Browsing by Subject "UNCERTAINTY"

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  • Viskari, Toni; Laine, Maisa; Kulmala, Liisa; Mäkelä, Jarmo; Fer, Istem; Liski, Jari (2020)
    Model-calculated forecasts of soil organic carbon (SOC) are important for approximating global terrestrial carbon pools and assessing their change. However, the lack of detailed observations limits the reliability and applicability of these SOC projections. Here, we studied whether state data assimilation (SDA) can be used to continuously update the modeled state with available total carbon measurements in order to improve future SOC estimations. We chose six fallow test sites with measurement time series spanning 30 to 80 years for this initial test. In all cases, SDA improved future projections but to varying degrees. Furthermore, already including the first few measurements impacted the state enough to reduce the error in decades-long projections by at least 1 tCha(-1). Our results show the benefits of implementing SDA methods for forecasting SOC as well as highlight implementation aspects that need consideration and further research.
  • Nevalainen, Maisa Katariina; Vanhatalo, Jarno; Helle, Inari (2019)
    Risk of an Arctic oil spill has become a global matter of concern. Climate change induced opening of shipping routes increases the Arctic maritime traffic which exposes the area to negative impacts of potential maritime accidents. Still, quantitative analyses of the likely environmental impacts of such accidents are scarce, and our understanding of the uncertainties related to both accidents and their consequences is poor. There is an obvious need for analysis tools that allow us to systematically analyze the impacts of oil spills on Arctic species, so the risks can be taken into account when new sea routes or previously unexploited oil reserves are utilized. In this paper, an index‐based approach is developed to study exposure potential (described via probability of becoming exposed to spilled oil) and sensitivity (described via oil‐induced mortality and recovery) of Arctic biota in the face of an oil spill. First, a conceptual model presenting the relevant variables that contribute to exposure potential and sensitivity of key Arctic marine functional groups was built. Second, based on an extensive literature review, a probabilistic estimate was assigned for each variable, and the variables were combined to an index representing the overall vulnerability of Arctic biota. The resulting index can be used to compare the relative risk between functional groups and accident scenarios. Results indicate that birds have the highest vulnerability to spilled oil, and seals and whales the lowest. Polar bears’ vulnerability varies greatly between seasons, while ice seals’ vulnerability remains the same in every accident scenario. Exposure potential of most groups depends strongly on type of oil, whereas their sensitivity contains less variation.
  • LaMere, Kelsey; Mäntyniemi, Samu; Vanhatalo, Jarno; Haapasaari, Päivi (2020)
    Eliciting stakeholders’ mental models is an important participatory modeling (PM) tool for building systems knowledge, a frequent challenge in natural resource management. Therefore, mental models constitute a valu-able source of information, making it imperative to document them in detail, while preserving the integrity of stakeholders’ beliefs. We propose a methodology, the Rich Elicitation Approach (REA), which combines direct and indirect elicitation techniques to meet these goals. We describe the approach in the context of the effects of climate change on Baltic salmon. The REA produced holistic depictions of mental models, with more variables and causal relationships per diagram than direct elicitation alone, thus providing a solid knowledge base on which to begin PM studies. The REA was well received by stakeholders and fulfilled the substantive, normative, instrumental, and educational functions of PM. However, motivating stakeholders to confirm the accuracy of their models during the verification stage of the REA was challenging.
  • Jorcin, Pierre; Barthe, Laurent; Berroneau, Matthieu; Dore, Florian; Geniez, Philippe; Grillet, Pierre; Kabouche, Benjamin; Movia, Alexandre; Naimi, Babak; Pottier, Gilles; Thirion, Jean-Marc; Cheylan, Marc (2019)
    The Ocellated Lizard, Timon lepidus (Daudin 1802) occupies the Mediterranean regions of southwestern Europe (Portugal, Spain, France, and the extreme northwest of Italy). Over the last decades, a marked decline in its population has been observed, particularly on the northern edge of its distribution. As a result, it is currently considered a threatened species, especially in France and Italy. In France, a national action plan for its conservation has been put in place. In this study, ecological niche modelling (ENM) was carried out over the entire area of France in order to evaluate the species' potential distribution, more accurately define its ecological niche, guide future surveys, and inform land use planning so this species can be better taken into consideration. The modelling used data representing 2,757 observation points spread over the known range of the species, and 34 ecogeographical variables (climate, topography, and vegetation cover) were evaluated. After removing correlated variables, models were fitted with several combinations of variables using eight species distribution model (SDM) algorithms, and then their performance was assessed using three model accuracy metrics. Iterative trials changing the input variables were used to obtain the best model. The optimized model included nine determining variables. The results indicate the presence of this species is linked primarily to three climate variables: precipitation in the driest month, precipitation seasonality, and mean temperature in the driest quarter. The model was checked by a sample dataset that was not used to fit the model, and this validation dataset represented 25% of the overall field observations. Of the known occurrence locations kept aside to check the results, 94% fell within the presence area predicted by the modelled map with a presence probability greater than 0.7, and 90% fell within the area with a presence probability ranging from 0.8 to 1, which represents a very high predictive value. These results indicate that the models closely matched the observed distribution, suggesting a low impact of either geographical factors (barriers to dispersal), historical factors (dispersal process), or ecological factors (e.g., competition, trophic resources). The overlap between the predicted distribution and protected areas for this species reveals that less than 1% of the potential distribution area is protected by strong regulatory measures (e.g., national parks and natural reserves). The knowledge obtained in this study allows us to recommend some guidelines that would favor the conservation of this species.
