Tropical forests and the changing earth system

Tropical forests are global epicentres of biodiversity and important modulators of the rate of climate change. Recent research on deforestation rates and ecological changes within intact forests, both areas of recent research and debate, are reviewed, and the implications for biodiversity (species loss) and climate change (via the global carbon cycle) addressed. Recent impacts have most likely been: (i) a large source of carbon to the atmosphere, and major loss of species, from deforestation and (ii) a large carbon sink within remaining intact forest, accompanied by accelerating forest dynamism and widespread biodiversity changes. Finally, I look to the future, suggesting that the current carbon sink in intact forests is unlikely to continue, and that the tropical forest biome may even become a large net source of carbon, via one or more of four plausible routes: changing photosynthesis and respiration rates, biodiversity changes in intact forest, widespread forest collapse via drought, and widespread forest collapse via fire. Each of these scenarios risks potentially dangerous positive feedbacks with the climate system that could dramatically accelerate and intensify climate change. Given that continued land-use change alone is already thought to be causing the sixth mass extinction event in Earth's history, should such feedbacks occur, the resulting biodiversity and societal consequences would be even more severe.     

Generating carbon finance through avoided deforestation and its potential to create climatic, conservation and human development benefits

Recent proposals to compensate developing countries for reducing emissions from deforestation (RED) under forthcoming climate change mitigation regimes are receiving increasing attention. Here we demonstrate that if RED credits were traded on international carbon markets, even moderate decreases in deforestation rates could generate billions of Euros annually for tropical forest conservation. We also discuss the main challenges for a RED mechanism that delivers real climatic benefits. These include providing sufficient incentives while only rewarding deforestation reductions beyond business-as-usual scenarios, addressing risks arising from forest degradation and international leakage, and ensuring permanence of emission reductions. Governance may become a formidable challenge for RED because some countries with the highest RED potentials score poorly on governance indices. In addition to climate mitigation, RED funds could help achieve substantial co-benefits for biodiversity conservation and human development. However, this will probably require targeted additional support because the highest biodiversity threats and human development needs may exist in countries that have limited income potentials from RED. In conclusion, how successfully a market-based RED mechanism can contribute to climate change mitigation, conservation and development will strongly depend on accompanying measures and carefully designed incentive structures involving governments, business, as well as the conservation and development communities.     

降雨量和降雨时间共同调控黄河三角洲典型盐沼湿地土壤碳矿化

研究降雨格局(如降雨量和降雨时间)对滨海盐沼湿地土壤碳矿化的影响,对于深入理解土壤碳的稳定性和积累机制具有重要意义。本研究选取远离海岸且不受潮汐影响的黄河三角洲原生盐地碱蓬盐沼湿地为对象,通过野外原状土柱的控制试验,分析土壤碳矿化(CO₂和CH₄通量)在不同时期(干旱期和湿润期)对降雨事件的响应。结果表明: 降雨时间和降雨量对土壤CO₂通量的影响存在交互作用。在干旱期,大降雨事件显著降低了土壤CO₂通量;而湿润期的降雨事件对土壤CO₂通量没有显著影响,这可能与盐沼湿地的水盐运移有关。降雨量、降雨时间及其交互作用均对土壤CH₄通量没有显著影响。降雨时间和降雨量对CH₄/CO₂比率均没有显著影响,但是相关分析表明随着土壤含水量和盐分的升高,CH₄/CO₂比率呈升高趋势。随着降雨量的增加,土壤含水量和土壤盐分都显著增加,且两因素呈现显著的正相关关系。因此,未来该地区降雨体系改变将可能通过调控土壤水盐运移等条件对该滨海湿地土壤碳矿化和碳汇功能产生深远影响。     

Large uncertainty in carbon uptake potential of land‐based climate‐change mitigation efforts

