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"Fisher, J. B."
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A trade-off between plant and soil carbon storage under elevated CO2
Terrestrial ecosystems remove about 30 per cent of the carbon dioxide (CO
2
) emitted by human activities each year
1
, yet the persistence of this carbon sink depends partly on how plant biomass and soil organic carbon (SOC) stocks respond to future increases in atmospheric CO
2
(refs.
2
,
3
). Although plant biomass often increases in elevated CO
2
(eCO
2
) experiments
4
–
6
, SOC has been observed to increase, remain unchanged or even decline
7
. The mechanisms that drive this variation across experiments remain poorly understood, creating uncertainty in climate projections
8
,
9
. Here we synthesized data from 108 eCO
2
experiments and found that the effect of eCO
2
on SOC stocks is best explained by a negative relationship with plant biomass: when plant biomass is strongly stimulated by eCO
2
, SOC storage declines; conversely, when biomass is weakly stimulated, SOC storage increases. This trade-off appears to be related to plant nutrient acquisition, in which plants increase their biomass by mining the soil for nutrients, which decreases SOC storage. We found that, overall, SOC stocks increase with eCO
2
in grasslands (8 ± 2 per cent) but not in forests (0 ± 2 per cent), even though plant biomass in grasslands increase less (9 ± 3 per cent) than in forests (23 ± 2 per cent). Ecosystem models do not reproduce this trade-off, which implies that projections of SOC may need to be revised.
A synthesis of elevated carbon dioxide experiments reveals that when plant biomass is strongly stimulated by elevated carbon dioxide levels, soil carbon storage declines, and where biomass is weakly stimulated, soil carbon accumulates.
Journal Article
Benchmark products for land evapotranspiration: LandFlux-EVAL multi-data set synthesis
Land evapotranspiration (ET) estimates are available from several global data sets. Here, monthly global land ET synthesis products, merged from these individual data sets over the time periods 1989–1995 (7 yr) and 1989–2005 (17 yr), are presented. The merged synthesis products over the shorter period are based on a total of 40 distinct data sets while those over the longer period are based on a total of 14 data sets. In the individual data sets, ET is derived from satellite and/or in situ observations (diagnostic data sets) or calculated via land-surface models (LSMs) driven with observations-based forcing or output from atmospheric reanalyses. Statistics for four merged synthesis products are provided, one including all data sets and three including only data sets from one category each (diagnostic, LSMs, and reanalyses). The multi-annual variations of ET in the merged synthesis products display realistic responses. They are also consistent with previous findings of a global increase in ET between 1989 and 1997 (0.13 mm yr−2 in our merged product) followed by a significant decrease in this trend (−0.18 mm yr−2), although these trends are relatively small compared to the uncertainty of absolute ET values. The global mean ET from the merged synthesis products (based on all data sets) is 493 mm yr−1 (1.35 mm d−1) for both the 1989–1995 and 1989–2005 products, which is relatively low compared to previously published estimates. We estimate global runoff (precipitation minus ET) to 263 mm yr−1 (34 406 km3 yr−1) for a total land area of 130 922 000 km2. Precipitation, being an important driving factor and input to most simulated ET data sets, presents uncertainties between single data sets as large as those in the ET estimates. In order to reduce uncertainties in current ET products, improving the accuracy of the input variables, especially precipitation, as well as the parameterizations of ET, are crucial.