  • Lötjönen, Sanna; Ollikainen, Markku; Kotamäki, Niina; Huttunen, Markus; Huttunen, Inese (2021)
    We examine how nutrient load compensation could help a firm expand its production when production is a source of nutrient loads, threatening the ecological status of a water body. We ask whether compensation is technically feasible and whether it can be made in an ecologically sustainable way. Credits for compensation may be provided by point or nonpoint sources. We apply our approach to the case of Finnish Lake Kallavesi, where the Supreme Administrative Court, based on the Water Framework Directive, refused an environmental permit for a plan to build a large pulp mill. We employ a lake nutrient response model to determine water quality using probabilistic analysis of the ecological status of the lake. The supply potential of phosphorus credits from point sources was too low to keep the lake in good ecological status with at least 80% probability and must be complemented by credits from agricultural nonpoint sources. Using a trade ratio of 1:1.2 to reflect uncertainty on credits from nonpoint sources suggests that the reduction in agricultural phosphorus loading would suffice on its own to ensure the good ecological status by 90% probability. The cost of buying nutrient reduction credits would be at most 2% of the investment.
  • Sihvonen, Matti Juhani; Hyytiäinen, Kari Petri; Valkama, Elena; Turtola, Eila (2018)
    Nitrogen (N) and phosphorus (P) are both essential plant nutrients. However, their joint response to plant growth is seldom described by models. This study provides an approach for modeling the joint impact of inorganic N and P fertilization on crop production, considering the P supplied by the soil, which was approximated using the soil test P (STP). We developed yield response models for Finnish spring barley crops (Hordeum vulgare L.) for clay and coarse-textured soils by using existing extensive experimental datasets and nonlinear estimation techniques. Model selection was based on iterative elimination from a wide diversity of plausible model formulations. The Cobb-Douglas type model specification, consisting of multiplicative elements, performed well against independent validation data, suggesting that the key relationships that determine crop responses are captured by the models. The estimated models were extended to dynamic economic optimization of fertilization inputs. According to the results, a fair STP level should be maintained on both coarse-textured soils (9.9 mg L-1 a(-1)) and clay soils (3.9 mg L-1 a(-1)). For coarse soils, a higher steady-state P fertilization rate is required (21.7 kg ha(-1) a(-1)) compared with clay soils (6.75 kg ha(-1) a(-1)). The steady-state N fertilization rate was slightly higher for clay soils (102.4 kg ha(-1) a(-1)) than for coarse soils (95.8 kg ha(-1) a(-1)). This study shows that the iterative elimination of plausible functional forms is a suitable method for reducing the effects of structural uncertainty on model output and optimal fertilization decisions.
