Browsing by Subject "time series"

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  • Puttonen, Eetu; Lehtomäki, Matti; Litkey, Paula; Näsi, Roope; Feng, Ziyi; Liang, Xinlian; Wittke, Samantha; Pandzic, Milos; Hakala, Teemu; Karjalainen, Mika; Pfeifer, Norbert (Frontiers Reseach Foundation, 2019)
    Frontiers in Plant Science
    Terrestrial Laser Scanning (TLS) can be used to monitor plant dynamics with a frequency of several times per hour and with sub-centimeter accuracy, regardless of external lighting conditions. TLS point cloud time series measured at short intervals produce large quantities of data requiring fast processing techniques. These must be robust to the noise inherent in point clouds. This study presents a general framework for monitoring circadian rhythm in plant movements from TLS time series. Framework performance was evaluated using TLS time series collected from two Norway maples (Acer platanoides) and a control target, a lamppost. The results showed that the processing framework presented can capture a plant's circadian rhythm in crown and branches down to a spatial resolution of 1 cm. The largest movements in both Norway maples were observed before sunrise and at their crowns' outer edges. The individual cluster movements were up to 0.17 m (99th percentile) for the taller Norway maple and up to 0.11 m (99th percentile) for the smaller tree from their initial positions before sunset.
  • Kaikkonen, Laura; Enberg, Sara; Blomster, Jaanika; Luhtanen, Anne-Mari; Autio, Riitta; Rintala, Janne-Markus (Springer Nature, 2020)
    Polar Biology 43 9 (2020)
    Marine microbial communities undergo drastic changes during the seasonal cycle in high latitude seas. Despite the dominance of microbial biomass in the oceans, comprehensive studies on the seasonal changes of microbial plankton during the complete winter period are lacking. To study the seasonal variation in abundance of the microbial community, water samples were collected weekly in the Northern Baltic Sea from October to May. During ice cover from mid-January to April, samples from the sea ice and the underlying water were taken in addition to the water column samples. Abundances of bacteria, virus-like particles, nanoflagellates, and chlorophyll a concentrations were measured from sea ice, under-ice water, and the water column, and examined in relation to environmental conditions. All studied organisms had clear seasonal changes in abundance, and the sea-ice microbial community had an independent wintertime development compared to the water column. Bacteria were observed to have a key role in the biotic interactions in both ice and the water column, and the dormant period during the cold-water months (October–May) was limited to before ice formation. Our results provide the first insights into the temporal dynamics of bacteria and viruses during the whole cold-water season (October–May) in coastal high latitude seas, and demonstrate that changes in the environmental conditions are likely to affect bacterial dynamics and have implications on trophic interactions.
  • Cano Bernal, José Enrique; Rankinen, Katri; Thielking, Sophia (Academic Press, 2022)
    Journal of Environmental Management
    The majority of the carbon worldwide is in soil. In a river catchment, the tight relationship between soil, water and climate makes carbon likely to be eroded and transported from the soil to the rivers. There are multiple variables which can trigger and accelerate the process. In order to assess the importance of the factors involved, and their interactions resulting in the changes in the carbon cycle within catchments, we have studied the catchments of 26 Finnish rivers from 2000 to 2019. These catchments are distributed all over Finland, but we have grouped them into three categories: southern, peatland and northern. We have run a boosted regression tree (BRT) analysis on chemical, physical, climatic and anthropogenic factors to determine their influence on the variations of total organic carbon (TOC) concentration. TOC concentration has decreased in Finland between 2000 and 2019 by 0.91 mg/l, driven principally by forest ditching and % old forest in the catchment. Old forest is especially dominant in the northern catchments with an influence on TOC of 40.5%. In southern and peatland catchments, average precipitation is an important factor to explain the changes in TOC whilst in northern catchments, organic fields have more influence.
