scholarly journals LifeDNAquatic: A priori settings and refined pipelines of eDNA metabarcoding to generate "big data" for solid fish, mussel and amphibian SDMs

2021 ◽  
Vol 4 ◽  
Author(s):  
Micaela Hellstrom ◽  
Kat Bruce ◽  
Rein Brys ◽  
Bernd Hänfling ◽  
David Halfmaerten ◽  
...  
Keyword(s):  
Big Data ◽  
A Priori ◽  
Large River ◽  
Freshwater Ecosystems ◽  
Distribution Data ◽  
Sampling Strategies ◽  
Distribution Models ◽  
Spatial Changes ◽  
Landscape Scales ◽  
Field Planning

Sound environmental management decisions - in accordance with the EU WFD for aquatic ecosystems – mainly depend on reliable species presence- and distribution- data. Here we present a workflow from sampling strategies to results and decision making using eDNA metabarcoding analyses for fish, amphibians, and mussels from habitat to landscape scales with focus on sampling strategies for "big data" in marine and freshwater ecosystems in Sweden. The project LifeDNAquatic highlights a solid eDNA pipeline and comparison of methods, which cover field planning and the entire pipeline generating data for Species Distribution Models (SDMs). Intense sampling over a large river catchment highlights previoulsy unanswered questionsand and provides insights to a priori settings for sampling strategies to retrieve "big data". The results provide novel insights to DNA distribution in the environment, seasonal and spatial changes in eDNA composition, and validation of data.

scholarly journals Application Natura 2000 Data For The Invasive Plants Spread Prediction

2015 ◽  
Vol 46 (4) ◽  
pp. 159-166 ◽  
Author(s):  
J. Pěknicová ◽  
D. Petrus ◽  
K. Berchová-Bímová
Keyword(s):  
Environmental Factors ◽  
Invasive Plants ◽  
Species Distribution ◽  
Natura 2000 ◽  
Distribution Model ◽  
Distribution Data ◽  
Habitat Types ◽  
Distribution Models ◽  
Occurrence Data ◽  
Heracleum Mantegazzianum

AbstractThe distribution of invasive plants depends on several environmental factors, e.g. on the distance from the vector of spreading, invaded community composition, land-use, etc. The species distribution models, a research tool for invasive plants spread prediction, involve the combination of environmental factors, occurrence data, and statistical approach. For the construction of the presented distribution model, the occurrence data on invasive plants (Solidagosp.,Fallopiasp.,Robinia pseudoaccacia,andHeracleum mantegazzianum) and Natura 2000 habitat types from the Protected Landscape Area Kokořínsko have been intersected in ArcGIS and statistically analyzed. The data analysis was focused on (1) verification of the accuracy of the Natura 2000 habitat map layer, and the accordance with the habitats occupied by invasive species and (2) identification of a suitable scale of intersection between the habitat and species distribution. Data suitability was evaluated for the construction of the model on local scale. Based on the data, the invaded habitat types were described and the optimal scale grid was evaluated. The results show the suitability of Natura 2000 habitat types for modelling, however more input data (e.g. on soil types, elevation) are needed.

Diversity and distribution of Phanaeini (Coleoptera: Scarabaeidae: Scarabaeinae) in Mexico

Zootaxa ◽  
2017 ◽  
Vol 4358 (2) ◽  
pp. 271 ◽  
Author(s):  
VIRIDIANA LIZARDO ◽  
FEDERICO ESCOBAR ◽  
OCTAVIO ROJAS-SOTO
Keyword(s):  
Relevant Literature ◽  
Volcanic Belt ◽  
Field Studies ◽  
Distribution Data ◽  
Biological Databases ◽  
Distribution Models ◽  
Distribution Maps ◽  
Distribution Ranges ◽  
Starting Point ◽  
Sierra Madre

