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Beryllium-10 cosmic-ray exposure (CRE) dating has revolutionized our understanding of glacier fluctuations around the globe. A key prerequisite for the successful application of this dating method is the determination of regional production rates of in situ accumulated 10 Be, usually inferred at independently dated calibration sites. Until now, no calibration site has been available for the mid-elevation mountain ranges of central Europe. We fill this gap by determining in situ 10 Be concentrations in large boulders on moraines and by applying radiocarbon and infrared-stimulated luminescence (IRSL) dating to stratigraphically younger lake sediments in the southern Black Forest, SW Germany. The dating methods yielded concordant results, and, based on age–depth modelling with 14 C ages, the age of a cryptotephra, and IRSL ages, we deduced a regional 10 Be production rate in quartz. Calibrating the Black Forest production rate (BFPR) in the Cosmic-Ray Exposure program (CREp) resulted in a spallogenic sea-level and high-latitude (SLHL) production rate of 3.64±0.11 atoms 10 Be g -1 quartz a -1 when referring to time-dependent Lal–Stone scaling, the European Reanalysis (ERA)-40 atmosphere model, and the atmospheric 10 Be-based geomagnetic database in CREp. The BFPR turned out to be ∼11 % lower than both those at the nearest calibration site in the Alps (4.10±0.10 atoms 10 Be g -1 quartz a -1 at SLHL) and the canonical global 10 Be production rate (4.11±0.19 atoms 10 Be g -1 quartz a -1 at SLHL) in CREp. A stronger weathering and snow cover bias and a higher impact of forest, soil, moss, and shrub cover at the study site likely explain this discrepancy. [ABSTRACT FROM AUTHOR]

The continuous advancement of remote sensing technology has been instrumental in improving models for estimating terrestrial gross primary productivity (GPP). However, challenges arise from inconsistent spatial distributions and interannual variations in GPP datasets, impeding our comprehensive understanding of the entire terrestrial carbon cycle. In contrast to previous models relying on remote sensing and environmental variables, we developed a an ensemble model based on random forest named GPPERF. This model utilized the GPP outputs from established remote sensing-based models (EC-LUE, GPP-kNDVI, GPP-NIRv, Revised-EC-LUE) as inputs for GPP estimations. GPPERF demonstrated significant effectiveness by explaining 83.7 % of the monthly variation in GPP across 171 sites. This performance surpassed the selected remote sensing models (72.4 %–77.1 %) and an independent random forest model using remote sensing and environmental variables (77.7 %). Over the period from 2001 to 2022, the global estimated GPP value using the ensemble model based on random forest was 131.2 PgC yr-1, exhibiting a trend of 0.45 PgC yr-2. Furthermore, evaluation results utilizing flux sites from ChinaFlux indicated that the dateset exhibited good generalization. In summary, the machine learning-based ensemble method helps to reduce the uncertainty in the estimation of a single remote sensing model and provides a more reliable estimation of global GPP. [ABSTRACT FROM AUTHOR]

The continuous advancement of remote sensing technology has been instrumental in improving models for estimating terrestrial gross primary productivity (GPP). However, challenges arise from inconsistent spatial distributions and interannual variations in GPP datasets, impeding our comprehensive understanding of the entire terrestrial carbon cycle. In contrast to previous models relying on remote sensing and environmental variables, we developed a an ensemble model based on random forest named GPPERF. This model utilized the GPP outputs from established remote sensing-based models (EC-LUE, GPP-kNDVI, GPP-NIRv, Revised-EC-LUE) as inputs for GPP estimations. GPPERF demonstrated significant effectiveness by explaining 83.7 % of the monthly variation in GPP across 171 sites. This performance surpassed the selected remote sensing models (72.4 %–77.1 %) and an independent random forest model using remote sensing and environmental variables (77.7 %). Over the period from 2001 to 2022, the global estimated GPP value using the ensemble model based on random forest was 131.2 PgC yr-1, exhibiting a trend of 0.45 PgC yr-2. Furthermore, evaluation results utilizing flux sites from ChinaFlux indicated that the dateset exhibited good generalization. In summary, the machine learning-based ensemble method helps to reduce the uncertainty in the estimation of a single remote sensing model and provides a more reliable estimation of global GPP. [ABSTRACT FROM AUTHOR]

Relating forest productivity to local variations in forest structure has been a long-standing challenge. Previous studies often focused on the connection between forest structure and stand-level photosynthesis (GPP). However, biomass production (NPP) and net ecosystem exchange (NEE) are also subject to respiration and other carbon losses, which vary with local conditions and life history traits. Here, we use a simulation approach to study how these losses impact forest productivity and reveal themselves in forest structure. We fit the process-based forest model Formind to a 25 ha inventory of an old-growth temperate forest in China and classify trees as "mature" (full-grown) or "immature" based on their intrinsic carbon use efficiency. Our results reveal a strong negative connection between the stand-level carbon use efficiency and the prevalence of mature trees: GPP increases with the total basal area, whereas NPP and NEE are driven by the basal area of immature trees. Accordingly, the basal area entropy - a structural proxy for the prevalence of immature trees - correlated well with NPP and NEE and had a higher predictive power than other structural characteristics such as Shannon diversity and height standard deviation. Our results were robust across spatial scales (0.04-1 ha) and yield promising hypotheses for field studies and new theoretical work. [ABSTRACT FROM AUTHOR]

Late-spring frost (LSF) is a critical factor influencing the functioning of temperate, forest ecosystems. Frost damage in the form of canopy defoliation impedes the ability of trees to effectively photosynthesize thereby reducing tree productivity. In recent decades, LSF frequency has increased across Europe, likely intensified by the effects of climate change. With increasing warming, many deciduous tree species have shifted towards earlier budburst and leaf development. The earlier start of the growing season not only facilitates forest productivity but also lengthens the period during which trees are most susceptible to LSF. Moreover, recent forest transformation efforts in Europe intended to increase forest resilience to climate change have focused on increasing the share of deciduous species in forests. To assess the ability of forests to remain productive under climate change, dynamic vegetation models (DVMs) have proven to be useful tools. Currently, however, most state-of-the-art DVMs do not model processes related to LSF and the associated impacts. Here, we present a novel LSF module for integration with the dynamic vegetation model LPJ-GUESS. This new model implementation, termed LPJ-GUESS-FROST, provides the ability to directly attribute impacts on simulated forest productivity dynamics to LSF. We use the example of European beech, one of the dominant deciduous species in Central Europe, to demonstrate the functioning of our novel LSF module. Using a network of tree-ring observations from past frost events we show that LPJ-GUESS-FROST can reproduce productivity reductions caused by LSF. Further, to exemplify the effects of including LSF dynamics in DVMs, we run LPJ-GUESS-FROST for a study region in southern Germany for which high-resolution climate observations are available. Here, we show that modeling LSF plays a substantial role in regulating regional NPP and biomass dynamics emphasizing the need for LSF to be more widely accounted for in DVMs. [ABSTRACT FROM AUTHOR]

The extent of the potassium (K) limitation of forest productivity is probably more widespread than previously thought, and K limitation could influence the response of forests to future global changes. To understand the effects of K limitation on forest primary production, we have developed the first ecophysiological model simulating the K cycle and its interactions with the carbon (C) and water cycles. We focused on the limitation of the gross primary productivity (GPP) by K availability in tropical eucalypt plantations in Brazil. We used results from stand-scale fertilisation experiments as well as C flux measurements in two tropical eucalypt plantations to parameterise the model. The model was parameterised for fertilised conditions and then used to test for the effects of contrasting additions of K fertiliser. Simulations showed that K deficiency limits GPP by more than 50 % during a 6-year rotation, a value in agreement with estimations in K-limited eucalypt stands. Simulations showed a decrease of modelled canopy transpiration of around 50 % and a decrease in modelled water-use efficiency WUE GPP of 10 %. Through a sensitivity analysis, we used the model to identify the most critical processes to consider when studying K limitation of GPP. The inputs of K to the stands, such as the atmospheric deposition and weathering fluxes, and the regulation of the cycle of K within the ecosystem were critical for the response of the system to K deficiency. Litter leaching processes were of lower importance, since residence time of K in litter was low. The new forest K-cycle model developed in the present study includes multiple K processes interacting with the carbon and water cycles, and strong feedbacks on GPP were outlined. This is a first step in identifying the source or sink limitation of forest growth by K. [ABSTRACT FROM AUTHOR]

Potassium (K) availability constrains forest productivity. Brazilian eucalypt plantations are a good example of the K limitation of wood production. Here, we built upon a previously described model (CASTANEA-MAESPA-K) and used it to understand whether the simulated decline in C source under K deficiency was sufficient to explain the K limitation of wood productivity in Brazilian eucalypt plantations. We developed allocation schemes for both C and K and included these in CASTANEA-MAESPA-K. Neither direct limitations of the C-sink activity nor direct modifications of the C allocation by K availability were included in the model. Simulation results show that the model was successful in replicating the observed patterns of wood productivity limitation by K deficiency. Simulations also show that the response of net primary productivity (NPP) is not linear with increasing K fertilisation. Simulated stem carbon use and water use efficiencies decreased with decreasing levels of K availability. Simulating a direct stoichiometric limitation of NPP or wood growth was not necessary to reproduce the observed decline of productivity under K limitation, suggesting that K stoichiometric plasticity could be different to that of N and P. Confirming previous results from the literature, the model simulated an intense recirculation of K in the trees, suggesting that retranslocation processes were essential for tree functioning. Optimal K fertilisation levels calculated by the model were similar to nutritional recommendations currently applied in Brazilian eucalypt plantations, paving the way for validation of the model at a larger scale and of this approach for developing decision-making tools to improve fertilisation practices. [ABSTRACT FROM AUTHOR]