Most climate mitigation scenarios involve negative emissions, especially those that aim to limit global temperature increase to 2°C or less. However, the carbon uptake potential in land‐based climate change mitigation efforts is highly uncertain. Here, we address this uncertainty by using two land‐based mitigation scenarios from two land‐use models (IMAGE and MAgPIE) as input to four dynamic global vegetation models (DGVMs; LPJ‐GUESS, ORCHIDEE, JULES, LPJmL). Each of the four combinations of land‐use models and mitigation scenarios aimed for a cumulative carbon uptake of ~130 GtC by the end of the century, achieved either via the cultivation of bioenergy crops combined with carbon capture and storage (BECCS) or avoided deforestation and afforestation (ADAFF). Results suggest large uncertainty in simulated future land demand and carbon uptake rates, depending on the assumptions related to land use and land management in the models. Total cumulative carbon uptake in the DGVMs is highly variable across mitigation scenarios, ranging between 19 and 130 GtC by year 2099. Only one out of the 16 combinations of mitigation scenarios and DGVMs achieves an equivalent or higher carbon uptake than achieved in the land‐use models. The large differences in carbon uptake between the DGVMs and their discrepancy against the carbon uptake in IMAGE and MAgPIE are mainly due to different model assumptions regarding bioenergy crop yields and due to the simulation of soil carbon response to land‐use change. Differences between land‐use models and DGVMs regarding forest biomass and the rate of forest regrowth also have an impact, albeit smaller, on the results. Given the low confidence in simulated carbon uptake for a given land‐based mitigation scenario, and that negative emissions simulated by the DGVMs are typically lower than assumed in scenarios consistent with the 2°C target, relying on negative emissions to mitigate climate change is a highly uncertain strategy.     

The consequences of uncertainties in land use, climate and vegetation responses on the terrestrial carbon

The IPCC SRES narratives were implemented in IMAGE 2.2 to evaluate the future con-dition of the climate system (including the biosphere). A series of scenario experiments was used to assess possible ranges in emissions and concentrations of greenhouse gases, climate changeand impacts. These experiments focussed on the role of the terrestrial carbon cycle. The experi-ments show that the SRES narratives dominate human emissions and not natural processes. In contrary, atmospheric CO_2 concentration strongly differs between the experiments. Atmospheric CO_2 concentrations range for A1B from 714 to 1009 ppmv CO_2 in 2100. The spread of this range is comparable with the full SRES range as implemented in IMAGE 2.2 (515-895 μmol/mol CO_2).The most important negative and positive feedback processes in IMAGE 2.2 on the build-up ofCO_2 concentrations are CO_2 fertilisation and soil respiration respectively. Indirect effects of theseprocesses further change land-use patterns, deforestation rates and alter the natural C fluxes. Thecumulative effects of these changes have a pronounced influence on the final CO_2 concentrations. Our scenario experiments highlight the importance of a proper parameterisation of feedback proc-esses, C-cycle and land use in determining the future states of the climate system.     

The consequences of uncertainties in land use, climate and vegetation responses on the terrestrial carbon

The IPCC SRES narratives were implemented in IMAGE 2.2 to evaluate thefuture condition of the climate system (including the biosphere). A series of scenario experiments was used to assess possible ranges in emissions and concentrations of greenhouse gases, climate change and impacts. These experiments focussed on the role of the terrestrial carbon cycle. The experiments show that the SRES narratives dominate human emissions and not natural processes. In contrary, atmospheric CO2 concentration strongly differs between the experiments. Atmospheric CO2 concentrations range for A1B from 714 to 1009 ppmv CO2 in 2100. The spread of this range is comparable with the full SRES range as implemented in IMAGE 2.2 (515-895 μmol/mol CO2). The most important negative and positive feedback processes in IMAGE 2.2 on the build-up of CO2 concentrations are CO2 fertilisation and soil respiration respectively. Indirect effects of these processes furtherchange land-use patterns, deforestation rates and alter the natural C fluxes. The cumulative effects of these changes have a pronounced influence on the final CO2 concentrations. Our scenario experiments highlight the importance of a proper parameterisation of feedback processes, C-cycle and land use in determining the future states of the climate system.     

