Browsing by Subject "community ecology"

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  • Woolley, Skipton; Bax, Nicolas; Currie, Jock; Dunn, Daniel; Hansen, Cecilie; Hill, Nicole; O'Hara, Timothy; Ovaskainen, Otso; Sayre, Roger; Vanhatalo, Jarno; Dunstan, Piers (2020)
    Bioregions are important tools for understanding and managing natural resources. Bioregions should describe locations of relatively homogenous assemblages of species occur, enabling managers to better regulate activities that might affect these assemblages. Many existing bioregionalization approaches, which rely on expert-derived, Delphic comparisons or environmental surrogates, do not explicitly include observed biological data in such analyses. We highlight that, for bioregionalizations to be useful and reliable for systems scientists and managers, the bioregionalizations need to be based on biological data; to include an easily understood assessment of uncertainty, preferably in a spatial format matching the bioregions; and to be scientifically transparent and reproducible. Statistical models provide a scientifically robust, transparent, and interpretable approach for ensuring that bioregions are formed on the basis of observed biological and physical data. Using statistically derived bioregions provides a repeatable framework for the spatial representation of biodiversity at multiple spatial scales. This results in better-informed management decisions and biodiversity conservation outcomes.
  • Hill, Nicole; Woolley, Skipton N. C.; Foster, Scott; Dunstan, Piers K.; McKinlay, John; Ovaskainen, Otso; Johnson, Craig (2020)
    Areas that contain ecologically distinct biological content, called bioregions, are a central component to spatial and ecosystem-based management. We review and describe a variety of commonly used and newly developed statistical approaches for quantitatively determining bioregions. Statistical approaches to bioregionalization can broadly be classified as two-stage approaches that either 'Group First, then Predict' or 'Predict First, then Group', or a newer class of one-stage approaches that simultaneously analyse biological data with reference to environmental data to generate bioregions. We demonstrate these approaches using a selection of methods applied to simulated data and real data on demersal fish. The methods are assessed against their ability to answer several common scientific or management questions. The true number of simulated bioregions was only identified by both of the one-stage methods and one two-stage method. When the number of bioregions was known, many of the methods, but not all, could adequately infer the species, environmental and spatial characteristics of bioregions. One-stage approaches, however, do so directly via a single model without the need for separate post-hoc analyses and additionally provide an appropriate characterization of uncertainty. One-stage approaches provide a comprehensive and consistent method for objectively identifying and characterizing bioregions using both biological and environmental data. Potential avenues of future development in one-stage methods include incorporating presence-only and multiple data types as well as considering functional aspects of bioregions.
  • Dawson, Samantha Katherine; Boddy, Lynne; Halbwachs, Hans; Bässler, Claus; Andrew, Carrie; Crowther, Thomas Ward; Heilmann-Clausen, Jacob; Nordén, Jenni; Ovaskainen, Otso; Jönsson, Mari (2019)
    Functional traits are widely recognized as a useful framework for testing mechanisms underlying species community assemblage patterns and ecosystem processes. Functional trait studies in the plant and animal literature have burgeoned in the past 20 years, highlighting a need for standardized ways to measure ecologically meaningful traits across taxa and ecosystems. However, standardized measurements of functional traits are lacking for many organisms and ecosystems, including fungi. Basidiomycete wood fungi occur in all forest ecosystems world-wide, where they are decomposers and also provide food or habitat for other species, or act as tree pathogens. Despite their major role in the functioning of forest ecosystems, the understanding and application of functional traits in studies of communities of wood fungi lags behind other disciplines. As the research field of fungal functional ecology is growing, there is a need for standardized ways to measure fungal traits within and across taxa and spatial scales. This handbook reviews pre-existing fungal trait measurements, proposes new core fungal traits, discusses trait ecology in fungi and highlights areas for future work on basidiomycete wood fungi. We propose standard and potential future methodologies for collecting traits to be used across studies, ensuring replicability and fostering between-study comparison. Combining concepts from fungal ecology and functional trait ecology, methodologies covered here can be related to fungal performance within a community and environmental setting. This manuscript is titled "a start with" as we only cover a subset of the fungal community here, with the aim of encouraging and facilitating the writing of handbooks for other members of the macrofungal community, for example, mycorrhizal fungi. A is available for this article.