  • Suikkanen, Sanna; Uusitalo, Laura; Lehtinen, Sirpa; Lehtiniemi, Maiju; Kauppila, Pirkko; Mäkinen, Katja; Kuosa, Harri (Elsevier, 2021)
    Food Webs 28, e00202
    Blooms of cyanobacteria are recurrent phenomena in coastal estuaries. Their maximum abundance coincides with the productive period of zooplankton and pelagic fish. Experimental studies indicate that diazotrophic, i.e. dinitrogen (N2)-fixing cyanobacterial (taxonomic order Nostocales) blooms affect zooplankton, as well as other phytoplankton. We used multidecadal monitoring data from one archipelago station (1992–2013) and ten open sea stations (1979–2013) in the Baltic Sea to explore the potential bottom-up connections between diazotrophic and non-diazotrophic cyanobacteria and phyto- and zooplankton in natural plankton communities. Random forest regression, combined with linear regression analysis showed that the biomass of cyanobacteria (both diazotrophic and non-diazotrophic) was barely connected to any of the phytoplankton and zooplankton variables examined. Instead, physico-chemical variables (salinity, temperature, total phosphorus), as well as spatial and temporal variability seemed to have more significant connections to both phytoplankton and zooplankton variables. Zooplankton variables were also connected to the biomass of phytoplankton groups other than cyanobacteria (such as chrysophytes, cryptophytes and prymnesiophytes), and phytoplankton variables had connections with the biomass of different zooplankton groups, especially copepods. Overall, negative relationships between cyanobacteria and other plankton taxa were scarcer than expected based on previous experimental studies.
  • Hampton, Stephanie E.; Galloway, Aaron W. E.; Powers, Stephen M.; Ozersky, Ted; Woo, Kara H.; Batt, Ryan D.; Labou, Stephanie G.; O'Reilly, Catherine M.; Sharma, Sapna; Lottig, Noah R.; Stanley, Emily H.; North, Rebecca L.; Stockwell, Jason D.; Adrian, Rita; Weyhenmeyer, Gesa A.; Arvola, Lauri; Baulch, Helen M.; Bertani, Isabella; Bowman, Larry L.; Carey, Cayelan C.; Catalan, Jordi; Colom-Montero, William; Domine, Leah M.; Felip, Marisol; Granados, Ignacio; Gries, Corinna; Grossart, Hans-Peter; Haberman, Juta; Haldna, Marina; Hayden, Brian; Higgins, Scott N.; Jolley, Jeff C.; Kahilainen, Kimmo K.; Kaup, Enn; Kehoe, Michael J.; MacIntyre, Sally; Mackay, Anson W.; Mariash, Heather L.; Mckay, Robert M.; Nixdorf, Brigitte; Noges, Peeter; Noges, Tiina; Palmer, Michelle; Pierson, Don C.; Post, David M.; Pruett, Matthew J.; Rautio, Milla; Read, Jordan S.; Roberts, Sarah L.; Ruecker, Jacqueline; Sadro, Steven; Silow, Eugene A.; Smith, Derek E.; Sterner, Robert W.; Swann, George E. A.; Timofeyev, Maxim A.; Toro, Manuel; Twiss, Michael R.; Vogt, Richard J.; Watson, Susan B.; Whiteford, Erika J.; Xenopoulos, Marguerite A. (2017)
    Winter conditions are rapidly changing in temperate ecosystems, particularly for those that experience periods of snow and ice cover. Relatively little is known of winter ecology in these systems, due to a historical research focus on summer 'growing seasons'. We executed the first global quantitative synthesis on under-ice lake ecology, including 36 abiotic and biotic variables from 42 research groups and 101 lakes, examining seasonal differences and connections as well as how seasonal differences vary with geophysical factors. Plankton were more abundant under ice than expected; mean winter values were 43.2% of summer values for chlorophyll a, 15.8% of summer phytoplankton biovolume and 25.3% of summer zooplankton density. Dissolved nitrogen concentrations were typically higher during winter, and these differences were exaggerated in smaller lakes. Lake size also influenced winter-summer patterns for dissolved organic carbon (DOC), with higher winter DOC in smaller lakes. At coarse levels of taxonomic aggregation, phytoplankton and zooplankton community composition showed few systematic differences between seasons, although literature suggests that seasonal differences are frequently lake-specific, species-specific, or occur at the level of functional group. Within the subset of lakes that had longer time series, winter influenced the subsequent summer for some nutrient variables and zooplankton biomass.