Droughts in Thailand are becoming more severe due to climate change. Developing a reliable drought monitoring and early warning system (DMEWS) is essential to strengthen a country's resilience to droughts. However, for a DMEWS to be valuable, the drought indicators provided to stakeholders must have relevance to tangible impacts on the ground. Here, we analyse drought indicator-to-impact relationships in Thailand, using a combination of correlation analysis and machine learning techniques (random forest). In the correlation analysis, we study the link between meteorological drought indicators and high-resolution remote sensing vegetation indices used as proxies for crop yield and forest growth impacts. Our analysis shows that this link varies depending on land use, season and region. The random forest models built to estimate regional crop productivity allow a more in-depth analysis of the crop- and region-specific importance of different drought indicators. The results highlight seasonal patterns of drought vulnerability for individual crops, usually linked to their growing season, although the effects are somewhat attenuated in irrigated regions. Integration of the approaches provides new, detailed knowledge of crop- and region-specific indicator-to-impact links, which can form the basis of targeted mitigation actions in an improved DMEWS in Thailand and could be applied to other parts of Southeast Asia and beyond. [ABSTRACT FROM AUTHOR]

We compiled published peer-reviewed CO2, CH4 and N2O data on drained organic forest soils in boreal and temperate zones, to revisit the current Tier 1 default emission factors (EFs) provided in the IPCC (2014) Wetlands Supplement: to see whether their uncertainty may be reduced, to evaluate possibilities for breaking the broad categories used for the IPCC EFs into more site-type specific ones, and to inspect the potential relevance of a number of environmental variables for predicting the annual soil greenhouse gas (GHG) balances, on which the EFs are based. Despite a considerable number of publications applicable for compiling EFs was added, only modest changes were found compared to the Tier 1 default EFs. However, the more specific site-type categories generated in this study showed narrower confidence intervals compared to the default categories. Overall, the highest CO2 EFs were found for temperate afforested agricultural lands, and boreal forestry-drained sites with very low tree-stand productivity. The highest CH4 EFs in turn prevailed at boreal nutrient-poor forests with very low tree-stand productivity and temperate forests irrespective of nutrient status, while the EFs for afforested sites were low or showed a sink function. The highest N2O EFs were found for afforested agricultural lands and forestry-drained nutrient-rich sites. The occasional wide confidence intervals could be mainly explained by single or few highly deviating estimates, rather than the broadness of the categories applied. Our EFs for the novel categories were further supported by the statistical models connecting the annual soil GHG balances to site-specific soil nutrient status indicators, tree stand characteristics, and temperature-associated weather and climate variables. The results of this synthesis have important implications for EF revisions and national emission reporting, e.g., by the use of different categories for afforested sites and forestry-drained sites, and more specific site productivity categories based on timber production potential. [ABSTRACT FROM AUTHOR]

Soil organic matter (SOM) plays an important role in the global carbon cycle, especially in alpine ecosystems. However, ongoing forest expansion in high elevation systems potentially alters SOM storage through changes in organic matter (OM) inputs and microclimate. In this study we investigated the effects of an Picea abies L. afforestation chrono-sequence (40–130 years) of a former subalpine pasture in Switzerland on soil organic carbon (SOC) stocks and SOM dynamics. We found that SOC stocks remained relatively constant throughout the chrono-sequence, with comparable SOC stocks in the mineral soils after afforestation and previous pasture (SOC40-year-old forest = 11.6 ± 1.1 kg m−2, SOC130-year-old forest = 11.0 ± 0.3 kg m−2, and SOC pasture = 11.5 ± 0.5 kg m−2). However, including the additional carbon of the organic horizons in the forest, reaching up to 1.7 kg m−2 in the 55-year-old forest, resulted in a slight in-crease in overall SOC stocks following afforestation. We found that the soil C:N ratio in the mineral soil increased in the topsoil (0–5cm) with increasing forest stand age, from 11.9 ± 1.3 in the grassland to 14.3 ± 1.8 in the 130-year-old forest. In turn, we observed a decrease in soil C:N ratio with increasing depth in all forest stand ages. This suggests that litter-derived organic matter (C:N from 35.1 ± 1.9 to 42.4 ± 10.8) is likely incorporated and translocated from the organic horizon to the mineral topsoil (0–10 cm) of the profiles. As roots had very high C:N ratios (pasture 63.5 ± 2.8 and forests between 54.7 ± 3.9 and 61.2 ± 2.9), particulate root-derived organic matter seems to have a minor influence on forest soil C:N ratio and thereby on SOC stock accumulation in the mineral soil. These results suggest that, although the afforestation only moderately affected the SOC stock, there is an apparent alteration in the SOC dynamics through changes of the litter composition caused by the vegetation shift. We conclude that spruce afforestation on a former subalpine pasture does not necessarily change the total SOC stock and that consequently there is no SOC sequestration on a decadal to centennial scale. [ABSTRACT FROM AUTHOR]

The extent of the potassium (K) limitation of forest productivity is probably more widespread than previously thought, and K-limitation could influence the response of forests to future global changes. To understand the effects of K-limitation on forest primary production, we have developed the first ecophysiological model simulating the K cycle and its interactions with the carbon (C) and water cycles. We focused on the limitation of the gross primary productivity (GPP) by K availability in tropical eucalypt plantations in Brazil. We used results from large-scale fertilisation experiments as well as C flux measurements in two tropical eucalypt plantations to parameterize the model. The model was parameterized for fertilised conditions and then used to test for the effects of contrasting additions of K fertiliser. Simulations showed that K-deficiency limits GPP by more than 50 % during a 6-year rotation, a value in agreement with the literature. The negative effects of K-deficiency on canopy transpiration and water use efficiency were also reported and discussed. Through a sensitivity analysis, we used the model to identify the most critical processes to consider when studying K-limitation of GPP. The external inputs of K to the stands, such as the atmospheric deposition and weathering fluxes, and the regulation of the internal fluxes of K within the ecosystem were critical for the response of the system to K deficiency. Litter decomposition processes were of lower importance. The new forest K-cycle model developed in the present study includes multiple K processes interacting with the carbon and water cycles, and strong feedbacks on GPP through forest growth were outlined. [ABSTRACT FROM AUTHOR]

The Paris Agreement commits 197 countries to achieve climate stabilisation at a global average surface temperature less than 2 °C above pre-industrial times, using nationally determined contributions (NDCs) to demonstrate progress vis-à-vis this goal. Numerous industrialised economies have targets to achieve territorial climate neutrality by 2050, primarily in the form of "net zero" greenhouse gas (GHG) emissions. However, particular uncertainty remains over the role of countries' agriculture, forestry and land use (AFOLU) sectors for numerous reasons, inter alia: the need to balance mitigation of difficult-to-abate agricultural emissions against food security; agriculture emissions of methane do not need to be reduced to zero to achieve climate stabilisation; land use should be a large net sink globally to offset residual emissions. These issues are represented at a coarse level in integrated assessment models (IAMS) that indicate the role of AFOLU in global pathways towards climate stabilisation. However, there is an urgent need to determine appropriate AFOLU management strategies at national level within NDCs. Here, we present a new model designed to evaluate detailed AFOLU scenarios at national scale, using the example of Ireland where 34 % of national GHG emissions originate from AFOLU. GOBLIN (General Overview for a Back-casting approach of Livestock Intensification) is designed to run randomised scenarios of agricultural activities and land use combinations in 2050 within biophysical constraints (e.g. available land area, livestock productivities, fertiliser-driven grass yields and forest growth rates). Based on AFOLU emission factors used for national GHG inventory reporting, GOBLIN then calculates annual GHG emissions out to 2050 for each scenario. The long-term dynamics of forestry are represented up to 2120, so that scenarios can also be evaluated against the Paris Agreement commitment to achieve a balance between emissions and removals over the second half of this century. We outline the rationale and methodology behind the development of this biophysical model intended to provide robust evidence on the biophysical linkages across food production, GHG emissions and carbon sinks at national level. We then demonstrate how GOBLIN can be applied to evaluate different scenarios in relation to a few possible simple definitions of "climate neutrality", discussing opportunities and limitations. [ABSTRACT FROM AUTHOR]

The Weddell Sea (WS) represents a point of origin in the Southern Ocean where globally-important water masses form. Biological activities in WS surface waters thus affect large-scale ocean biogeochemistry. During summer 2018/2019, we measured net primary production (NPP), nitrogen (nitrate, ammonium, urea) uptake, and nitrification in the western WS at the Antarctic Peninsula (AP) and Larsen C Ice Shelf (LCIS), in the southwestern Weddell Gyre (WG), and at Fimbul Ice Shelf (FIS) in the south-eastern WS. The highest average rates of NPP and greatest nutrient drawdown occurred at LCIS. Here, the phytoplankton community was dominated by colonial Phaeocystis antarctica, with diatoms increasing in abundance later in the season as sea-ice melt increased. At the other stations, NPP was variable, and diatoms known to enhance carbon export (e.g., Thalassiosira spp.) were dominant. Euphotic zone nitrification was always below detection, such that nitrate uptake could be used as a proxy for carbon export potential, which was highest in absolute terms at LCIS and the AP. Surprisingly, the highest f-ratios occurred near FIS rather than LCIS (average of 0.73 ± 0.09 versus 0.47 ± 0.08). We attribute this to ammonium inhibition of nitrate uptake at LCIS (where ammonium concentrations were 0.6 ± 0.4 μM, versus 0.05 ± 0.1 μM at FIS) driven by increased heterotrophy following the accumulation of nitrate-fuelled phytoplankton biomass in early summer. Across the WS, carbon export appears to be driven by a combination of physical, chemical, and biological factors, with the highest export flux occurring at the ice shelves and lowest in the central WG. [ABSTRACT FROM AUTHOR]

