Abstract
Decaying wood plays an important role in forest biodiversity, nutrient cycling and carbon balance. Community structure of wood-inhabiting fungi changes with mass loss of wood, but the ...relationship between substrate quality and decomposers is poorly understood. This limits the extent to which these ecosystem services can be effectively managed. We studied the fungal community and physico-chemical quality (stage of decay, dimensions, density, moisture, C : N ratio, lignin and water or ethanol extractives) of 543 Norway spruce logs in five unmanaged boreal forest sites of southern Finland. Fungi were identified using denaturing gradient gel electrophoresis and sequencing of DNA extracted directly from wood samples. Macroscopic fruiting bodies were also recorded. Results showed a fungal community succession with decreasing wood density and C : N ratio, and increasing moisture and lignin content. Fungal diversity peaked in the most decayed substrates. Ascomycetes typically colonized recently fallen wood. Brown-rot fungi preferred the intermediate decay stages. White-rot fungi represented approximately one-fifth of sequenced species in all decay phases excluding the final phase, where ectomycorrhizal (ECM) fungi became dominant. Lignin content of logs with white-rot fungi was low, and ECM fungi were associated with substrates containing abundant nitrogen. Macroscopic fruiting bodies were observed for only a small number of species detected with molecular techniques.
We investigated the interaction between fungal communities of soil and dead wood substrates. For this, we applied molecular species identification and stable isotope tracking to both soil and ...decaying wood in an unmanaged boreal Norway spruce-dominated stand. Altogether, we recorded 1990 operational taxonomic units, out of which more than 600 were shared by both substrates and 589 were found to exclusively inhabit wood. On average the soil was more species-rich than the decaying wood, but the species richness in dead wood increased monotonically along the decay gradient, reaching the same species richness and community composition as soil in the late stages. Decaying logs at all decay stages locally influenced the fungal communities from soil, some fungal species occurring in soil only under decaying wood. Stable isotope analyses suggest that mycorrhizal species colonising dead wood in the late decay stages actively transfer nitrogen and carbon between soil and host plants. Most importantly, Piloderma sphaerosporum and Tylospora sp. mycorrhizal species were highly abundant in decayed wood. Soil- and wood-inhabiting fungal communities interact at all decay phases of wood that has important implications in fungal community dynamics and thus nutrient transportation.
We present three robust methods to accurately and automatically recognize tree species from terrestrial laser scanner data. The recognition is based on the use of quantitative structure tree models, ...which are hierarchical geometric primitive models accurately approximating the branching structure, geometry, and volume of the trees. Fifteen robust tree features are presented and tested with all different combinations for tree species classification. The classification methods presented are k-nearest neighbours, multinomial regression, and support vector machine based approaches. Three mainly single-species forest plots of Silver birch, Scots pine and Norway spruce, and two mixed-species forest plots located in Finland and a total number of trees over 1200 were used for demonstration. The results show that by using single-species forest plots for training and testing, it is possible to find a feature combination between 5 and 15 features, that results in an average classification accuracy above 93% for all the methods. For the preliminary mixed-species forest plot testing, accuracy was lower but the classification approach presented potential to generalize to more diverse cases. Moreover, the results show that the post-processing of terrestrial laser scanning data of multi-hectare forest, from tree extraction and modelling to species classification, can be done automatically.
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•TLS data dimensionality is increased by using quantitative structure models.•Tree species recognised with 15 features derived from model geometry and topology.•Classification accuracy tested with 5 forest plots, totaling over 1200 trees.•Tree extraction, model reconstruction and feature computation are fully automatic.•Three different classification methods are tested and compared.
Forecasting the impact of future global warming on biodiversity requires understanding how temperature limits the distribution of species. Here we rely on Liebig's Law of Minimum to estimate the ...effect of temperature on the maximum potential abundance that a species can attain at a certain location. We develop 95%‐quantile regressions to model the influence of effective temperature sum on the maximum potential abundance of 25 common understory plant species of Finland, along 868 nationwide plots sampled in 1985. Fifteen of these species showed a significant response to temperature sum that was consistent in temperature‐only models and in all‐predictors models, which also included cumulative precipitation, soil texture, soil fertility, tree species and stand maturity as predictors. For species with significant and consistent responses to temperature, we forecasted potential shifts in abundance for the period 2041–2070 under the IPCC A1B emission scenario using temperature‐only models. We predict major potential changes in abundance and average northward distribution shifts of 6–8 km yr−1. Our results emphasize inter‐specific differences in the impact of global warming on the understory layer of boreal forests. Species in all functional groups from dwarf shrubs, herbs and grasses to bryophytes and lichens showed significant responses to temperature, while temperature did not limit the abundance of 10 species. We discuss the interest of modelling the ‘maximum potential abundance’ to deal with the uncertainty in the predictions of realized abundances associated to the effect of environmental factors not accounted for and to dispersal limitations of species, among others. We believe this concept has a promising and unexplored potential to forecast the impact of specific drivers of global change under future scenarios.