  • Liu, Xing (Svenska handelshögskolan, 2012)
    Economics and Society – 249
    The integration of European agriculture into the world economy has also accelerated price interaction between member states and the rest of the world during last decades. Consequently, the fluctuation in world market prices was more quickly transmitted to European member states, including Finland. Increasing price uncertainty and price volatility in agricultural products became more evident. The openness of regional agriculture such as EU and Finnish to the world is irreversible, and the international community needs timely and differentiated information on the situation in different places in order to respond appropriately. The theme of this dissertation concerns the properties of price linkage of agricultural commodities across space during the last decades. Such properties include hedging issues, price transmission and marketing margin in the agricultural commodity market. By understanding the issues, agricultural market participants, including farmers, processors, industries, consumers and policy makers can benefit from insights into these issues either in order to assess past actions and decisions or to derive guidelines for future action. In summary, this dissertation consists of 5 independent articles. Article 1 presents a case study on optimal hedging on Finnish wheat under both price and yield risks. The result shows that the forward contract might not be the best hedging tool for the farmers in Finland where the yield volatility per unit is bigger than price volatility. Article 2 presents an efficiency test of the CPO futures market in Malaysia for European participants using the cointegration technique. The results suggest that the futures market in Malaysia is not efficient for European participants, which indicates that they should be more cautious in using the hedging strategy in this futures market. Articles 3 focuses on the price transmission of the Finnish food market at vertical level, and Article 4 investigates horizontal price transmission of the Finnish meat market towards the European market in both symmetric and asymmetric ways. The result from Article 3 implies that the Finnish market is characterized by buyer power according to the measure of Lloyd et al. (2009). The result from Article 4 detects that the Finnish meat sector is integrated with EU benchmark countries symmetrically or asymmetrically. Moreover, the degree of integration and speed of adjustment of Finnish pork and beef towards the EU market are proved in different level. Article 5 presents an inventory model to investigate the relationship between price volatility and the inventory in the global wheat market. The results reveal that there is only a short-term significant relationship between price volatility and the inventory.
  • Haagsma, Juanita A.; Olij, Branko F.; Majdan, Marek; van Beeck, Ed F.; Vos, Theo; Castle, Chris D.; Dingels, Zachary; Fox, Jack T.; Hamilton, Erin B.; Liu, Zichen; Roberts, Nicholas L. S.; Sylte, Dillon O.; Aremu, Olatunde; Baernighausen, Till Winfried; Borzi, Antonio M.; Briggs, Andrew M.; Carrero, Juan J.; Cooper, Cyrus; El-Khatib, Ziad; Ellingsen, Christian Lycke; Fereshtehnejad, Seyed-Mohammad; Filip, Irina; Fischer, Florian; Haro, Josep Maria; Jonas, Jost B.; Kiadaliri, Aliasghar A.; Koyanagi, Ai; Lunevicius, Raimundas; Meretoja, Tuomo J.; Mohammed, Shafiu; Pathak, Ashish; Radfar, Amir; Rawaf, Salman; Rawaf, David Laith; Riera, Lidia Sanchez; Shiue, Ivy; Vasankari, Tommi Juhani; James, Spencer L.; Polinder, Suzanne (2020)
    Introduction Falls in older aged adults are an important public health problem. Insight into differences in fall-related injury rates between countries can serve as important input for identifying and evaluating prevention strategies. The objectives of this study were to compare Global Burden of Disease (GBD) 2017 estimates on incidence, mortality and disability-adjusted life years (DALYs) due to fall-related injury in older adults across 22 countries in the Western European region and to examine changes over a 28-year period. Methods We performed a secondary database descriptive study using the GBD 2017 results on age-standardised fall-related injury in older adults aged 70 years and older in 22 countries from 1990 to 2017. Results In 2017, in the Western European region, 13 840 per 100 000 (uncertainty interval (UI) 11 837-16 113) older adults sought medical treatment for fall-related injury, ranging from 7594 per 100 000 (UI 6326-9032) in Greece to 19 796 per 100 000 (UI 15 536-24 233) in Norway. Since 1990, fall-related injury DALY rates showed little change for the whole region, but patterns varied widely between countries. Some countries (eg, Belgium and Netherlands) have lost their favourable positions due to an increasing fall-related injury burden of disease since 1990. Conclusions From 1990 to 2017, there was considerable variation in fall-related injury incidence, mortality, DALY rates and its composites in the 22 countries in the Western European region. It may be useful to assess which fall prevention measures have been taken in countries that showed continuous low or decreasing incidence, death and DALY rates despite ageing of the population.