The Canadian Land Surface Scheme Including Biogeochemical Cycles (CLASSIC) is an open-source community model designed to address research questions that explore the role of the land surface in the global climate system. Here, we evaluate how well CLASSIC reproduces the energy, water, and carbon cycle when forced with quasi-observed meteorological data. Model skill scores summarize how well model output agrees with observation-based reference data across multiple statistical metrics. A lack of agreement may be due to deficiencies in the model, its forcing data, and/or reference data. To address uncertainties in the forcing, we evaluate an ensemble of CLASSIC runs that is based on three meteorological data sets. To account for observational uncertainty, we compute benchmark skill scores that quantify the level of agreement among independent reference data sets. The benchmark scores demonstrate what score values a model may realistically achieve given the uncertainties in the observations. Our results show that uncertainties associated with the forcing and observations are considerably large. For instance, for 10 out of 19 variables assessed in this study, the sign of the bias changes depending on what forcing and reference data are used. Benchmark scores are much lower than expected, implying large observational uncertainties. Model and benchmark score values are mostly similar, indicating that CLASSIC performs well when considering observational uncertainty. Future model development should address (i) a positive albedo bias and resulting shortwave radiation bias in parts of the Northern Hemisphere (NH) extratropics and Tibetan Plateau, (ii) an out-of-phase seasonal gross primary productivity cycle in the humid tropics of South America and Africa, (iii) a lacking spatial correlation of annual mean net ecosystem exchange with site-level measurements, (iv) an underestimation of fractional area burned and corresponding emissions in the boreal forests, (v) a negative soil organic carbon bias in high latitudes, and (vi) a time lag in seasonal leaf area index maxima in parts of the NH extratropics. Our results will serve as a baseline for guiding and monitoring future CLASSIC development. [ABSTRACT FROM AUTHOR]

Terrestrial Biosphere Modeling (TBM) is an invaluable approach for studying plant-atmosphere interactions at multiple spatial and temporal scales, as well as the global change impacts on ecosystems. Yet, TBM projections suffer from large uncertainties that limit their usefulness. A large part of this uncertainty arises from the empirical allometric (size-tomass) relationships that are used to represent forest structure in TBMs. Forest structure actually drives a large part of TBM uncertainty as it regulates key processes such as the transfer of carbon, energy, and water between the land and atmosphere, but remains challenging to measure and reliably represent. The poor representation of forest structure in TBMs results in models that are able to reproduce observed land fluxes, but which fail to realistically represent carbon pools, forest composition, and demography. Recent advances in Terrestrial Laser Scanning (TLS) techniques offer a huge opportunity to capture the three-dimensional structure of the ecosystem and transfer this information to TBMs in order to increase their accuracy. In this study, we quantified the impacts of integrating structural observations of individual trees (namely tree height, leaf area, woody biomass, and crown area) derived from TLS into the state-of-the-art Ecosystem Demography model (ED2.2) at a temperate forest site. We assessed the relative model sensitivity to initial conditions, allometric parameters, and canopy representation by changing them in turn from default configurations to site-specific, TLS-derived values. We show that forest demography and productivity as modelled by ED2.2 are sensitive to the imposed initial state, the model structural parameters, and the way canopy is represented. In particular, we show that: 1) the imposed openness of the canopy dramatically influenced the potential vegetation, the optimal ecosystem leaf area, and the vertical distribution of light in the forest, as simulated by ED2.2; 2) TLS-derived allometric parameters increased simulated leaf area index and aboveground biomass by 57 and 75 %, respectively; 3) the choice of model structure and allometric coefficient both significantly impacted the optimal set of parameters necessary to reproduce eddy covariance flux data. [ABSTRACT FROM AUTHOR]

Meeting internationally agreed-upon climate targets requires carbon dioxide removal (CDR) strategies coupled with an urgent phase-down of fossil fuel emissions. However, the efficacy and wider impacts of CDR are poorly understood. Enhanced rock weathering (ERW) is a land-based CDR strategy requiring large-scale field trials. Here we show that a low 3.44 t ha -1 wollastonite treatment in an 11.8 ha acid-rain-impacted forested watershed in New Hampshire, USA, led to cumulative carbon capture by carbonic acid weathering of 0.025–0.13 t CO 2 ha -1 over 15 years. Despite a 0.8–2.4 t CO 2 ha -1 logistical carbon penalty from mining, grinding, transportation, and spreading, by 2015 weathering together with increased forest productivity led to net CDR of 8.5–11.5 t CO 2 ha -1. Our results demonstrate that ERW may be an effective, scalable CDR strategy for acid-impacted forests but at large scales requires sustainable sources of silicate rock dust. [ABSTRACT FROM AUTHOR]

Large amounts of total organic carbon are temporarily stored in soils, which makes soil respiration one of the major sources of terrestrial CO 2 fluxes within the global carbon cycle. More than half of global soil organic carbon (SOC) is stored in subsoils (below 30 cm), which represent a significant carbon (C) pool. Although several studies and models have investigated soil respiration, little is known about the quantitative contribution of subsoils to total soil respiration or about the sources of CO 2 production in subsoils. In a 2-year field study in a European beech forest in northern Germany, vertical CO 2 concentration profiles were continuously measured at three locations, and CO 2 production was quantified in the topsoil and the subsoil. To determine the contribution of fresh litter-derived C to CO 2 production in the three soil profiles, an isotopic labelling experiment, using 13 C-enriched leaf litter, was performed. Additionally, radiocarbon measurements of CO 2 in the soil atmosphere were used to obtain information about the age of the C source in the CO 2 production. At the study site, it was found that 90 % of total soil respiration was produced in the first 30 cm of the soil profile, where 53 % of the SOC stock is stored. Freshly labelled litter inputs in the form of dissolved organic matter were only a minor source for CO 2 production below a depth of 10 cm. In the first 2 months after litter application, fresh litter-derived C contributed, on average, 1 % at 10 cm depth and 0.1 % at 150 cm depth to CO 2 in the soil profile. Thereafter, its contribution was less than 0.3 % and 0.05 % at 10 and 150 cm depths, respectively. Furthermore CO 2 in the soil profile had the same modern radiocarbon signature at all depths, indicating that CO 2 in the subsoil originated from young C sources despite a radiocarbon age bulk SOC in the subsoil. This suggests that fresh C inputs in subsoils, in the form of roots and root exudates, are rapidly respired, and that other subsoil SOC seems to be relatively stable. The field labelling experiment also revealed a downward diffusion of 13 CO 2 in the soil profile against the total CO 2 gradient. This isotopic dependency should be taken into account when using labelled 13 C and 14 C isotope data as an age proxy for CO 2 sources in the soil. [ABSTRACT FROM AUTHOR]

A flash drought is characterized by its rapid onset and arouses widespread concerns due to its devastating impacts on the environment and society without sufficient early warnings. The increasing frequency of soil moisture flash droughts in a warming climate highlights the importance of understanding its impact on terrestrial ecosystems. Previous studies investigated the vegetation dynamics during several extreme cases of flash drought, but there is no quantitative assessment on how fast the carbon fluxes respond to flash droughts based on decade-long records with different climates and vegetation conditions. Here we identify soil moisture flash drought events by considering decline rate of soil moisture and the drought persistency, and we detect the response of ecosystem carbon and water fluxes to a soil moisture flash drought during its onset and recovery stages based on observations at 29 FLUXNET stations from croplands to forests. Corresponding to the sharp decline in soil moisture and higher vapor pressure deficit (VPD), gross primary productivity (GPP) drops below its normal conditions in the first 16 d and decreases to its minimum within 24 d for more than 50 % of the 151 identified flash drought events, and savannas show highest sensitivity to flash drought. Water use efficiency increases for forests but decreases for cropland and savanna during the recovery stage of flash droughts. These results demonstrate the rapid responses of vegetation productivity and resistance of forest ecosystems to flash drought. [ABSTRACT FROM AUTHOR]

Theory predicts positive effects of species richness on the productivity of plant communities through complementary resource use and facilitative interactions between species. Results from manipulative experiments with tropical tree species indicate a positive diversity-productivity relationship (DPR), but the existing evidence from natural forests is scarce and contradictory. We studied forest aboveground productivity in more than 80 humid tropical montane old-growth forests in two highly diverse Andean regions with large geological and topographic heterogeneity, and related productivity to tree diversity and stand structural, edaphic and climatic factors with likely influence on productivity. Main determinants of aboveground productivity in the perhumid study regions were elevation (as a proxy of temperature), soil nutrient (N, P and base cation) availability, and forest structural parameters (wood specific gravity, aboveground biomass). Tree diversity had only a small positive influence on productivity, even though tree species numbers varied largely (6-27 species per 0.04 ha). We conclude that the productivity of Neotropical humid montane forests is primarily controlled by thermal, edaphic and stand structural factors, while tree diversity is of minor importance. [ABSTRACT FROM AUTHOR]