Soil organic matter is the dominant pool of carbon (C) in terrestrial ecosystems. Recent advances in understanding of the mechanisms of C stabilization in the soil emphasize microbes as the main ...drivers. Special attention is placed on the accumulation of bacterial and fungal necromasses. This calls for development of fast and reliable methods to estimate microbial necromass in a various type of soils, including peat soils. Here we provide precise method to measure fungal and bacterial necromasses with high-pressure liquid chromatography-fluorescence detector (HPLC-FLD) and its comparison with gas chromatography method. Purity of the chromatographic peaks was confirmed with mass spectrometry. The HPLC-FLD method provides reliable results for mineral, organic and highly organic peat soils.
•we provide a method to study bacterial and fungal necromass using HPLC-FLD.•we confirmed purity of the chromatographic peaks with mass spectrometry.•method enables to measure microbial necromass from mineral and highly organic soils.
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•Soil organic carbon (SOC) stock changes of upland forest sites were studied in 1995–2016.•Mean annual SOC stock increase was 36 g m−2 yr−1 in the organic layer and mineral soil ...(0–40 cm).•An opposite trend was observed on harvested plots or plots where part of the standing tree biomass was lost due to disturbances.•Total forest vegetation biomass correlated positively and soil C/N ratio negatively with the annual SOC stock increase.•Top mineral soil layer played an important role in annual SOC stock increase.
This study’s aim was to evaluate the soil organic carbon (SOC) stock changes of the upland forest sites (ICP Forests, Level II network) in relation to factors affecting the stocks in the long run, such as soil and stand properties. The SOC stock changes were based on repeated soil surveys carried out in 1995, 2006 and 2016 on ten plots on managed boreal forest ecosystems, and they represent typical mature forest stands in Finland. In addition, two plots in old-growth forests and two with a short monitoring history were studied. SOC stocks (organic layer, mineral soil 0–40 cm depth) were significantly higher in the spruce stands than in pine stands due to the higher site fertility of the spruce stands, and the biomass in the litter layer was positively correlated with the SOC stocks. The mean annual increase in the SOC stock was 36 g m−2 yr−1 for ten of the plots, which were monitored for the period between 1995 and 2016. An opposite trend was observed on two of the monitored plots, which were on harvested stands or plots where part of the standing tree biomass was lost due to disturbances before 2016. Total forest vegetation biomass was positively correlated, and the soil C/N ratio negatively, with the SOC stock’s annual increase. The top mineral soil layer (0–20 cm) played an important role in the SOC stock’s average annual increase.
Information on the habitat requirements of wood-inhabiting fungi is needed to understand the factors that affect their diversity. We applied culture-free DNA extraction and 454-pyrosequencing to ...study the mycobiota of decaying Norway spruce (Picea abies) logs in five unmanaged boreal forests. Fungal habitat preferences in respect of wood density gradient were then estimated with generalized additive mixed models. Fungal diversity and wood density were inversely related, i.e., OTU richness generally increased as the log became increasingly decomposed. White-rot fungi (e.g., Phellinus nigrolimitatus) and members of Hyphodontia did not show a clear response to the wood-density gradient, whereas abundance of Phellinus viticola and brown-rot fungi (e.g., Fomitopsis pinicola, Antrodia serialis, Coniophora olivaceae) peaked during intermediate decay and mycorrhizal fungi (e.g., Piloderma, Tylospora, Russula) increased in the later stages. This information on fungal habitat requirements facilitates the development of management practices that preserve fungal diversity in managed forests.
•Fungi inhabiting dead spruce were identified by 454-sequencing.•Fungal richness increased with the loss of wood density.•Brown-rot fungi peaked during intermediate and mycorrhizal fungi in the later decay stages.•Modeled fungal habitat requirements can be applied in forest management planning.
Solar-induced chlorophyll fluorescence (SIF) has been shown to be a suitable remote sensing proxy of photosynthesis at multiple scales. However, the relationship between fluorescence and ...photosynthesis observed at the leaf level cannot be directly applied to the interpretation of retrieved SIF due to the impact of canopy structure. We carried out a SIF modelling study for a heterogeneous forest canopy considering the effect of canopy structure in the Discrete Anisotropic Radiative Transfer (DART) model. A 3D forest simulation scene consisting of realistic trees and understory, including multi-scale clumping at branch and canopy level, was constructed from terrestrial laser scanning data using the combined model TreeQSM and FaNNI for woody structure and leaf insertion, respectively. Next, using empirical data and a realistic range of leaf-level biochemical and physiological parameters, we conducted a local sensitivity analysis to demonstrate the potential of the approach for assessing the impact of structural, biochemical and physiological factors on top of canopy (TOC) SIF. The analysis gave insight into the factors that drive the intensity and spectral properties of TOC SIF in heterogeneous boreal forest canopies. DART simulated red TOC fluorescence was found to be less affected by biochemical factors such as chlorophyll and dry matter contents or the senescent factor than far-red fluorescence. In contrast, canopy structural factors such as overstory leaf area index (LAI), leaf angle distribution and fractional cover had a substantial and comparable impact across all SIF wavelengths, with the exception of understory LAI that affected predominantly far-red fluorescence. Finally, variations in the fluorescence quantum efficiency (Fqe) of photosystem II affected all TOC SIF wavelengths. Our results also revealed that not only canopy structural factors but also understory fluorescence should be considered in the interpretation of tower, airborne and satellite SIF datasets, especially when acquired in the (near-) nadir viewing direction and for forests with open canopies. We suggest that the modelling strategy introduced in this study, coupled with the increasing availability of TLS and other 3D data sources, can be applied to resolve the interplay between physiological, biochemical and structural factors affecting SIF across ecosystems and independently of canopy complexity, paving the way for future SIF-based 3D photosynthesis models.