  • Sokka, L.; Antikainen, R.; Kauppi, P.E. (Inderscience Enterprises, 2004)
    Nitrogen (N) and phosphorus (P) are two nutrients contributing to several environmental problems, particularly eutrophication of surface waters. Leakages of these nutrients occur through human activity. In this study, the flows of N and P in the Finnish municipal waste system in 1952–1999 were determined and analysed using substance flow analysis (SFA). Nutrient flows in both wastewaters and solid waste peaked in 1990, after which they declined until 1994 but thereafter increased again although remaining lower than in 1990. At the end of the 1990s the wastewater and solid waste from municipalities and rural households contained ca. 7.0 kg N person–1 a–1 and 1.1 kg P person–1 a–1. Untreated wastewater contained three times more N and four times more P than solid waste. The amounts of N and P involved in recycling increased over the study period being 10% for N and 50% for P at the end of the 1990s.
  • Braaten, Hans Fredrik Veiteberg; Akerblom, Staffan; Kahilainen, Kimmo K.; Rask, Martti; Vuorenmaa, Jussi; Mannio, Jaakko; Malinen, Tommi; Lydersen, Espen; Poste, Amanda E.; Amundsen, Per-Arne; Kashulin, Nicholas; Kashulina, Tatiana; Terentyev, Petr; Christensen, Guttorm; de Wit, Heleen A. (American Chemical Society, 2019)
    Environmental Science & Technology 2019 53 (4), 1834-1843
    Temporally (1965–2015) and spatially (55°–70°N) extensive records of total mercury (Hg) in freshwater fish showed consistent declines in boreal and subarctic Fennoscandia. The database contains 54 560 fish entries (n: pike > perch ≫ brown trout > roach ≈ Arctic charr) from 3132 lakes across Sweden, Finland, Norway, and Russian Murmansk area. 74% of the lakes did not meet the 0.5 ppm limit to protect human health. However, after 2000 only 25% of the lakes exceeded this level, indicating improved environmental status. In lakes where local pollution sources were identified, pike and perch Hg concentrations were significantly higher between 1965 and 1990 compared to values after 1995, likely an effect of implemented reduction measures. In lakes where Hg originated from long-range transboundary air pollution (LRTAP), consistent Hg declines (3–7‰ per year) were found for perch and pike in both boreal and subarctic Fennoscandia, suggesting common environmental controls. Hg in perch and pike in LRTAP lakes showed minimal declines with latitude, suggesting that drivers affected by temperature, such as growth dilution, counteracted Hg loading and food web exposure. We recommend that future fish Hg monitoring sampling design should include repeated sampling and collection of pollution history, water chemistry, fish age, and stable isotopes to enable evaluation of emission reduction policies.