Vegetation provides key ecosystem services and is an important component in the hydrological cycle. Traditionally, the global distribution of vegetation is explained through climatic water availability. Locally, however, groundwater can aid growth by providing an extra water source (e.g. oases) or hinder growth by presenting a barrier to root expansion (e.g. swamps). In this study we analyse the global correlation between humidity (expressing climate-driven water and energy availability), groundwater and forest growth, approximated by the fraction of absorbed photosynthetically active radiation, and link this to climate and landscape position. The results show that at the continental scale, climate is the main driver of forest productivity; climates with higher water availability support higher energy absorption and consequentially more growth. Within all climate zones, however, landscape position substantially alters the growth patterns, both positively and negatively. The influence of the landscape on vegetation growth varies over climate, displaying the importance of analysing vegetation growth in a climate–landscape continuum. [ABSTRACT FROM AUTHOR]

The photosynthesis governs productivity and health of the forests. Traditionally, remote sensing derived reflectance measures have been used to assess forest phenology, productivity and stress. The chlorophyll pigments absorb solar radiation, and emit fluorescence in far red region of electromagnetic spectrum. Chlorophyll fluorescence directly relates to the photosynthetic activity of the plants. Measurement of chlorophyll fluorescence from space has recently been achieved in the form of Sun-Induced Fluorescence (SIF). But SIF response have been found variable with respect to variation in vegetation type, hence, there is a need to study SIF response of tropical forests of India considering their wide extent, contribution to national carbon cycle and climate resilience. In this study, intra- and inter-annual GOME-2 and OCO-2 SIF responses of contrasting Indian tropical forest types viz., dry deciduous (Betul, Madhya Pradesh), moist deciduous (Kalahandi, Orissa) and wet evergreen forests (Uttara Kannada, Karnataka) has been investigated with respect to rainfall, NDVI and GPP trends. The results show that dry, moist and wet forests of India have differences in photosynthetic activity at intra- and inter-annual scale. GOME-2 SIF observations were more variables than OCO-2 SIF, particularly during green-up and senescence phase. SIF explained higher seasonality for dry deciduous followed by moist deciduous and wet evergreen. Annually integrated SIF (proxy of GPP) was in order: wet evergreen > moist deciduous > dry deciduous. [ABSTRACT FROM AUTHOR]

Meeting internationally agreed-upon climate targets requires Carbon Dioxide Removal (CDR) strategies coupled with an urgent phase-down of fossil fuel emissions. However, the efficacy and wider impacts of CDR are poorly understood. Enhanced rock weathering (ERW) is a land-based CDR strategy requiring large-scale field trials. Here we show that a low 3.44 t ha-1 wollastonite treatment in an 11.8-ha acid-rain-impacted forested watershed in New Hampshire, USA led to cumulative carbon capture by carbonic acid weathering of 0.025-0.13 t CO2 ha-1 over 15 years. Despite a 0.8-2.4 t CO2 ha-1 logistical carbon penalty from mining, grinding, transportation and spreading, by 2015 weathering together with increased forest productivity led to net CDR of 8.5-11.5 t CO2 ha-1. Our results demonstrate that ERW may be an effective, scalable CDR strategy for acid-impacted forests but at large-scale requires sustainable sources of silicate rock dust. [ABSTRACT FROM AUTHOR]

Land-use models and Integrated Assessment Models provide scenarios of land use/cover (LULC) changes following pathways or storylines related to different socio-economic and environmental developments. The large diversity of available scenario projections leads to a recognizable variability in impacts on land ecosystems and the levels of services provided. We evaluated 16 projections of future LULC until 2040 that reflected different assumptions on socio-economic demands and modeling protocols. By using these LULC projections in a state of the art dynamic global vegetation model, we simulated their effect on selected ecosystem service indicators related to ecosystem productivity and carbon sequestration potential, agricultural production and the water cycle. We found that although a common trend for agricultural expansion exists across the scenarios, where and how particular LULC changes are realized differs widely across models and scenarios. They are linked to model-specific considerations of some demands over others and their respective translation into LULC changes and also reflect the simplified or missing representation of processes related to land dynamics or other influencing factors (e.g., trade, climate change). As a result, some scenarios show questionable and possibly unrealistic features in their LULC allocations, including highly regionalized LULC changes with rates of conversion that are contrary to or exceeding rates observed in the past. Across the diverging LULC projections we identified positive global trends of net primary productivity (+10.2 %), vegetation carbon (+9.2 %), crop production (+31.2 %) and water runoff (+9.3 %), and a negative trend of soil and litter carbon stocks (-0.5 %). The variability in ecosystem service indicators across scenarios was especially high for vegetation carbon stocks (± 4.1 %) and crop production (± 12.2 %). Regionally, variability was highest in tropical forest regions, especially at current forest edges, because of intense and strongly diverging LULC change projections in combination with high vegetation productivity dampening or amplifying the effects of climatic change. Our results emphasize that information on future changes in ecosystem functioning and the related ecosystem service indicators should be seen in light of the variability originating from diverging projections of LULC. This is necessary to allow for adequate policy support towards sustainable transformations. [ABSTRACT FROM AUTHOR]

Plant functional traits determine vegetation responses to environmental variation, but variation in trait values is large, even within a single site. Likewise, uncertainty in how these traits map to Earth system feedbacks is large. We use a vegetation demographic model (VDM), the Functionally Assembled Terrestrial Ecosystem Simulator (FATES), to explore parameter sensitivity of model predictions, and comparison to observations, at a tropical forest site: Barro Colorado Island in Panama. We define a single 12-dimensional distribution of plant trait variation, derived primarily from observations in Panama, and define plant functional types (PFTs) as random draws from this distribution. We compare several model ensembles, where individual ensemble members vary only in the plant traits that define PFTs, and separate ensembles differ from each other based on either model structural assumptions or non-trait, ecosystem-level parameters, which include (a) the number of competing PFTs present in any simulation and (b) parameters that govern disturbance and height-based light competition. While single-PFT simulations are roughly consistent with observations of productivity at Barro Colorado Island, increasing the number of competing PFTs strongly shifts model predictions towards higher productivity and biomass forests. Different ecosystem variables show greater sensitivity than others to the number of competing PFTs, with the predictions that are most dominated by large trees, such as biomass, being the most sensitive. Changing disturbance and height-sorting parameters, i.e., the rules of competitive trait filtering, shifts regimes of dominance or coexistence between early- and late-successional PFTs in the model. Increases to the extent or severity of disturbance, or to the degree of determinism in height-based light competition, all act to shift the community towards early-successional PFTs. In turn, these shifts in competitive outcomes alter predictions of ecosystem states and fluxes, with more early-successional-dominated forests having lower biomass. It is thus crucial to differentiate between plant traits, which are under competitive pressure in VDMs, from those model parameters that are not and to better understand the relationships between these two types of model parameters to quantify sources of uncertainty in VDMs. [ABSTRACT FROM AUTHOR]

Phosphorus (P) is a limiting factor of primary productivity in most forest ecosystems but little is known about retention within and losses of P from forests. Subsurface flow (SSF) is one of the important pathways of P export but few attempts exist to quantify it. We present results of sprinkling experiments with ca. 150 mm, 2H labelled, total rainfall conducted at 200 m² plots on hillslopes with slopes between 14° and 28° at three beech forests in Germany in summer and spring. We aimed at quantifying vertical and lateral SSF and associated P transport in the forest floor, the mineral soil and the saprolite. The study sites differed regarding soil depth, skeleton content and soil P stocks (between 678 g/m² and 209 g/m², in the first 1 m soil depth). Vertical SSF in the mineral soil and in the saprolite was at least two orders of magnitude larger than lateral SSF in the same depth. Vertical and lateral SSF consisted mainly of pre-event water that was replaced by sprinkling water (piston flow mechanism). Short spikes of event water at the beginning of the experiment at two of the sites with high skeleton content indicate that preferential flow occurred in parallel to matrix flow. We observed a significant decrease in P concentrations in SSF with increasing soil depth suggesting effective retention of P by adsorption to soil particles in all three forest ecosystems. Higher P concentrations in SSF at the beginning of the experiments indicate nutrient flushing but P concentrations were nearly constant thereafter despite strong increase in SSF. P concentrations did also not change significantly with increasing share of event water in SSF. These chemostatic transport conditions suggests that P mobilization rates were similar to transport rates in both, P-rich and P-poor sites. The observed first flush effect implies that P export by SSF will increase as rainfall events with high transport capacity are predicted to occur more frequent under future climatic conditions. [ABSTRACT FROM AUTHOR]