Journal Article
The WACMOS-ET project – Part 2: Evaluation of global terrestrial evaporation data sets
The WAter Cycle Multi-mission Observation Strategy – EvapoTranspiration (WACMOS-ET) project aims to advance the development of land evaporation estimates on global and regional scales. Its main objective is the derivation, validation, and intercomparison of a group of existing evaporation retrieval algorithms driven by a common forcing data set. Three commonly used process-based evaporation methodologies are evaluated: the Penman–Monteith algorithm behind the official Moderate Resolution Imaging Spectroradiometer (MODIS) evaporation product (PM-MOD), the Global Land Evaporation Amsterdam Model (GLEAM), and the Priestley–Taylor Jet Propulsion Laboratory model (PT-JPL). The resulting global spatiotemporal variability of evaporation, the closure of regional water budgets, and the discrete estimation of land evaporation components or sources (i.e. transpiration, interception loss, and direct soil evaporation) are investigated using river discharge data, independent global evaporation data sets and results from previous studies. In a companion article (Part 1), Michel et al. (2016) inspect the performance of these three models at local scales using measurements from eddy-covariance towers and include in the assessment the Surface Energy Balance System (SEBS) model. In agreement with Part 1, our results indicate that the Priestley and Taylor products (PT-JPL and GLEAM) perform best overall for most ecosystems and climate regimes. While all three evaporation products adequately represent the expected average geographical patterns and seasonality, there is a tendency in PM-MOD to underestimate the flux in the tropics and subtropics. Overall, results from GLEAM and PT-JPL appear more realistic when compared to surface water balances from 837 globally distributed catchments and to separate evaporation estimates from ERA-Interim and the model tree ensemble (MTE). Nonetheless, all products show large dissimilarities during conditions of water stress and drought and deficiencies in the way evaporation is partitioned into its different components. This observed inter-product variability, even when common forcing is used, suggests that caution is necessary in applying a single data set for large-scale studies in isolation. A general finding that different models perform better under different conditions highlights the potential for considering biome- or climate-specific composites of models. Nevertheless, the generation of a multi-product ensemble, with weighting based on validation analyses and uncertainty assessments, is proposed as the best way forward in our long-term goal to develop a robust observational benchmark data set of continental evaporation.
Journal Article
الصحراء وبلاد السودان
سهارا أند زودان (الصحراء وبلاد السودان) هو وصف مفصل لرحلة عبر الصحراء الكبرى استغرقت ست سنوات قام بها في 1869-1875 المستكشف الألماني غوستاف ناختيغال (1834-1885).ولد ناختيغال لقس لوثري ببلدة آيششتدت في ولاية سكسونيا-أنهالت وتدرب ليصبح طبيبا ومارس مهنته لعدة سنوات كجراح عسكري في كولونيا. وبعد أن أصيب بداء عضال في الرئة، سافر في أكتوبر 1862 إلى بونه (عنابة الحالية) بالجزائر على أمل الاستشفاء في طقس دافئ جاف. بعد ذلك بعام غادر إلى تونس، حيث أقام لعدة سنوات ومارس الطب وتعلم العربية. كان ناختيغال على وشك العودة إلى ألمانيا حينما طلب منه المستكشف الألماني غيرهارد رولفس أن يذهب في مهمة إلى مملكة بورنو، التي كانت تقع في الجزء الشمالي لنيجيريا الحالية وذلك نيابة عن ملك بروسيا فلهلم الأول. كان فلهلم يريد أن يشكر سلطان بورنو على العطف الذي أولاه للمستكشف الألماني هاينرش بارت (1821-1865). قبل ناختيغال التكليف وغادر في فبراير 1869 مرتحلا عبر الصحراء في معية ستة رجال وثمانية جمال. يسرد المجلد الأول : من سهارا أند زودان، الذي نشر في 1879، الجزء الأول من تلك الرحلة، التي قادته من طرابلس (ليبيا الحالية) عبر فزان في جنوب غرب ليبيا وإقليم تبستي (الواقع حاليا في ليبيا وتشاد والنيجر) ومن ثم إلى بورنو، حيث قدم هدايا من الملك الروسي إلى السلطان. المجلد الثاني : من الكتاب، الذي نشر في 1881، يغطي الجزء الثاني من الرحلة، من بورنو إلى سلطنة باغيرمي (تشاد الحالية) ثم إلى تمبكتو (مالي الحالية). أما المجلد الثالث : الذي نشر في 1889، أي بعد أربع سنوات من رحيل ناختيغال، فهو يسرد الجزء الأخير : من البعثة، من وداي (في شرق تشاد الحالية) عبر دارفور (في غرب السودان الحالي) وأخيرا إلى الخرطوم على نهر النيل. قطع ناختيغال إجمالا حوالي 10,000 كيلومتر، متنقلا في أجزاء من إفريقيا لم تطأها قدم أي أوربي قبله. يعتبر ناختيغال أحد أعظم مكتشفي إفريقيا الأوربيين، فهو يظل مثل مواطنه بارت، محل احترام كبير لغزارة علمه وملاحظاته الدقيقة وجهوده لفهم الشعوب التي تنقل بينها ولا يزال سهارا أند زودان يمثل مصدرا تاريخيا هاما لتلك البلاد الشاسعة التي تنقل عبرها ناختيغال.
