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  • 1.
    Edler, Daniel
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för fysik.
    Klein, Johannes
    Antonelli, Alexandre
    Silvestro, Daniele
    raxmlGUI 2.0: A graphical interface and toolkit for phylogenetic analyses using RAxML2021Ingår i: Methods in Ecology and Evolution, E-ISSN 2041-210X, Vol. 12, nr 2, s. 373-377Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    raxmlGUI is a graphical user interface to RAxML, one of the most popular and widely used softwares for phylogenetic inference using maximum likelihood. Here we present raxmlGUI 2.0, a complete rewrite of the GUI which seamlessly integrates RAxML binaries for all major operating systems with an intuitive graphical front-end to setup and run phylogenetic analyses. Our program offers automated pipelines for analyses that require multiple successive calls of RAxML, built-in functions to concatenate alignment files while automatically specifying the appropriate partition settings, and one-click model testing to select the best substitution models using ModelTest-NG. In addition to RAxML 8.x, raxmlGUI 2.0 also supports the new RAxML-NG, which provides new functionality and higher performance on large datasets. raxmlGUI 2.0 facilitates phylogenetic analyses by coupling an intuitive interface with the unmatched performance of RAxML.

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  • 2.
    Ekström, Magnus
    et al.
    Umeå universitet, Samhällsvetenskapliga fakulteten, Handelshögskolan vid Umeå universitet, Statistik. Department of Forest Resource Management, Swedish University of Agricultural Sciences, Umeå, Sweden.
    Sandring, Saskia
    Department of Forest Resource Management, Swedish University of Agricultural Sciences, Umeå, Sweden.
    Grafström, Anton
    Department of Forest Resource Management, Swedish University of Agricultural Sciences, Umeå, Sweden.
    Esseen, Per-Anders
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för ekologi, miljö och geovetenskap.
    Jonsson, Bengt Gunnar
    Department of Natural Sciences, Mid Sweden University, Sundsvall, Sweden.
    Ståhl, Göran
    Department of Forest Resource Management, Swedish University of Agricultural Sciences, Umeå, Sweden.
    Estimating density from presence/absence data in clustered populations2020Ingår i: Methods in Ecology and Evolution, E-ISSN 2041-210X, Vol. 11, nr 3, s. 390-402Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Inventories of plant populations are fundamental in ecological research and monitoring, but such surveys are often prone to field assessment errors. Presence/absence (P/A) sampling may have advantages over plant cover assessments for reducing such errors. However, the linking between P/A data and plant density depends on model assumptions for plant spatial distributions. Previous studies have shown, for example, how that plant density can be estimated under Poisson model assumptions on the plant locations. In this study, new methods are developed and evaluated for linking P/A data with plant density assuming that plants occur in clustered spatial patterns. New theory was derived for estimating plant density under Neyman-Scott-type cluster models such as the Matern and Thomas cluster processes. Suggested estimators, corresponding confidence intervals and a proposed goodness-of-fit test were evaluated in a Monte Carlo simulation study assuming a Matern cluster process. Furthermore, the estimators were applied to plant data from environmental monitoring in Sweden to demonstrate their empirical application. The simulation study showed that our methods work well for large enough sample sizes. The judgment of what is' large enough' is often difficult, but simulations indicate that a sample size is large enough when the sampling distributions of the parameter estimators are symmetric or mildly skewed. Bootstrap may be used to check whether this is true. The empirical results suggest that the derived methodology may be useful for estimating density of plants such as Leucanthemum vulgare and Scorzonera humilis. By developing estimators of plant density from P/A data under realistic model assumptions about plants' spatial distributions, P/A sampling will become a more useful tool for inventories of plant populations. Our new theory is an important step in this direction.

