Temperate Forest Sites Research Articles

Canopy photosynthetic capacity drives contrasting age dynamics of resource use efficiencies between mature temperate evergreen and deciduous forests.

Forest resource use efficiencies (RUEs) can vary with tree age, but the nature of these trends and their underlying mechanisms are not well understood. Understanding the age dynamics of forest RUEs and their drivers is vital for assessing the trade-offs between forest functions and resource consumption, making rational management policy, and projecting ecosystem carbon dynamics. Here we used the FLUXNET2015 and AmeriFlux datasets and published literature to explore the age-dependent variability of forest light use efficiency (LUE) and inherent water use efficiency as well as their main regulatory variables in temperate regions. Our results showed that evergreen forest RUEs initially increased before reaching the mature stage (i.e., around 90years old), and then gradually declined; in contrast, RUEs continuously increased with age for mature deciduous forests. Changing canopy photosynthetic capacity (Amax) was the primary cause of age-related changes in RUEs across temperate forest sites. More importantly, soil nitrogen (N) increased in mature deciduous forests through time but decreased in older evergreen forests. The age-dependent changes in soil N were closely linked with the age dynamics of Amax for mature temperate forests. Additionally, soil nutrient conditions played a greater role in deciduous forest RUEs than evergreen forest RUEs. This study highlights the importance of stand age and forest type on temperate forest RUEs over the long term.

Influence of Vertical Heterogeneities in the Canopy Microenvironment on Interannual Variability of Carbon Uptake in Temperate Deciduous Forests

AbstractVegetation structure and function are key design choices in terrestrial models that affect the relationship between carbon uptake and environmental drivers. Here, we investigate how representing canopy vertical structure in a terrestrial biosphere model—that is, micrometeorological, leaf area, and leaf water profiles—influences carbon uptake at five U.S. temperate deciduous forest sites in July. Specifically, we test whether the interannual variability (IAV) of gross primary productivity (GPP) responds differently to four abiotic environmental drivers—air temperature, relative humidity, incoming shortwave radiation, and soil moisture—using either a Community Land Model multilayer canopy model (CLM‐ml) or a big‐leaf model (CLM4.5/CLM5). We conclude that vertical leaf area and microclimatic profiles (temperature, humidity, and wind) do not impact GPP IAV compared to a single‐layer model when plant hydraulics is excluded. However, with a mechanistic representation of plant hydraulics there is vertically varying water stress in CLM‐ml, and the sensitivity of carbon uptake to particular climate variables changes with height, resulting in dampened canopy‐scale GPP IAV relative to CLM4.5. Dampening is due to both a reduced dependence on soil moisture and opposing climatic forcing on different leaf layers. Such dampening is not evident in the single‐layer representation of plant hydraulic water stress implemented in the recently released CLM5. Overall, both model representations of the canopy fail to accurately simulate observed GPP IAV and this may be related by their inability to capture the upper range of observed hourly GPP and diffuse light‐GPP relationships that cannot be resolved by canopy structure alone.

Soil and root nutrient chemistry structure root-associated fungal assemblages in temperate forests.

Root-associated fungi (RAF) link nutrient fluxes between soil and roots and thus play important roles in ecosystem functioning. To enhance our understanding of the factors that control RAF, we fitted statistical models to explain variation in RAF community structure using data from 150 temperate forest sites covering a broad range of environmental conditions and chemical root traits. We found that variation in RAF communities was related to both root traits (e.g., cations, carbohydrates, NO3 - ) and soil properties (pH, cations, moisture, C/N). The identified drivers were the combined result of distinct response patterns of fungal taxa (determined at the rank of orders) to biotic and abiotic factors. Our results support that RAF community variation is related to evolutionary adaptedness of fungal lineages and consequently, drivers of RAF communities are context-dependent.

