Pasi Korpelainen

Bio: Pasi Korpelainen is an academic researcher from University of Eastern Finland. The author has contributed to research in topics: Multispectral image & Vegetation (pathology). The author has an hindex of 1, co-authored 3 publications receiving 6 citations.

Accelerated vegetation succession but no hydrological change in a boreal fen during 20 years of recent climate change.

Abstract: Northern mires (fens and bogs) have significant climate feedbacks and contribute to biodiversity, providing habitats to specialized biota. Many studies have found drying and degradation of bogs in response to climate change, while northern fens have received less attention. Rich fens are particularly important to biodiversity, but subject to global climate change, fen ecosystems may change via direct response of vegetation or indirectly by hydrological changes. With repeated sampling over the past 20 years, we aim to reveal trends in hydrology and vegetation in a pristine boreal fen with gradient from rich to poor fen and bog vegetation. We resampled 203 semi-permanent plots and compared water-table depth (WTD), pH, concentrations of mineral elements, and dissolved organic carbon (DOC), plant species occurrences, community structure, and vegetation types between 1998 and 2018. In the study area, the annual mean temperature rose by 1.0°C and precipitation by 46 mm, in 20-year periods prior to sampling occasions. We found that wet fen vegetation decreased, while bog and poor fen vegetation increased significantly. This reflected a trend of increasing abundance of common, generalist hummock species at the expense of fen specialist species. Changes were the most pronounced in high pH plots, where Sphagnum mosses had significantly increased in plot frequency, cover, and species richness. Changes of water chemistry were mainly insignificant in concentration levels and spatial patterns. Although indications toward drier conditions were found in vegetation, WTD had not consistently increased, instead, our results revealed complex dynamics of WTD as depending on vegetation changes. Overall, we found significant trend in vegetation, conforming to common succession pattern from rich to poor fen and bog vegetation. Our results suggest that responses intrinsic to vegetation, such as increased productivity or altered species interactions, may be more significant than indirect effects via local hydrology to the ecosystem response to climate warming.

Detection of European Aspen (Populus tremula L.) Based on an Unmanned Aerial Vehicle Approach in Boreal Forests

Abstract: European aspen (Populus tremula L.) is a keystone species for biodiversity of boreal forests. Large-diameter aspens maintain the diversity of hundreds of species, many of which are threatened in Fennoscandia. Due to a low economic value and relatively sparse and scattered occurrence of aspen in boreal forests, there is a lack of information of the spatial and temporal distribution of aspen, which hampers efficient planning and implementation of sustainable forest management practices and conservation efforts. Our objective was to assess identification of European aspen at the individual tree level in a southern boreal forest using high-resolution photogrammetric point cloud (PPC) and multispectral (MSP) orthomosaics acquired with an unmanned aerial vehicle (UAV). The structure-from-motion approach was applied to generate RGB imagery-based PPC to be used for individual tree-crown delineation. Multispectral data were collected using two UAV cameras: Parrot Sequoia and MicaSense RedEdge-M. Tree-crown outlines were obtained from watershed segmentation of PPC data and intersected with multispectral mosaics to extract and calculate spectral metrics for individual trees. We assessed the role of spectral data features extracted from PPC and multispectral mosaics and a combination of it, using a machine learning classifier—Support Vector Machine (SVM) to perform two different classifications: discrimination of aspen from the other species combined into one class and classification of all four species (aspen, birch, pine, spruce) simultaneously. In the first scenario, the highest classification accuracy of 84% (F1-score) for aspen and overall accuracy of 90.1% was achieved using only RGB features from PPC, whereas in the second scenario, the highest classification accuracy of 86 % (F1-score) for aspen and overall accuracy of 83.3% was achieved using the combination of RGB and MSP features. The proposed method provides a new possibility for the rapid assessment of aspen occurrence to enable more efficient forest management as well as contribute to biodiversity monitoring and conservation efforts in boreal forests.

