132 research outputs found
CO2 Enhancement of Forest Productivity Constrained by Limited Nitrogen Availability
Stimulation of terrestrial productivity by rising CO~2~ concentration is projected to reduce the airborne fraction of anthropogenic CO~2~ emissions; coupled climate-carbon (C) cycle models, including those used in the IPCC Fourth Assessment Report (AR4), are sensitive to this negative feedback on atmospheric CO~2~^1^. The representation of the so-called CO~2~ fertilization effect in the 11 models used in AR4 and subsequent models^2,3^ was broadly consistent with experimental evidence from four free-air CO~2~ enrichment (FACE) experiments, which indicated that net primary productivity (NPP) of forests was increased by 23 +/- 2% in response to atmospheric CO~2~ enrichment to 550 ppm^4^. Substantial uncertainty remains, however, because of the expectation that feedbacks through the nitrogen (N) cycle will reduce the CO~2~ stimulation of NPP^5,6^; these feedbacks were not included in the AR4 models and heretofore have not been confirmed by experiments in forests^7^. Here, we provide new evidence from a FACE experiment in a deciduous Liquidambar styraciflua (sweetgum) forest stand in Tennessee, USA, that N limitation has significantly reduced the stimulation of NPP by elevated atmospheric CO~2~ concentration (eCO~2~). Isotopic evidence and N budget analysis support the premise that N availability in this forest ecosystem has been declining over time, and declining faster in eCO~2~. Model analyses and evidence from leaf- and stand-level observations provide mechanistic evidence that declining N availability constrained the tree response to eCO2. These results provide a strong rationale and process understanding for incorporating N limitation and N feedback effects in ecosystem and global models used in climate change assessments
Plant root distributions and nitrogen uptake predicted by a hypothesis of optimal root foraging
CO2-enrichment experiments consistently show that rooting depth increases when trees are grown at elevated CO2 (eCO2), leading in some experiments to increased capture of available soil nitrogen (N) from deeper soil. However, the link between N uptake an
Global mangrove root production, its controls and roles in the blue carbon budget of mangroves
Mangroves are among the most carbon-dense ecosystems worldwide. Most of the carbon in mangroves is found belowground, and root production might be an important control of carbon accumulation, but has been rarely quantified and understood at the global scale. Here, we determined the global mangrove root production rate and its controls using a systematic review and a recently formalised, spatially explicit mangrove typology framework based on geomorphological settings. We found that global mangrove root production averaged ~770 ± 202 g of dry biomass m-2 year-1 globally, which is much higher than previously reported and close to the root production of the most productive tropical forests. Geomorphological settings exerted marked control over root production together with air temperature and precipitation (r2 ≈ 30%, p < .001). Our review shows that individual global changes (e.g. warming, eutrophication, drought) have antagonist effects on root production, but they have rarely been studied in combination. Based on this newly established root production rate, root-derived carbon might account for most of the total carbon buried in mangroves, and 19 Tg C lost in mangroves each year (e.g. as CO2). Inclusion of root production measurements in understudied geomorphological settings (i.e. deltas), regions (Indonesia, South America and Africa) and soil depth (>40 cm), as well as the creation of a mangrove root trait database will push forward our understanding of the global mangrove carbon cycle for now and the future. Overall, this review presents a comprehensive analysis of root production in mangroves, and highlights the central role of root production in the global mangrove carbon budget. </p
Controls on Fine-Scale Spatial and Temporal Variability of Plant-Available Inorganic Nitrogen in a Polygonal Tundra Landscape
Grand Challenges in Understanding the Interplay of Climate and Land Changes
Half of Earth’s land surface has been altered by human activities, creating various consequences on the climate and weather systems at local to global scales, which in turn affect a myriad of land surface processes and the adaptation behaviors. This study reviews the status and major knowledge gaps in the interactions of land and atmospheric changes and present 11 grand challenge areas for the scientific research and adaptation community in the coming decade. These land-cover and land-use change (LCLUC)-related areas include 1) impacts on weather and climate, 2) carbon and other biogeochemical cycles, 3) biospheric emissions, 4) the water cycle, 5) agriculture, 6) urbanization, 7) acclimation of biogeochemical processes to climate change, 8) plant migration, 9) land-use projections, 10) model and data uncertainties, and, finally, 11) adaptation strategies. Numerous studies have demonstrated the effects of LCLUC on local to global climate and weather systems, but these putative effects vary greatly in magnitude and even sign across space, time, and scale and thus remain highly uncertain. At the same time, many challenges exist toward improved understanding of the consequences of atmospheric and climate change on land process dynamics and services. Future effort must improve the understanding of the scale-dependent, multifaceted perturbations and feedbacks between land and climate changes in both reality and models. To this end, one critical cross-disciplinary need is to systematically quantify and better understand measurement and model uncertainties. Finally, LCLUC mitigation and adaptation assessments must be strengthened to identify implementation barriers, evaluate and prioritize opportunities, and examine how decision-making processes work in specific contexts
Comprehensive ecosystem model-data synthesis using multiple data sets at two temperate forest free-air CO2 enrichment experiments: Model performance at ambient CO2 concentration
