Callitrichaceae, Polygonaceae: Euro+Med-Checklist Notulae 6

Peer reviewe

Contributions to the bryophyte flora of Kyrgyzstan

Based on a recent expedition, we report 36 moss species and one liverwort species from Kyrgyzstan. Orthotrichum affine Brid. is a new record for the country, and several species are reported as new to various provinces. Many of the species are common in large areas of the Northern Hemisphere, which demonstrates how the bryophyte flora of Kyrgyzstan is still poorly known.Peer reviewe

Airborne dual-wavelength waveform LiDAR improves species classification accuracy of boreal broadleaved and coniferous trees

Funding Information: This study was conducted on course FOR-254 ‘Advanced Forest Inventory and Management Project’ at the University of Helsinki. Plots IM and OG were measured by students and assistants on course FOR110B with the kind permission of Prof. Pauline Stenberg. Dr. Pekka Kaitaniemi provided phenological observations during LiDAR campaigns, and support by Dr. Antti Uotila was crucial in finding aspen, alder and larch samples in Hyytiälä. The LiDAR and field data in 2013 were collected and processed with funding from the Academy of Finland and Metsämiesten säätiö. Other work by made possible by the University of Helsinki. Publisher Copyright: © 2022, Finnish Society of Forest Science. All rights reserved.Tree species identification constitutes a bottleneck in remote sensing applications. Waveform LiDAR has been shown to offer potential over discrete-return observations, and we assessed if the combination of two-wavelength waveform data can lead to further improvements. A total of 2532 trees representing seven living and dead conifer and deciduous species classes found in Hyytiälä forests in southern Finland were included in the experiments. LiDAR data was acquired by two single-wavelength sensors. The 1064-nm and 1550-nm data were radiometrically corrected to enable range-normalization using the radar equation. Pulses were traced through the canopy, and by applying 3D crown models, the return waveforms were assigned to individual trees. Crown models and a terrain model enabled a further split of the waveforms to strata representing the crown, understory and ground segments. Different geometric and radiometric waveform attributes were extracted per return pulse and aggregated to tree-level mean and standard deviation features. We analyzed the effect of tree size on the features, the correlation between features and the between-species differences of the waveform features. Feature importance for species classification was derived using F-test and the Random Forest algorithm. Classification tests showed significant improvement in overall accuracy (74→83% with 7 classes, 88→91% with 4 classes) when the 1064-nm and 1550-nm features were merged. Most features were not invariant to tree size, and the dependencies differed between species and LiDAR wavelength. The differences were likely driven by factors such as bark reflectance, height growth induced structural changes near the treetop as well as foliage density in old trees.Peer reviewe

Current distribution and conservation of Najas tenuissima (Hydrocharitaceae)

Non peer reviewe

Examining goodness of a tree diameter growth model using time-series analysis in NFI-data