The relative importance of deforestation,precipitation change,and temperature sensitivity in determining the future distributions and diversity of Amazonian plant species

Tropical forests are threatened by many human disturbances – two of the most important of which are deforestation and climate change. To mitigate the impacts of these disturbances, it is important to understand their potential effects on the distributions of species. In the tropics, such understanding has been hindered by poor knowledge of the current distributions and range limits of most species. Here, we use herbarium collection records to model the current and future distributions of ca. 3000 Amazonian plant species. We project these distributions into the future under a range of different scenarios related to the magnitude of climate change and extent of deforestation as well as the response of species to changes in temperature, precipitation, and atmospheric concentrations of CO₂ . We find that the future of Amazonian diversity will be dependant primarily on the ability of species to tolerate or adapt to rising temperatures. If the thermal niches of tropical plant species are fixed and incapable of expanding under rapid warming, then the negative effects of climate change will overshadow the effects of deforestation, greatly reducing the area of suitable habitat available to most species and potentially leading to massive losses of biodiversity throughout the Amazon. If tropical species are generally capable of tolerating warmer temperatures, rates of habitat loss will be greatly reduced but many parts of Amazonia may still experience rapid losses of diversity, with the effects of enhanced seasonal water stress being similar in magnitude to the effects of deforestation.     

Improving predictions of tropical forest response to climate change through integration of field studies and ecosystem modeling

Tropical forests play a critical role in carbon and water cycles at a global scale. Rapid climate change is anticipated in tropical regions over the coming decades and, under a warmer and drier climate, tropical forests are likely to be net sources of carbon rather than sinks. However, our understanding of tropical forest response and feedback to climate change is very limited. Efforts to model climate change impacts on carbon fluxes in tropical forests have not reached a consensus. Here, we use the Ecosystem Demography model (ED2) to predict carbon fluxes of a Puerto Rican tropical forest under realistic climate change scenarios. We parameterized ED2 with species‐specific tree physiological data using the Predictive Ecosystem Analyzer workflow and projected the fate of this ecosystem under five future climate scenarios. The model successfully captured interannual variability in the dynamics of this tropical forest. Model predictions closely followed observed values across a wide range of metrics including aboveground biomass, tree diameter growth, tree size class distributions, and leaf area index. Under a future warming and drying climate scenario, the model predicted reductions in carbon storage and tree growth, together with large shifts in forest community composition and structure. Such rapid changes in climate led the forest to transition from a sink to a source of carbon. Growth respiration and root allocation parameters were responsible for the highest fraction of predictive uncertainty in modeled biomass, highlighting the need to target these processes in future data collection. Our study is the first effort to rely on Bayesian model calibration and synthesis to elucidate the key physiological parameters that drive uncertainty in tropical forests responses to climatic change. We propose a new path forward for model‐data synthesis that can substantially reduce uncertainty in our ability to model tropical forest responses to future climate.     

Tree allometry and improved estimation of carbon stocks and balance in tropical forests

Tropical forests hold large stores of carbon, yet uncertainty remains regarding their quantitative contribution to the global carbon cycle. One approach to quantifying carbon biomass stores consists in inferring changes from long-term forest inventory plots. Regression models are used to convert inventory data into an estimate of aboveground biomass (AGB). We provide a critical reassessment of the quality and the robustness of these models across tropical forest types, using a large dataset of 2,410 trees ≥ 5 cm diameter, directly harvested in 27 study sites across the tropics. Proportional relationships between aboveground biomass and the product of wood density, trunk cross-sectional area, and total height are constructed. We also develop a regression model involving wood density and stem diameter only. Our models were tested for secondary and old-growth forests, for dry, moist and wet forests, for lowland and montane forests, and for mangrove forests. The most important predictors of AGB of a tree were, in decreasing order of importance, its trunk diameter, wood specific gravity, total height, and forest type (dry, moist, or wet). Overestimates prevailed, giving a bias of 0.5–6.5% when errors were averaged across all stands. Our regression models can be used reliably to predict aboveground tree biomass across a broad range of tropical forests. Because they are based on an unprecedented dataset, these models should improve the quality of tropical biomass estimates, and bring consensus about the contribution of the tropical forest biome and tropical deforestation to the global carbon cycle. Electronic Supplementary Material Supplementary material is available for this article at     