Modeling the Carbon Cost of Plant Nitrogen and Phosphorus Uptake Across Temperate and Tropical Forests

Nutrient limitation is a key source of uncertainty in predicting terrestrial carbon (C) uptake. Models have begun to include nitrogen (N) dynamics; however, phosphorus (P), which can also limit or co-limit net primary production (NPP) in many ecosystems, is currently absent in most models. To meet this challenge, we integrated P dynamics into a cutting-edge plant nutrient uptake model (Fixation and Uptake of Nitrogen: FUN 2.0) that mechanistically tracks the C cost of N uptake from soil based on the cost of allocating C to leaf resorption and root/root-microbial uptake, and the availability of N in soil. We incorporated the direct C cost of P uptake, as well as a N cost of synthesizing phosphatase enzymes to extract P from soil, into a new model formulation (Fixation and Uptake of Nutrients: FUN 3.0). We confronted and validated FUN 3.0 against empirical estimates of canopy, root, and soil P pools from 45 temperate forest plots in Indiana, USA and 18 tropical dry forest plots located in Guanacaste, Costa Rica that vary in P availability and distribution of arbuscular mycorrhizal- (AM) and ectomycorrhizal- (ECM) associated trees. FUN 3.0 was able to accurately predict N and P retranslocation across the temperate and tropical forest sites (slopes of 0.95 and 0.92 for P and N retranslocation, respectively). Carbon costs for acquiring P were three times higher in tropical forest sites compared to temperate forest sites, driving overall higher C costs in tropical sites. In addition, the N costs for acquiring P in tropical forest sites lead to a substantial increase in N fixation to support phosphatase enzyme production. Sensitivity analyses showed that tropical sites appeared to be severely P limited, while the temperate sites showed evidence for co-limitation by N and P. Collectively, FUN 3.0 provides a novel framework for predicting coupled N and P limitation that earth system models can leverage to enhance predictions of ecosystem response to global change.

Above- and Below-ground Cascading Effects of Wild Ungulates in Temperate Forests

Ungulates have become abundant in many temperate forests, shifting tree species composition by browsing and altering soil physical conditions by trampling. Whether these effects cascade down to other trophic levels and ecosystem processes is poorly understood. Here, we assess the paths through which ungulates have cascading effects on other trophic levels (regeneration, litter, invertebrates, rodents and organic matter decomposition). We compared ungulate effects by comparing 15 response variables related to different trophic levels between paired fenced and unfenced plots in twelve temperate forest sites across the Netherlands, and used pathway analysis model to identify the (in)direct pathways through which ungulates have influenced these variables. We found that plots with ungulates (that is, unfenced) compared to plots without (that is, fenced) had lower litter depth, sapling diversity, sapling density, rodent activity, macro-invertebrate biomass, decomposition rate of tea bags, pine and birch litter and higher soil compaction. These findings were used in a path analysis to establish potential causal relationships, which showed that ungulate presence: decreased sapling density, which indirectly decreased rodent activity; decreased litter depth, which indirectly reduced invertebrate diversity; increased soil compaction, which also decreased invertebrate diversity. Soil pH decreased invertebrate biomass, which also increased nitrogen mineralization. Yet, we did not find cascading effects of ungulates on decomposition rates. Importantly, an increase in ungulate abundance strengthens the cascading effects in this system. Our results suggest that ungulates can trigger cascading effects on lower trophic levels, yet decomposition and mineralization rates are resilient to ungulate browsing and trampling. Therefore, temperate forests conservation could benefit by limiting ungulate abundance.

Nitrous oxide emissions in proportion to nitrification in moist temperate forests

Chronic elevated nitrogen deposition has increased nitrogen availability in many forest ecosystems globally, and this phenomenon has been suggested to increase soil nitrification. Although it is believed that increased nitrogen availability would also increase nitrous oxide (N2O) emissions from forest ecosystems, its impact on N2O flux is poorly known. In this study, 3-years monitoring of N2O emissions was performed in a forested watershed receiving elevated nitrogen deposition and located in the suburbs of Tokyo, Japan. In addition, a comparative field survey was carried out in nine temperate forest sites with varying nitrogen availabilities. In the intensively studied forest site showing typical nitrogen saturation, the average annual N2O emissions from the whole watershed were estimated to be 0.88 kg N ha−1 year−1, comparable to the highest observed levels for temperate forests except for some very high emission sites in Europe. Although no correlation was found for humid spots with WFPS > 60%, a clear positive correlation was noted between N2O flux and net nitrification rate in situ for plots with water-filled pore space (WFPS) < 60%. The N2O flux varied across nine forest sites almost in proportional to the stream water NO3− concentration in the watershed that ranged from 0.14 to 1.64 mg N/L. We conclude that N2O emissions are related to nitrification in moist temperate forest, which may be associated with the magnitude of nitrogen saturation.