Suomessa eri-ikäisrakenteinen kasvatus sallittiin vuonna 2014 säädetyssä metsälaissa, jonka jälkeen jatkuva kasvatus lisättiin metsänhoidon suosituksiin. Lakimuutoksen jälkeen eri-ikäisrakenteisen kasvatuksen suosio on lisääntynyt, jonka seurauksena metsien rakenteissa ja metsänhoidon kehityksessä on tapahtunut muutosta. Myös muuttuvalla ilmastolla on havaittu olevan vaikutusta puuston kasvureaktioihin. Tämän vuoksi aiemmin luodut metsän kehitysmallit eivät ole itsessään yhtä käyttökelpoisia kuin ennen. Puuston kehitystä kuvaavat mallit ovat yleensä tilastollisia malleja, jonka vuoksi ne toimivat luotettavasti niin pitkään, kunnes puuston kasvureaktiot poikkeavat mallin laadinta-aineiston kasvureaktioista. Myös yleisesti mallin hyvyyden kannalta on tärkeää tarkastella mallin toimintaa laadinta-aineiston ulkopuolella, jotta mallin luotettavuudesta ja soveltuvuudesta eri ajanjaksojen puustoon voi sanoa. Tämä lisää myös päätösten luotettavuutta, jotka perustuvat mallilla saatuihin estimaatteihin. Tutkielman tavoitteena on tarkastella Pukkalan ym. (2021) läpimitan kasvumallin viiden vuoden kasvuennusteiden eroja kahdella eri valtakunnan metsien inventoinnin ajanjaksolla (VMI10-11 (mallin laadinta-aineisto) ja VMI11-12). Tavoitteena on myös tutkia, selittäisivätkö maanpintamallista luodut topografiaa kuvaavat tunnukset mallin jäännösvaihtelua. Lisäksi mallia on pyritty kalibroimaan koealatasolla näillä jäännösvaihtelua selittävillä maanpintamallin tunnuksilla. Tutkielman aineistona on käytetty valtakunnan metsien 10., 11. ja 12. inventoinneissa Keski-Suomesta mitattujen pysyvien koealojen (n=299) lukupuita. Maanpintamallina tutkielmassa on käytetty Maanmittauslaitoksen avoimen paikkatiedon maaston korkeusmallia. Mallin hyvyyden analysoinnissa hyödynnettiin tilastollisia tunnuslukuja sekä graafista tarkastelua. Kalibrointimalleilla estimoitiin mallin logaritmista ennustevirhettä lineaarisen varianssikomponenttianalyysin avulla perustuen maanpintamallin tunnuksiin. Merkittäviä eroja mallin estimaateissa eri ajanjaksojen välillä ei huomattu eli malli toimi hyvin laadinta-aineiston ulkopuolella VMI11-12 ajanjaksossa. Mallilla saadut kasvuennusteet olivat kaikissa tilanteissa mitattuja kasvuennusteita suurempia kummallakin ajanjaksolla. Koko aineiston kesken tarkasteltuna ennustevirheen harha oli 13,5 % pienempi laadinta-aineiston ulkopuolella VMI11-12 ajanjaksossa. Mallin estimaattien tarkkuudessa ei havaittu merkittäviä eroja ajanjaksojen välillä eri luokissa (puulaji, kasvupaikka- tyyppi, puuluokka jne.). Mallin estimaatit olivat tarkimpia mäntyvaltaisilla kuivilla kankailla ja mitä ravinteikkaampaan ja kuusivaltaisempaan kasvupaikkaan siirryttiin, sitä suuremmaksi harha kasvoi. Maanpintamallin tunnusten ja mallin selittämättömän jäännösvaihtelun välille ei löytynyt selkeää yhteyttä. Mallin kalibroiminen maanpintamallin tunnuksilla pienensi huomattavasti koealakohtaista harhaa, kun kalibrointiaineistona käytettiin vähintään yhtä puuta 20 koealalta ja kalibroitiin vain kalibrointiaineistoon kuuluvien koealojen puita. Kalibroimisen onnistuminen johtui maastototuuden lisäämisestä analyysiin. Tutkielman mukaan läpimitan kasvumallia voi soveltaa luotettavasti kaiken rakenteisiin metsikköihin laadinta-aineiston ulkopuolella huomioiden kuitenkin tutkielman ajallisen ja maantieteellisen rajoittuneisuuden. Erot mallin estimaateissa eri ajanjaksoilla eivät olleet mallin käytännön sovelluksen kannalta merkittäviä. Mallin jäännösvirheeseen vaikuttavat muut kuin tutkielmassa käytetyt maanpintamallin tunnukset, jonka vuoksi tutkielma ei tuonut uutta tietoa mallin jäännösvirheeseen vaikuttavista tekijöistä. Maanpintamallin tunnukset toimivat hyvin mallin ennustevirheen mallinnukseen perustuvassa kalibroinnissa. Kalibroinnin avulla voi saada tarkempia kasvun ennusteita, jotka johtavat luotettavimpiin metsikön tulevaisuuden kehityksen simuloinnin skenaarioihin.Uneven aged forest management was allowed in the Finnish forestry law in 2014 and after that continuous cover management was added to the Finnish forest management recommendations. After the amendment, the popularity of uneven aged forest management has increased and changed the development of forest structures and silviculture. The changing climate has also effect on forest growth reactions. Because of this, previously created forest development models are not as useful as before in itself. Statistical models describing development of a stand give unbiased estimates if tree growth reactions