  • GBD 2017 Population Fertility Coll (2018)
    Background Population estimates underpin demographic and epidemiological research and are used to track progress on numerous international indicators of health and development. To date, internationally available estimates of population and fertility, although useful, have not been produced with transparent and replicable methods and do not use standardised estimates of mortality. We present single-calendar year and single-year of age estimates of fertility and population by sex with standardised and replicable methods. Methods We estimated population in 195 locations by single year of age and single calendar year from 1950 to 2017 with standardised and replicable methods. We based the estimates on the demographic balancing equation, with inputs of fertility, mortality, population, and migration data. Fertility data came from 7817 location-years of vital registration data, 429 surveys reporting complete birth histories, and 977 surveys and censuses reporting summary birth histories. We estimated age-specific fertility rates (ASFRs; the annual number of livebirths to women of a specified age group per 1000 women in that age group) by use of spatiotemporal Gaussian process regression and used the ASFRs to estimate total fertility rates (TFRs; the average number of children a woman would bear if she survived through the end of the reproductive age span [age 10-54 years] and experienced at each age a particular set of ASFRs observed in the year of interest). Because of sparse data, fertility at ages 10-14 years and 50-54 years was estimated from data on fertility in women aged 15-19 years and 45-49 years, through use of linear regression. Age-specific mortality data came from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017 estimates. Data on population came from 1257 censuses and 761 population registry location-years and were adjusted for underenumeration and age misreporting with standard demographic methods. Migration was estimated with the GBD Bayesian demographic balancing model, after incorporating information about refugee migration into the model prior. Final population estimates used the cohort-cotnponent method of population projection, with inputs of fertility, mortality, and migration data. Population uncertainty was estimated by use of out-of-sample predictive validity testing. With these data, we estimated the trends in population by age and sex and in fertility by age between 1950 and 2017 in 195 countries and territories. Findings From 1950 to 2017, TFRs decreased by 49.4% (95% uncertainty interval [UI] 46.4-52.0). The TFR decreased from 4.7 livebirths (4.5-4.9) to 2.4 livebirths (2.2-2.5), and the ASFR of mothers aged 10-19 years decreased from 37 livebirths (34-40) to 22 livebirths (19-24) per 1000 women. Despite reductions in the TFR, the global population has been increasing by an average of 83.8 million people per year since 1985. The global population increased by 197-2% (193.3-200.8) since 1950, from 2.6 billion (2.5-2.6) to 7.6 billion (7.4-7.9) people in 2017; much of this increase was in the proportion of the global population in south Asia and sub-Saharan Africa. The global annual rate of population growth increased between 1950 and 1964, when it peaked at 2.0%; this rate then remained nearly constant until 1970 and then decreased to 1.1% in 2017. Population growth rates in the southeast Asia, east Asia, and Oceania GBD super-region decreased from 2.5% in 1963 to O7% in 2017, whereas in sub-Saharan Africa, population growth rates were almost at the highest reported levels ever in 2017, when they were at 2.7%. The global average age increased from 26.6 years in 1950 to 32.1 years in 2017, and the proportion of the population that is of working age (age 15-64 years) increased from 59.9% to 65.3%. At the national level, the TFR decreased in all countries and territories between 1950 and 2017; in 2017, TFRs ranged from a low of 1.0 livebirths (95% UI 0. 9-1.2) in Cyprus to a high of 7.1 livebirths (6.8-7.4) in Niger. The TFR under age 25 years (TFU25; number of livebirths expected by age 25 years for a hypothetical woman who survived the age group and was exposed to current ASFRs) in 2017 ranged from 0.08 livebirths (0.07-0.09) in South Korea to 2.4 livebirths (2.2-2.6) in Niger, and the TFR over age 30 years (I F030; number of livebirths expected for a hypothetical woman ageing from 30 to 54 years who survived the age group and was exposed to current ASFRs) ranged from a low of 0.3 livebirths (0.3-0-4) in Puerto Rico to a high of 3.1 livebirths (3.0-3.2) in Niger. TF030 was higher than TFU25 in 145 countries and territories in 2017.33 countries had a negative population growth rate from 2010 to 2017, most of which were located in central, eastern, and western Europe, whereas population growth rates of more than 2.0% were seen in 33 of 46 countries in sub-Saharan Africa. In 2017, less than 65% of the national population was of working age in 12 of 34 high-income countries, and less than 50% of the national population was of working age in Mali, Chad, and Niger. Interpretation Population trends create demographic dividends and headwinds (ie, economic benefits and detriments) that affect national economies and determine national planning needs. Although TFRs are decreasing, the global population continues to grow as mortality declines, with diverse patterns at the national level and across age groups. To our knowledge, this is the first study to provide transparent and replicable estimates of population and fertility, which can be used to inform decision making and to monitor progress. Copyright (C) 2018 The Author(s). Published by Elsevier Ltd.
  • Uusitalo, Ruut; Siljander, Mika; Culverwell, C. Lorna; Hendrickx, Guy; Linden, Andreas; Dub, Timothee; Aalto, Juha; Sane, Jussi; Marsboom, Cedric; Suvanto, Maija T.; Vajda, Andrea; Gregow, Hilppa; Korhonen, Essi M.; Huhtamo, Eili; Pellikka, Petri; Vapalahti, Olli (2021)
    Pogosta disease is a mosquito-borne infection, caused by Sindbis virus (SINV), which causes epidemics of febrile rash and arthritis in Northern Europe and South Africa. Resident grouse and migratory birds play a significant role as amplifying hosts and various mosquito species, including Aedes cinereus, Culex pipiens, Cx. torrentium and Culiseta morsitans are documented vectors. As specific treatments are not available for SINV infections, and joint symptoms may persist, the public health burden is considerable in endemic areas. To predict the environmental suitability for SINV infections in Finland, we applied a suite of geospatial and statistical modeling techniques to disease occurrence data. Using an ensemble approach, we first produced environmental suitability maps for potential SINV vectors in Finland. These suitability maps were then combined with grouse densities and environmental data to identify the influential determinants for SINV infections and to predict the risk of Pogosta disease in Finnish municipalities. Our predictions suggest that both the environmental suitability for vectors and the high risk of Pogosta disease are focused in geographically restricted areas. This provides evidence that the presence of both SINV vector species and grouse densities can predict the occurrence of the disease. The results support material for public-health officials when determining area-specific recommendations and deliver information to health care personnel to raise awareness of the disease among physicians.