MODIS-Derived Estimation of Soil Respiration within Five Cold Temperate Coniferous Forest Sites in the Eastern Loess Plateau, China

Soil respiration (Rs) is seldom analyzed using remotely sensed data because satellite technology has difficulty monitoring various respiratory processes in the soil. We investigated the potential of remote sensing data products to estimate Rs, including land surface temperature (LST) and spectral vegetation indices from the Moderate Resolution Imaging Spectroradiometer (MODIS), using a nine-year (2007–2015) field measurement dataset of Rs and soil temperature (Ts) at five forest sites at the eastern Loess Plateau, China. The results indicate that soil temperature is the primary factor influencing the seasonal variation of Rs at the five sites. The accuracy of the model based on the observed data is not significantly different from the model based on MODIS-derived nighttime LST values. There was a significant difference with the model based on MODIS-derived daytime LST values. Therefore, nighttime LST was the optimum LST for estimation of Rs. The normalized difference vegetation index (NDVI) consistently exhibited a stronger correlation with Rs when compared to the green edge chlorophyll index and enhanced vegetation index. Further analysis showed that adding the NDVI into the model considering only Ts or nighttime LST could significantly improve the simulation accuracy of Rs. The models depending on nighttime LST and NDVI showed comparable accuracy with the models based on the in situ Ts and NDVI. These results suggest that models based entirely on remote sensing data from MODIS have the potential to estimate Rs at the cold temperate coniferous forest sites. The performance of the model in other vegetation types or regions has also been proved. Our conclusions further confirmed that it is feasible for large-scale estimates of Rs by means of MODIS data in temperate coniferous forest ecosystems.

Sensitivity of Bistatic TanDEM-X Data to Stand Structural Parameters in Temperate Forests

Synthetic aperture radar (SAR) satellite data provide a valuable means for the large-scale and long-term monitoring of structural components of forest stands. The potential of TanDEM-X interferometric SAR (InSAR) for the assessment of forest structural properties has been widely verified. However, present studies are mostly restricted to homogeneous forests and do not account for stratification in assessing model performance. A systematic sensitivity analysis of the TanDEM-X SAR signal to forest structural parameters was carried out with emphasis on different strata of forest stands (location of the study site, forest type, and development stage). Forest structure was parameterized by forest height metrics and stem volume. Results show that X-band volume coherence is highly sensitive to the forest canopy. Volume scattering within the canopy is dependent on the vertical heterogeneity of the forest stand. In general, TanDEM-X coherence is more sensitive to forest vertical structure compared to backscatter. The relations between TanDEM-X volume coherence and forest structural properties were significant at the level of a single test site as well as across sites in temperate forests in Germany. Forest type does not affect the overall relationship between the SAR signal and the forests’ vertical structure. The prediction of forest structural parameters based on the outcome of the sensitivity analysis yielded model accuracies between 15% (relative root mean square error) for Lorey’s height and 32% for stem volume. The global database of single-polarized bistatic TanDEM-X data provides an important source for mapping structural parameters in temperate forests at large scale, irrespective of forest type.

Airborne Lidar Sampling Strategies to Enhance Forest Aboveground Biomass Estimation from Landsat Imagery

Accurately estimating aboveground biomass (AGB) is important in many applications, including monitoring carbon stocks, investigating deforestation and forest degradation, and designing sustainable forest management strategies. Although lidar provides critical three-dimensional forest structure information for estimating AGB, acquiring comprehensive lidar coverage is often cost prohibitive. This research focused on developing a lidar sampling framework to support AGB estimation from Landsat images. Two sampling strategies, systematic and classification-based, were tested and compared. The proposed strategies were implemented over a temperate forest study site in northern New York State and the processes were then validated at a similar site located in central New York State. Our results demonstrated that while the inclusion of lidar data using systematic or classification-based sampling supports AGB estimation, the systematic sampling selection method was highly dependent on site conditions and had higher accuracy variability. Of the 12 systematic sampling plans, R2 values ranged from 0.14 to 0.41 and plot root mean square error (RMSE) ranged from 84.2 to 93.9 Mg ha−1. The classification-based sampling outperformed 75% of the systematic sampling strategies at the primary site with R2 of 0.26 and RMSE of 70.1 Mg ha−1. The classification-based lidar sampling strategy was relatively easy to apply and was readily transferable to a new study site. Adopting this method at the validation site, the classification-based sampling also worked effectively, with an R2 of 0.40 and an RMSE of 108.2 Mg ha−1 compared to the full lidar coverage model with an R2 of 0.58 and an RMSE of 96.0 Mg ha−1. This study evaluated different lidar sample selection methods to identify an efficient and effective approach to reduce the volume and cost of lidar acquisitions. The forest type classification-based sampling method described in this study could facilitate cost-effective lidar data collection in future studies.