Temperature and rainfall interact to control carbon cycling in tropical forests

Tropical forests dominate global terrestrial carbon (C) exchange, and recent droughts in the Amazon Basin have contributed to short‐term declines in terrestrial carbon dioxide uptake and storage. However, the effects of longer‐term climate variability on tropical forest carbon dynamics are still not well understood. We synthesised field data from more than 150 tropical forest sites to explore how climate regulates tropical forest aboveground net primary productivity (ANPP) and organic matter decomposition, and combined those data with two existing databases to explore climate – C relationships globally. While previous analyses have focused on the effects of either temperature or rainfall on ANPP, our results highlight the importance of interactions between temperature and rainfall on the C cycle. In cool forests (< 20 °C), high rainfall slowed rates of C cycling, but in warm tropical forests (> 20 °C) it consistently enhanced both ANPP and decomposition. At the global scale, our analysis showed an increase in ANPP with rainfall in relatively warm sites, inconsistent with declines in ANPP with rainfall reported previously. Overall, our results alter our understanding of climate – C cycle relationships, with high precipitation accelerating rates of C exchange with the atmosphere in the most productive biome on earth.     

Challenges to estimating carbon emissions from tropical deforestation

An accurate estimate of carbon fluxes associated with tropical deforestation from the last two decades is needed to balance the global carbon budget. Several studies have already estimated carbon emissions from tropical deforestation, but the estimates vary greatly and are difficult to compare due to differences in data sources, assumptions, and methodologies. In this paper, we review the different estimates and datasets, and the various challenges associated with comparing them and with accurately estimating carbon emissions from deforestation. We performed a simulation study over legal Amazonia to illustrate some of these major issues. Our analysis demonstrates the importance of considering land-cover dynamics following deforestation, including the fluxes from reclearing of secondary vegetation, the decay of product and slash pools, and the fluxes from regrowing forest. It also suggests that accurate carbon-flux estimates will need to consider historical land-cover changes for at least the previous 20 years. However, this result is highly sensitive to estimates of the partitioning of cleared carbon into instantaneous burning vs. long-timescale slash pools. We also show that carbon flux estimates based on 'committed flux' calculations, as used by a few studies, are not comparable with the 'annual balance' calculation method used by other studies.     

Determination of tropical deforestation rates and related carbon losses from 1990 to 2010

We estimate changes in forest cover (deforestation and forest regrowth) in the tropics for the two last decades (1990–2000 and 2000–2010) based on a sample of 4000 units of 10 ×10 km size. Forest cover is interpreted from satellite imagery at 30 × 30 m resolution. Forest cover changes are then combined with pan‐tropical biomass maps to estimate carbon losses. We show that there was a gross loss of tropical forests of 8.0 million ha yr^?1 in the 1990s and 7.6 million ha yr^?1 in the 2000s (0.49% annual rate), with no statistically significant difference. Humid forests account for 64% of the total forest cover in 2010 and 54% of the net forest loss during second study decade. Losses of forest cover and Other Wooded Land (OWL) cover result in estimates of carbon losses which are similar for 1990s and 2000s at 887 MtC yr^?1 (range: 646–1238) and 880 MtC yr^?1 (range: 602–1237) respectively, with humid regions contributing two‐thirds. The estimates of forest area changes have small statistical standard errors due to large sample size. We also reduce uncertainties of previous estimates of carbon losses and removals. Our estimates of forest area change are significantly lower as compared to national survey data. We reconcile recent low estimates of carbon emissions from tropical deforestation for early 2000s and show that carbon loss rates did not change between the two last decades. Carbon losses from deforestation represent circa 10% of Carbon emissions from fossil fuel combustion and cement production during the last decade (2000–2010). Our estimates of annual removals of carbon from forest regrowth at 115 MtC yr^?1 (range: 61–168) and 97 MtC yr^?1 (53–141) for the 1990s and 2000s respectively are five to fifteen times lower than earlier published estimates.     

Responses of global plant diversity capacity to changes in carbon dioxide concentration and climate

We model plant species diversity globally by country to show that future plant diversity capacity has a strong dependence on changing climate and carbon dioxide concentration. CO2 increase, through its impact on net primary production and warming is predicted to increase regional diversity capacity, while warming with constant CO2 leads to decreases in diversity capacity. Increased CO2 concentrations are unlikely to counter projected extinctions of endemic species, shown in earlier studies to be more strongly dependent on changing land use patterns than climate per se. Model predictions were tested against (1) contemporary observations of tree species diversity in different biomes, (2) an independent global map of contemporary species diversity and (3) time sequences of plant naturalisation for different locations. Good agreements between model, observations and naturalisation patterns support the suggestion that future diversity capacity increases are likely to be filled from a 'cosmopolitan weed pool' for which migration appears to be an insignificant barrier.     