  • Chazot, Nicolas; Wahlberg, Niklas; Lucci Freitas, Andre Victor; Mitter, Charles; Labandeira, Conrad; Sohn, Jae-Cheon; Sahoo, Ranjit Kumar; Seraphim, Noemy; de Jong, Rienk; Heikkilä, Maria (2019)
    The need for robust estimates of times of divergence is essential for downstream analyses, yet assessing this robustness is still rare. We generated a time-calibrated genus-level phylogeny of butterflies (Papilionoidea), including 994 taxa, up to 10 gene fragments and an unprecedented set of 12 fossils and 10 host-plant node calibration points. We compared marginal priors and posterior distributions to assess the relative importance of the former on the latter. This approach revealed a strong influence of the set of priors on the root age but for most calibrated nodes posterior distributions shifted from the marginal prior, indicating significant information in the molecular data set. Using a very conservative approach we estimated an origin of butterflies at 107.6 Ma, approximately equivalent to the latest Early Cretaceous, with a credibility interval ranging from 89.5 Ma (mid Late Cretaceous) to 129.5 Ma (mid Early Cretaceous). In addition, we tested the effects of changing fossil calibration priors, tree prior, different sets of calibrations and different sampling fractions but our estimate remained robust to these alternative assumptions. With 994 genera, this tree provides a comprehensive source of secondary calibrations for studies on butterflies.
  • Akl, Elie A.; Carrasco-Labra, Alonso; Brignardello-Petersen, Romina; Neumann, Ignacio; Johnston, Bradley C.; Sun, Xin; Briel, Matthias; Busse, Jason W.; Ebrahim, Shanil; Granados, Carlos E.; Iorio, Alfonso; Irfan, Affan; Martinez Garcia, Laura; Mustafa, Reem A.; Ramirez-Morera, Anggie; Selva, Anna; Sola, Ivan; Sanabria, Andrea Juliana; Tikkinen, Kari A. O.; Vandvik, Per O.; Vernooij, Robin W. M.; Zazueta, Oscar E.; Zhou, Qi; Guyatt, Gordon H.; Alonso-Coello, Pablo (2015)
    Objectives: To describe how systematic reviewers are reporting missing data for dichotomous outcomes, handling them in the analysis and assessing the risk of associated bias. Methods: We searched MEDLINE and the Cochrane Database of Systematic Reviews for systematic reviews of randomised trials published in 2010, and reporting a meta-analysis of a dichotomous outcome. We randomly selected 98 Cochrane and 104 non-Cochrane systematic reviews. Teams of 2 reviewers selected eligible studies and abstracted data independently and in duplicate using standardised, piloted forms with accompanying instructions. We conducted regression analyses to explore factors associated with using complete case analysis and with judging the risk of bias associated with missing participant data. Results: Of Cochrane and non-Cochrane reviews, 47% and 7% (p Conclusions: Though Cochrane reviews are somewhat less problematic, most Cochrane and non-Cochrane systematic reviews fail to adequately report and handle missing data, potentially resulting in misleading judgements regarding risk of bias.
  • Makela, Jarmo; Minunno, Francesco; Aalto, Tuula; Makela, Annikki; Markkanen, Tiina; Peltoniemi, Mikko (2020)
    Forest ecosystems are already responding to changing environmental conditions that are driven by increased atmospheric CO2 concentrations. These developments affect how societies can utilise and benefit from the woodland areas in the future, be it for example climate change mitigation as carbon sinks, lumber for wood industry, or preserved for nature tourism and recreational activities. We assess the effect and the relative magnitude of different uncertainty sources in ecosystem model simulations from the year 1980 to 2100 for two Finnish boreal forest sites. The models used in this study are the land ecosystem model JSBACH and the forest growth model PREBAS. The considered uncertainty sources for both models are model parameters and four prescribed climates with two RCP (representative concentration pathway) scenarios. Usually, model parameter uncertainty is not included in these types of uncertainty studies. PREBAS simulations also include two forest management scenarios. We assess the effect of these sources of variation at four different points in time on several ecosystem indicators, e.g. gross primary production (GPP), ecosystem respiration, soil moisture, recurrence of drought, length of the vegetation active period (VAP), length of the snow melting period and the stand volume. The uncertainty induced by the climate models remains roughly the same throughout the simulations and is overtaken by the RCP scenario impact halfway through the experiment. The management actions are the most dominant uncertainty factors for Hyytiala and as important as RCP scenarios at the end of the simulations, but they contribute only half as much for Sodankyla. The parameter uncertainty is the least influential of the examined uncertainty sources, but it is also the most elusive to estimate due to non-linear and adverse effects on the simulated ecosystem indicators. Our analysis underlines the importance of carefully considering the implementation of forest use when simulating future ecosystem conditions, as human impact is evident and even increasing in boreal forested regions.