  • 3. Falster, Daniel S.
    et al.
    FitzJohn, Richard G.
    Brännström, Åke
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik. Evolution and Ecology Program, International Institutefor Applied Systems Analysis, Schlossplatz 1, A-2361 Laxen burg, Au stria.
    Dieckmann, Ulf
    Westoby, Mark
    plant: A package for modelling forest trait ecology and evolution2016Ingår i: Methods in Ecology and Evolution, E-ISSN 2041-210X, Vol. 7, nr 2, s. 136-146Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Population dynamics in forests are strongly size-structured: larger plants shade smaller plants while also expending proportionately more energy on building and maintaining woody stems. Although the importance of size structure for demography is widely recognized, many models either omit it entirely or include only coarse approximations. Here, we introduce the plant package, an extensible framework for modelling size- and trait-structured demography, ecology and evolution in simulated forests. At its core, plant is an individual-based model where plant physiology and demography are mediated by traits. Individual plants from multiple species can be grown in isolation, in patches of competing plants or in metapopulations under a disturbance regime. These dynamics can be integrated into metapopulation-level estimates of invasion fitness and vegetation structure. Because fitness emerges as a function of traits, plant provides a novel arena for exploring eco-evolutionary dynamics. plant is an open source R package and is available at . Accessed from R, the core routines in plant are written in C++. The package provides for alternative physiologies and for capturing trade-offs among parameters. A detailed test suite is provided to ensure correct behaviour of the code. plant provides a transparent platform for investigating how physiological rules and functional trade-offs interact with competition and disturbance regimes to influence vegetation demography, structure and diversity.

  • 4.
    Farage, Carmel
    et al.
    Department of Life Sciences, Ben-Gurion University of the Negev, Beer-Sheva, Israel.
    Edler, Daniel
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för fysik. Gothenburg Global Biodiversity Centre, Gothenburg, Sweden; Department of Biological and Environmental Sciences, University of Gothenburg, Gothenburg, Sweden.
    Eklöf, Anna
    Division of Theoretical Biology, Department of Physics, Chemistry and Biology, Linköping University, Linköping, Sweden.
    Rosvall, Martin
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för fysik.
    Pilosof, Shai
    Department of Life Sciences, Ben-Gurion University of the Negev, Beer-Sheva, Israel.
    Identifying flow modules in ecological networks using Infomap2021Ingår i: Methods in Ecology and Evolution, E-ISSN 2041-210X, Vol. 12, nr 5, s. 778-786Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Analysing how species interact in modules is a fundamental problem in network ecology. Theory shows that a modular network structure can reveal underlying dynamic ecological and evolutionary processes, influence dynamics that operate on the network and affect the stability of the ecological system. Although many ecological networks describe flows, such as biomass flows in food webs or disease transmission, most modularity analyses have ignored network flows, which can hinder our understanding of the interplay between structure and dynamics. Here we present Infomap, an established method based on network flows to the field of ecological networks. Infomap is a flexible tool that can identify modules in virtually any type of ecological network and is particularly useful for directed, weighted and multilayer networks. We illustrate how Infomap works on all these network types. We also provide a fully documented repository with additional ecological examples. Finally, to help researchers to analyse their networks with Infomap, we introduce the open-source R package infomapecology. Analysing flow-based modularity is useful across ecology and transcends to other biological and non-biological disciplines. A dynamic approach for detecting modular structure has strong potential to provide new insights into the organisation of ecological networks.

  • 5. Keuskamp, Joost A.
    et al.
    Dingemans, Bas J. J.
    Lehtinen, Taru
    Sarneel, Judith M.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för ekologi, miljö och geovetenskap. Aquatic Ecology, Netherlands Institute of Ecology (NIOO-KNAW), Wageningen, The Netherlands.
    Hefting, Mariet M.
    Tea Bag Index: a novel approach to collect uniform decomposition data across ecosystems2013Ingår i: Methods in Ecology and Evolution, E-ISSN 2041-210X, Vol. 4, nr 11, s. 1070-1075Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    1. Changes in the balance between soil carbon storage and release can significantly amplify or attenuate global warming. Although a lot of progress has been made in determining potential drivers of carbon release through large-scale decomposition experiments, climate predictions are still hampered by data limitation at a global scale as a result of high effort and measurement costs of comparative litter decomposition studies.

    2. We introduce an innovative, cost-effective, well-standardised method to gather data on decomposition rate and litter stabilisation using commercially available tea bags as standardised test kits. By using two tea types with contrasting decomposability, we can construct a decomposition curve using a single measurement in time. The acquired Tea Bag Index (TBI) consists of two parameters describing decomposition rate (k) and litter stabilisation factor (S).

    3. The method was tested for its sensitivity and robustness in contrasting ecosystems and biomes, confirming that the TBI is sensitive enough to discriminate between these systems. Within an ecosystem, TBI is responsive to differences in abiotic circumstances such as soil temperature and moisture content. The collected k and S values are in accordance with expectations based on decomposition process literature. They are therefore interpretable within the current knowledge framework.