Decadal fates and impacts of nitrogen additions on temperate forest carbon storage: a data–model comparison

Abstract. To accurately capture the impacts of nitrogen (N) on the land carbon (C) sink in Earth system models, model responses to both N limitation and ecosystem N additions (e.g., from atmospheric N deposition and fertilizer) need to be evaluated. The response of the land C sink to N additions depends on the fate of these additions: that is, how much of the added N is lost from the ecosystem through N loss pathways or recovered and used to increase C storage in plants and soils. Here, we evaluate the C–N dynamics of the latest version of a global land model, the Community Land Model version 5 (CLM5), and how they vary when ecosystems have large N inputs and losses (i.e., an open N cycle) or small N inputs and losses (i.e., a closed N cycle). This comparison allows us to identify potential improvements to CLM5 that would apply to simulated N cycles along the open-to-closed spectrum. We also compare the short- (&lt; 3 years) and longer-term (5–17 years) N fates in CLM5 against observations from 13 long-term 15N tracer addition experiments at eight temperate forest sites. Simulations using both open and closed N cycles overestimated plant N recovery following N additions. In particular, the model configuration with a closed N cycle simulated that plants acquired more than twice the amount of added N recovered in 15N tracer studies on short timescales (CLM5: 46±12 %; observations: 18±12 %; mean across sites ±1 standard deviation) and almost twice as much on longer timescales (CLM5: 23±6 %; observations: 13±5 %). Soil N recoveries in simulations with closed N cycles were closer to observations in the short term (CLM5: 40±10 %; observations: 54±22 %) but smaller than observations in the long term (CLM5: 59±15 %; observations: 69±18 %). Simulations with open N cycles estimated similar patterns in plant and soil N recovery, except that soil N recovery was also smaller than observations in the short term. In both open and closed sets of simulations, soil N recoveries in CLM5 occurred from the cycling of N through plants rather than through direct immobilization in the soil, as is often indicated by tracer studies. Although CLM5 greatly overestimated plant N recovery, the simulated increase in C stocks to recovered N was not much larger than estimated by observations, largely because the model's assumed C:N ratio for wood was nearly half that suggested by measurements at the field sites. Overall, results suggest that simulating accurate ecosystem responses to changes in N additions requires increasing soil competition for N relative to plants and examining model assumptions of C:N stoichiometry, which should also improve model estimates of other terrestrial C–N processes and interactions.

Spatial species diversity in temperate species-rich forest ecosystems: Revisiting and extending the concept of spatial species mingling

• Spatial species mingling was extended to better describe species-rich forest ecosystems. • We demonstrated the value of the new species segregation function through cluster analysis. • Evidence of improvement was obtained from applying the innovative spatial reconstruction method. • The new characteristic is robust and effective in monitoring species-rich plant communities. Species rich woodland communities play an important role in ecosystem functioning at local, regional and global scale. With ongoing climate change and an ever-increasing human world population we certainly cannot take high species diversity for granted. In fact species diversity is a precious and threatened commodity that requires monitoring and conservation. China has a wealth of natural woodlands with high species diversity that stretch over several climate zones and even in the temperate zone tree diversity is considerable in this country. For monitoring species diversity it is crucial to rely on meaningful summary characteristics that offer sufficient information to make correct decisions in conservation. We analysed large, fully mapped plots from ten species-rich temperate forest sites with the new species segregation function as a significantly more meaningful extension of the traditional spatial species mingling index. The new characteristic is a function of distance and we defined a number of auxiliary measures describing its shape for a more effective analysis of spatial species diversity. We could show that these auxiliary characteristics helped to classify species-rich forests as part of a cluster analysis, which supports the view that the species segregation function provides high quality information. We also successfully applied non-parametric modelling through spatial reconstruction for testing the contribution of the species segregation function to a synthesis of observed spatial species diversity patterns. The results demonstrated that the new characteristic described the complex diversity patterns well and has the potential of being a robust and effective characteristic in monitoring species-rich woodland communities.