Process-based vegetation models are widely used to predict local and global ecosystem dynamics and climate change impacts. Due to their complexity, they require careful parameterization and evaluation to ensure that projections are accurate and reliable. The PROFOUND Database (PROFOUND DB) provides a wide range of empirical data on European forests to calibrate and evaluate vegetation models that simulate climate impacts at the forest stand scale. A particular advantage of this database is its wide coverage of multiple data sources at different hierarchical and temporal scales, together with environmental driving data as well as the latest climate scenarios. Specifically, the PROFOUND DB provides general site descriptions, soil, climate, CO2 , nitrogen deposition, tree and forest stand level, and remote sensing data for nine contrasting forest stands distributed across Europe. Moreover, for a subset of five sites, time series of carbon fluxes, atmospheric heat conduction and soil water are also available. The climate and nitrogen deposition data contain several datasets for the historic period and a wide range of future climate change scenarios following the Representative Concentration Pathways (RCP2.6, RCP4.5, RCP6.0, RCP8.5). We also provide pre-industrial climate simulations that allow for model runs aimed at disentangling the contribution of climate change to observed forest productivity changes. The PROFOUND DB is available freely as a "SQLite" relational database or "ASCII" flat file version (at 10.5880/PIK.2020.006/; Reyer et al., 2020). The data policies of the individual contributing datasets are provided in the metadata of each data file. The PROFOUND DB can also be accessed via the ProfoundData R package (https://CRAN.R-project.org/package=ProfoundData ; Silveyra Gonzalez et al., 2020), which provides basic functions to explore, plot and extract the data for model set-up, calibration and evaluation. [ABSTRACT FROM AUTHOR]

Tree degradation in National Parks poses a serious risk to the birds and animals and to a larger extent the general ecosystem. The essence of Forest degradation mapping is to detect the extent of damage on the trees over time, hence providing stakeholders with a basis for forest rehabilitation and intervention. The study proposes a workflow for detection and classification of degrading acacia vegetation along Lake Nakuru riparian reserve. Inspired by previous research on the use of Dual Polarized Sentinel 1 Ground Range Detected (GRD) data for vegetation detection, a set of six Sentinel 1 GRD and Sentinel 2 MSI of corresponding dates (2018–2019) were used. Our study confirms the existing correlation between vegetation indices derived from optical sensors and the backscatter indices from S1 SAR image of the same land cover classes. Factors that were used in validating the results include some comparisons between pixelwise and object-based classification, with a focus on the underlying segmentation and classification algorithms, the polarimetric attributes (VV+VH intensity bands) and the reflectance bands (NIR, SWIR & GREEN), the Haralick features (GLCM) vs. some geometric attributes (area & moment of inertia). Classification carried out on the temporal datasets considering geometric attributes and the Random Forest classifier yielded the highest Overall Accuracy (OA) with 94.25 %, and a Kappa coefficient of 0.90. [ABSTRACT FROM AUTHOR]

Temperate rainforest soils of the Pacific Northwest are often carbon (C) rich and encompass a wide range of fertility, reflecting varying nitrogen (N) and phosphorus (P) availability. Soil resource stoichiometry (C : N : P) may provide an effective measure of site nutrient status and help refine species-dependent patterns in forest productivity across edaphic gradients. We determined mineral soil and forest floor nutrient concentrations across very wet (perhumid) rainforest sites of southwestern Vancouver Island (Canada) and employed soil element ratios as covariates in a long-term planting density trial to test their utility in defining basal area growth response of four conifer species. There were strong positive correlations in mineral soil C, N, and organic P (P o) concentrations and close alignment in C : N and C : P o both among and between substrates. Stand basal area after 5 decades was best reflected by mineral soil and forest floor C : N, but in either case included a significant species–soil interaction. The conifers with ectomycorrhizal fungi had diverging growth responses displaying either competitive (Picea sitchensis) or stress-tolerant (Tsuga heterophylla , Pseudotsuga menziesii) attributes, in contrast to a more generalist response by an arbuscular mycorrhizal tree (Thuja plicata). Despite the consistent patterns in organic matter quality, we found no evidence for increased foliar P concentrations with declining element ratios (C : P o or C : P total) as we did for N. The often high C : P o ratios (as much as 3000) of these soils may reflect a stronger immobilization sink for P than N, which, along with ongoing sorption of PO4- , could limit the utility of C : P o or N : P o to adequately reflect P supply. The dynamics and availability of soil P to trees, particularly as P o , deserves greater attention, as many perhumid rainforests were co-limited by N and P, or, in some stands, possibly P alone. [ABSTRACT FROM AUTHOR]

Soil mineral weathering is one of the major sources of base cations (BC), which play a dual role in forest ecosystems: they function as plant nutrients and buffer against the acidification of catchment runoff. On a long-term basis, soil weathering rates determine the highest sustainable forest productivity that does not cause acidification. It is believed that the hydrologic residence time plays a key role in determining the weathering rates at the landscape scale. The PROFILE weathering model has been used for almost 30 years to calculate weathering rates in the rooting zone of forest soils. However, the mineral dissolution equations in PROFILE are not adapted for the saturated zone, and employing these equations at the catchment scale results in a significant overprediction of base cation release rates to surface waters. In this study, we use a revised set of PROFILE equations which, among other features, include retardation due to silica concentrations. Relationships between the water transit time (WTT) and soil water concentrations were derived for each base cation, by simulating the soil water chemistry along a one-dimensional flow path, using the mineralogy from a glacial till soil. We show how the revised PROFILE equations are able to reproduce patterns in BC and silica concentrations as well as BC ratios (Ca2+/BC , Mg2+/BC and Na+/BC) that are observed in the soil water profiles and catchment runoff. In contrast to the original set of PROFILE equations, the revised set of equations could reproduce the fact that increasing WTT led to a decreasing Na+/BC ratio and increasing Ca2+/BC and Mg2+/BC ratios. Furthermore, the total release of base cations from a hillslope was calculated using a mixing model, where water with different WTTs was mixed according to an externally modeled WTT distribution. The revised set of equations gave a 50 % lower base cation release (0.23 eq m -2 yr -1) than the original PROFILE equations and are in better agreement with mass balance calculations of weathering rates. Thus, the results from this study demonstrate that the revised mineral dissolution equations for PROFILE are a major step forward in modeling weathering rates at the catchment scale. [ABSTRACT FROM AUTHOR]

Plant functional traits determine vegetation responses to environmental variation, but variation in trait values is large, even within a single site. Likewise, uncertainty in how these traits map to Earth system feedbacks is large. We use a vegetation demographic model (VDM), the Functionally Assembled Terrestrial Ecosystem Simulator (FATES), to explore parameter sensitivity of model predictions, and comparison to observations, at a tropical forest site: Barro Colorado Island in Panama. We define a single 12-dimensional distribution of plant trait variation, derived primarily from observations in Panama, and define plant functional types (PFTs) as random draws from this distribution. We compare several model ensembles, where individual ensemble members vary only in the plant traits that define PFTs, and separate ensembles differ from each other based on either model structural assumptions or non-trait, ecosystem-level parameters, which include: (a) the number of competing PFTs present in any simulation, and (b) parameters that govern disturbance and height-based light competition. While single-PFT simulations are roughy consistent with observations of productivity at BCI, increasing the number of competing PFTs strongly shifts model predictions towards higher productivity and biomass forests. Different ecosystem variables show greater sensitivity than others to the number of competing PFTs, with the predictions that are most dominated by large trees, such as biomass, being the most sensitive. Changing disturbance and height-sorting parameters, i.e. the rules of competitive trait filtering, shifts regimes of dominance or coexistence between early and late successional PFTs in the model. Increases to the extent or severity of disturbance, or to the degree of determinism in height-based light competition, all act to shift the community towards early-successional PFTs. In turn, these shifts in competitive outcomes alter predictions of ecosystem states and fluxes, with more early-successional dominated forests having lower biomass. It is thus crucial to differentiate between plant traits, which are under competitive pressure in VDMs, from those model parameters that are not, and to better understand the relationships between these two types of model parameters, to quantify sources of uncertainty in VDMs. [ABSTRACT FROM AUTHOR]

Temperate rainforest soils of the Pacific Northwest are often carbon (C) rich and encompass a wide range in fertility reflecting varying nitrogen (N) and phosphorus (P) availability. Soil resource stoichiometry (C : N : P) may provide an effective measure of site nutrient status and help refine species-dependent patterns in forest productivity across edaphic gradients. We described the nature of soil organic matter for mineral soil and forest floor substrates across very wet (perhumid) rainforest sites of southwestern Vancouver Island (Canada), and employed soil element ratios as covariates in a long-term planting density trial to test their utility in defining basal area growth response of four conifer species. There were strong positive correlations in mineral soil C, N and organic P (Po) concentrations, and close alignment in C : N and C : Po both among and between substrates. Stand basal area after five decades was best reflected by soil C : N but included a significant species-soil interaction. The conifers with ectomycorrhizal fungi had diverging growth responses displaying either competitive (Picea sitchensis) or stress-tolerant (Tsuga heterophylla, Pseudotsuga menziesii) attributes, in contrast to a more generalist response by an arbuscular mycorrhizal tree (Thuja plicata). Despite the consistent patterns in organic matter quality we found no evidence via foliar nutrition for increased P availability with declining element ratios as we did for N. The often high C : Po ratios (as much as 3000) of these soils may reflect a stronger immobilization sink for P than N, which, along with ongoing sorption of PO4-, could limit the utility of C : Po or N : Po to adequately reflect P supply. The dynamics and availability of soil P to trees, particularly as Po, deserves greater attention as many perhumid rainforests were co-limited by N and P, or, in some stands, possibly P alone. [ABSTRACT FROM AUTHOR]