differ from growth reactions of model fitting data. In general, it is also important to examine the goodness and functionality of the model outside of the model fitting data, to gain additional information about the reliability and suitability of the model. At the same time, reliability of decisions based on model estimates also improves. Aim of the study is to examine differences in the five-year growth estimates of the tree diameter model between two National Forest Inventory periods (NFI10-11 and NFI11-12). The aim is also to examine whether topography variables would explain residual variation of the model. In addition, the model has been tried to calibrate in a plot level with topography variables that have effects on the residual variation. The study dataset consisted of 299 permanent plots measured in the 10th, 11th, and 12th National Forest Inventories in Central Finland. Digital elevation model was acquired from open sources from National Land Survey of Finland. Statistical measures and graphical review were used in the model goodness of fit analysis. Calibration was based on linear variance component analysis where the logarithmic prediction error of the diameter growth model was estimated by topography variables. No significant differences were noticed in the model estimates between different time periods, i.e., the model worked well outside of the model fitting data in the NFI11-12 period. The model diameter growth estimates were higher than the measured diameter growths in all situations and in both periods. Bias was 13,5 % lower in the NFI11-12 period than in the NFI10-11 period, when the entire dataset was examined. No significant differences between periods were observed in the accuracy of the model estimates in different classes (species, habitat type, tree class etc.) The model estimates were the most accurate in pine dominated xeric heath forests. The bias increased when the model was used in more spruce dominated and nutritious stand. There was no unambiguous connection between topography variables and unexplained residual variation of the model. Model calibration based on topography variables reduced plot-specific bias when calibration dataset included at least one measured diameter of a tree from 20 plots and only trees belonging to the dataset were calibrated. Success of the calibration was due to the addition of terrain truth to the analysis. According to the results, the diameter growth model can be applied to all structured stands outside of the model fitting data. However, temporal, and geographical limitations of the dataset of the thesis must be considered when the model is used outside of the model fitting data. The differences between periods in the accuracies of the model estimates weren’t significant in terms of practical application of the model. No new information was obtained on the factors affecting the residual variation of the model. Some topography variables other than those used in the thesis may have an effect on the residual variation of the model. The topography variables worked well in the prediction error-based calibration of the model. Calibration can be used to get more accurate diameter growth estimates, which lead to a more reliable simulation scenario of the future development of the forest

Mammals divert endogenous genotoxic formaldehyde into one-carbon metabolism

The folate-driven one-carbon (1C) cycle is a fundamental metabolic hub in cells that enables the synthesis of nucleotides and amino acids and epigenetic modifications. This cycle might also release formaldehyde, a potent protein and DNA crosslinking agent that organisms produce in substantial quantities. Here we show that supplementation with tetrahydrofolate, the essential cofactor of this cycle, and other oxidation-prone folate derivatives kills human, mouse and chicken cells that cannot detoxify formaldehyde or that lack DNA crosslink repair. Notably, formaldehyde is generated from oxidative decomposition of the folate backbone. Furthermore, we find that formaldehyde detoxification in human cells generates formate, and thereby promotes nucleotide synthesis. This supply of 1C units is sufficient to sustain the growth of cells that are unable to use serine, which is the predominant source of 1C units. These findings identify an unexpected source of formaldehyde and, more generally, indicate that the detoxification of this ubiquitous endogenous genotoxin creates a benign 1C unit that can sustain essential metabolism