Permafrost degradation at two monitored palsa mires in north-west Finland

Abstract: Abstract. Palsas and peat plateaus are expected to disappear from many regions, including Finnish Lapland. However, detailed long-term monitoring data of the degradation process on palsas are scarce. Here, we present the results of the aerial photography time series analysis (1959–2021), annual real-time kinematic (RTK) GNSS and active layer monitoring (2007–2021), and annual unoccupied aerial system surveys (2016–2021) at two palsa sites (Peera and Laassaniemi, 68∘ N) located in north-west Finland. We analysed temporal trends of palsa degradation and their relation to climate using linear regression. At both sites, the decrease in palsa area by −77 % to −90 % since 1959 and height by −16 % to −49 % since 2007 indicate substantial permafrost degradation throughout the study periods. The area loss rates are mainly connected to winter air temperature changes at Peera and winter precipitation changes at Laassaniemi. The active layer thickness (ALT) has varied annually between 2007 and 2021 with no significant trend and is related mainly to the number of very warm days during summer, autumn rainfall of previous year, and snow depths at Peera. At Laassaniemi, the ALT is weakly related to climate and has been decreasing in the middle part of the palsa during the past 8 years despite the continuous decrease in palsa volume. Our findings imply that the ALT in the inner parts of palsas do not necessarily reflect the overall permafrost conditions and underline the importance of surface position monitoring alongside the active layer measurements. The results also showed a negative relationship between the ALT and snow cover onset, indicating the complexity of climate–permafrost feedbacks in palsa mires.

Transient simulations of the carbon and nitrogen dynamics in northern peatlands: from the Last Glacial Maximum to the 21st century

Abstract: . The development of northern high-latitude peatlands played an important role in the carbon (C) balance of the land biosphere since the Last Glacial Maximum (LGM). At present, carbon storage in northern peatlands is substantial and estimated to be 500 ± 100 Pg C (1 Pg C = 1015 g C). Here, we develop and apply a peatland module embedded in a dynamic global vegetation and land surface process model (LPX-Bern 1.0). The peatland module features a dynamic nitrogen cycle, a dynamic C transfer between peatland acrotelm (upper oxic layer) and catotelm (deep anoxic layer), hydrology- and temperature-dependent respiration rates, and peatland specific plant functional types. Nitrogen limitation down-regulates average modern net primary productivity over peatlands by about half. Decadal acrotelm-to-catotelm C fluxes vary between −20 and +50 g C m−2 yr−1 over the Holocene. Key model parameters are calibrated with reconstructed peat accumulation rates from peat-core data. The model reproduces the major features of the peat core data and of the observation-based modern circumpolar soil carbon distribution. Results from a set of simulations for possible evolutions of northern peat development and areal extent show that soil C stocks in modern peatlands increased by 365–550 Pg C since the LGM, of which 175–272 Pg C accumulated between 11 and 5 kyr BP. Furthermore, our simulations suggest a persistent C sequestration rate of 35–50 Pg C per 1000 yr in present-day peatlands under current climate conditions, and that this C sink could either sustain or turn towards a source by 2100 AD depending on climate trajectories as projected for different representative greenhouse gas concentration pathways.

Rising temperature modulates pH niches of fen species.

Abstract: Rising temperatures may endanger fragile ecosystems because their character and key species show different habitat affinities under different climates. This assumption has only been tested in limited geographical scales. In fens, one of the most endangered ecosystems in Europe, broader pH niches have been reported from cold areas and are expected for colder past periods. We used the largest European-scale vegetation database from fens to test the hypothesis that pH interacts with macroclimate temperature in forming realized niches of fen moss and vascular plant species. We calibrated the data set (29,885 plots after heterogeneity-constrained resampling) with temperature, using two macroclimate variables, and with the adjusted pH, a variable combining pH and calcium richness. We modelled temperature, pH and water level niches for one hundred species best characterizing European fens using generalized additive models and tested the interaction between pH and temperature. Fifty-five fen species showed a statistically significant interaction between pH and temperature (adj p ˂ .01). Forty-six of them (84%) showed a positive interaction manifested by a shift or restriction of their niche to higher pH in warmer locations. Nine vascular plants and no moss showed the opposite interaction. Mosses showed significantly greater interaction. We conclude that climate significantly modulates edaphic niches of fen plants, especially bryophytes. This result explains previously reported regional changes in realized pH niches, a current habitat-dependent decline of endangered taxa, and distribution changes in the past. A warmer climate makes growing seasons longer and warmer, increases productivity, and may lower the water level. These effects prolong the duration and intensity of interspecific competition, support highly competitive Sphagnum mosses, and, as such, force niches of specialized fen species towards narrower high-pH ranges. Recent anthropogenic landscape changes pose a severe threat to many fen species and call for mitigation measures to lower competition pressure in their refugia.