  • Holmberg, Maria; Akujärvi, Anu; Anttila, Saku; Autio, Iida; Haakana, Markus; Junttila, Virpi; Karvosenoja, Niko; Kortelainen, Pirkko; Mäkelä, Annikki; Minkkinen, Kari; Minunno, Francesco; Rankinen, Katri; Ojanen, Paavo; Paunu, Ville-Veikko; Peltoniemi, Mikko; Rasilo, Terhi; Sallantaus, Tapani; Savolahti, Mikko; Tuominen, Sakari; Tuominen, Seppo; Vanhala, Pekka; Forsius, Martin (2021)
    Climate change mitigation is a global response that requires actions at the local level. Quantifying local sources and sinks of greenhouse gases (GHG) facilitate evaluating mitigation options. We present an approach to collate spatially explicit estimated fluxes of GHGs (carbon dioxide, methane and nitrous oxide) for main land use sectors in the landscape, to aggregate, and to calculate the net emissions of an entire region. Our procedure was developed and tested in a large river basin in Finland, providing information from intensively studied eLTER research sites. To evaluate the full GHG balance, fluxes from natural ecosystems (lakes, rivers, and undrained mires) were included together with fluxes from anthropogenic activities, agriculture and forestry. We quantified the fluxes based on calculations with an anthropogenic emissions model (FRES) and a forest growth and carbon balance model (PREBAS), as well as on emission coefficients from the literature regarding emissions from lakes, rivers, undrained mires, peat extraction sites and cropland. Spatial data sources included CORINE land use data, soil map, lake and river shorelines, national forest inventory data, and statistical data on anthropogenic activities. Emission uncertainties were evaluated with Monte Carlo simulations. Artificial surfaces were the most emission intensive land-cover class. Lakes and rivers were about as emission intensive as arable land. Forests were the dominant land cover in the region (66%), and the C sink of the forests decreased the total emissions of the region by 72%. The region's net emissions amounted to 4.37 ± 1.43 Tg CO2-eq yr−1, corresponding to a net emission intensity 0.16 Gg CO2-eq km−2 yr−1, and estimated per capita net emissions of 5.6 Mg CO2-eq yr−1. Our landscape approach opens opportunities to examine the sensitivities of important GHG fluxes to changes in land use and climate, management actions, and mitigation of anthropogenic emissions.
  • Aalto, J.; Karjalainen, O.; Hjort, J.; Luoto, M. (2018)
    Mean annual ground temperature (MAGT) and active layer thickness (ALT) are key to understanding the evolution of the ground thermal state across the Arctic under climate change. Here a statistical modeling approach is presented to forecast current and future circum-Arctic MAGT and ALT in relation to climatic and local environmental factors, at spatial scales unreachable with contemporary transient modeling. After deploying an ensemble of multiple statistical techniques, distance-blocked cross validation between observations and predictions suggested excellent and reasonable transferability of the MAGT and ALT models, respectively. The MAGT forecasts indicated currently suitable conditions for permafrost to prevail over an area of 15.1 +/- 2.8 x 10(6) km(2). This extent is likely to dramatically contract in the future, as the results showed consistent, but region-specific, changes in ground thermal regime due to climate change. The forecasts provide new opportunities to assess future Arctic changes in ground thermal state and biogeochemical feedback.