Process-based vegetation models are widely used to predict local and global ecosystem dynamics and climate change impacts. Due to their complexity, they require careful parameterization and evaluation to ensure that projections are accurate and reliable. The PROFOUND Database (PROFOUND DB) provides a wide range of empirical data to calibrate and evaluate vegetation models that simulate climate impacts at the forest stand scale. A particular advantage of this database is its wide coverage of multiple data sources at different hierarchical and temporal scales, together with environmental driving data as well as the latest climate scenarios. Specifically, the PROFOUND DB provides general site descriptions, soil, climate, CO2, nitrogen deposition, tree and forest stand-level, as well as remote sensing data for nine contrasting forest stands distributed across Europe. Moreover, for a subset of five sites, time series of carbon fluxes, atmospheric heat conduction, and soil water are also available. The climate and nitrogen deposition data contain several datasets for the historic period and a wide range of future climate change scenarios following the Representative Concentration Pathways (RCP2.6, RCP4.5, RCP6.0, RCP8.5). We also provide pre-industrial climate simulations that allow for model runs aimed at disentangling the contribution of climate change to observed forest productivity changes. The PROFOUND DB is available freely as a "SQLite" relational database or "ASCII" flat file version (at https://doi.org/10.5880/PIK.2019.008). The data policies of the individual, contributing datasets are provided in the metadata of each data file. The PROFOUND DB can also be accessed via the ProfoundData R-package (https://github.com/COST-FP1304-PROFOUND/ProfoundData), which provides basic functions to explore, plot, and extract the data for model set-up, calibration and evaluation. [ABSTRACT FROM AUTHOR]

Forests of the Western Himalaya, India, are impacted by the summer monsoon and winter seasonal rainfall events and associated changes in the meteorology. Here, we assess the scale interactions between observed forest ecosystem fluxes and meteorological parameters, particularly rainfall seasonality and extremes. The scale interactions were investigated using daily observed fluxes and meteorological parameters of 1080 days of 2014-2016 from a Pinus roxburghii dominated forest and using wavelet spectral analysis method. The mixed forest of this study was a sink of CO2 having the average NEE -3.21 gC m-2 day-1 for the period of observations. Result of the wavelet coherence analysis from observed data indicated a statistically significant correlation (> 0.7 at 95% confidence level) between daily average NEE and daily total rainfall having band periods of 70-120 days, 35-64 days and 60-90 days of monsoon periods of 2014-16, respectively, where rainfall leading to NEE. Impact of heavy rainfall events of monsoon periods over NEE of the forest patch was found to have average band periods of 4 days; whereas, the winter time heavy rainfall events were having average band periods of 15 days with very high local correlation (> 0.7 at 95% confidence level) inferring that ecosystem exchange rate was mirroring rainfall events. Although CASA-GFDE3 model simulated daily NEE values of 2014-15 were found have a low fraction of explained variance (= 0.08) with respect to observations, modeled NEE-rainfall relationship of 2014 was found to corroborate well with the observed pattern; however for 2015, the phase relationship between modeled NEE and rainfall around band period of 100 days was opposite to the flux tower observations. Subsequently, heavy rainfall events and daily average air temperatures were also found to be coherent during monsoon period having wavelet coherences > 0.8 indicating a cause and effect relationship between both parameters, and rainfall events were mirroring temperature variations. Therefore, it is anticipated that the Pinus roxburghii dominated forest productivity of Western Himalaya, India, are expected to increase even with the increment of heavy rainfall events in the near 20 future. [ABSTRACT FROM AUTHOR]

Rising temperatures due to climate change influence the wood production of forests. Observations show that some temperate forests increase their productivity, whereas others reduce their productivity. This study focuses on how species composition and forest structure properties influence the temperature sensitivity of aboveground wood production (AWP). It further investigates which forests will increase their productivity the most with rising temperatures. We described forest structure by leaf area index, forest height and tree height heterogeneity. Species composition was described by a functional diversity index (Rao's Q) and a species distribution index (ΩAWP). ΩAWP quantified how well species are distributed over the different forest layers with regard to AWP. We analysed 370 170 forest stands generated with a forest gap model. These forest stands covered a wide range of possible forest types. For each stand, we estimated annual aboveground wood production and performed a climate sensitivity analysis based on 320 different climate time series (of 1-year length). The scenarios differed in mean annual temperature and annual temperature amplitude. Temperature sensitivity of wood production was quantified as the relative change in productivity resulting from a 1 °C rise in mean annual temperature or annual temperature amplitude. Increasing ΩAWP positively influenced both temperature sensitivity indices of forest, whereas forest height showed a bell-shaped relationship with both indices. Further, we found forests in each successional stage that are positively affected by temperature rise. For such forests, large AWP values were important. In the case of young forests, low functional diversity and small tree height heterogeneity were associated with a positive effect of temperature on wood production. During later successional stages, higher species diversity and larger tree height heterogeneity were an advantage. To achieve such a development, one could plant below the closed canopy of even-aged, pioneer trees a climax-species-rich understorey that will build the canopy of the mature forest. This study highlights that forest structure and species composition are both relevant for understanding the temperature sensitivity of wood production. [ABSTRACT FROM AUTHOR]

Land use change (LUC) is among the main anthropogenic disturbances in the global carbon cycle. Here we present the model developments in a global dynamic vegetation model ORCHIDEE-MICT v8.4.2 for a more realistic representation of LUC processes. First, we included gross land use change (primarily shifting cultivation) and forest wood harvest in addition to net land use change. Second, we included sub-grid evenly aged land cohorts to represent secondary forests and to keep track of the transient stage of agricultural lands since LUC. Combination of these two features allows the simulation of shifting cultivation with a rotation length involving mainly secondary forests instead of primary ones. Furthermore, a set of decision rules regarding the land cohorts to be targeted in different LUC processes have been implemented. Idealized site-scale simulation has been performed for miombo woodlands in southern Africa assuming an annual land turnover rate of 5% grid cell area between forest and cropland. The result shows that the model can correctly represent forest recovery and cohort aging arising from agricultural abandonment. Such a land turnover process, even though without a net change in land cover, yields carbon emissions largely due to the imbalance between the fast release from forest clearing and the slow uptake from agricultural abandonment. The simulation with sub-grid land cohorts gives lower emissions than without, mainly because the cleared secondary forests have a lower biomass carbon stock than the mature forests that are otherwise cleared when sub-grid land cohorts are not considered. Over the region of southern Africa, the model is able to account for changes in different forest cohort areas along with the historical changes in different LUC activities, including regrowth of old forests when LUC area decreases. Our developments provide possibilities to account for continental or global forest demographic change resulting from past anthropogenic and natural disturbances. [ABSTRACT FROM AUTHOR]

The seasonal and sub-seasonal dynamics of iron availability within the sub-Antarctic zone (SAZ, ~ 40-45° S) play an important role in the distribution, biomass and productivity of the phytoplankton community. The variability in iron availability is due to an interplay between winter entrainment, diapycnal diffusion, storm-driven entrainment, iron scavenging and iron recycling processes. Biological observations utilising grow-out iron addition incubation experiments were performed at different stages of the seasonal cycle within the SAZ to determine the importance of these supply mechanisms. Here we demonstrate that at the beginning of the growing season there is sufficient iron to meet the demands of the phytoplankton community, but as the growing season develops the supply mechanisms fail to meet this demand. Phytoplankton increase their photosynthetic efficiency and net growth rates following iron addition from mid to late summer, with no differences determined during early summer; suggestive of seasonal iron depletion and low iron resupply. The result of which is residual macronutrients at the end of the growing season, and the prevalence of the high-nutrient low-chlorophyll (HNLC) condition. We conclude that despite the prolonged growing season characteristic of the sub-Antarctic zone, which can extend into late summer/early autumn, the results suggest that the iron supply mechanisms are insufficient to maintain potential maximal growth and productivity throughout the season. [ABSTRACT FROM AUTHOR]

Fire is a dynamic ecological process in forests and impacts the carbon (C) cycle through direct combustion emissions, tree mortality, and by impairing the ability of surviving trees to sequester carbon. While studies on young trees have demonstrated that fire intensity is a determinant of post-fire net primary productivity, wildland fires at landscape to regional scales have largely been assumed to either cause tree mortality, or conversely, cause no physiological impact, ignoring the impacted but surviving trees. Our objective was to understand how fire intensity affects post-fire net primary productivity in conifer-dominated forested ecosystems at the spatial scale of large wildland fires. We examined the relationships between fire radiative power (FRP), its temporal integral (fire radiative energy - FRE), and net primary productivity (NPP) using 16 years of data from the MOderate Resolution Imaging Spectrometer (MODIS) for 15 large fires in western United States coniferous forests. The greatest NPP post-fire loss occurred one year post-fire and ranged from -67 to -312 g C m-2 yr-1 (-13 to -54%) across all fires. Forests dominated by fire-resistant species (species that typically survive low intensity fires) experienced the lowest relative NPP reductions compared to forests with less resistant species. Post-fire NPP in forests that were dominated by fire-susceptible species were not as sensitive to FRP or FRE, indicating that NPP in these forests may be reduced to similar levels regardless of fire intensity. Conversely, post-fire NPP in forests dominated by fire resistant and mixed species decreased with increasing FRP or FRE. In some cases, this dose-response relationship persisted for more than a decade post-fire, highlighting a legacy effect of fire intensity on post-fire C dynamics in these forests. [ABSTRACT FROM AUTHOR]

