The effect of vegetation in a climate model simulation on the Younger Dryas

The effect of vegetation on the Younger Dryas (YD) climate is studied by comparing the results of four experiments performed with the ECHAM-4 atmospheric general circulation model (AGCM): (1) modern control climate, (2) simulation with YD boundary conditions, but with modern vegetation, (3 and 4) identical to (2), but with paleo-vegetation. Prescribing paleo-vegetation instead of modern vegetation resulted in temperature anomalies (both positive and negative) of up to 4°C in the Northern Hemisphere mid-latitudes, mainly as an effect of changes in forest cover (change in albedo). Moreover, changes in precipitation and evaporation were found, most notably during December–January–February (DJF) in the tropics and were caused by the replacement of forests by grasslands. These results are consistent with other model studies on the role of vegetation changes on climate and they suggest that it is important in paleoclimate simulation studies to prescribe realistic vegetation types, belonging to the period of interest. However, in our case the addition of YD vegetation did not improve the agreement with proxy data in Europe, as the temperatures were increasing during winter compared to the YD simulation with modern vegetation. It must be noted that this increase was not statistically significant. The model-data mismatch suggests that other factors probably played an important role, such as permafrost and atmospheric dust. We infer that during the last glacial-interglacial transition, the time lag between the first temperature increase and the northward migration of trees, estimated at 500–1000 years, could have delayed the warming of the Eurasian continent. The relatively open vegetation that existed during the early stages of the last glacial-interglacial transition had a relatively high albedo, thus tempering warming up of the Eurasian land surfaces.     

Reconstructing the Younger Dryas ice dammed lake in the Baltic Basin: Bathymetry, area and volume

A digital 3D-reconstruction of the Baltic Ice Lake's (BIL) configuration during the termination of the Younger Dryas cold phase (ca. 11 700 cal. yr BP) was compiled using a combined bathymetric–topographic Digital Terrain Model (DTM), Scandinavian ice sheet limits, Baltic Sea Holocene bottom sediment thickness information, and a paleoshoreline database maintained at the Lund University. The bathymetric–topographic DTM, assembled from publicly available data sets, has a resolution of 500 × 500 m on Lambert Azimuthal Equal Area projection allowing area and volume calculations of the BIL to be made with an unprecedented accuracy. When the damming Scandinavian ice sheet margin eventually retreated north of Mount Billingen, the high point in terrain of Southern central Sweden bordering to lower terrain further to the north, the BIL was catastrophically drained resulting in a 25 m drop of the lake level. With our digital reconstruction, we estimate that approximately 7800 km³ of water drained during this event and that the ice dammed lake area was reduced by ca. 18%. Building on previous results suggesting drainage over 1 to 2 years, our lake volume calculations imply that the freshwater flux to the contemporaneous sea in the west was between about 0.12 and 0.25 Sv. The BIL reconstruction provides new detailed information on the paleogeography in the area of southern Scandinavia, both before and after the drainage event, with implications for interpretations of geological records concerning the post-glacial environmental development.     

Biomization and quantitative climate reconstruction techniques in northwestern Mexico—With an application to four Holocene pollen sequences