In this study, we systematized available distribution data, obtained from biological databases and relevant literature, for Mexican species belonging to the tribe Phanaeini. The main objectives were to provide an overall description of the distribution records in biological collections, to detect potential sampling biases, to describe the seasonality of collections and to obtain species distribution models using the Desktop GARP algorithm. A total of 5,562 records, corresponding to 32 species in Mexico, were compiled, including the recently described Phanaeus zoque Moctezuma & Halffter, 2017. This compilation includes 784 unique collection records at 325 localities. These records were mainly distributed along the Trans-Mexican Volcanic Belt, the Sierra Madre Oriental and Sierra Madre Occidental mountain ranges and throughout the states of Chiapas and Veracruz. The Mexican High Plateau, the state of Tlaxcala and the Yucatan Peninsula are lacking in records. Distribution maps were created for species of three genera (Phanaeus MacLeay, 1819, Coprophanaeus Olsoufieff, 1924, and Sulcophanaeus Olsoufieff, 1924) and for 29 species present in Mexico. These species distributions are largely delimited by geomorphological features and vegetation types and coincide with expert descriptions of this tribe; some species show expanded distribution ranges. These maps provide a starting point for further analyses, the planning of future field studies, and the verification of possible new species in the Mexican territory. 

Examining Local Transferability of Predictive Species Distribution Models for Invasive Plants: An Example with Cogongrass (Imperata cylindrica)

2011 ◽  
Vol 4 (4) ◽  
pp. 390-401 ◽  
Author(s):  
Gary N. Ervin ◽  
D. Christopher Holly
Keyword(s):  
Invasive Species ◽  
Species Distribution ◽  
Species Distribution Models ◽  
Imperata Cylindrica ◽  
Environmental Data ◽  
Training Data ◽  
Distribution Data ◽  
Strongly Correlated ◽  
Distribution Models ◽  
Tree Canopy Cover

AbstractSpecies distribution modeling is a tool that is gaining widespread use in the projection of future distributions of invasive species and has important potential as a tool for monitoring invasive species spread. However, the transferability of models from one area to another has been inadequately investigated. This study aimed to determine the degree to which species distribution models (SDMs) for cogongrass, developed with distribution data from Mississippi (USA), could be applied to a similar area in neighboring Alabama. Cogongrass distribution data collected in Mississippi were used to train an SDM that was then tested for accuracy and transferability with cogongrass distribution data collected by a forest management company in Alabama. Analyses indicated the SDM had a relatively high predictive ability within the region of the training data but had poor transferability to the Alabama data. Analysis of the Alabama data, via independent SDM development, indicated that predicted cogongrass distribution in Alabama was more strongly correlated with soil variables than was the case in Mississippi, where the SDM was most strongly correlated with tree canopy cover. Results suggest that model transferability is influenced strongly by (1) data collection methods, (2) landscape context of the survey data, and (3) variations in qualitative aspects of environmental data used in model development.

scholarly journals New diagnostics for multiply stressed marine and freshwater ecosystems: integrating models, ecoinformatics and big data

2016 ◽  
Vol 67 (4) ◽  
pp. 391 ◽  
Author(s):  
D. J. Baird ◽  
P. J. Van den Brink ◽  
A. A. Chariton ◽  
K. A. Dafforn ◽  
E. L. Johnston
Keyword(s):  
Big Data ◽  
Freshwater Ecosystems

scholarly journals Big data: Hell or heaven? Digital platforms and market power in the data-driven economy

2018 ◽  
Vol 23 (3) ◽  
pp. 312-328 ◽  
Author(s):  
Massimiliano Nuccio ◽  
Marco Guerzoni
Keyword(s):  
Big Data ◽  
Economies Of Scale ◽  
A Priori ◽  
Information Economics ◽  
Market Concentration ◽  
Fair Use ◽  
Policy Debate ◽  
Digital Platforms ◽  
Continuous Innovation ◽  
The One