Ongoing Fen–Bog Transition in a Boreal Aapa Mire Inferred from Repeated Field Sampling, Aerial Images, and Landsat Data

Abstract: Northern aapa mire complexes are characterized by patterned fens with flarks (wet fen surfaces) and bog zone margins with Sphagnum moss cover. Evidence exists of a recent increase in Sphagnum over fens that can alter ecosystem functions. Contrast between flarks and Sphagnum moss cover may enable remote sensing of these changes with satellite proxies. We explored recent changes in hydro-morphological patterns and vegetation in a south-boreal aapa mire in Finland and tested the performance of Landsat bands and indices in detecting Sphagnum increase in aapa mires. We combined aerial image analysis and vegetation survey, repeated after 60 years, to support Landsat satellite image analysis. Aerial image analysis revealed a decrease in flark area by 46% between 1947 and 2019. Repeated survey showed increase in Sphagnum mosses (S. pulchrum, S. papillosum) and deep-rooted vascular plants (Menyanthes trifoliata, Carex rostrata). A supervised classification of high-resolution UAV image recognized the legacy of infilled flarks in the patterning of Sphagnum carpets. Among Landsat variables, all separate spectral bands, the Green Difference Vegetation Index (GDVI), and the Automated Water Extraction Index (AWEI) correlated with the flark area. Between 1985 and 2020, near-infrared (NIR) and GDVI increased in the central flark area, and AWEI decreased throughout the mire area. In aapa mire complexes, flark fen and Sphagnum bog zones have contrasting Landsat NIR reflectance, and NIR band is suggested for monitoring changes in flarks. The observed increase in Sphagnum mosses supports the interpretation of ongoing fen–bog transitions in Northern European aapa mires, indicating significant ecosystem-scale changes.

Will climate change cause the global peatland to expand or contract? Evidence from the habitat shift pattern of Sphagnum mosses

Abstract: Peatlands play a crucial role in the global carbon cycle. Sphagnum mosses (peat mosses) are considered to be the peatland ecosystem engineers and contribute to the carbon accumulation in the peatland ecosystems. As cold‐adapted species, the dominance of Sphagnum mosses in peatlands will be threatened by climate warming. The response of Sphagnum mosses to climate change is closely related to the future trajectory of carbon fluxes in peatlands. However, the impact of climate change on the habitat suitability of Sphagnum mosses on a global scale is poorly understood. To predict the potential impact of climate change on the global distribution of Sphagnum mosses, we used the MaxEnt model to predict the potential geographic distribution of six Sphagnum species that dominate peatlands in the future (2050 and 2070) under two greenhouse gas emission scenarios (SSP1‐2.6 and SSP5‐8.5). The results show that the mean temperature of the coldest quarter, precipitation of the driest month, and topsoil calcium carbonate are the main factors affecting the habitat availability of Sphagnum mosses. As the climate warms, Sphagnum mosses tend to migrate northward. The suitable habitat and abundance of Sphagnum mosses increase extensively in the high‐latitude boreal peatland (north of 50°N) and decrease on a large scale beyond the high‐latitude boreal peatland. The southern edge of boreal peatlands would experience the greatest decline in the suitable habitat and richness of Sphagnum mosses with the temperature rising and would be a risk area for the transition from carbon sink to carbon source. The spatial–temporal pattern changes of Sphagnum mosses simulated in this study provide a reference for the development of management and conservation strategies for Sphagnum bogs.

A New Individual Tree Species Classification Method Based on the ResU-Net Model

Abstract: Individual tree species (ITS) classification is one of the key issues in forest resource management. Compared with traditional classification methods, deep learning networks may yield ITS classification results with higher accuracy. In this research, the U-Net and ResNet networks were combined to form a Res-UNet network by changing the structure of the convolutional layer to the residual structure in ResNet based on the framework of the U-Net model. In addition, a second Res-UNet network named Res-UNet2 was further constructed to explore the effect of the stacking of residual structures on network performance. The Res-UNet2 model structure is similar to that of the Res-UNet model, but the convolutional layer in the U-Net model is created with a double-layer residual structure. The two networks proposed in this work were used to classify ITSs in WorldView-3 images of the Huangshan Mountains, Anhui Province, China, acquired in March 2019. The resulting ITS map was compared with the classification results obtained with U-Net and ResNet. The total classification accuracy of the ResU-Net network reached 94.29% and was higher than that generated by the U-Net and ResNet models, verifying that the ResU-Net model can more accurately classify ITSs. The Res-UNet2 model performed poorly compared to Res-UNet, indicating that stacking the residual modules in ResNet does not achieve an accuracy improvement.