Assessment of multi-wavelength SAR and multispectral instrument data for forest aboveground biomass mapping using random forest kriging

Aboveground biomass (AGB) plays an important role in carbon cycle. Assessment of AGB presents a challenge in forest management. Reported studies have explored the potential of synthetic aperture radar (SAR) and multispectral instrument (MSI) data using random forest (RF) approach in AGB mapping. However, how AGB prediction would be affected by using data from different sources based on random forest kriging (RFK), which integrates RF and estimates residuals by ordinary kriging (OK), deserves further exploration. This study reported an assessment of multisensor data from Advanced Land Observing Satellite 2 (ALOS-2) L band and Sentinel-1C band SAR, Shuttle Radar Topography Mission (SRTM) digital elevation model (DEM), and Sentinel-2 MSI for forest AGB mapping using RFK. The effectiveness of 97 predictor variables derived from multisensor data was evaluated for AGB prediction in a temperate continental forest site in northeastern China. The assessment was tested by field-measured data from 1167 forest plots in 2017. The results showed that the RFK model achieved the accuracy with mean error, mean absolute error, root mean square error and correlation coefficient in –0.11, 19.37, 28.15 Mg ha−1 and 0.98, respectively. The study revealed that backscatters and texture features from ALOS-2 L band SAR and vegetation indices from Sentinel-2 MSI were primary contributors for explaining the observed variability of AGB. Topographic indices from SRTM DEM were more important than C band SAR backscatters and texture features. The accuracy improvement on forest AGB mapping by RFK over RF was more distinguished in models using a single sensor than those using multisensors.

Evaluating the E3SM land model version 0 (ELMv0) at a temperate forest site using flux and soil water measurements

Abstract. Accurate simulations of soil respiration and carbon dioxide (CO2) fluxes are critical to project global biogeochemical cycles and the magnitude of carbon–climate feedbacks in Earth system models (ESMs). Currently, soil respiration is not represented well in ESMs, and few studies have attempted to address this deficiency. In this study, we evaluated the simulation of soil respiration in the Energy Exascale Earth System Model (E3SM) land model version 0 (ELMv0) using long-term observations from the Missouri Ozark AmeriFlux (MOFLUX) forest site in the central US. Simulations using the default model parameters underestimated soil water potential (SWP) during peak growing seasons and overestimated SWP during non-growing seasons and consequently underestimated annual soil respiration and gross primary production (GPP). A site-specific soil water retention curve greatly improved model simulations of SWP, GPP, and soil respiration. However, the model continued to underestimate the seasonal and interannual variabilities and the impact of the extreme drought in 2012. Potential reasons may include inadequate representations of vegetation mortality, the soil moisture function, and the dynamics of microbial organisms and soil macroinvertebrates. Our results indicate that the simulations of mean annual GPP and soil respiration can be significantly improved by better model representations of the soil water retention curve.

Long-Term Nitrogen Addition Does Not Increase Soil Carbon Storage or Cycling Across Eight Temperate Forest and Grassland Sites on a Sandy Outwash Plain

Experimental nitrogen (N) deposition generally inhibits decomposition and promotes carbon (C) accumulation in soils, but with substantial variation among studies. Differences in ecosystem properties could help explain this variability: N could have distinct effects on decomposition and soil C due to differences in vegetation characteristics (that is, root C inputs and chemistry) that influence microbial biomass or soil properties like pH that can affect organic matter stabilization. We used a 12-year N addition experiment to determine effects of sustained N addition on soil C pool sizes and cycling across different grassland, conifer and deciduous forest sites in Minnesota, USA, while controlling for soil type and climate. We conducted a year-long soil incubation, and fit one- and two-pool decay models to respiration data to identify C pool sizes and decay rates. Contrary to previous studies, we found no consistent effects of N on soil C across sites: soil C stocks, microbial respiration, soil C decay rates and pool sizes all showed no general response to N in these sandy soils. Nevertheless, microbial biomass, microbial respiration, and the root biomass C pool responses to N addition were highly correlated, suggesting that soil C responses were ultimately driven by fine root biomass C responses to N addition, which in turn affected microbial biomass. However, the inconsistent directional responses to N among sites with similar vegetation cover highlight that N addition effects can be site-specific and raise caution for broad extrapolation of results from individual systems to global models.