Digital transformation has triggered a process of concentration in several markets for information goods with digital platforms rising to dominate key industries by leveraging on network externalities and economies of scale in the use of consumer data. The policy debate, therefore, focuses on the market control allegedly held by incumbents who build their competitive advantage on big data. In this paper, we evaluate the risk of abuse of a dominant position by analysing three major aspects highlighted in economic theory: entry barriers, price discrimination, and potential for technological improvement. Drawing on industrial and information economics, we argue that the very nature of big data, on the one hand, prompts market concentration and, on the other, limits the possibility of abuse. This claim is not an a-priori apologia of large incumbents in digital markets, but rather an attempt to argue that market concentration is not necessarily detrimental when it stimulates continuous innovation. Nonetheless, the concentration of power in a few global players should raise other concerns linked with the supranational nature of these firms, which can easily cherry-pick locations to exploit tax competition among countries or more favourable privacy legislation and the fair use of data.

A Ramsar wetland in crisis - the Coorong, Lower Lakes and Murray Mouth, Australia

2011 ◽  
Vol 62 (3) ◽  
pp. 255 ◽  
Author(s):  
Richard T. Kingsford ◽  
Keith F. Walker ◽  
Rebecca E. Lester ◽  
William J. Young ◽  
Peter G. Fairweather ◽  
...  
Keyword(s):  
Environmental Flows ◽  
Large River ◽  
Freshwater Ecosystems ◽  
Water Levels ◽  
Environmental Benefits ◽  
Low Flow ◽  
Freshwater Turtles ◽  
Murray Darling Basin ◽  
High Conservation ◽  
Sulfate Soils

The state of global freshwater ecosystems is increasingly parlous with water resource development degrading high-conservation wetlands. Rehabilitation is challenging because necessary increases in environmental flows have concomitant social impacts, complicated because many rivers flow between jurisdictions or countries. Australia’s Murray–Darling Basin is a large river basin with such problems encapsulated in the crisis of its Ramsar-listed terminal wetland, the Coorong, Lower Lakes and Murray Mouth. Prolonged drought and upstream diversion of water dropped water levels in the Lakes below sea level (2009–2010), exposing hazardous acid sulfate soils. Salinities increased dramatically (e.g. South Lagoon of Coorong >200 g L–1, cf. modelled natural 80 g L–1), reducing populations of waterbirds, fish, macroinvertebrates and littoral plants. Calcareous masses of estuarine tubeworms (Ficopomatus enigmaticus) killed freshwater turtles (Chelidae) and other fauna. Management primarily focussed on treating symptoms (e.g. acidification), rather than reduced flows, at considerable expense (>AU$2 billion). We modelled a scenario that increased annual flows during low-flow periods from current levels up to one-third of what the natural flow would have been, potentially delivering substantial environmental benefits and avoiding future crises. Realisation of this outcome depends on increasing environmental flows and implementing sophisticated river management during dry periods, both highly contentious options.

Big Data and consumer behavior: imminent opportunities

2016 ◽  
Vol 33 (2) ◽  
pp. 89-97 ◽  
Author(s):  
Charles F. Hofacker ◽  
Edward Carl Malthouse ◽  
Fareena Sultan
Keyword(s):  
Big Data ◽  
Consumer Behavior ◽  
A Priori ◽  
Secondary Data ◽  
Poor Quality ◽  
Consumer Decision Making ◽  
Marketing Practice ◽  
Content Type ◽  
Skill Sets ◽  
Data Culture

Purpose – The purpose of this paper is to assess how the study of consumer behavior can benefit from the presence of Big Data. Design/methodology/approach – This paper offers a conceptual overview of potential opportunities and changes to the study of consumer behavior that Big Data will likely bring. Findings – Big Data have the potential to further our understanding of each stage in the consumer decision-making process. While the field has traditionally moved forward using a priori theory followed by experimentation, it now seems that the nature of the feedback loop between theory and results may shift under the weight of Big Data. Research limitations/implications – A new data culture is now represented in marketing practice. The new group advocates inductive data mining and A/B testing rather than human intuition harnessed for deduction. The group brings with it interest in numerous secondary data sources. However, Big Data may be limited by poor quality, unrepresentativeness and volatility, among other problems. Practical implications – Managers who need to understand consumer behavior will need a workforce with different skill sets than in the past, such as Big Data consumer analytics. Originality/value – To the authors ' knowledge, this is one of the first articles to assess how the study of consumer behavior can evolve in the context of the Big Data revolution.