  • Holopainen, Sari; Arzel, Celine; Elmberg, Johan; Fox, Anthony D.; Guillemain, Matthieu; Gunnarsson, Gunnar; Nummi, Petri; Sjöberg, Kjell; Väänänen, Veli-Matti; Alhainen, Mikko; Pöysä, Hannu (2018)
    Eurasian migratory duck species represent a natural resource shared between European countries. As is evident throughout human harvest history, lack of coordinated management and monitoring at appropriate levels often leads to 'the tragedy of the commons', where shared populations suffer overexploitation. Effective management can also be hampered by poor understanding of the factors that limit and regulate migratory populations throughout their flyways, and over time. Following decades of population increase, some European duck populations now show signs of levelling off or even decline, underlining the need for more active and effective management. In Europe, the existing mechanisms for delivering effective management of duck populations are limited, despite the need and enthusiasm for establishing adaptive management (AM) schemes for wildlife populations. Existing international legal agreements already oblige European countries to sustainably manage migratory waterbirds. Although the lack of coordinated demographic and hunting data remains a challenge to sustainable management planning, AM provides a robust decision-making framework even in the presence of uncertainty regarding demographic and other information. In this paper we investigate the research and monitoring needs in Europe to successfully apply AM to ducks, and search for possible model species, focusing on freshwater species (in contrast to sea duck species) in the East Atlantic flyway. Based on current knowledge, we suggest that common teal Anas crecca, Eurasian wigeon Mareca penelope and common goldeneye Bucephala clangula represent the best species for testing the application of an AM muddling approach to duck populations in Europe. Applying AM to huntable species with relatively good population data as models for broader implementation represents a cost effective way of starting to develop AM on a European flyway scale for ducks, and potentially other waterbirds in the future.
  • Pastorello, Gilberto; Trotta, Carlo; Canfora, Eleonora; Chu, Housen; Christianson, Danielle; Cheah, You-Wei; Poindexter, Cristina; Chen, Jiquan; Elbashandy, Abdelrahman; Humphrey, Marty; Isaac, Peter; Polidori, Diego; Ribeca, Alessio; van Ingen, Catharine; Zhang, Leiming; Amiro, Brian; Ammann, Christof; Arain, M. Altaf; Ardo, Jonas; Arkebauer, Timothy; Arndt, Stefan K.; Arriga, Nicola; Aubinet, Marc; Aurela, Mika; Baldocchi, Dennis; Barr, Alan; Beamesderfer, Eric; Marchesini, Luca Belelli; Bergeron, Onil; Beringer, Jason; Bernhofer, Christian; Berveiller, Daniel; Billesbach, Dave; Black, Thomas Andrew; Blanken, Peter D.; Bohrer, Gil; Boike, Julia; Bolstad, Paul V.; Bonal, Damien; Bonnefond, Jean-Marc; Bowling, David R.; Bracho, Rosvel; Brodeur, Jason; Bruemmer, Christian; Buchmann, Nina; Burban, Benoit; Burns, Sean P.; Buysse, Pauline; Cale, Peter; Cavagna, Mauro; Cellier, Pierre; Chen, Shiping; Chini, Isaac; Christensen, Torben R.; Cleverly, James; Collalti, Alessio; Consalvo, Claudia; Cook, Bruce D.; Cook, David; Coursolle, Carole; Cremonese, Edoardo; Curtis, Peter S.; D'Andrea, Ettore; da Rocha, Humberto; Dai, Xiaoqin; Davis, Kenneth J.; De Cinti, Bruno; de Grandcourt, Agnes; De Ligne, Anne; De Oliveira, Raimundo C.; Delpierre, Nicolas; Desai, Ankur R.; Di Bella, Carlos Marcelo; di Tommasi, Paul; Dolman, Han; Domingo, Francisco; Dong, Gang; Dore, Sabina; Duce, Pierpaolo; Dufrene, Eric; Dunn, Allison; Dusek, Jiri; Eamus, Derek; Eichelmann, Uwe; ElKhidir, Hatim Abdalla M.; Eugster, Werner; Ewenz, Cacilia M.; Ewers, Brent; Famulari, Daniela; Fares, Silvano; Feigenwinter, Iris; Feitz, Andrew; Fensholt, Rasmus; Filippa, Gianluca; Fischer, Marc; Frank, John; Galvagno, Marta; Gharun, Mana; Gianelle, Damiano; Gielen, Bert; Gioli, Beniamino; Gitelson, Anatoly; Goded, Ignacio; Goeckede, Mathias; Goldstein, Allen H.; Gough, Christopher M.; Goulden, Michael L.; Graf, Alexander; Griebel, Anne; Gruening, Carsten; Gruenwald, Thomas; Hammerle, Albin; Han, Shijie; Han, Xingguo; Hansen, Birger