New paleovegetation and paleoclimatic reconstructions from the Sierra Madre Occidental (SMO) in northwestern Mexico are presented. This work involves climate and biome reconstruction using Plant Functional Types (PFT) assigned to pollen taxa. We used fossil pollen data from four Holocene peat bogs located at different altitudes (1500‑2000 m) at the border region of Sonora and Chihuahua at around 28° N latitude (Ortega-Rosas, C.I. 2003. Palinología de la Ciénega de Camilo: datos para la historia de la vegetación y el clima del Holoceno medio y superior en el NW de la Sierra Madre Occidental, Sonora, Mexico. Master Thesis, Universidad Nacional Autónoma de México, México D.F.; Ortega-Rosas, C.I., Peñalba, M.C., Guiot, J. Holocene altitudinal shifts in vegetation belts and environmental changes in the Sierra Madre Occidental, Northwestern Mexico. Submitted for publication of Palaeobotany and Palynology). The closest modern pollen data come from pollen analysis across an altitudinal transect from the Sonoran Desert towards the highlands of the temperate SMO at the same latitude (Ortega-Rosas, C.I. 2003. Palinología de la Ciénega de Camilo: datos para la historia de la vegetación y el clima del Holoceno medio y superior en el NW de la Sierra Madre Occidental, Sonora, Mexico. Master Thesis, Universidad Nacional Autónoma de México, México D.F.). An additional modern pollen dataset of 400 sites across NW Mexico and the SW United States was compiled from different sources (Davis, O.K., 1995. Climate and vegetation pattern in surface samples from arid western U.S.A.: application to Holocene climatic reconstruction. Palynology 19, 95–119, North American Pollen Database, Latin-American Pollen Database, personal data, and different scientific papers). For the biomization method (Prentice, I.C., Guiot, J., Huntley, B., Jolly, D., Cheddadi, R., 1996. Reconstructing biomes from paleoecological data: a general method and its application to European pollen data at 0 and 6 ka. Climate Dynamics 12, 185–194), we modified the pollen-PFT and PFT-biomes assignation of Thompson and Anderson (Thompson, R.S., Anderson, K.H., 2000. Biomes of western North America at 18,000; 6000 and 0 14C yr BP reconstructed from pollen and packrat midden data. Journal of Biogeography 27, 555–584) for a better representation of the modern vegetation of NW Mexico. The biome reconstruction method was validated with the modern pollen sites and applied to the fossil sites. Our results show that, during the early Holocene, a cool conifer forest extended at least down to 1700 m, while today this biome is present above 2000 m in the Chihuahua state. The Younger Dryas event was recorded in one site with cold and dry conditions. The reconstructed annual temperature for this period was 3°–6 °C colder than today, and annual precipitation was 250 mm lower than at present (900 mm/yr). The middle Holocene after 9200 cal yr BP was marked by a warming trend, reaching temperatures 2 °C warmer than today at 7000 cal yr BP, and by the installation of a warm mixed forest, the present day biome, at 1700 m elevation, while at higher elevations (1900 m) the cool conifer forest was still present. Summer precipitation was 200 mm/yr above the early Holocene values, suggesting that monsoon-like conditions strengthened since 9200 cal yr BP at this region. During the last 4000 yr, the same warm mixed forest was reconstructed below 1700 m and a conifer forest above 1700 m. A great variability of vegetation and climate patterns was recorded for the last 3000 yr particularly at high elevation sites, where warming and cooling trends would be coeval of the Medieval warm period and Little Ice Age, likely related to ENSO variability.     

Temperature changes on the Tibetan Plateau during the past 600 years inferred from ice cores and tree rings

The climatological signal of δ¹⁸O variations preserved in ice cores recovered from Puruogangri ice field in the central Tibetan Plateau (TP) was calibrated with regional meteorological data for the past 50 years. For the period AD 1860–2000, 5-yearly averaged ice core δ¹⁸O and a summer temperature reconstruction derived from pollen data from the same ice core were compared. The statistical results provide compelling evidence that Puruogangri ice core δ¹⁸O variations represent summer temperature changes for the central TP, and hence regional temperature history during the past 600 years was revealed. A comparison of Puruogangri ice core δ¹⁸О with several other temperature reconstructions shows that broad-scale climate anomalies since the Little Ice Age occurred synchronously across the eastern and southern TP, and the Himalayas. Common cold periods were identified in the 15th century, 1625–1645 AD, 1660–1700 AD, 1725–1775 AD, 1795–1830 AD, 1850–1870 AD, 1890–1920 AD, 1940–1950 AD, and 1975–1985 AD. The period 1725–1775 AD was one of the most prolonged cool periods during the past 400 years and corresponded to maximum Little Ice Age glacier advance of monsoonal temperate glaciers of the TP.     

Postglacial relative sea-level change and stratigraphy of raised coastal basins on Kola Peninsula, northwest Russia

A relative sea-level curve for the Holocene is constructed for Polyarny on the Kola Peninsula, northwest Russia. The curve is based on 18 radiocarbon dates of isolation contacts, identified from lithological and diatomological criteria, in nine lake basins situated between 12 and 57 m a.s.l. Most of the lakes show a conformable, regressive I–II–III (marine–transitional–freshwater) facies succession, indicating a postglacial history comprising an early (10,000–9000 radiocarbon years BP) phase of rapid, glacio-isostatically induced emergence (5 cm year⁻¹) and a later phase (after 7000 years BP,) having a moderate rate of emergence (<0.5 cm year⁻¹). Three lakes together record a phase of very low rate of emergence or slight sea-level rise at a level of 27 m a.s.l., between 8500 and 7000 years BP, which correlates with the regional Tapes transgression. Pollen stratigraphy in the highest lake shows that the area was deglaciated before the Younger Dryas and that previously reconstructed Younger Dryas glacier margins along the north Kola coast lie too far north.     