scholarly journals Evaluation of species distribution models for estimating animal dark diversity

2021 ◽  
Author(s):  
Camilo Matus-Olivares ◽  
Jaime Carrasco ◽  
José Luis Yela ◽  
Paula Meli ◽  
Andres Weintraub ◽  
...  
Keyword(s):  
Spatial Patterns ◽  
Species Distribution ◽  
Species Distribution Model ◽  
Predictive Performance ◽  
The Other ◽  
Distribution Model ◽  
Distribution Data ◽  
Ensemble Model ◽  
Distribution Models ◽  
Software Environment

Abstract Aim Applying wide and effective sampling of animal communities is rarely possible due to the associated costs and the use of techniques that are not always efficient. Thus, many areas have a faunistic hidden diversity we denote Animal Dark Diversity (ADD), defined as the diversity that is present but not yet detected plus the diversity defined by Pärtel et al. (2011) that is not (yet) present despite the area’s favourable habitat conditions. We evaluated different species distribution model types (SDM techniques) on the basis of three requirements for ADD estimate reliability: 1) estimated spatial patterns of ADD do not differ significantly from other SDM techniques; 2) good predictive performances; and 3) low overfitting. Location Iberian Peninsula. Taxon Chiroptera and Noctuoidea (Lepidoptera) Methods We used distribution data for 25 species of bats and 352 species of moths. We evaluated eleven SDM techniques using biomod2 package implemented in the R software environment. We fitted the various SDM techniques to the data for each species and compared the resulting ADD estimates for the two animal groups under three threshold types. Results The results demonstrated that estimated ADD spatial patterns vary significantly between SDM techniques and depend on the threshold type. They also showed that SDM techniques with overfitting tend to generate smaller ADD sizes, thus reducing the possible species presence estimates. Among the SDMs studied, the ensemble models delivered ADD geographic patterns more like the other techniques while also presenting a high predictive performance for both faunal groups. However, the Ensemble Model Committee Average (ECA) performed much better on the sensitivity metric than all other techniques under any of the thresholds tested. In addition, ECA stood out clearly from the other ensemble model techniques in displaying low-medium overfitting. Main conclusions SDM techniques should no differ among each other in their ADD estimations, have good predictive performances and exhibit low overfitting. Furthermore, to reduce estimate uncertainty it is suggested that the threshold type be one that transforms high values of presences probabilities into binary information and furthermore that the SDM technique have a sensitivity bias, as otherwise the estimates will perform better for species absence in cases where it is not in fact known whether a species is truly absent.

Food Web Interactions in Freshwater Ecosystems

2017 ◽  
Author(s):  
Christer Brönmark ◽  
Lars-Anders Hansson
Keyword(s):  
Food Web ◽  
Alternative Stable States ◽  
Ecosystem Approach ◽  
Freshwater Ecosystems ◽  
Stable States ◽  
Food Web Interactions ◽  
Spatial Changes ◽  
Temporal And Spatial ◽  
Cascading Trophic Interactions ◽  
Food Web Theory

This chapter on food web interactions connects the organisms and their interactions with the abiotic frame and provides a helicopter perspective on the function of freshwater ecosystems. Initially, the theoretical basis for an ecosystem approach is outlined, including food web theory, the bottom-up and top-down concepts and how these have evolved in concert with empirical advances. Specifically, the concepts of cascading trophic interactions and alternative stable states are discussed both from a theoretical and empirical viewpoint, as well as in both benthic and pelagic habitats. This chapter links all components, from microbes to vertebrates, to temporal and spatial changes in abiotic features leading to successional patterns in populations and communities.

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