Estimating fine-root production by tree species and understorey functional groups in two contrasting peatland forests

Background and aims Estimation of root-mediated carbon fluxes in forested peatlands is needed for understanding ecosystem functioning and supporting greenhouse gas inventories. Here, we aim to determine the optimal methodology for utilizing ingrowth cores in estimating annual fine-root production (FRP) and its vertical distribution in trees, shrubs and herbs. Methods We used 3-year data obtained with modified ingrowth core method and tested two calculation methods: 'ingrowth-dividing' and `ingrowth-subtracting'. Results The ingrowth-dividing method combined with a 2-year incubation of ingrowth cores can be used for the 'best estimate' of FRP. The FRP in the nutrient-rich fen forest (561 g m(-2)) was more than twice that in the nutrient-poor bog forest (244 g m(-2)). Most FRP occurred in the top 20-cm layer (76-82 %). Tree FRP accounted for 71 % of total FRP in the bog and 94 % in the fen forests, respectively, following the aboveground vegetation patterns; however, in fen forest the proportions of spruce and birch in FRP were higher than their proportions in stand basal area. Conclusions Our methodology may be used to study peatland FRP patterns more widely and will reduce the volume of labour-intensive work, but will benefit from verification with other methods, as is the case in all in situ FRP studies.Peer reviewe

Drivers of treeline shift in different European mountains

A growing body of evidence suggests that processes of upward treeline expansion and shifts in vegetation zones may occur in response to climate change. However, such shifts can be limited by a variety of non-climatic factors, such as nutrient availability, soil conditions, landscape fragmentation and some species-specific traits. Many changes in species distributions have been observed, although no evidence of complete community replacement has been registered yet. Climatic signals are often confounded with the effects of human activity, for example, forest encroachment at the treeline owing to the coupled effect of climate change and highland pasture abandonment. Data on the treeline ecotone, barriers to the expected treeline or dominant tree species shifts due to climate and land use change, and their possible impacts on biodiversity in 11 mountain areas of interest, from Italy to Norway and from Spain to Bulgaria, are reported. We investigated the role of environmental conditions on treeline ecotone features with a focus on treeline shift. The results showed that treeline altitude and the altitudinal width of the treeline ecotone, as well as the significance of climatic and soil parameters as barriers against tree species shift, significantly decreased with increasing latitude. However, the largest part of the commonly observed variability in mountain vegetation near the treeline in Europe seems to be caused by geomorphological, geological, pedological and microclimatic variability in combination with different land use history and present socio-economic relation Vegetation zone shift · Climate change · Climate models · Treeline ecotone · European mountains · Ecosystem service

Applicability of the PROSPECT model for Norway spruce needles

The potential applicability of the leaf radiative transfer model PROSPECT (version 3.01) was tested for Norway spruce (Picea abies (L.) Karst.) needles collected from stress resistant and resilient trees. Direct comparison of the measured and simulated leaf optical properties between 450–1000 nm revealed the requirement to recalibrate the PROSPECT chlorophyll and dry matter specific absorption coefficients kab(λ) and km(λ). The subsequent validation of the modified PROSPECT (version 3.01.S) showed close agreement with the spectral measurements of all three needle age-classes tested; the root mean square error (RMSE) of all reflectance (r) values within the interval of 450– 1000nm was equal to 1.74%, for transmittance (τ) it was 1.53% and for absorbance (α) it was 2.91%. The total chlorophyll concentration, dry matter content, and leaf water content were simultaneously retrieved by a constrained inversion of the original PROSPECT 3.01 and the adjusted PROSPECT 3.01.S. The chlorophyll concentration estimated by inversion of both model versions was similar, but the inversion accuracy of the dry matter and water content was significantly improved. Decreases in RMSE from 0.0079 g cm¯² to 0.0019 g cm¯² for dry matter and from 0.0019 cm to 0.0006 cm for leaf water content proved the improved performance of the recalibrated PROSPECT version 3.01.S

A new hyperspectral index for chlorophyll estimation of a forest canopy: Area under curve normalised to maximal band depth between 650-725 nm