Rain-fed farming is the primary livelihood of semi-arid west Africa. Changes in land cover have the potential to affect precipitation, the critical resource for production. Turbulent flux measurements from two eddy-covariance towers and additional observations from a dense network of small, wireless meteorological stations combine to relate land cover (savanna forest and agriculture) to evaporation in a small (3.5 km2) catchment in Burkina Faso, west Africa. We observe larger sensible and latent heat fluxes over the savanna forest in the headwater area relative to the agricultural section of the watershed all year. Higher fluxes above the savanna forest are attributed to the greater number of exposed rocks and trees and the higher productivity of the forest compared to rain-fed, hand-farmed agricultural fields. Vegetation cover and soil moisture are found to be primary controls of the evaporative fraction. Satellite-derived vegetation index (NDVI) and soil moisture are determined to be good predictors of evaporative fraction, as indicators of the physical basis of evaporation. Our measurements provide an estimator that can be used to derive evaporative fraction when only NDVI is available. Such large-scale estimates of evaporative fraction from remotely sensed data are valuable where groundbased measurements are lacking, which is the case across the African continent and many other semi-arid areas. Evaporative fraction estimates can be combined, for example, with sensible heat from measurements of temperature variance, to provide an estimate of evaporation when only minimal meteorological measurements are available in remote regions of the world. These findings reinforce local cultural beliefs of the importance of forest fragments for climate regulation and may provide support to local decision makers and rural farmers in the maintenance of the forest areas. [ABSTRACT FROM AUTHOR]

Plantation forest area in the conterminous United States (CONUS) ranked second among the world's nations in the land area apportioned to forest plantation. As compared to the naturally regenerated forests, plantation forests demonstrate significant differences in biophysical characteristics, and biogeochemical and hydrological cycles as a result of more intensive management practices. Inventory data have been reported for multiple time periods on plot, state, and regional scales across the CONUS, but the requisite annual and spatially explicit plantation data set over a long-term period for analysis of the role of plantation management on regional or national scales is lacking. Through synthesis of multiple inventory data sources, this study developed methods to spatialize the time series plantation forest and tree species distribution data for the CONUS over the 1928–2012 time period. According to this new data set, plantation forest area increased from near zero in the 1930s to 268.27 thousand km2 in 2012, accounting for 8.65 % of the total forestland area in the CONUS. Regionally, the South contained the highest proportion of plantation forests, accounting for about 19.34 % of total forestland area in 2012. This time series and gridded data set developed here can be readily applied in regional Earth system modeling frameworks for assessing the impacts of plantation management practices on forest productivity, carbon and nitrogen stocks, and greenhouse gases (e.g., CO2, CH4, and N2O) and water fluxes on regional or national scales. [ABSTRACT FROM AUTHOR]

As a result of different types of disturbance, forests are a mixture of stands at different stages of ecological succession. Successional stage is likely to influence forest productivity and carbon storage, linking the degree of forest disturbance to the global carbon cycle and climate. Although tropical montane forests are an important part of tropical forest ecosystems (ca. 8%, elevation >1000ma.s.l.), there are still significant knowledge gaps regarding the carbon dynamics and stocks of these forests, and how these differ between early (ES) and late successional (LS) stages. This study examines the carbon (C) stock, relative growth rate (RGR) and net primary production (NPP) of ES and LS forest stands in an Afromontane tropical rainforest using data from inventories of quantitatively important ecosystem compartments in fifteen 0.5?ha plots in Nyungwe National Park in Rwanda. The total C stock was 35% larger in LS compared to ES plots due to significantly larger above-ground biomass (AGB; 185 and 76Mg Cha-1 in LS and ES plots), while the soil and root C stock (down to 45cm depth in the mineral soil) did not significantly differ between the two successional stages (178 and 204?Mg Cha-1 in LS and ES plots). The main reasons for the difference in AGB were that ES trees had significantly lower stature and wood density compared to LS trees. However, ES and LS stands had similar total NPP (canopy, wood and roots of all plots ~9.4Mg Cha-1) due to counterbalancing effects of differences in AGB (higher in LS stands) and RGR (higher in ES stands). The AGB in the LS plots was considerably higher than the average value reported for old-growth tropical montane forest of south-east Asia and Central and South America at similar elevations and temperatures, and of the same magnitude as in tropical lowland forest of these regions. The results of this study highlight the importance of accounting for disturbance regimes and differences in wood density and allometry of tree species dominating at different successional stages in an attempt to quantify the C stock and sink strength of tropical montane forests and how they may differ among continents. [ABSTRACT FROM AUTHOR]

Much of the western US is projected to become warmer and drier over the coming century, underscoring the need to understand how climate influences terrestrial ecosystems in this region. We quantified the response of tree net primary productivity (NPP), live biomass (BIO), and mean carbon residence time (CRT = BIO/NPP) to spatial variation in climatic water availability in the western US. We used forest inventory measurements from 1,953 mature stands (≥ 100 years) in Washington, Oregon, and California (WAORCA) along with satellite and climate data sets covering the western US. We summarized forest structure and function in both domains along a 400 cm yr-1 hydrologic gradient, quantified with a climate moisture index based on the difference between precipitation and reference evapotranspiration summed from October-September (i.e., water-year) and then averaged annually from 1985-2014 (CMIwy). Median NPP, BIO, and CRT computed at 10 cm yr-1 intervals along the CMIwy gradient increased monotonically with increasing CMIwy across both WAORCA (rs = 0.93-0.96, p < 0.001) and the western US (rs = 0.93-0.99, p < 0.001). Field measurements from WAORCA showed that median NPP increased from 2.2 to 5.6 Mg C ha-1 yr- between the driest and wettest 5 % of sites, while BIO increased from 26 to 281 Mg C ha-1 and CRT increased from 11 to 49 years. The satellite data sets revealed similar changes over the western US, though these data sets tended to plateau in the wettest areas, suggesting that additional efforts are needed to better quantify NPP and BIO from satellites in high-productivity, high-biomass forests. Our results indicate that mature forests in this region were widely sensitive to changes in water availability, suggesting that projected climatic change over the coming century could reduce NPP, BIO, and CRT in many parts of this region, particularly the Southwest, with resulting impacts on ecosystem services. [ABSTRACT FROM AUTHOR]

As a result of different types of disturbance, forests are a mixture of stands at different stages of ecological succession. Successional stage is likely to influence forest productivity and carbon storage, linking the degree of forest disturbance to the global carbon cycle and climate. Although tropical montane forests are an important part of tropical forest ecosystems (c. 8%, elevation > 1000 m a.s.l.), there are still significant knowledge gaps regarding the carbon dynamics and stocks of these forests, and how these differ between early (ES) and late successional (LS) stages. This study examines the carbon (C) stock, relative growth rate (RGR), and net primary production (NPP) of ES and LS forest stands in an Afromontane tropical rainforest using data from inventories of quantitatively important ecosystem compartments in fifteen 0.5 ha plots in Nyungwe National Park in Rwanda. The total C stock was 35% larger in LS compared to ES plots due to significantly larger above ground biomass (AGB; 185 and 76 Mg C ha-1 in LS and ES plots, respectively), while the soil and root C stock (down to 45 cm depth in the mineral soil) did not significantly differ between the two successional stages (178 and 204 Mg C ha-1 in LS and ES plots, respectively). The main reasons for the difference in AGB were that ES trees had significantly lower stature and wood density compared to LS trees. However, ES and LS stands had similar total NPP (canopy, wood and roots of all plots ~ 9.4 Mg C ha-1) due to counterbalancing effects of differences in AGB (higher in LS stands) and RGR (higher in ES stands). The AGB in the LS plots was considerably higher than the average value reported for old-growth tropical montane forest of Southeast Asia and central and South America at similar elevations and temperatures, and of the same magnitude as in tropical lowland forest of different regions. The results of this study highlight the importance of accounting for disturbance regimes and differences in wood density and allometry of tree species dominating at different successional stages in attempts to quantify the C stock and sink strength of tropical montane forests and how it may differ among continents. [ABSTRACT FROM AUTHOR]

Increasing atmospheric CO2 and temperature may increase forest productivity, including litterfall, but the consequences for soil organic matter remain poorly understood. To address this, we measured soil carbon and nutrient concentrations at nine depths to 2 m after six years of continuous litter removal and litter addition in a semi-evergreen rain forest in Panama. Soils in litter addition plots, compared to litter removal plots, had higher pH and contained greater concentrations of KCl17 extractable nitrate (both to 30 cm); Mehlich-III extractable phosphorus and total carbon (both to 20 cm); total nitrogen (to 15 cm); Mehlich-III calcium (to 10 cm); Mehlich-III magnesium and lower bulk density (both to 5 cm). In contrast, litter manipulation did not affect ammonium, manganese, potassium or zinc, and soils deeper than 30 cm did not differ for any nutrient. Comparison with previous analyses in the experiment indicates that overall the effect of litter manipulation on nutrient concentrations and the depth to which the effects are significant are increasing with time. To allow for changes in bulk density in calculation of changes in carbon stocks, we standardized total carbon and nitrogen on the basis of a constant mineral mass. For 200 kg m-2 of mineral soil (approximately the upper 20 cm of the profile) about 0.5 kg C m-2 was 'missing' from the litter removal plots, with a similar amount accumulated in the litter addition plots. There was an additional 0.4 kg C m-2 extra in the litter standing crop of the litter addition plots compared to the control. This increase in carbon in surface soil and the litter standing crop can be interpreted as a potential partial mitigation of the effects of increasing CO2 concentrations in the atmosphere. [ABSTRACT FROM AUTHOR]