The effect of climate change on carbon in Canadian peatlands

Peatlands, which are dominant features of the Canadian landscape, cover approximately 1.136 million km², or 12% of the land area. Most of the peatlands (97%) occur in the Boreal Wetland Region (64%) and Subarctic Wetland Region (33%). Because of the large area they cover and their high organic carbon content, these peatlands contain approximately 147 Gt soil carbon, which is about 56% of the organic carbon stored in all Canadian soils.A model for estimating peatland sensitivity to climate warming was used to determine both the sensitivity ratings of various peatland areas and the associated organic carbon masses. Calculations show that approximately 60% of the total area of Canadian peatlands and 51% of the organic carbon mass in all Canadian peatlands is expected to be severely to extremely severely affected by climate change.The increase in average annual air temperature of 3–5 °C over land and 5–7 °C over the oceans predicted for northern Canada by the end of this century would result in the degradation of frozen peatlands in the Subarctic and northern Boreal wetland regions and severe drying in the southern Boreal Wetland Region. In addition, flooding of coastal peatlands is expected because of the predicted rise in sea levels. As a result of these changes, a large part of the carbon in the peatlands expected to be severely and extremely severely affected by climate change could be released into the atmosphere as carbon dioxide (CO₂) and methane (CH₄), which will further increase climate warming.     

The link between abrupt climate change and basin stratigraphy: a numerical approach

To use basin stratigraphy for studying past climate change, it is important to understand the influence of evolving boundary conditions (river discharge and sediment flux, initial bathymetry, sea level, subsidence) and the complex interplay of the redistribution processes (plumes, turbidity currents, debris flows). To provide understanding of this complexity, we have employed source to sink numerical models to evaluate which process dominates the observed variability in a sedimentary record of two coastal Pacific basins, Knight Inlet in British Columbia and the Eel Margin of northern California.During the last glacial period, the Eel River supplied comparatively more sediment with a less variable flux to the ocean, while today the river is dominated by episodic events. Model results show this change in the variability of sediment flux to be as important to the deposit character as is the change in the volume of sediment supply. Due to the complex interaction of flooding events and ocean storm events, the more episodic flood deposits of recent times are less well preserved than the flood deposits associated with an ice-age climate.In Knight Inlet, the evolving boundary conditions (rapidly prograding coastline, secondary transport by gravity flows from sediment failures) are a strong influence on the sedimentary record. The delta and gravity flow deposits punctuate the sedimentary record formed by hemipelagic sedimentation from river plumes. Missing time intervals due to sediment failures can take away the advantage of the otherwise amplified lithologic record of discharge events, given the enclosed nature of the fjord basin.     

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.     

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.     

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.     

The economic impact of climate change on Kenyan crop agriculture: A Ricardian approach

This paper measures the economic impact of climate on crops in Kenya. We use cross-sectional data on climate, hydrological, soil and household level data for a sample of 816 households. We estimate a seasonal Ricardian model to assess the impact of climate on net crop revenue per acre. The results show that climate affects crop productivity. There is a non-linear relationship between temperature and revenue on one hand and between precipitation and revenue on the other. Estimated marginal impacts suggest that global warming is harmful for crop productivity. Predictions from global circulation models confirm that global warming will have a substantial impact on net crop revenue in Kenya. The results also show that the temperature component of global warming is much more important than precipitation. Findings call for monitoring of climate change and dissemination of information to farmers to encourage adaptations to climate change. Improved management and conservation of available water resources, water harvesting and recycling of wastewater could generate water for irrigation purposes especially in the arid and semi-arid areas.     

Uncertainties in climate change prediction: El Niño-Southern Oscillation and monsoons

The sensitivity of climate phenomena in the low latitudes to enhanced greenhouse conditions is a scientific issue of high relevance to billions of people in the poorest countries of the globe. So far, most studies dealt with individual model results. In the present analysis, we refer to 79 coupled ocean–atmosphere simulations from 12 different climate models under 6 different IPCC scenarios. The basic question is as to what extent various state-of-the-art climate models agree in predicting changes in the main features of El Niño-Southern Oscillation (ENSO) and the monsoon climates in South Asia and West Africa. The individual model runs are compared with observational data in order to judge whether the spatio-temporal characteristics of ENSO are well reproduced. The model experiments can be grouped into multi-model ensembles. Thus, climate change signals in the classical index time series, in the principal components and in the time series of interannual variability can be evaluated against the background of internal variability and model uncertainty.There are large differences between the individual model predictions until the end of the 21st century, especially in terms of monsoon rainfall and the Southern Oscillation index (SOI). The majority of the models tends to project La Niña-like anomalies in the SOI and an intensification of the summer monsoon precipitation in India and West Africa. However, the response barely exceeds the level of natural variability and the systematic intermodel variations are larger than the impact of different IPCC scenarios. Nonetheless, there is one prominent climate change signal, which stands out from model variations and internal noise: All forced model experiments agree in predicting a substantial warming in the eastern tropical Pacific. This oceanic heating does not necessarily lead to a modification of ENSO towards more frequent El Niño and/or La Niña events. It simply represents a change in the background state of ENSO. Indeed, we did not find convincing multi-model evidence for a modification of the wavelet spectra in terms of ENSO or the monsoons. Some models suggest an intensification of the annual cycle but this signal is fairly model-dependent. Thus, large model uncertainty still exists with respect to the future behaviour of climate in the low latitudes. This has to be taken into account when addressing climate change signals in individual model experiments and ensembles.     