  • Broman, Elias; Bonaglia, Stefano; Norkko, Alf; Creer, Simon; Nascimento, Francisco J. A. (2021)
    Benthic macrofauna is regularly used in monitoring programmes, however the vast majority of benthic eukaryotic biodiversity lies mostly in microscopic organisms, such as meiofauna (invertebrates <1 mm) and protists, that rapidly responds to environmental change. These communities have traditionally been hard to sample and handle in the laboratory, but DNA sequencing has made such work less time consuming. While DNA sequencing captures both alive and dead organisms, environmental RNA (eRNA) better targets living organisms or organisms of recent origin in the environment. Here, we assessed the biodiversity of three known bioindicator microeukaryote groups (nematodes, foraminifera, and ciliates) in sediment samples collected at seven coastal sites along an organic carbon (OC) gradient. We aimed to investigate if eRNA shotgun sequencing can be used to simultaneously detect differences in (i) biodiversity of multiple microeukaryotic communities; and (ii) functional feeding traits of nematodes. Results showed that biodiversity was lower for nematodes and foraminifera in high OC (6.2%-6.9%), when compared to low OC sediments (1.2%-2.8%). Dissimilarity in community composition increased for all three groups between Low OC and High OC, as well as the classified feeding type of nematode genera (with more nonselective deposit feeders in high OC sediment). High relative abundant genera included nematodeSabatieriaand foraminiferaElphidiumin high OC, andCryptocaryon-like ciliates in low OC sediments. Considering that future sequencing technologies are likely to decrease in cost, the use of eRNA shotgun sequencing to assess biodiversity of benthic microeukaryotes could be a powerful tool in recurring monitoring programmes.
  • Tikhonov, Gleb; Opedal, Oystein H.; Abrego, Nerea; Lehikoinen, Aleksi; de Jonge, Melinda M. J.; Oksanen, Jari; Ovaskainen, Otso (2020)
    Joint Species Distribution Modelling (JSDM) is becoming an increasingly popular statistical method for analysing data in community ecology. Hierarchical Modelling of Species Communities (HMSC) is a general and flexible framework for fitting JSDMs. HMSC allows the integration of community ecology data with data on environmental covariates, species traits, phylogenetic relationships and the spatio-temporal context of the study, providing predictive insights into community assembly processes from non-manipulative observational data of species communities. The full range of functionality of HMSC has remained restricted to Matlab users only. To make HMSC accessible to the wider community of ecologists, we introduce Hmsc 3.0, a user-friendly r implementation. We illustrate the use of the package by applying Hmsc 3.0 to a range of case studies on real and simulated data. The real data consist of bird counts in a spatio-temporally structured dataset, environmental covariates, species traits and phylogenetic relationships. Vignettes on simulated data involve single-species models, models of small communities, models of large species communities and models for large spatial data. We demonstrate the estimation of species responses to environmental covariates and how these depend on species traits, as well as the estimation of residual species associations. We demonstrate how to construct and fit models with different types of random effects, how to examine MCMC convergence, how to examine the explanatory and predictive powers of the models, how to assess parameter estimates and how to make predictions. We further demonstrate how Hmsc 3.0 can be applied to normally distributed data, count data and presence-absence data. The package, along with the extended vignettes, makes JSDM fitting and post-processing easily accessible to ecologists familiar with r.
  • Nirhamo, Aleksi; Pykälä, Juha; Halme, Panu; Komonen, Atte (Wiley, 2021)
    Applied Vegetation Science 24: 2
    Questions: Aspen (Populus tremula) is declining in the old-growth forests of boreal Fennoscandia. This threatens the numerous taxa that are dependent on old aspens, including many epiphytic lichens. Potential methods to aid epiphytic lichens on aspen are centered around treatments which affect the density of Norway spruce (Picea abies). In this study, we investigated how epiphytic lichen communities on aspen are affected by the variation of spruce density in the immediate vicinity of the focal aspen. Location: Southern boreal forests in Finland. Methods: We recorded the occurrence of lichens from 120 aspens in 12 semi-natural forest sites. We used spruce basal area as the measure for spruce density. The selected aspens represented a gradient in spruce basal area in the vicinity of the aspen from 0 to 36 m2/ha. We also measured other tree- and stand-level variables that are known to influence lichen occurrence. Results: Lichen communities on aspen were affected by spruce density, stand age and bark pH. Both lichen species richness and the richness of red-listed species were highest at an intermediate spruce density, and both increased with stand age. Lichen species richness was higher when bark pH was lower. Additionally, community composition was influenced the most by spruce density, followed by bark pH. Conclusions: Our study highlights the detrimental effects of high spruce density on lichen diversity on aspens. This is caused by high spruce density resulting in low light availability. Lichen diversity on aspens was highest when spruce density was intermediate. Spruce thinning in aspen-rich old-growth forests can be helpful in ensuring the long-term persistence of old-growth lichens on aspen in protected forests.
  • Aivelo, Tuomas; Medlar, Alan (2018)
    Despite metabarcoding being widely used to analyse bacterial community composition, its application in parasitological research remains limited. What interest there has been has focused on previously intractable research settings where traditional methods are inappropriate, for example, in longitudinal studies and studies involving endangered species. In settings such as these, non-invasive sampling combined with metabarcoding can provide a fast and accurate assessment of component communities. In this paper we review the use of metabarcoding in the study of helminth communities in wild mammals, outlining the necessary procedures from sample collection to statistical analysis. We highlight the limitations of the metabarcoding approach and speculate on what type of parasitological study would benefit from such methods in the future.