Variation in compositional and structural components of community assemblage and its determinants

AbstractQuestionsWhat are the ecological processes that determine the spatial distribution of species and species diversity? Partitioning beta diversity can provide fundamental insights into the processes that determine the spatial variation of species assemblages. However, studying beta diversity is conventionally based only on species composition data, ignoring the structural component of communities.Study siteTemperate mixed broadleaf–conifer forest in Jiaohe, Jilin Province, northeastern China.MethodsWe characterized the variation of community assemblages in terms of species composition, size structure, or considering both components. We then employed environmental and spatial variables as explanatory factors to partition the variation in both compositional and structural components of community assemblage and assess the relative contributions of the niche and neutral processes to community assembly.ResultsThe values of overall beta diversity (BD statistics) and the relative contribution of individual sampling units to beta diversity (LCBD indices) depended on whether the species composition, size structure, or both together had been taken into account. The value of compositional–structural beta diversity was the largest, followed by traditional compositional beta diversity; the smallest was the structural beta diversity. The sites with high contributions to beta diversity (LCBD values) varied among structural and compositional components. The explanatory power of the environmental variables and the spatial variables also varied widely with different components of a community. The combination of environmental and spatial variables explained the highest proportion of variation (43.8%) in the compositional component and explained the lowest proportion of variation (25.4%) in the structural component of community assemblage.ConclusionBoth deterministic and stochastic processes are acting to determine community assemblages in terms of species composition and structure in our temperate forest site. Our study highlights the importance of considering the structural component of forest communities, in addition to compositional data, when studying beta diversity.

Evidence of secondary sulfate production in the mineral soil of a temperate forested catchment in southern Québec, Canada

The analysis of sulfate stable isotope ratios (δ18O-SO4 and δ34S-SO4) in different hydrological compartments of forested catchments has revealed the major role of the humus layer in recycling atmospherically derived sulfur (S). The contribution of the mineral soil to S recycling is still uncertain and may vary among forest types. Here, seasonal variations in SO4 concentration, δ18O-SO4 and δ34S-SO4 were investigated over a period of two and a half years in precipitation and at various depths in the soil solutions in a temperate forest catchment dominated by sugar maple in southern Québec, Canada. δ18O-SO4 declined from precipitation (11.8‰) to the humus solution (4.8‰) and to the soil solution beneath the upper B-horizon (1.2‰). No decline was observed below the upper B-horizon. This decline from precipitation to the humus layer reflected a production of secondary sulfate through chemical oxidation of SO2 in the canopy, while the decline in the soil resulted from microbial mineralization of organic S. In contrast with findings at other boreal and temperate forest sites, lower δ18O-SO4 in the upper mineral soil than in the humus layer was indicative of microbial transformations of S not only in the humus layer but also deeper in the upper part of the mineral soil. Significant seasonal variations were found for δ18O-SO4 in precipitation and in soil solutions beneath the humus and the top mineral horizon, reflecting the influence of both hydrological and microbiological factors. Higher δ18O-SO4 in the soil solution in fall than in spring and summer resulted from the release of primary sulfate from snow cover in early spring, which was subsequently recycled by soil microorganisms during the growth season, resulting in a higher proportion of secondary sulfate in fall than in spring and summer.

Concord and discord among Northern Hemisphere paleotemperature reconstructions from tree rings

We review the current generation of large-scale, millennial-length temperature reconstructions derived from tree rings and highlight areas of agreement and disagreement among these state-of-the-art paleotemperature estimates. Although thousands of tree ring-width chronologies are now available from temperate and boreal forest sites across the Northern Hemisphere, only a small fraction of those records are suited as proxies for surface temperature. Maximum latewood density is clearly a superior temperature proxy but is less available, with few densitometric records that are both long and up-to-date. Compared to previous efforts, the newest generation of tree-ring reconstructions correlate more strongly against hemispheric summer temperatures and show better performance in tracking decadal/multi-decadal variability and year-to-year fluctuations. They also fit the observed memory structure of instrumental temperatures more closely than their predecessors. These new estimates still show signs of the so-called ‘divergence problem’ (the apparent loss of temperature sensitivity under recent warming), but do not extend after 2004 and cannot be used to evaluate the impact of the past decade's warming on northern temperature-limited forests. We caution against averaging together the latest hemispheric-scale reconstructions because they have each been constructed to suit different purposes and share much of the same underlying tree-ring data, especially prior to CE 1500. Past temperatures are recorded more clearly in maximum latewood density than total ring-width, so we recommend the Northern Hemisphere densitometry network be modernized through a new round of field collections and observations.