•A 3D boreal forest scene generated from TLS data for simulation of TOC SIF•The potential of the scheme was demonstrated with a local sensitivity analysis.•Understory SIF can substantially contribute to TOC SIF in open-canopy forests.•TOC red SIF was largely independent of foliar Cab content compared to far-red SIF.
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•SOC:Clay ratio with a threshold of 1:13 was tested as a soil carbon loss indicator.•European 2009 LUCAS soil and national GHG inventory data were used for testing.•SOC content was ...affected by not only clay content but also by land cover and climate.•SOC:Clay ratio and GHG inventory estimates for soil C loss were not consistent.•A single indicator with one threshold value cannot serve for monitoring soil C loss.
Climate action plans under the Paris Climate Agreement and other national commitments aimed at improving soil-based ecosystem services require the operational monitoring of soil carbon (C). The European Union is aiming to enhance soil health, and as part of the proposed Soil Monitoring Law, the European Commission recommends the monitoring of the soil C loss indicator among other soil health indicators. In this study, we evaluate the feasibility of the proposed soil C loss indicator by assessing its performance using the EU-wide 2009 LUCAS soil survey data. The proposed indicator is the soil organic carbon (SOC) to clay ratio, with a threshold value of 1:13. The results are also compared with the C stock changes reported by countries to the climate convention (UNFCCC). Our results reveal that the variation in SOC and clay content at European scale exceeds that of the data used to develop the proposed indicator. We also found that the variation in the SOC content was influenced not only by clay content but also by climate and land-use reflecting C input levels. Therefore, the defined threshold is inadequate for detecting degraded soils if the SOC and clay content are beyond the conditions used to establish the criteria. Furthermore, major discrepancies were observed between the soil carbon stock changes reported by the national greenhouse gas (GHG) inventories and the proportions of degraded soils identified by using the soil C loss indicator. We conclude that employing a single indicator such as SOC:Clay ratio with one threshold value for all soils across various land covers, management practices, and climatic conditions, as defined by the European Commission for the Soil Monitoring Law, is inappropriate for monitoring soil C loss.
•Preliminary study of chlorophyll estimation using hyperspectral LiDAR (HSL).•HSL produces point clouds with spectral information for every point.•Estimation tested using empirical vegetation indices ...and conifer shoots.•HSL enables nondestructive 3D chlorophyll estimation within vegetation canopy.
We propose an empirical method for nondestructive estimation of chlorophyll in tree canopies. The first prototype of a full waveform hyperspectral LiDAR instrument has been developed by the Finnish Geodetic Institute (FGI). The instrument efficiently combines the benefits of passive and active remote sensing sensors. It is able to produce 3D point clouds with spectral information included for every point, which offers great potential in the field of environmental remote sensing.
The investigation was conducted by using chlorophyll sensitive vegetation indices applied to hyperspectral LiDAR data and testing their performance in chlorophyll estimation. The amount of chlorophyll in vegetation is an important indicator of photosynthetic capacity and stress, and thus important for monitoring of forest condition and carbon sequestration on Earth.
Performance of chlorophyll estimation was evaluated for 27 published vegetation indices applied to waveform LiDAR collected from ten Scots pine shoots. Reference data were collected by laboratory chlorophyll concentration analysis. The performance of the indices in chlorophyll estimation was determined by linear regression and leave-one-out cross-validation.
The chlorophyll estimates derived from hyperspectral LiDAR linearly correlate with the laboratory analyzed chlorophyll concentrations, and they are able to represent a range of chlorophyll concentrations in Scots pine shoots (R2=0.88, RMSE=0.10mg/g). Furthermore, they are insensitive to measurement scale as nearly the same values of vegetation indices were measured in natural setting while scanning the whole canopy and from clipped shoots re-measured with hyperspectral LiDAR in laboratory. The results indicate that the hyperspectral LiDAR instrument has the potential to estimate vegetation biochemical parameters such as the chlorophyll concentration. The instrument holds much potential in various environmental applications and provides a significant improvement over single wavelength LiDAR or passive optical systems for environmental remote sensing.
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