciers between the end of the Little Ice Age (LIA; mid-19th century), 1990 and 2003 have been estimated through the delineation of glacier outlines and the LIA moraine positions on the Landsat TM and ASTER imagery for 1990 and 2003 respectively. By 2003, the glacier surface area had decreased by 19% of the LIA value, which constitutes a 76 km² reduction in glacier surface area. Mapping of 109 glaciers using the 1965 1:25,000 maps revealed that glacier surface area decreased by 12.6% of the 1965 value between 1965 and 2003. Detailed mapping of 10 glaciers using historical maps and aerial photographs from the 1943–1977 period, has enabled glacier extent variations over the 20th century to be identified with a higher temporal resolution. Glacial retreat was slow in the early 20th century but increased considerably between 1943 and 1956 and then again after 1977. The post-1990 period has been marked by the most rapid glacier retreat since the end of the LIA. The observed changes in the extent of glaciers are in line with the observed climatic warming. The regional weather stations have revealed a strong climatic warming during the ablation season since the 1950s at a rate of 0.02–0.03 °C a^− 1. At the higher elevations in the study area represented by the Tien Shan meteorological station, the summer warming was accompanied by negative anomalies in annual precipitation in the 1990s enhancing glacier retreat. However, trends in precipitation in the post-1997 period cannot be evaluated due to the change in observational practices at this station. Neither station in the study area exhibits significant long-term trends in precipitation.     

Transient projections of permafrost distribution in Canada during the 21st century under scenarios of climate change

Most general circulation models (GCMs) project that climate will be warmer in the 21st century, especially in high latitudes. Climate warming will induce permafrost degradation, which would have great impacts on hydrology, ecosystems and soil biogeochemistry, and could destabilize the foundations of infrastructure. In this study, we simulated transient changes of permafrost distribution in Canada in the 21st century using a process-based permafrost model driven by six GCM-generated climate scenarios. The results show that the area underlain by permafrost in Canada would be reduced by 16.0–19.7% from the 1990s to the 2090s. This estimate was smaller than equilibrium projections because the ground thermal regime was in disequilibrium at the end of the 21st century and permafrost degradation would continue. The simulation shows significant permafrost thaw from the top: On average for the area where permafrost exists in all the years during 1990–2100, active-layer thickness increased by 0.3–0.7 m (or 41–104%), the depth to permafrost table increased by 1.9–5.0 m, and the area with taliks increased exponentially. Permafrost was also thawed from the bottom in southern regions.     

Sediment flux sensitivity to climate change: A case study in the Longchuanjiang catchment of the upper Yangtze River, China

Climate change may affect the sediment generation and transportation processes and the consequent sediment flux in a river. The sensitivity of suspended sediment flux to climate change in the Longchuanjiang catchment is investigated with Artificial Neural Networks (ANNs). ANNs were calibrated and validated using sediment flux data from 1960 to 1990 during which the influence from human activities was relatively stable. The established ANN is used to predict the responses of sediment flux to 25 hypothetical climate scenarios, which were generated by adjusting the baseline temperature up to − 1, 1, 2 and 3 °C and by scaling the baseline precipitation by +/− 10% and +/− 20%. The results indicated when temperature remains unchanged, an increase in rainfall will lead to a rise in sediment flux; when rainfall level remains unchanged, an increase in temperature is likely to result in a decrease in sediment flux. Same percentage of changes in rainfall and temperature are likely to trigger higher responses in wetter months than in drier months. However, it is the combination of the change in temperature and rainfall that determines the change of sediment flux in a river. Higher sediment flux is expected to appear under wetter and warmer climate, when higher transport capacity is accompanied by higher erosion rate.     

Modeling the interannual variability and trends in gross and net primary productivity of tropical forests from 1982 to 1999

The role of tropical ecosystems in global carbon cycling is uncertain, at least partially due to an incomplete understanding of climatic forcings of carbon fluxes. To reduce this uncertainty, we simulated and analyzed 1982–1999 Amazonian, African, and Asian carbon fluxes using the Biome-BGC prognostic carbon cycle model driven by National Centers for Environmental Prediction reanalysis daily climate data. We first characterized the individual contribution of temperature, precipitation, radiation, and vapor pressure deficit to interannual variations in carbon fluxes and then calculated trends in gross primary productivity (GPP) and net primary productivity (NPP). In tropical ecosystems, variations in solar radiation and, to a lesser extent, temperature and precipitation, explained most interannual variation in GPP. On the other hand, temperature followed by solar radiation primarily determined variation in NPP. Tropical GPP gradually increased in response to increasing atmospheric CO₂. Confirming earlier studies, changes in solar radiation played a dominant role in CO₂ uptake over the Amazon relative to other tropical regions. Model results showed negligible impacts from variations and trends in precipitation or vapor pressure deficits on CO₂ uptake.