Forest Structure Characterization From SAR Tomography at L-Band

Synthetic aperture radar (SAR) remote sensing configurations are able to provide continuous measurements on global scales sensitive to the vertical structure of forests with a high spatial and temporal resolution. Furthermore, the development of tomographic SAR techniques allows the reconstruction of the three-dimensional (3-D) radar reflectivity opening the door for 3-D forest monitoring. However, the link between 3-D radar reflectivity and 3-D forest structure is not yet established. In this sense, this paper introduced a framework that allows a qualitative and quantitative interpretation of physical forest structure from tomographic SAR data at L-band. For this, forest structure is parameterized into a set of a horizontal and a vertical structure index. From inventory data, both indices can be derived from the spatial distribution and the dimensions of the trees. Similarly, two structure indices are derived from the 3-D spatial distribution of the local maxima of the reconstructed 3-D radar reflectivity profiles at L-band. The proposed methodology is tested by means of experimental tomographic L-band data acquired over the temperate forest site of Traunstein in Germany. The obtained horizontal and vertical structure indices are validated against the corresponding estimates obtained from inventory measurements and against the same indices derived from the vertical profiles of airborne Lidar data. The high correlation between the forest structure indices obtained from these three different data sources (expressed by correlation coefficients between 0.75 and 0.87) indicates the potential of the proposed framework.

Abiotic and biotic drivers of species diversity in understory layers of cold temperate coniferous forests in North China

Understory plants are important components of forest ecosystems and play a crucial role in regulating community structures, function realization, and community succession. However, little is known about how abiotic and biotic drivers affect the diversity of understory species in cold temperate coniferous forests in the semiarid climate region of North China. We hypothesized that (1) topographic factors are important environmental factors affecting the distribution and variation of understory strata, and (2) different understory strata respond differently to environmental factors; shrubs may be significantly affected by the overstory stratum, and herbs may be more affected by surface soil conditions. To test these hypotheses, we used the boosted regression tree method to analyze abiotic and biotic environmental factors that influence understory species diversity, using data from 280 subplots across 56 sites in cold temperate coniferous forests of North China. Elevation and slope aspect were the dominant and indirect abiotic drivers affecting understory species diversity, and individual tree size inequality (DBH variation) was the dominant biotic driver of understory species diversity; soil water content was the main edaphic factors affecting herb layers. Elevation, slope aspect, and DBH variation accounted for 36.4, 14.5, and 12.1%, respectively, of shrub stratum diversity. Shrub diversity decreased with elevation within the range of altitude of this study, but increased with DBH variation; shrub diversity was highest on north-oriented slopes. The strongest factor affecting herb stratum species diversity was slope aspect, accounting for 25.9% of the diversity, followed by elevation (15.7%), slope (12.2%), and soil water content (10.3%). The highest herb diversity was found on southeast-oriented slopes and the lowest on northeast-oriented slopes; herb diversity decreased with elevation and soil water content, but increased with slope. The results of the study provide a reference for scientific management and biodiversity protection in cold temperate coniferous forests of North China.

Precipitation is not limiting for xylem formation dynamics and vessel development in European beech from two temperate forest sites.

We investigated the dynamics of xylem differentiation processes and vessel characteristics in Fagus sylvatica L. to evaluate the plasticity of xylem structures under different environmental conditions. In 2008-10, analyses were performed on microcores collected weekly from two temperate sites: Menina planina (1200 m above sea level (a.s.l.)) and Panska reka (400 m a.s.l.). The duration between the onset and end of major cell differentiation steps and vessel characteristics (i.e., density, VD; mean diameter, MVD; mean area, MVA; and theoretic conductivity area, TCA) were analysed in the first and last quarters of the xylem rings, also in respect of local weather conditions (precipitation, temperature). Although the onset, duration and end of xylem formation phases differed between the two sites, the time spans between the successive wood formation phases were similar. Significant differences in MVD, MVA and TCA values were found between the first and last quarters of xylem increment, regardless of the site and year. Vessel density, on the other hand, depended on xylem-ring width and differed significantly between the sites, being about 30% higher at the high elevation site, in beech trees with 54% narrower xylem rings. Vessel density in the first quarter of the xylem ring showed a positive correlation with the onset of cell expansion, whereas a negative correlation of VD with the cessation of cell production was found in the last quarter of xylem increment. This may be explained by year-to-year differences in the timing of cambial reactivation and leaf development, which effect hormonal regulation of radial growth. No significant linkage between intra-annual weather conditions and conduit characteristics was found. It can thus be presumed that precipitation is not a limiting factor for xylem growth and cell differentiation in beech at the two temperate study sites and sites across Europe with similar weather conditions.