    4. Tea Bag Index is a unique, multifunctional method requiring few resources and minimal prior knowledge. The standardisation and simplicity of the method make it possible to collect comparable, globally distributed data through crowdsourcing. TBI can further provide an excellent decomposition reference and has the potential to increase reliability of soil carbon flux estimates based on extrapolations of decomposition data.

  • 6.
    Krab, Eveline J
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för ekologi, miljö och geovetenskap. Department of Ecological Science, Faculty of Earth and Life Sciences, Amsterdam, The Netherlands.
    Cornelissen, Johannes H C
    Berg, Matty P
    A simple experimental set-up to disentangle the effects of altered temperature and moisture regimes on soil organisms2015Ingår i: Methods in Ecology and Evolution, E-ISSN 2041-210X, Vol. 6, nr 10, s. 1159-1168Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Climate manipulation experiments in the field and laboratory incubations are common methods to study the impact of climate change on soils and their biota. However, both types of methods have drawbacks either on their mechanistic interpretation or ecological relevance. We propose an experimental set-up that combines the best of both methods and can be easily obtained by modifying widely available Tullgren soil fauna extractors. This set-up creates or alters temperature and moisture gradients within intact field soil cores, after which soil biota, their activity and vertical movements can be studied. We assessed the performance and demonstrated the applicability of this set-up through a case study on Collembola response to changes in microclimatic gradients in peat bogs. Warming created a vertical temperature gradient of 14 degrees C in peat cores without varying soil moisture conditions, while at a given temperature regime, precipitation and drought treatments shifted natural soil moisture gradients to 'wetter' and 'drier', respectively. This allowed for disentangling interacting warming and moisture effects on soil fauna. In our case study, Collembola communities showed peat layer-specific responses to these climate treatments. Warming decreased Collembola density and altered community composition in the shallowest layer, whereas precipitation increase affected Collembola community composition in the deepest layer. We showed that climate change can have layer-specific effects on soil organisms that are 'hidden' by not taking microclimatic vertical gradients into account. This experimental set-up facilitates studying (multitrophic) organism responses to climate changes, with only a small adjustment of equipment that is often already present in soil ecology laboratories. Moreover, this set-up can be easily customized to study many more other research questions related to wide-ranging organisms and ecosystems.

  • 7.
    Olajos, Fredrik
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för ekologi, miljö och geovetenskap.
    Bokma, Folmer
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för ekologi, miljö och geovetenskap.
    Bartels, Pia
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för ekologi, miljö och geovetenskap.
    Myrstener, Erik
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för ekologi, miljö och geovetenskap.
    Rydberg, Johan
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för ekologi, miljö och geovetenskap.
    Öhlund, Gunnar
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för ekologi, miljö och geovetenskap.
    Bindler, Richard
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för ekologi, miljö och geovetenskap.
    Wang, Xiao-Ru
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för ekologi, miljö och geovetenskap.
    Zale, Rolf
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för ekologi, miljö och geovetenskap.
    Englund, Göran
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för ekologi, miljö och geovetenskap.
    Estimating species colonization dates using DNA in lake sediment2018Ingår i: Methods in Ecology and Evolution, E-ISSN 2041-210X, Vol. 9, nr 3, s. 535-543Artikel i tidskrift (Refereegranskat)
    Abstract [en]
    1. Detection of DNA in lake sediments holds promise as a tool to study processes like extinction, colonization, adaptation and evolutionary divergence. However, low concentrations make sediment DNA difficult to detect, leading to high false negative rates. Additionally, contamination could potentially lead to high false positive rates. Careful laboratory procedures can reduce false positive and negative rates, but should not be assumed to completely eliminate them. Therefore, methods are needed that identify potential false positive and negative results, and use this information to judge the plausibility of different interpretations of DNA data from natural archives.
    2. We developed a Bayesian algorithm to infer the colonization history of a species using records of DNA from lake-sediment cores, explicitly labelling some observations as false positive or false negative. We illustrate the method by analysing DNA of whitefish (Coregonus lavaretus L.) from sediment cores covering the past 10,000 years from two central Swedish lakes. We provide the algorithm as an R-script, and the data from this study as example input files.
    3. In one lake, Stora Lögdasjön, where connectivity with the proto-Baltic Sea and the degree of whitefish ecotype differentiation suggested colonization immediately after deglaciation, DNA was indeed successfully recovered and amplified throughout the post-glacial sediment. For this lake, we found no loss of detection probability over time, but a high false negative rate. In the other lake, Hotagen, where connectivity and ecotype differentiation suggested colonization long after deglaciation, DNA was amplified only in the upper part of the sediment, and colonization was estimated at 2,200 bp based on the assumption that successful amplicons represent whitefish presence. Here the earliest amplification represents a false positive with a posterior probability of 41%, which increases the uncertainty in the estimated time of colonization.
    4. Complementing careful laboratory procedures aimed at preventing contamination, our method estimates contamination rates from the data. By combining these results with estimates of false negative rates, our models facilitate unbiased interpretation of data from natural DNA archives.
  • 8.
    Pontarp, Mikael
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för ekologi, miljö och geovetenskap. Department of Biology, Lund University, Lund, Sweden; Department of Evolutionary Biology and Environmental Studies, University of Zurich, Zurich, Switzerland.
    Brännström, Åke
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik. Evolution and Ecology Program,International Institute for Applied Systems Analysis (IIASA), Laxenburg, Austria.
    Petchey, Owen L.
    Inferring community assembly processes from macroscopic patterns using dynamic eco-evolutionary models and Approximate Bayesian Computation (ABC)2019Ingår i: Methods in Ecology and Evolution, E-ISSN 2041-210X, Vol. 10, nr 4, s. 450-460Artikel, forskningsöversikt (Refereegranskat)
    Abstract [en]