Increasing atmospheric CO2 and temperature may increase forest productivity, including litterfall, but the consequences for soil organic matter remain poorly understood. To address this, we measured soil carbon and nutrient concentrations at nine depths to 2 m after six years of continuous litter removal and litter addition in a semi-evergreen rain forest in Panama. Soils in litter addition plots, compared to litter removal plots, had higher pH and contained greater concentrations of KCl-extractable nitrate (both to 30 cm); Mehlich-III extractable phosphorus and total carbon (both to 20 cm); total nitrogen (to 15 cm); Mehlich-III calcium (to 10 cm); Mehlich-III magnesium and lower bulk density (both to 5 cm). In contrast, litter manipulation did not affect ammonium, manganese, potassium or zinc, and soils deeper than 30 cm did not differ for any nutrient. Comparison with previous analyses in the experiment indicates that overall the effect of litter manipulation on nutrient concentrations and the depth to which the effects are significant are increasing with time. To allow for changes in bulk density in calculation of changes in carbon stocks, we standardized total carbon and nitrogen on the basis of a constant mineral mass. For 200 kg m-2 of mineral soil (approximately the upper 20 cm of the profile) about 0.5 kg C m-2 was 'missing' from the litter removal plots, with a similar amount accumulated in the litter addition plots. There was an additional 0.4 kg C m-2 extra in the litter standing crop of the litter addition plots compared to the control. This increase in carbon in surface soil and the litter standing crop can be interpreted as a potential partial mitigation of the effects of increasing CO2 concentrations in the atmosphere. [ABSTRACT FROM AUTHOR]

Management of temperate forests has the potential to increase carbon sinks and mitigate climate change. However, those opportunities may be confounded by negative climate change impacts. We therefore need a better understanding of climate change alterations to temperate forest carbon dynamics before developing mitigation strategies. The purpose of this project was to investigate the interactions of species composition, fire, management and climate change on the Copper–Pine creek valley, a temperate coniferous forest with a wide range of growing conditions. To do so, we used the LANDIS-II modelling framework including the new Forest Carbon Succession extension to simulate forest ecosystems under four different productivity scenarios, with and without climate change effects, until 2050. Significantly, the new extension allowed us to calculate the Net Sector Productivity, a carbon accounting metric that integrates above and below-ground carbon dynamics, disturbances, and the eventual fate of forest products. The model output was validated against literature values. The results implied that the species optimum growing conditions relative to current and future conditions strongly influenced future carbon dynamics. Warmer growing conditions led to increased carbon sinks and storage in the colder and wetter ecoregions but not necessarily in the others. Climate change impacts varied among species and site conditions and this indicates that both of these components need to be taken into account in when considering climate change mitigation activities and adaptive management. The introduction of a new carbon indicator – Net Sector Productivity, promises to be useful in assessing management effectiveness and mitigation activities. [ABSTRACT FROM AUTHOR]

Estimations of tree annual biomass increments are used by a variety of studies related to forest productivity or carbon fluxes. Biomass increment estimations can be easily obtained from diameter surveys or historical diameter reconstructions based on tree rings' records. However, the biomass models rely on the assumption that wood density is constant. Converting volume increment into biomass also requires assumptions about the wood density. Wood density has been largely reported to vary both in time and between trees. In Norway spruce, wood density is known to increase with decreasing ring width. This could lead to underestimating the biomass or carbon deposition in bad years. The variations between trees of wood density have never been discussed but could also contribute to deviations. A modelling approach could attenuate these effects but will also generate errors. Here a model of wood density variations in Norway spruce, and an allometric model of volume growth were developed. We accounted for variations in wood density both between years and between trees, based on specific measurements. We compared the effects of neglecting each variation source on the estimations of annual biomass increment. We also assessed the errors of the biomass increment predictions at tree level, and of the annual productivity at plot level. Our results showed a partial compensation of the decrease in ring width in bad years by the increase in wood density. The underestimation of the biomass increment in those years reached 15%. The errors related to the use of an allometric model of volume growth were modest, around ±15%. The errors related to variations in wood density were much larger, the biggest component being the inter-tree variability. The errors in plot-level annual biomass productivity reached up to 40%, with a full account of all the error sources. [ABSTRACT FROM AUTHOR]

During the past several decades, observational data have shown a faster increase in hot temperature extremes than the change in mean temperature. Increasingly high extreme temperatures are expected to affect terrestrial ecosystem function. The ecological impact of hot extremes on vegetation production, however, remains uncertain across biomes in natural climatic conditions. In this study, we investigated the effects of hot temperature extremes on vegetation production by combining the MODIS enhanced vegetation index (EVI) data set and in situ climatic records during the period 2000 to 2009 from 12 long-term experimental sites across biomes and climate. Our results show that higher mean annual maximum temperatures (Tmax) greatly reduced grassland production, and yet enhanced forest production after removing the effect of precipitation. The relative decrease in vegetation production was 16 % for arid grassland and 7 % for mesic grassland, and the increase was 5 % for forest. We also observed a significantly positive relationship between interannual aboveground net primary production (ANPP) and Tmax for the forest biome (R² = 0.79, P < 0.001). This line of evidence suggests that hot temperature extremes lead to contrasting ecosystem-level responses of vegetation production between grassland and forest biomes. Given that many terrestrial ecosystem models use average daily temperature as input, predictions of ecosystem production should consider such contrasting responses to increasingly hot temperature extreme regimes associated with climate change. [ABSTRACT FROM AUTHOR]

Repeated long-term censuses have revealed largescale spatial patterns in Amazon basin forest structure and dynamism, with some forests in the west of the basin having up to a twice as high rate of aboveground biomass production and tree recruitment as forests in the east. Possible causes for this variation could be the climatic and edaphic gradients across the basin and/or the spatial distribution of tree species composition. To help understand causes of this variation a new individual-based model of tropical forest growth, designed to take full advantage of the forest census data available from the Amazonian Forest Inventory Network (RAINFOR), has been developed. The model allows for withinstand variations in tree size distribution and key functional traits and between-stand differences in climate and soil physical and chemical properties. It runs at the stand level with four functional traits - leaf dry mass per area (Ma), leaf nitrogen (NL) and phosphorus (PL) content and wood density (DW) varying from tree to tree - in a way that replicates the observed continua found within each stand. We first applied the model to validate canopy-level water fluxes at three eddy covariance flux measurement sites. For all three sites the canopy-level water fluxes were adequately simulated. We then applied the model at seven plots, where intensive measurements of carbon allocation are available. Treeby- tree multi-annual growth rates generally agreed well with observations for small trees, but with deviations identified for larger trees. At the stand level, simulations at 40 plots were used to explore the influence of climate and soil nutrient availability on the gross (ΠG) and net (ΠN) primary production rates as well as the carbon use efficiency (CU). Simulated ΠG, ΠN and CU were not associated with temperature. On the other hand, all three measures of stand level productivity were positively related to both mean annual precipitation and soil nutrient status. Sensitivity studies showed a clear importance of an accurate parameterisation of within-and between-stand trait variability on the fidelity of model predictions. For example, when functional tree diversity was not included in the model (i.e. with just a single plant functional type with mean basin-wide trait values) the predictive ability of the model was reduced. This was also the case when basin-wide (as opposed to site-specific) trait distributions were applied within each stand.We conclude that models of tropical forest carbon, energy and water cycling should strive to accurately represent observed variations in functionally important traits across the range of relevant scales. [ABSTRACT FROM AUTHOR]

In Amazonia, wetlands constitute about 30% of its entire basin, of which ancient fluvial terraces located in vast interfluvial regions cover a large portion. Although the increased number of permanent plots in the recent years has contributed to improved understanding of regional variation in forest dynamics across the Amazon Basin, the functioning of large lowland interfluvial wetlands remain poorly understood. Here we present the first field-based estimate for tree ages, wood biomass productivity and biomass turnover rates for eight 1 ha plots in wetland and non-flooded forests distributed along the BR-319 Highway along a distance of about 600 km crossing the Purus-Madeira rivers interfluvial region in central-southwestern Amazon Basin. We estimate stand age, wood biomass productivity and biomass turnover rates combining tree-ring data and an allometric equation based on diameter, tree height and wood density and relate these structural parameters to physical soil and hydrological restrictions. Wood biomass and productivity varied twofold among the plots, with wood biomass stocks ranging between 138-294Mg ha-1 and productivity varying between 3.4-6.6Mg ha-1 yr-1. Soil effective depth, topography, structure and mainly soil water saturation significantly affected stand age (64-103 yr) and forest dynamics in terms of annual biomass turnover rates (2.0-3.2%). On harsher soils characterized by a poor structure, low effective depth and high water saturation, biomass turnover rates were increased and forests stands were younger compared to well-drained sites. We suggest that soil constraints, especially soil water saturation, limit the development of the stand structure, resulting in forests with younger stand ages and higher biomass turnover rates compared to forests growing on well-drained soils. We do not find, however, any relation between physical soil restrictions or hydrology and wood biomass productivity, but there is a trend of increasing wood biomass productivity and phosphorus concentrations at the soil surface. Based on our results we establish hypotheses for different dynamical processes between forests growing on water-logged and well-drained soils and discuss how these results can be applied in the background of conservation as well as the potential development of forest management plans in this region, which will experience increased deforestation due to the construction of the BR-319 Highway crossing the interfluvial region of the Purus-Madeira rivers. [ABSTRACT FROM AUTHOR]