Amazon's vulnerability to climate change heightened by deforestation and man‐made dispersal barriers

Species migrations in response to climate change have already been observed in many taxonomic groups worldwide. However, it remains uncertain if species will be able to keep pace with future climate change. Keeping pace will be especially challenging for tropical lowland rainforests due to their high velocities of climate change combined with high rates of deforestation, which may eliminate potential climate analogs and/or increase the effective distances between analogs by blocking species movements. Here, we calculate the distances between current and future climate analogs under various climate change and deforestation scenarios. Under even the most sanguine of climate change models (IPSL_CM4, A1b emissions scenario), we find that the median distance between areas in the Amazon rainforest and their closest future (2050) climate analog as predicted based on just temperature changes alone is nearly 300 km. If we include precipitation, the median distance increases by over 50% to >475 km. Since deforestation is generally concentrated in the hottest and driest portions of the Amazon, we predict that the habitat loss will have little direct impact on distances between climate analogs. If, however, deforested areas also act as a barrier to species movements, nearly 30% or 55% of the Amazon will effectively have no climate analogs anywhere in tropical South America under projections of reduced or Business‐As‐Usual deforestation, respectively. These ‘disappearing climates’ will be concentrated primarily in the southeastern Amazon. Consequently, we predict that several Amazonian ecoregions will have no areas with future climate analogs, greatly increasing the vulnerability of any populations or species specialized on these conditions. These results highlight the importance of including multiple climatic factors and human land‐use in predicting the effects of climate change, as well as the daunting challenges that Amazonian diversity faces in the near future.     

Implications of future climate and atmospheric CO2 content for regional biogeochemistry,biogeography and ecosystem services across East Africa

We model future changes in land biogeochemistry and biogeography across East Africa. East Africa is one of few tropical regions where general circulation model (GCM) future climate projections exhibit a robust response of strong future warming and general annual‐mean rainfall increases. Eighteen future climate projections from nine GCMs participating in the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment were used as input to the LPJ dynamic global vegetation model (DGVM), which predicted vegetation patterns and carbon storage in agreement with satellite observations and forest inventory data under the present‐day climate. All simulations showed future increases in tropical woody vegetation over the region at the expense of grasslands. Regional increases in net primary productivity (NPP) (18–36%) and total carbon storage (3–13%) by 2080–2099 compared with the present‐day were common to all simulations. Despite decreases in soil carbon after 2050, seven out of nine simulations continued to show an annual net land carbon sink in the final decades of the 21st century because vegetation biomass continued to increase. The seasonal cycles of rainfall and soil moisture show future increases in wet season rainfall across the GCMs with generally little change in dry season rainfall. Based on the simulated present‐day climate and its future trends, the GCMs can be grouped into four broad categories. Overall, our model results suggest that East Africa, a populous and economically poor region, is likely to experience some ecosystem service benefits through increased precipitation, river runoff and fresh water availability. Resulting enhancements in NPP may lead to improved crop yields in some areas. Our results stand in partial contradiction to other studies that suggest possible negative consequences for agriculture, biodiversity and other ecosystem services caused by temperature increases.     

Rainfall and temperatures changes have confounding impacts on Phytophthora cinnamomi occurrence risk in the southwestern USA under climate change scenarios

Global change will simultaneously impact many aspects of climate, with the potential to exacerbate the risks posed by plant pathogens to agriculture and the natural environment; yet, most studies that explore climate impacts on plant pathogen ranges consider individual climatic factors separately. In this study, we adopt a stochastic modeling approach to address multiple pathways by which climate can constrain the range of the generalist plant pathogen Phytophthora cinnamomi (Pc): through changing winter soil temperatures affecting pathogen survival; spring soil temperatures and thus pathogen metabolic rates; and changing spring soil moisture conditions and thus pathogen growth rates through host root systems. We apply this model to the southwestern USA for contemporary and plausible future climate scenarios and evaluate the changes in the potential range of Pc. The results indicate that the plausible range of this pathogen in the southwestern USA extends over approximately 200 000 km² under contemporary conditions. While warming temperatures as projected by the IPCC A2 and B1 emissions scenarios greatly expand the range over which the pathogen can survive winter, projected reductions in spring rainfall reduce its feasible habitat, leading to spatially complex patterns of changing risk. The study demonstrates that temperature and rainfall changes associated with possible climate futures in the southwestern USA have confounding impacts on the range of Pc, suggesting that projections of future pathogen dynamics and ranges should account for multiple pathways of climate–pathogen interaction.     