  • Tiihonen, Iiro (Helsingin yliopisto, 2020)
    Työni aihe on Gaussisten prosessien (Gp) soveltaminen aikasarjojen analysointiin. Erityisesti lähestyn aikasarjojen analysointia verrattain harvinaisen sovellusalan, historiallisten aikasarja-aineistojen analysoinnin näkökulmasta. Bayesilaisuus on tärkeä osa työtä: parametreja itsessään kohdellaan satunnaismuuttujina, mikä vaikuttaa sekä mallinnusongelmien muotoiluun että uusien ennusteiden tekemiseen työssä esitellyillä malleilla. Työni rakentuu paloittain. Ensin esittelen Gp:t yleisellä tasolla, tilastollisen mallinnuksen työkaluna. Gp:eiden keskeinen idea on, että Gp-prosessin äärelliset osajoukot noudattavat multinormaalijakaumaa, ja havaintojen välisiä yhteyksiä mallinnetaan ydinfunktiolla (kernel), joka samaistaa havaintoja niihin liittyvien selittäjien ja parametriensa funktiona. Oikeanlaisen ydinfunktion valinta ja datan suhteen optimoidut parametrit mahdollistavat hyvinkin monimutkaisten ja heikosti ymmärrettyjen ilmiöiden mallintamisen Gp:llä. Esittelen keskeiset tulokset, jotka mahdollistavat sekä GP:n sovittamisen aineistoon että sen käytön ennusteiden tekemiseen ja mallinnetun ilmiön alatrendien erittelyyn. Näiden perusteiden jälkeen siirryn käsittelemään sitä, miten GP-malli formalisoidaan ja sovitetaan, kun lähestymistapa on Bayesilainen. Käsittelen sekä eri sovittamistapojen vahvuuksia ja heikkouksia, että mahdollisuutta liittää Gp osaksi laajempaa tilastollista mallia. Bayesilainen lähestymistapa mahdollistaa mallinnettua ilmiötä koskevan ennakkotiedon syöttämisen osaksi mallin formalismia parametrien priorijakaumien muodossa. Lisäksi se tarjoaa systemaattisen, todennäköisyyksiin perustuvan tavan puhua sekä ennakko-oletuksista että datan jälkeisistä parametreihin ja mallinnetun ilmiön tuleviin arvoihin liittyvistä uskomuksista. Seuraava luku käsittelee aikasarjoihin erityisesti liittyviä Gp-mallintamisen tekniikoita. Erityisesti käsittelen kolmea erilaista mallinnustilannetta: ajassa tapahtuvan Gp:n muutoksen, useammasta eri alaprosessista koostuvan Gp:n ja useamman keskenään korreloivan Gp:n mallintamista. Tämän käsittelyn jälkeen työn teoreettinen osuus on valmis: aikasarjojen konkreettinen analysointi työssä esitellyillä työkaluilla on mahdollista. Viimeinen luku käsittelee historiallisten ilmiöiden mallintamista aiemmissa luvuissa esitellyillä tekniikoilla. Luvun tarkoitus on ensisijaisesti esitellä lyhyesti useampi potentiaalinen sovelluskohde, joita on yhteensä kolme. Ensimmäinen luvussa käsitelty mahdollisuus on usein vain repalaisesti havaintoja sisältävien historiallisten aikasarja-aineistojen täydentäminen GP-malleista saatavilla ennusteilla. Käytännön tulokset korostivat tarvetta vahvoille prioreille, sillä historialliset aikasarjat ovat usein niin harvoja, että mallit ovat valmiita hylkäämän havaintojen merkityksen ennustamisessa. Toinen esimerkki käsittelee historiallisia muutoskohtia, esimerkkitapaus on Englannin sisällissodan aikana äkillisesti räjähtävä painotuotteiden määrä 1640-luvun alussa. Sovitettu malli onnistuu päättelemään sisällissodan alkamisen ajankohdan. Viimeisessä esimerkissä mallinnan painotuotteiden määrää per henkilö varhaismodernissa Englannissa, käyttäen ajan sijaan selittäjinä muita ajassa kehittyviä muuttujia (esim. urbanisaation aste), jotka tulkitaan alaprosesseiksi. Tämänkin esimerkin tekninen toteutus onnistui, mikä kannustaa sekä tilastollisesti että historiallisesti kattavampaan analyysiin. Kokonaisuutena työni sekä esittelee että demonstroi Gp-lähestymistavan mahdollisuuksia aikasarjojen analysoinnissa. Erityisesti viimeinen luku kannustaa jatkokehitykseen historiallisten ilmiöiden mallintamisen uudella sovellusalalla.