    Statistical techniques exist for inferring community assembly processes from community patterns. Habitat filtering, competition, and biogeographical effects have, for example, been inferred from signals in phenotypic and phylogenetic data. The usefulness of current inference techniques is, however, debated as a mechanistic and causal link between process and pattern is often lacking, and evolutionary processes and trophic interactions are ignored.

    Here, we revisit the current knowledge on community assembly across scales and, in line with several reviews that have outlined challenges associated with current inference techniques, we identify a discrepancy between the current paradigm of eco-evolutionary community assembly and current inference techniques that focus mainly on competition and habitat filtering. We argue that trait-based dynamic eco-evolutionary models in combination with recently developed model fitting and model evaluation techniques can provide avenues for more accurate, reliable, and inclusive inference. To exemplify, we implement a trait-based, spatially explicit eco-evolutionary model and discuss steps of model modification, fitting, and evaluation as an iterative approach enabling inference from diverse data sources.

    Through a case study on inference of prey and predator niche width in an eco-evolutionary context, we demonstrate how inclusive and mechanistic approaches-eco-evolutionary modelling and Approximate Bayesian Computation (ABC)-can enable inference of assembly processes that have been largely neglected by traditional techniques despite the ubiquity of such processes.

    Much literature points to the limitations of current inference techniques, but concrete solutions to such limitations are few. Many of the challenges associated with novel inference techniques are, however, already to some extent resolved in other fields and thus ready to be put into action in a more formal way for inferring processes of community assembly from signals in various data sources.

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  • 9.
    Rodriguez, Alvaro
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för fysik.
    Zhang, Hanqing
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för fysik.
    Klaminder, Jonatan
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för ekologi, miljö och geovetenskap.
    Brodin, Tomas
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för ekologi, miljö och geovetenskap.
    Andersson, Patrik L.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Kemiska institutionen.
    Andersson, Magnus
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för fysik.
    ToxTrac: a fast and robust software for tracking organisms2018Ingår i: Methods in Ecology and Evolution, E-ISSN 2041-210X, Vol. 9, nr 3, s. 460-464Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    1. Behavioral analysis based on video recording is becoming increasingly popular within research fields such as; ecology, medicine, ecotoxicology, and toxicology. However, the programs available to analyze the data, which are; free of cost, user-friendly, versatile, robust, fast and provide reliable statistics for different organisms (invertebrates, vertebrates and mammals) are significantly limited.

    2. We present an automated open-source executable software (ToxTrac) for image-based tracking that can simultaneously handle several organisms monitored in a laboratory environment. We compare the performance of ToxTrac with current accessible programs on the web.

    3. The main advantages of ToxTrac are: i) no specific knowledge of the geometry of the tracked bodies is needed; ii) processing speed, ToxTrac can operate at a rate >25 frames per second in HD videos using modern computers; iii) simultaneous tracking of multiple organisms in multiple arenas; iv) integrated distortion correction and camera calibration; v) robust against false positives; vi) preservation of individual identification; vii) useful statistics and heat maps in real scale are exported in image, text and excel formats.