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.     

Future desertification and climate change: The need for land-surface system evaluation improvement

In already drought-stressed areas and places with the potential for desertification as a result of greenhouse-induced change, high quality model-derived climate projections are essential for sustainable management. Today's challenge is how to select from the plethora of models and proposed new analyses the tools most likely to be valid for areas already water-stressed and those threatened by future surface moisture reduction. Here, the land-surface skills of models involved in the IPCC Fourth Assessment Report and new techniques of isotopic enrichment of components of evapotranspiration are analyzed. Both are found to have shortcomings. Surprisingly poor reporting of fundamental components of the land-surface system in standard model output was the largest challenge for widely accepted models. We show that very few of a large group (20) of today's climate models report land-surface water and energy budgets correctly in a well-controlled international experiment and that most fail basic conservation tests. Our analysis of a smaller (5) experiment suggests that isotopic techniques employed in arid zone irrigation management may not transition to evaluation and model improvement. Land-surface conditions important for policy are found to be poorly reported which raises questions about equal weighting given by international assessments to all models: good and bad.     

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.     

Measuring the economic impact of climate change on major South African field crops: a Ricardian approach

This study employed a Ricardian model to measure the impact of climate change on South Africa's field crops and analysed potential future impacts of further changes in the climate. A regression of farm net revenue on climate, soil and other socio-economic variables was conducted to capture farmer-adapted responses to climate variations. The analysis was based on agricultural data for seven field crops (maize, wheat, sorghum, sugarcane, groundnut, sunflower and soybean), climate and edaphic data across 300 districts in South Africa. Results indicate that production of field crops was sensitive to marginal changes in temperature as compared to changes in precipitation. Temperature rise positively affects net revenue whereas the effect of reduction in rainfall is negative. The study also highlights the importance of season and location in dealing with climate change showing that the spatial distribution of climate change impact and consequently needed adaptations will not be uniform across the different agro-ecological regions of South Africa. Results of simulations of climate change scenarios indicate many impacts that would induce (or require) very distinct shifts in farming practices and patterns in different regions. Those include major shifts in crop calendars and growing seasons, switching between crops to the possibility of complete disappearance of some field crops from some region.     

Sensitivities of species compositions of the mixed forest in eastern Eurasian continent to climate change

Sensitivities of species compositions of the broadleaf–conifer mixed forest in eastern Eurasian continent to climate change were evaluated with three forest gap models, namely KOPIDE, NEWCOP, and ForClim. Testing sites are located on Changbai Mountain, the middle of the distribution range for the mixed forest. Six climate change scenarios characterizing increase in temperature and increase/decrease in precipitation were used to test the sensitivities of species composition to climate change. Simulations suggest that the mixed forest in temperate Monsoon Asia will face changes in species composition should climate change be almost certain. At the minimum level, the order of dominant species is going to change due to species competition, resulting in the increase in the proportion of broadleaved tree species in the forest. If air temperature increases and precipitation decreases, Pinus koraiensis is going to disappear from the forest and the mixed forest will become hardwood forest. This experiment supports some earlier predictions under other climate change scenarios.     

Borehole temperatures, climate change and the pre-observational surface air temperature mean: allowance for hydraulic conditions

Joint analysis of surface air temperature series recorded at weather stations together with the inversion of the temperature-depth profiles logged in the near-by boreholes enables an estimate of the conditions existing prior to the beginning of the meteorological observation, the so-called pre-observational mean (POM) temperature.Such analysis is based on the presumption of pure diffusive conditions in the underground. However, in real cases a certain subsurface fluid movement cannot be excluded and the measured temperature logs may contain an advective component. The paper addresses the correction for the hydraulic conditions, which may have perturbed the climate signal penetrating from the surface into the underground. The method accounts for vertical conductive and vertical advective heat transport in a 1-D horizontally layered stratum and provides a simultaneous evaluation of the POM-temperature together with the estimate of the Darcy fluid velocity. The correction strategy is illustrated on a synthetic example and its use is demonstrated on temperature logs measured in four closely spaced boreholes drilled near Tachlovice (located about 15 km SW of Prague, Czech Republic). The results revealed that in a case of moderately advectively affected subsurface conditions (fluid velocities about 10⁻⁹ m/s), the difference between POM-values assessed for a pure conductive approach and for combined vertical conductive/advective approach may amount up to 0.3–0.5 K, the value comparable with the amount usually ascribed to the 20th century climate warming.     

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.     

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.