  • Suominen, Tapio; Westerholm, Jan; Kalliola, Risto; Attila, Jenni (MDPI, 2021)
    Remote Sensing vol 13(11):2104
    Seawaters exhibit various types of cyclic and trend-like temporal alterations in their biological, physical, and chemical processes. Surface water dynamics may vary, for instance, when the timings, durations, or amplitudes of seasonal developments of water properties alter between years and locations. We introduce a workflow using remote sensing to identify surface waters undergoing similar dynamics. The method, called ocean surface dynamics partitioning, classifies pixels based on their temporal change patterns instead of their properties at successive time snapshots. We apply an efficient parallel computing method to calculate Dynamic Time Warping (DTW) time series distances of large datasets of Earth Observation MERIS-instrument reflectance data Rrs(510 nm) and Rrs(620 nm), and produce a matrix of time series distances between 12,252 locations/time series in the Baltic Sea, for both wavelengths. We define cluster prototypes by hierarchical clustering of distance matrices and use them as initial prototypes for an iterative process of partitional clustering in order to identify areas that have similar reflectance dynamics. Lastly, we compute distances from the time series of the reflectance data to selected physical factors (wind, precipitation, and changes in sea surface temperature) obtained from Copernicus data archives. The workflow is reproducible and capable of managing large datasets in reasonable computation times and identifying areas of distinctive dynamics. The results show spatially coherent and logical areas without a priori information about the locations of the satellite image time series. The alignments of the reflectance time series vs. the observational time series of the physical environment clarify the causalities behind the cluster formation. We conclude that following the changes in an aquatic realm by biogeochemical observations at certain temporal intervals alone is not sufficient to identify environmental shifts. We foresee that the changes in dynamics are a sensitive measure of environmental threats and therefore they will be important to follow in the future.
  • Brando, Vittorio E.; Sammartino, Michela; Colella, Simone; Bracaglia, Marco; Di Cicco, Annalisa; D’Alimonte, Davide; Kajiyama, Tamito; Kaitala, Seppo; Attila, Jenni (MDPI, 2021)
    Remote Sensing 2021, 13(16), 3071
    A relevant indicator for the eutrophication status in the Baltic Sea is the Chlorophyll-a concentration (Chl-a). Alas, ocean color remote sensing applications to estimate Chl-a in this brackish basin, characterized by large gradients in salinity and dissolved organic matter, are hampered by its optical complexity and atmospheric correction limits. This study presents Chl-a retrieval improvements for a fully reprocessed multi-sensor time series of remote-sensing reflectances (Rrs) at ~1 km spatial resolution for the Baltic Sea. A new ensemble scheme based on multilayer perceptron neural net (MLP) bio-optical algorithms has been implemented to this end. The study documents that this approach outperforms band-ratio algorithms when compared to in situ datasets, reducing the gross overestimates of Chl-a observed in the literature for this basin. The Rrs and Chl-a time series were then exploited for eutrophication monitoring, providing a quantitative description of spring and summer phytoplankton blooms in the Baltic Sea over 1998–2019. The analysis of the phytoplankton dynamics enabled the identification of the latitudinal variations in the spring bloom phenology across the basin, the early blooming in spring in the last two decades, and the description of the spatiotemporal coverage of summer cyanobacterial blooms in the central and southern Baltic Sea.