    4. ToxTrac can be used for high speed tracking of insects, fish, rodents or other species, and provides useful locomotor information in animal behavior experiments. Download ToxTrac here: https://toxtrac.sourceforge.io  (Current version v2.61).

  • 10.
    Ståhl, Göran
    et al.
    Department of Forest Resource Management, SwedishUniversity of Agricultural Sciences, SE 901 83 Umeå, Sweden.
    Ekström, Magnus
    Umeå universitet, Samhällsvetenskapliga fakulteten, Handelshögskolan vid Umeå universitet, Statistik.
    Dahlgren, Jonas
    Department of Forest Resource Management, SwedishUniversity of Agricultural Sciences, SE 901 83 Umeå, Sweden.
    Esseen, Per-Anders
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för ekologi, miljö och geovetenskap.
    Grafström, Anton
    Department of Forest Resource Management, SwedishUniversity of Agricultural Sciences, SE 901 83 Umeå, Sweden.
    Jonsson, Bengt-Gunnar
    Department of Natural Sciences, Mid-Sweden University, SE 851 70 Sundsvall, Sweden.
    Informative plot sizes in presence-absence sampling of forest floor vegetation2017Ingår i: Methods in Ecology and Evolution, E-ISSN 2041-210X, Vol. 8, nr 10, s. 1284-1291Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    1. Plant communities are attracting increased interest in connection with forest and landscape inventories due to society’s interest in ecosystem services. However, the acquisition of accurate information about plant communities poses several methodological challenges. Here, we investigate the use of presence-absence sampling with the aim to monitor state and change in plant density. We study what plot sizes are informative, i.e. the estimators should have as high precision as possible.

    2. Plant occurrences were modelled through different Poisson processes and tests were developed for assessing the plausibility of the model assumptions. Optimum plot sizes were determined by minimizing the variance of the estimators. While state estimators of similar kind as ours have been proposed in previous studies, our tests and change estimation procedures are new.

    3. We found that the most informative plot size for state estimation is 1.6 divided by the plant density, i.e. if the true density is 1 plant per square metre the optimum plot size is 1.6 square metres. This is in accordance with previous findings. More importantly, the most informative plot size for change estimation was smaller and depended on the change patterns. We provide theoretical results as well as some empirical results based on data from the Swedish National Forest Inventory.

    4. Use of too small or too large plots resulted in poor precision of the density (and density change) estimators. As a consequence, a range of different plot sizes would be required for jointly monitoring both common and rareplants using presence-absence sampling in monitoring programmes.

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  • 11. Ståhl, Göran
    et al.
    Ekström, Magnus
    Umeå universitet, Samhällsvetenskapliga fakulteten, Handelshögskolan vid Umeå universitet, Statistik. Department of Forest Resource Management, Swedish University of Agricultural Sciences, Umeå, Sweden.
    Dahlgren, Jonas
    Esseen, Per-Anders
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för ekologi, miljö och geovetenskap.
    Grafström, Anton
    Jonsson, Bengt-Gunnar
    Presence-absence sampling for estimating plant density using survey data with variable plot size2020Ingår i: Methods in Ecology and Evolution, E-ISSN 2041-210X, Vol. 11, nr 4, s. 580-590Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Presence–absence sampling is an important method for monitoring state and change of both individual plant species and communities. With this method, only the presence or absence of the target species is recorded on plots and thus the method is straightforward to apply and less prone to surveyor judgement compared to other vegetation monitoring methods. However, in the basic setting, all plots must be equally large or otherwise it is unclear how data should be analysed. In this study, we propose and evaluate five different methods for estimating plant density based on presence–absence registrations from surveys with variable plot sizes.

    Using artificial plant population data as well as empirical data from the Swedish National Forest Inventory, we evaluated the performance of the proposed methods. The main analysis was conducted through sampling simulation in artificial populations, whereby bias and variance of density estimators for the different methods were quantified and compared.

    Both for state and change estimation of plant density, we found that the best method to handle variable plot size was to perform generalized least squares regression, using plot size as an independent variable. Methods where plots smaller than a certain threshold were excluded or their registrations recalculated were, however, almost as good. Using all registrations as if they were obtained from plots with the nominal plot size resulted in substantial bias.