Ulf; Hanson, Chad; Hatakka, Juha; He, Yongtao; Hehn, Markus; Heinesch, Bernard; Hinko-Najera, Nina; Hoertnagl, Lukas; Hutley, Lindsay; Ibrom, Andreas; Ikawa, Hiroki; Jackowicz-Korczynski, Marcin; Janous, Dalibor; Jans, Wilma; Jassal, Rachhpal; Jiang, Shicheng; Kato, Tomomichi; Khomik, Myroslava; Klatt, Janina; Knohl, Alexander; Knox, Sara; Kobayashi, Hideki; Koerber, Georgia; Kolle, Olaf; Kosugi, Yoshiko; Kotani, Ayumi; Kowalski, Andrew; Kruijt, Bart; Kurbatova, Julia; Kutsch, Werner L.; Kwon, Hyojung; Launiainen, Samuli; Laurila, Tuomas; Law, Bev; Leuning, Ray; Li, Yingnian; Liddell, Michael; Limousin, Jean-Marc; Lion, Marryanna; Liska, Adam J.; Lohila, Annalea; Lopez-Ballesteros, Ana; Lopez-Blanco, Efren; Loubet, Benjamin; Loustau, Denis; Lucas-Moffat, Antje; Lueers, Johannes; Ma, Siyan; Macfarlane, Craig; Magliulo, Vincenzo; Maier, Regine; Mammarella, Ivan; Manca, Giovanni; Marcolla, Barbara; Margolis, Hank A.; Marras, Serena; Massman, William; Mastepanov, Mikhail; Matamala, Roser; Matthes, Jaclyn Hatala; Mazzenga, Francesco; McCaughey, Harry; McHugh, Ian; McMillan, Andrew M. S.; Merbold, Lutz; Meyer, Wayne; Meyers, Tilden; Miller, Scott D.; Minerbi, Stefano; Moderow, Uta; Monson, Russell K.; Montagnani, Leonardo; Moore, Caitlin E.; Moors, Eddy; Moreaux, Virginie; Moureaux, Christine; Munger, J. William; Nakai, Taro; Neirynck, Johan; Nesic, Zoran; Nicolini, Giacomo; Noormets, Asko; Northwood, Matthew; Nosetto, Marcelo; Nouvellon, Yann; Novick, Kimberly; Oechel, Walter; Olesen, Jorgen Eivind; Ourcival, Jean-Marc; Papuga, Shirley A.; Parmentier, Frans-Jan; Paul-Limoges, Eugenie; Pavelka, Marian; Peichl, Matthias; Pendall, Elise; Phillips, Richard P.; Pilegaard, Kim; Pirk, Norbert; Posse, Gabriela; Powell, Thomas; Prasse, Heiko; Prober, Suzanne M.; Rambal, Serge; Rannik, Ullar; Raz-Yaseef, Naama; Reed, David; de Dios, Victor Resco; Restrepo-Coupe, Natalia; Reverter, Borja R.; Roland, Marilyn; Sabbatini, Simone; Sachs, Torsten; Saleska, Scott R.; Sanchez-Canete, Enrique P.; Sanchez-Mejia, Zulia M.; Schmid, Hans Peter; Schmidt, Marius; Schneider, Karl; Schrader, Frederik; Schroder, Ivan; Scott, Russell L.; Sedlak, Pavel; Serrano-Ortiz, Penelope; Shao, Changliang; Shi, Peili; Shironya, Ivan; Siebicke, Lukas; Sigut, Ladislav; Silberstein, Richard; Sirca, Costantino; Spano, Donatella; Steinbrecher, Rainer; Stevens, Robert M.; Sturtevant, Cove; Suyker, Andy; Tagesson, Torbern; Takanashi, Satoru; Tang, Yanhong; Tapper, Nigel; Thom, Jonathan; Tiedemann, Frank; Tomassucci, Michele; Tuovinen, Juha-Pekka; Urbanski, Shawn; Valentini, Riccardo; van der Molen, Michiel; van Gorsel, Eva; van Huissteden, Ko; Varlagin, Andrej; Verfaillie, Joseph; Vesala, Timo; Vincke, Caroline; Vitale, Domenico; Vygodskaya, Natalia; Walker, Jeffrey P.; Walter-Shea, Elizabeth; Wang, Huimin; Weber, Robin; Westermann, Sebastian; Wille, Christian; Wofsy, Steven; Wohlfahrt, Georg; Wolf, Sebastian; Woodgate, William; Li, Yuelin; Zampedri, Roberto; Zhang, Junhui; Zhou, Guoyi; Zona, Donatella; Agarwal, Deb; Biraud, Sebastien; Torn, Margaret; Papale, Dario (2020)
    The FLUXNET2015 dataset provides ecosystem-scale data on CO2, water, and energy exchange between the biosphere and the atmosphere, and other meteorological and biological measurements, from 212 sites around the globe (over 1500 site-years, up to and including year 2014). These sites, independently managed and operated, voluntarily contributed their data to create global datasets. Data were quality controlled and processed using uniform methods, to improve consistency and intercomparability across sites. The dataset is already being used in a number of applications, including ecophysiology studies, remote sensing studies, and development of ecosystem and Earth system models. FLUXNET2015 includes derived-data products, such as gap-filled time series, ecosystem respiration and photosynthetic uptake estimates, estimation of uncertainties, and metadata about the measurements, presented for the first time in this paper. In addition, 206 of these sites are for the first time distributed under a Creative Commons (CC-BY 4.0) license. This paper details this enhanced dataset and the processing methods, now made available as open-source codes, making the dataset more accessible, transparent, and reproducible.