Tropical forests and atmospheric carbon dioxide

Tropical forests play a major role in determining the current atmospheric concentration of CO2, as both sources of CO2 following deforestation and sinks of CO2 probably resulting from CO2 stimulation of forest photosynthesis. Recently, researchers have tried to quantify this role. The results suggest that both the carbon sources and sinks in tropical forests are significantly greater than previously thought.     

Evaluation of the terrestrial carbon cycle, future plant geography and climate-carbon cycle feedbacks using five Dynamic Global Vegetation Models (DGVMs)

This study tests the ability of five Dynamic Global Vegetation Models (DGVMs), forced with observed climatology and atmospheric CO₂, to model the contemporary global carbon cycle. The DGVMs are also coupled to a fast ‘climate analogue model’, based on the Hadley Centre General Circulation Model (GCM), and run into the future for four Special Report Emission Scenarios (SRES): A1FI, A2, B1, B2. Results show that all DGVMs are consistent with the contemporary global land carbon budget. Under the more extreme projections of future environmental change, the responses of the DGVMs diverge markedly. In particular, large uncertainties are associated with the response of tropical vegetation to drought and boreal ecosystems to elevated temperatures and changing soil moisture status. The DGVMs show more divergence in their response to regional changes in climate than to increases in atmospheric CO₂ content. All models simulate a release of land carbon in response to climate, when physiological effects of elevated atmospheric CO₂ on plant production are not considered, implying a positive terrestrial climate‐carbon cycle feedback. All DGVMs simulate a reduction in global net primary production (NPP) and a decrease in soil residence time in the tropics and extra‐tropics in response to future climate. When both counteracting effects of climate and atmospheric CO₂ on ecosystem function are considered, all the DGVMs simulate cumulative net land carbon uptake over the 21st century for the four SRES emission scenarios. However, for the most extreme A1FI emissions scenario, three out of five DGVMs simulate an annual net source of CO₂ from the land to the atmosphere in the final decades of the 21st century. For this scenario, cumulative land uptake differs by 494 Pg C among DGVMs over the 21st century. This uncertainty is equivalent to over 50 years of anthropogenic emissions at current levels.     

Climate change promotes transitions to tall evergreen vegetation in tropical Asia

Vegetation in tropical Asia is highly diverse due to large environmental gradients and heterogeneity of landscapes. This biodiversity is threatened by intense land use and climate change. However, despite the rich biodiversity and the dense human population, tropical Asia is often underrepresented in global biodiversity assessments. Understanding how climate change influences the remaining areas of natural vegetation is therefore highly important for conservation planning. Here, we used the adaptive Dynamic Global Vegetation Model version 2 (aDGVM2) to simulate impacts of climate change and elevated CO₂ on vegetation formations in tropical Asia for an ensemble of climate change scenarios. We used climate forcing from five different climate models for representative concentration pathways RCP4.5 and RCP8.5. We found that vegetation in tropical Asia will remain a carbon sink until 2099, and that vegetation biomass increases of up to 28% by 2099 are associated with transitions from small to tall woody vegetation and from deciduous to evergreen vegetation. Patterns of phenology were less responsive to climate change and elevated CO₂ than biomes and biomass, indicating that the selection of variables and methods used to detect vegetation changes is crucial. Model simulations revealed substantial variation within the ensemble, both in biomass increases and in distributions of different biome types. Our results have important implications for management policy, because they suggest that large ensembles of climate models and scenarios are required to assess a wide range of potential future trajectories of vegetation change and to develop robust management plans. Furthermore, our results highlight open ecosystems with low tree cover as most threatened by climate change, indicating potential conflicts of interest between biodiversity conservation in open ecosystems and active afforestation to enhance carbon sequestration.