Total chlorophyll (Cab) content of a forest canopy is used as indicator for the current state of a forest stand, and also as an input for various physiological vegetation models (i.e. models of photosynthesis, evapo-transpiration, etc.). Recent hyperspectral remote sensing allows retrieving the Cab concentration of vegetation using the appropriate optical indices, and/or by means of biochemical information, scaled up from leaf to canopy level within radiative transfer (RT) models. Plenty of chlorophyll optical indices can be found in the literature for the leaf level, nevertheless, only some of them were proposed for a complex vegetation canopy like a forest stand. A robust chlorophyll optical index at the canopy level should be driven by the Cab concentration without negative influence of other factors represented by soil background or understory, canopy closure, canopy structure (e.g. leaf area index (LAI), clumping of leaves), etc. A new optical index named Area under curve Normalised to Maximal Band depth between 650-725 nm (ANMB₆₅₀-₇₂₅) is proposed to estimate the chlorophyll content of a Norway spruce (Picea abies, /L./ Karst.) crown. This index was designed to exploit modifications of a vegetation reflectance signature invoked within the red-edge wavelengths mainly by the changes in leaf chlorophyll content. ANMB₆₅₀-₇₂₅ is based on the reflectance continuum removal of the chlorophyll absorption feature between wavelengths of 650-725 nm. Suitability of the index and sensitivity on disturbing factors was tested using a 3D Discrete Anisotropic Radiative Transfer (DART) model coupled with a leaf radiative transfer model PROSPECT adjusted for spruce needles. The results of the ANMB₆₅₀-₇₂₅ abilities within a coniferous forest canopy were compared with the performance of the chlorophyll indices ratio TCARI/OSAVI. Test results, carried out with the DART model simulating hyperspectral data with 0.9 m pixel size, showed a strong linear regression of the ANMB₆₅₀-₇₂₅ on spruce crown Cab concentration (R²=0.9798) and its quite strong resistance against varying canopy structural features such as LAI and canopy closure. The root mean square error (RMSE) between real and the ANMB₆₅₀-₇₂₅ estimated Cab concentrations was only 9.53 mg/cm² while the RMSE generated from prediction of the TCARI/OSAVI was two times higher (18.83 mg/cm²). Chlorophyll retrieval using the ANMB₆₅₀-₇₂₅ index remained stable also after introduction of two reflectance signal disturbing features: a) 20% of the spectral information of epiphytic lichen (Pseudevernia sp.) regularly distributed within the spruce canopy, and b) simulation of the sensor noise (computed for a signal to noise ratio equal to 5). RMSE of predicted Cab concentration after the introduction of lichens appeared to be 10.51 mg/cm² and the combined influence of lichen presence and sensor noise in the image caused an increase of the RMSE to 12.13 mg/cm²

Landscape-scale Ips typographus attack dynamics: from monitoring plots to GIS-based disturbance models

In natural spruce stands, a change of generation is usually initiated by wind or bark beetle disturbances. We combined semi-temporary monitoring plots, remote sensing, and GIS in order to understand and model these processes. Sub plots, called “active”, were located in areas with a high probability of bark beetle or wind disturbances. The optimal location of these plots is usually at an active forest edge, i.e., the zone of maximal change in bark beetle abundance over time, corresponding to the border between wind-damaged or bark beetle-attacked parts and undisturbed parts of a forest stand. The key variable investigated was tree mortality caused by bark beetles. Other variables were similar to those recorded in traditional forest monitoring. Tree defense indicators (resin flow, phenolic compounds) and reaction of a tree to bark beetle inoculation were measured. Terrestrial data were then combined with remote sensing data. Time series of satellite images were analyzed in order to define the pattern of wind and bark beetle damages. Weather monitoring data were used for predicting bark beetle and water stress development. All of the information was integrated in a GIS-based system and future bark beetle infestations were predicted. In this paper, we review previous studies and conclude that: (1) the hypotheses of habitat selection (non-host volatiles and semiochemical diversity) and location of moderately-stressed host trees are confirmed, although further work about olfactory orientation and host resistance is needed;(2) reactions of trees to bark beetle attack can be predicted by monitoring several parameters, e.g., air temperature and tree physiology; (3) data from ground monitoring can be integrated with GIS and remote sensing systems for bark beetle prognosis and management at the habitat and landscape levels

A neural network inversion of the DART model to retrieve Norway spruce LAI at a very high spatial resolution

Leaf Area Index (LAI) is a key input parameter in many eco-physiological and climate models. Therefore, the development of methods to accurately and timely retrieve LAI over large areas is essential to fully understand the Earth system. The inversion of radiative transfer models is a “universal” method to retrieve LAI from remotely sensed images because it is independent from the study area and the sampling conditions. In this paper, we study the potential of the 3D Discrete Anisotropic Radiative Transfer (DART) model to retrieve the LAI of a Norway spruce forest stand. An extensive airborne/field campaign was carried out in September 2004 to acquire AISA Eagle VNIR hyperspectral images (pixel size of 0.4 m) and to collect ground truth data for the image pre-processing, DART parameterization and validation of the LAI estimations. Because DART is a complex and computationally demanding model, it was first run in direct mode to build a large dataset of possible canopy realizations. Then, a relatively simple two-layer feed forward backpropragation neural network was trained using the simulated DART top of canopy reflectances and a priori information on canopy closure. Finally, the LAI inversion was performed over the radiometrically and atmospherically corrected AISA Eagle images by using a sliding window whose size matches the extent of the DART modelled forest scenes. Results indicate that the inversion of the DART model to retrieve the LAI of complex Norway spruce canopies using ANN is a promising tool. Nevertheless, the approach still has to be improved in case of very high spatial resolution images