  • Rahikainen, Mika; Helle, Inari; Haapasaari, Paivi; Oinonen, Soile; Kuikka, Sakari; Vanhatalo, Jarno; Mantyniemi, Samu; Hoviniemi, Kirsi-Maaria (2014)
  • Burner, Ryan C.; Stephan, Jorg G.; Drag, Lukas; Birkemoe, Tone; Muller, Joerg; Snäll, Tord; Ovaskainen, Otso; Potterf, Maria; Siitonen, Juha; Skarpaas, Olav; Doerfler, Inken; Gossner, Martin M.; Schall, Peter; Weisser, Wolfgang W.; Sverdrup-Thygeson, Anne (2021)
    Aim The aim of this study was to investigate the role of traits in beetle community assembly and test for consistency in these effects among several bioclimatic regions. We asked (1) whether traits predicted species' responses to environmental gradients (i.e. their niches), (2) whether these same traits could predict co-occurrence patterns and (3) how consistent were niches and the role of traits among study regions. Location Boreal forests in Norway and Finland, temperate forests in Germany. Taxon Wood-living (saproxylic) beetles. Methods We compiled capture records of 468 wood-living beetle species from the three regions, along with nine morphological and ecological species traits. Eight climatic and forest covariates were also collected. We used Bayesian hierarchical joint species distribution models to estimate the influence of traits and phylogeny on species' niches. We also tested for correlations between species associations and trait similarity. Finally, we compared species niches and the effects of traits among study regions. Results Traits explained some of the variability in species' niches, but their effects differed among study regions. However, substantial phylogenetic signal in species niches implies that unmeasured but phylogenetically structured traits have a stronger effect. Degree of trait similarity was correlated with species associations but depended idiosyncratically on the trait and region. Species niches were much more consistent-widespread taxa often responded similarly to an environmental gradient in each region. Main conclusions The inconsistent effects of traits among regions limit their current use in understanding beetle community assembly. Phylogenetic signal in niches, however, implies that better predictive traits can eventually be identified. Consistency of species niches among regions means niches may remain relatively stable under future climate and land use changes; this lends credibility to predictive distribution models based on future climate projections but may imply that species' scope for short-term adaptation is limited.
  • Tao, Fulu; Palosuo, Taru; Rötter, Reimund P.; Díaz-Ambrona, Carlos Gregorio Hernández; Inés Mínguez, M.; Semenov, Mikhail A.; Kersebaum, Kurt Christian; Cammarano, Davide; Specka, Xenia; Nendel, Claas; Srivastava, Amit Kumar; Ewert, Frank; Padovan, Gloria; Ferrise, Roberto; Martre, Pierre; Rodríguez, Lucía; Ruiz-Ramos, Margarita; Gaiser, Thomas; Höhn, Jukka G.; Salo, Tapio; Dibari, Camilla; Schulman, Alan H. (2020)
    Robust projections of climate impact on crop growth and productivity by crop models are key to designing effective adaptations to cope with future climate risk. However, current crop models diverge strongly in their climate impact projections. Previous studies tried to compare or improve crop models regarding the impact of one single climate variable. However, this approach is insufficient, considering that crop growth and yield are affected by the interactive impacts of multiple climate change factors and multiple interrelated biophysical processes. Here, a new comprehensive analysis was conducted to look holistically at the reasons why crop models diverge substantially in climate impact projections and to investigate which biophysical processes and knowledge gaps are key factors affecting this uncertainty and should be given the highest priorities for improvement. First, eight barley models and eight climate projections for the 2050s were applied to investigate the uncertainty from crop model structure in climate impact projections for barley growth and yield at two sites: Jokioinen, Finland (Boreal) and Lleida, Spain (Mediterranean). Sensitivity analyses were then conducted on the responses of major crop processes to major climatic variables including temperature, precipitation, irradiation, and CO2, as well as their interactions, for each of the eight crop models. The results showed that the temperature and CO2 relationships in the models were the major sources of the large discrepancies among the models in climate impact projections. In particular, the impacts of increases in temperature and CO2 on leaf area development were identified as the major causes for the large uncertainty in simulating changes in evapotranspiration, above-ground biomass, and grain yield. Our findings highlight that advancements in understanding the basic processes and thresholds by which climate warming and CO2 increases will affect leaf area development, crop evapotranspiration, photosynthesis, and grain formation in contrasting environments are needed for modeling their impacts.