    Our findings are important for plant population studies in a wide range of environmental monitoring programmes. In these programmes, plots are typically randomly laid out and may be located across boundaries between different land‐use or land‐cover classes, resulting in subplots of variable size. Such splitting of plots is common when large plots are used, for example, with the 100 m2 plots used in the Swedish National Forest Inventory. Our methods overcome problems to estimate plant density from presence–absence data observed in plots that vary in size.

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  • 12.
    Zhang, Lai
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik.
    Dieckmann, Ulf
    Brännström, Åke
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik. Evolution and Ecology Program, International Institute for Applied Systems Analysis, A-2361 Laxenburg, Austria.
    On the performance of four methods for the numerical solution of ecologically realistic size-structured population models2017Ingår i: Methods in Ecology and Evolution, E-ISSN 2041-210X, Vol. 8, nr 8, s. 948-956Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    1. Size-structured population models (SSPMs) are widely used in ecology to account for intraspecific variation in body size. Three characteristic features of size-structured populations are the dependence of life histories on the entire size distribution, intrinsic population renewal through the birth of new individuals, and the potential accumulation of individuals with similar body sizes due to determinate or stunted growth. Because of these three features, numerical methods that work well for structurally similar transport equations may fail for SSPMs and other transport-dominated models with high ecological realism, and thus their computational performance needs to be critically evaluated.

    2. Here, we compare the performance of four numerical solution schemes, the fixed-mesh upwind (FMU) method, the moving-mesh upwind (MMU) method, the characteristic method (CM), and the Escalator Boxcar Train (EBT) method, in numerically solving three reference problems that are representative of ecological systems in the animal and plant kingdoms. The MMU method is here applied for the first time to SSPMs, whereas the three other methods have been employed by other authors.

    3. Our results show that the EBT method performs best, except for one of the three reference problems, in which size-asymmetric competition affects individual growth rates. For that reference problem, the FMU method performs best, closely followed by the MMU method. Surprisingly, the CM method does not perform well for any of the three reference problems.

    4. We conclude that life-history features should be carefully considered when choosing the numerical method for analyzing ecologically realistic size-structured population models.

  • 13. Zizka, Alexander
    et al.
    Silvestro, Daniele
    Andermann, Tobias
    Azevedo, Josue
    Ritter, Camila Duarte
    Edler, Daniel
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för fysik. Department of Biological and Environmental Sciences, University of Gothenburg, Göteborg, Sweden; Gothenburg Global Biodiversity Centre, Göteborg, Sweden; .
    Farooq, Harith
    Herdean, Andrei
    Ariza, Maria
    Scharn, Ruud
    Svantesson, Sten
    Wengström, Niklas
    Zizka, Vera
    Antonelli, Alexandre
    CoordinateCleaner: Standardized cleaning of occurrence records from biological collection databases2019Ingår i: Methods in Ecology and Evolution, E-ISSN 2041-210X, Vol. 10, nr 5, s. 744-751Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Species occurrence records from online databases are an indispensable resource in ecological, biogeographical and palaeontological research. However, issues with data quality, especially incorrect geo-referencing or dating, can diminish their usefulness. Manual cleaning is time-consuming, error prone, difficult to reproduce and limited to known geographical areas and taxonomic groups, making it impractical for datasets with thousands or millions of records.

    Here, we present CoordinateCleaner, an r-package to scan datasets of species occurrence records for geo-referencing and dating imprecisions and data entry errors in a standardized and reproducible way. CoordinateCleaner is tailored to problems common in biological and palaeontological databases and can handle datasets with millions of records. The software includes (a) functions to flag potentially problematic coordinate records based on geographical gazetteers, (b) a global database of 9,691 geo-referenced biodiversity institutions to identify records that are likely from horticulture or captivity, (c) novel algorithms to identify datasets with rasterized data, conversion errors and strong decimal rounding and (d) spatio-temporal tests for fossils.

    We describe the individual functions available in CoordinateCleaner and demonstrate them on more than 90million occurrences of flowering plants from the Global Biodiversity Information Facility (GBIF) and 19,000 fossil occurrences from the Palaeobiology Database (PBDB). We find that in GBIF more than 3.4 million records (3.7%) are potentially problematic and that 179 of the tested contributing datasets (18.5%) might be biased by rasterized coordinates. In PBDB, 1205 records (6.3%) are potentially problematic.

    All cleaning functions and the biodiversity institution database are open-source and available within the CoordinateCleaner r-package.

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