  • Keningi, Eino (Helsingin yliopisto, 2022)
    In little over a decade, cryptocurrencies have become a highly speculative asset class in global financial markets, with Bitcoin leading the way. Throughout its relatively brief history, the price of bitcoin has gone through multiple cycles of growth and decline. As a consequence, Bitcoin has become a widely discussed – and polarizing – topic on Twitter. This work studies whether the sentiment of popular Bitcoin-related tweets can be used to predict the future price movements of bitcoin. In total, seven different algorithms are evaluated: Vector Autoregression, Vector Autoregression Moving-Average, Random Forest, XGBoost, LightGBM, Long Short-Term Memory, and Gated Recurrent Unit. By applying lexicon-based sentiment analysis, and heuristic filtering of tweets, it was discovered that sentiment-based features of popular tweets improve the prediction accuracy over baseline features (open-high-low-close data) in five of the seven algorithms tested. The tree-based algorithms (Random Forest, XGBoost, LightGBM) generally had the lowest prediction errors, while the neural network algorithms (Light Short-Term Memory and Gated Recurrent Unit) had the poorest performance. The findings suggest that the sentiment of popular Bitcoin-related tweets can be an important feature in predicting the future price movements of bitcoin.
  • Lapinlampi, George (Helsingin yliopisto, 2020)
    There’s a specific but sometimes quite a significant problem in time series modeling caused by changing means. First, the foundation behind the model addressing this problem is introduced in the form of the basic theory of Markov chains and problems related to hidden Markov chains. This approach builds on the ARMA (Autoregressive Moving average) model but is utilizing estimation methods from the areas not specifically dedicated to the time series analysis. The hybrid approach comprising Markov chains, EM (expectation-maximization) algorithm, and linear modeling may be well justified when the conventional methods do not seem to produce desired results and the modeler has competencies and means to attempt more sophisticated approaches. The literature review provides an insight into an earlier kind of models that have led to the development of the model investigated in this work. Finally, in the empirical part the model’s power is assessed against the conventional ARMA model. The modeling is performed on the simulated series in order to assess the functionality of the EM algorithm, to have a precise knowledge about real state variables, and to get an optimal comparison between a linear and non-linear models. The models are compared using multiple diagnostic procedures such as AIC (Akaike criterion), autocorrelation and partial autocorrelation functions, residuals variance, and other descriptive statistical measures.
  • Alibakhshi, Sara; Groen, Thomas A.; Rautiainen, Miina; Naimi, Babak (2017)
    The response of an ecosystem to external drivers may not always be gradual and reversible. Discontinuous and sometimes irreversible changes, called 'regime shifts' or 'Critical transitions', can occur. The likelihood of such shifts is expected to increase for a variety of ecosystems, and it is difficult to predict how close an ecosystem is to a critical transition. Recent modelling studies identified indicators of impending regime shifts that can be used to provide early warning signals of a critical transition. The identification of such transitions crucially depends on the ability to monitor key ecosystem variables, and their success may be limited by lack of appropriate data. Moreover, empirical demonstrations of the actual functioning of these indicators in real-world ecosystems are rare. This paper presents the first study which uses remote sensing data to identify a critical transition in a wetland ecosystem. In this study, we argue that a time series of remote sensing data can help to characterize and determine the timing of a critical transition. This can enhance our abilities to detect and anticipate them. We explored the potentials of remotely sensed vegetation (NDVI), water (MNDWI), and vegetation- water (VWR) indices, obtained from time series of MODIS satellite images to characterize the stability of a wetland ecosystem, Dorge Sangi, near the lake Urmia, Iran, that experienced a regime shift recently. In addition, as a control case, we applied the same methods to another wetland ecosystem in Lake Arpi, Armenia which did not experience a regime shift. We propose a new composite index (MVWR) based on combining vegetation and water indices, which can improve the ability to anticipate a critical transition in a wetland ecosystem. Our results revealed that MVWR in combination with autocorrelation at-lag-1 could successfully provide early warning signals for a critical transition in a wetland ecosystem, and showed a significantly improved performance compared to either vegetation (NDVI) or water (MNDWI) indices alone.