Book
A framework for benchmarking land models
Land models, which have been developed by the modeling community in the past few decades to predict future states of ecosystems and climate, have to be critically evaluated for their performance skills of simulating ecosystem responses and feedback to climate change. Benchmarking is an emerging procedure to measure performance of models against a set of defined standards. This paper proposes a benchmarking framework for evaluation of land model performances and, meanwhile, highlights major challenges at this infant stage of benchmark analysis. The framework includes (1) targeted aspects of model performance to be evaluated, (2) a set of benchmarks as defined references to test model performance, (3) metrics to measure and compare performance skills among models so as to identify model strengths and deficiencies, and (4) model improvement. Land models are required to simulate exchange of water, energy, carbon and sometimes other trace gases between the atmosphere and land surface, and should be evaluated for their simulations of biophysical processes, biogeochemical cycles, and vegetation dynamics in response to climate change across broad temporal and spatial scales. Thus, one major challenge is to select and define a limited number of benchmarks to effectively evaluate land model performance. The second challenge is to develop metrics of measuring mismatches between models and benchmarks. The metrics may include (1) a priori thresholds of acceptable model performance and (2) a scoring system to combine data–model mismatches for various processes at different temporal and spatial scales. The benchmark analyses should identify clues of weak model performance to guide future development, thus enabling improved predictions of future states of ecosystems and climate. The near-future research effort should be on development of a set of widely acceptable benchmarks that can be used to objectively, effectively, and reliably evaluate fundamental properties of land models to improve their prediction performance skills.
Journal Article
Evaluation of global observations-based evapotranspiration datasets and IPCC AR4 simulations
Quantification of global land evapotranspiration (ET) has long been associated with large uncertainties due to the lack of reference observations. Several recently developed products now provide the capacity to estimate ET at global scales. These products, partly based on observational data, include satellite ]based products, land surface model (LSM) simulations, atmospheric reanalysis output, estimates based on empirical upscaling of eddycovariance flux measurements, and atmospheric water balance datasets. The LandFlux-EVAL project aims to evaluate and compare these newly developed datasets. Additionally, an evaluation of IPCC AR4 global climate model (GCM) simulations is presented, providing an assessment of their capacity to reproduce flux behavior relative to the observations ]based products. Though differently constrained with observations, the analyzed reference datasets display similar large-scale ET patterns. ET from the IPCC AR4 simulations was significantly smaller than that from the other products for India (up to 1 mm/d) and parts of eastern South America, and larger in the western USA, Australia and China. The inter-product variance is lower across the IPCC AR4 simulations than across the reference datasets in several regions, which indicates that uncertainties may be underestimated in the IPCC AR4 models due to shared biases of these simulations.
Journal Article
Uncertainty in the response of terrestrial carbon sink to environmental drivers undermines carbon-climate feedback predictions
Terrestrial ecosystems play a vital role in regulating the accumulation of carbon (C) in the atmosphere. Understanding the factors controlling land C uptake is critical for reducing uncertainties in projections of future climate. The relative importance of changing climate, rising atmospheric CO
2
, and other factors, however, remains unclear despite decades of research. Here, we use an ensemble of land models to show that models disagree on the primary driver of cumulative C uptake for 85% of vegetated land area. Disagreement is largest in model sensitivity to rising atmospheric CO
2
which shows almost twice the variability in cumulative land uptake since 1901 (1 s.d. of 212.8 PgC vs. 138.5 PgC, respectively). We find that variability in CO
2
and temperature sensitivity is attributable, in part, to their compensatory effects on C uptake, whereby comparable estimates of C uptake can arise by invoking different sensitivities to key environmental conditions. Conversely, divergent estimates of C uptake can occur despite being based on the same environmental sensitivities. Together, these findings imply an important limitation to the predictability of C cycling and climate under unprecedented environmental conditions. We suggest that the carbon modeling community prioritize a probabilistic multi-model approach to generate more robust C cycle projections.
Journal Article