  • Vanhatalo, Jarno; Foster, Scott D.; Hosack, Geoffrey R. (2021)
    The categorization of multidimensional data into clusters is a common task in statistics. Many applications of clustering, including the majority of tasks in ecology, use data that is inherently spatial and is often also temporal. However, spatiotemporal dependence is typically ignored when clustering multivariate data. We present a finite mixture model for spatial and spatiotemporal clustering that incorporates spatial and spatiotemporal autocorrelation by including appropriate Gaussian processes (GP) into a model for the mixing proportions. We also allow for flexible and semiparametric dependence on environmental covariates, once again using GPs. We propose to use Bayesian inference through three tiers of approximate methods: a Laplace approximation that allows efficient analysis of large datasets, and both partial and full Markov chain Monte Carlo (MCMC) approaches that improve accuracy at the cost of increased computational time. Comparison of the methods shows that the Laplace approximation is a useful alternative to the MCMC methods. A decadal analysis of 253 species of teleost fish from 854 samples collected along the biodiverse northwestern continental shelf of Australia between 1986 and 1997 shows the added clarity provided by accounting for spatial autocorrelation. For these data, the temporal dependence is comparatively small, which is an important finding given the changing human pressures over this time.
  • Sutela, Tapio; Vehanen, Teppo; Jounela, Pekka; Aroviita, Jukka (John Wiley & Sons, 2021)
    Ecology and Evolution 11 (15), 10457-10467
    Species–environment relationships were studied between the occurrence of 13 fish and lamprey species and 9 mainly map-based environmental variables of Finnish boreal small streams. A self-organizing map (SOM) analysis showed strong relationships between the fish species and environmental variables in a single model (explained variance 55.9%). Besides basic environmental variables such as altitude, catchment size, and mean temperature, land cover variables were also explored. A logistic regression analysis indicated that the occurrence probability of brown trout, Salmo trutta L., decreased with an increasing percentage of peatland ditch drainage in the upper catchment. Ninespine stickleback, Pungitius pungitius (L.), and three-spined stickleback, Gasterosteus aculeatus L., seemed to benefit from urban areas in the upper catchment. Discovered relationships between fish species occurrence and land-use attributes are encouraging for the development of fish-based bioassessment for small streams. The presented ordination of the fish species in the mean temperature gradient will help in predicting fish community responses to climate change.
  • Huovinen, Lena (Helsingin yliopisto, 2021)
    Lake ecosystems are shaped by water chemistry processes that affect the lake environment and the species communities within. Changes in the water chemistry thus have far-reaching consequences. Water colour is one variable that affects water chemistry and stems from humic substances in the water. Dark water reduces light availability and also affects nutrient and oxygen availability. A trend of brownification of freshwater systems has been observed in recent years and it is expected to influence species community’s diversity and composition. The aim of this thesis was to study whether brownification is an ongoing issue in the study lakes and whether it has had a negative effect on phytoplankton diversity and resulted in shifts in the phytoplankton composition. A data set including about a 100 lakes in Finland with measurements from 1965 up until now served as the study system which was analysed with statistical methods. The results indicated a brownification trend in the past decades. The brownification so far had a positive impact on species richness but a negative impact on beta diversity. Brownification also affected species composition. Flagellates and autotrophic species increased in darker waters but mixotrophic species that are known to dominate in dark water colour, did not show a clear increase with water colour. Other hydrological variables than water colour could have had a bigger impact on the phytoplankton community than water colour but future monitoring of the phytoplankton community is recommended to see if water colour will have a negative impact on species diversity in the future.
  • Kikuchi, David W.; Herberstein, Marie E.; Barfield, Michael; Holt, Robert D.; Mappes, Johanna (2021)
    Warning signals are a striking example of natural selection present in almost every ecological community - from Nordic meadows to tropical rainforests, defended prey species and their mimics ward off potential predators before they attack. Yet despite the wide distribution of warning signals, they are relatively scarce as a proportion of the total prey available, and more so in some biomes than others. Classically, warning signals are thought to be governed by positive density-dependent selection, i.e. they succeed better when they are more common. Therefore, after surmounting this initial barrier to their evolution, it is puzzling that they remain uncommon on the scale of the community. Here, we explore factors likely to determine the prevalence of warning signals in prey assemblages. These factors include the nature of prey defences and any constraints upon them, the behavioural interactions of predators with different prey defences, the numerical responses of predators governed by movement and reproduction, the diversity and abundance of undefended alternative prey and Batesian mimics in the community, and variability in other ecological circumstances. We also discuss the macroevolution of warning signals. Our review finds that we have a basic understanding of how many species in some taxonomic groups have warning signals, but very little information on the interrelationships among population abundances across prey communities, the diversity of signal phenotypes, and prey defences. We also have detailed knowledge of how a few generalist predator species forage in artificial laboratory environments, but we know much less about how predators forage in complex natural communities with variable prey defences. We describe how empirical work to address each of these knowledge gaps can test specific hypotheses for why warning signals exhibit their particular patterns of distribution. This will help us to understand how behavioural interactions shape ecological communities.