Free-air CO2 enrichment (FACE) experiments provide a remarkable wealth of data which can be used to evaluate and improve terrestrial ecosystem models (TEMs). In the FACE model-data synthesis project, 11 TEMs were applied to two decadelong FACE experiments in temperate forests of the southeastern U.S.—the evergreen Duke Forest and the deciduous Oak Ridge Forest. In this baseline paper, we demonstrate our approach to model-data synthesis by evaluating the models' ability to reproduce observed net primary productivity (NPP), transpiration, and leaf area index (LAI) in ambient CO2 treatments. Model outputs were compared against observations using a range of goodness-of-fit statistics. Many models simulated annual NPP and transpiration within observed uncertainty. We demonstrate, however, that high goodness-of-fit values do not necessarily indicate a successful model, because simulation accuracy may be achieved through compensating biases in component variables. For example, transpiration accuracy was sometimes achieved with compensating biases in leaf area index and transpiration per unit leaf area. Our approach to model-data synthesis therefore goes beyond goodness-of-fit to investigate the success of alternative representations of component processes. Here we demonstrate this approach by comparing competing model hypotheses determining peak LAI. Of three alternative hypotheses—(1) optimization to maximize carbon export, (2) increasing specific leaf area with canopy depth, and (3) the pipe model—the pipe model produced peak LAI closest to the observations. This example illustrates how data sets from intensive field experiments such as FACE can be used to reduce model uncertainty despite compensating biases by evaluating individual model assumptions
Climate Change Alters Seedling Emergence and Establishment in an Old-Field Ecosystem
Background: Ecological succession drives large-scale changes in ecosystem composition over time, but the mechanisms whereby climatic change might alter succession remain unresolved. Here, we asked if the effects of atmospheric and climatic change would alter tree seedling emergence and establishment in an old-field ecosystem, recognizing that small shifts in rates of seedling emergence and establishment of different species may have long-term repercussions on the transition of fields to forests in the future. Methodology/Principal Findings: We introduced seeds from three early successional tree species into constructed old-field plant communities that had been subjected for 4 years to altered temperature, precipitation, and atmospheric CO 2 regimes in an experimental facility. Our experiment revealed that different combinations of atmospheric CO2 concentration, air temperature, and soil moisture altered seedling emergence and establishment. Treatments directly and indirectly affected soil moisture, which was the best predictor of seedling establishment, though treatment effects differed among species. Conclusions: The observed impacts, coupled with variations in the timing of seed arrival, are demonstrated as predictors o
Changes in leaf functional traits with leaf age: when do leaves decrease their photosynthetic capacity in Amazonian trees?
Most leaf functional trait studies in the Amazon basin do not consider ontogenetic variations (leaf age), which may influence ecosystem productivity throughout the year. When leaf age is taken into account, it is generally considered discontinuous, and leaves are classified into age categories based on qualitative observations. Here, we quantified age-dependent changes in leaf functional traits such as the maximum carboxylation rate of ribulose-1,5-biphosphate carboxylase/oxygenase (Rubisco) (Vcmax), stomatal control (Cgs%), leaf dry mass per area and leaf macronutrient concentrations for nine naturally growing Amazon tropical trees with variable phenological strategies. Leaf ages were assessed by monthly censuses of branch-level leaf demography; we also performed leaf trait measurements accounting for leaf chronological age based on days elapsed since the first inclusion in the leaf demography, not predetermined age classes. At the tree community scale, a nonlinear relationship between Vcmax and leaf age existed: young, developing leaves showed the lowest mean photosynthetic capacity, increasing to a maximum at 45 days and then decreasing gradually with age in both continuous and categorical age group analyses. Maturation times among species and phenological habits differed substantially, from 8 ± 30 to 238 ± 30 days, and the rate of decline of Vcmax varied from −0.003 to −0.065 μmol CO2 m−2 s−1 day−1. Stomatal control increased significantly in young leaves but remained constant after peaking. Mass-based phosphorus and potassium concentrations displayed negative relationships with leaf age, whereas nitrogen did not vary temporally. Differences in life strategies, leaf nutrient concentrations and phenological types, not the leaf age effect alone, may thus be important factors for understanding observed photosynthesis seasonality in Amazonian forests. Furthermore, assigning leaf age categories in diverse tree communities may not be the recommended method for studying carbon uptake seasonality in the Amazon, since the relationship between Vcmax and leaf age could not be confirmed for all trees
Toward a Coordinated Understanding of Hydro-Biogeochemical Root Functions in Tropical Forests for Application in Vegetation Models
Tropical forest root characteristics and resource acquisition strategies are underrepresented in vegetation and global models, hampering the prediction of forest–climate feedbacks for these carbon-rich ecosystems. Lowland tropical forests often have globally unique combinations of high taxonomic and functional biodiversity, rainfall seasonality, and strongly weathered infertile soils, giving rise to distinct patterns in root traits and functions compared with higher latitude ecosystems. We provide a roadmap for integrating recent advances in our understanding of tropical forest belowground function into vegetation models, focusing on water and nutrient acquisition. We offer comparisons of recent advances in empirical and model understanding of root characteristics that represent important functional processes in tropical forests. We focus on: (1) fine-root strategies for soil resource exploration, (2) coupling and trade-offs in fine-root water vs nutrient acquisition, and (3) aboveground–belowground linkages in plant resource acquisition and use. We suggest avenues for representing these extremely diverse plant communities in computationally manageable and ecologically meaningful groups in models for linked aboveground–belowground hydro-nutrient functions. Tropical forests are undergoing warming, shifting rainfall regimes, and exacerbation of soil nutrient scarcity caused by elevated atmospheric CO2. The accurate model representation of tropical forest functions is crucial for understanding the interactions of this biome with the climate
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