  • Banville, Hubert; Albuquerque, Isabela; Hyvärinen, Aapo; Moffat, Grame; Engemann, Denis-Alexander; Gramfort, Alexandre (IEEE, 2019)
  • Hewitt, Judi E.; Norkko, Joanna; Kauppi, Laura; Villnäs, Anna; Norkko, Alf (2016)
    While beta diversity has been implicated as a key factor in controlling resilience of communities to stressors, lack of long-term data sets has limited the study of temporal dynamics of beta diversity. With a time series at two sites in excess of 40yr, we investigated turnover of both species and functional traits in a system stressed by eutrophication and overfishing and undergoing climate change and invasion. The two sites, although located near to each other, differ in water depth (20 cf. 35m), but both sites have displayed increased abundances of an invasive polychaete since 1990. We tested two hypotheses related to the effect of an invasive species; that taxa richness and turnover would decrease, and trait richness would increase post invasion and that trait turnover would increase between arrival and establishment of the invasive. Generally, we observed different dynamics at the two sites and responses not consistent with our hypotheses. We detected an increase in taxa richness at both sites and an increase in taxa turnover and number of traits at one site only. Trait turnover was higher prior to the invasion, although again only at one site. Disjunctive responses between species and trait turnover occurred, with the invader contributing in a nonrandom fashion to trait turnover. The lack of strong, consistent responses to the arrival and establishment of the invasive, and the decrease in trait turnover, suggests that effects of invasives are not only system- and species-dependent, but also depend on community dynamics of the invaded site, in particular the assembly processes, and historical context.
  • Yrttimaa, Tuomas; Luoma, Ville; Saarinen, Ninni; Kankare, Ville; Junttila, Samuli; Holopainen, Markus; Hyyppä, Juha; Vastaranta, Mikko (2020)
    Terrestrial laser scanning (TLS) has been adopted as a feasible technique to digitize trees and forest stands, providing accurate information on tree and forest structural attributes. However, there is limited understanding on how a variety of forest structural changes can be quantified using TLS in boreal forest conditions. In this study, we assessed the accuracy and feasibility of TLS inquantifying changes in the structure of boreal forests. We collected TLS data and field reference from 37 sample plots in 2014 (T1) and 2019 (T2). Tree stems typically have planar, vertical, and cylindricalcharacteristics in a point cloud, and thus we applied surface normal filtering, point cloud clustering, and RANSAC-cylinder filtering to identify these geometries and to characterize trees and foreststands at both time points. The results strengthened the existing knowledge that TLS has the capacity to characterize trees and forest stands in space and showed that TLS could characterize structural changes in time in boreal forest conditions. Root-mean-square-errors (RMSEs) in the estimates for changes in the tree attributes were 0.99–1.22 cm for diameter at breast height (∆dbh), 44.14–55.49 cm2 for basal area (∆g), and 1.91–4.85 m for tree height (∆h). In general, tree attributes were estimated more accurately for Scots pine trees, followed by Norway spruce and broadleaved trees. At the forest stand level, an RMSE of 0.60–1.13 cm was recorded for changes in basal area-weighted meandiameter (∆Dg), 0.81–2.26 m for changes in basal area-weighted mean height (∆Hg), 1.40–2.34 m2 /ha for changes in mean basal area (∆G), and 74–193 n/ha for changes in the number of trees per hectare (∆TPH). The plot-level accuracy was higher in Scots pine-dominated sample plots than in Norway spruce-dominated and mixed-species sample plots. TLS-derived tree and forest structural attributes at time points T1 and T2 differed significantly from each other (p < 0.05). If there was an increase or decrease in dbh, g, h, height of the crown base, crown ratio, Dg, Hg, or G recorded in the field, a similar outcome was achieved by using TLS. Our results provided new information on the feasibility of TLS for the purposes of forest ecosystem growth monitoring.