scholarly journals Mapping near surface global marine ecosystems through cluster analysis of environmental data

2020 ◽  
Vol 35 (2) ◽  
pp. 327-342 ◽  
Author(s):  
Qianshuo Zhao ◽  
Zeenatul Basher ◽  
Mark J. Costello
Keyword(s):  
Cluster Analysis ◽  
Marine Ecosystems ◽  
Environmental Data ◽  
Near Surface

Degrading permafrost threatens Arctic nature and built environment

2020 ◽  
Author(s):  
Jan Hjort ◽  
Olli Karjalainen ◽  
Juha Aalto ◽  
Sebastian Westermann ◽  
Vladimir Romanovsky ◽  
...  
Keyword(s):  
Climate Change ◽  
At Risk ◽  
High Resolution ◽  
Human Activities ◽  
Environmental Data ◽  
The Arctic ◽  
Permafrost Degradation ◽  
Engineering Structures ◽  
Near Surface ◽  
Population At Risk

<p>Arctic earth surface systems are undergoing unprecedented changes, with permafrost thaw as one of the most striking examples. Permafrost is critical because it controls ecosystem processes, human activities, and landscape dynamics in the north. Degradation (i.e. warming and thawing) of permafrost is related to several hazards, which may pose a serious risk to humans and the environment. Thaw of ice-rich permafrost increases ground instability, landslides, and infrastructure damages. Degrading permafrost may lead to the release of significant amounts of greenhouse gases to the atmosphere and threatens also biodiversity, geodiversity and ecosystem services. Thawing permafrost may even jeopardize human health. Consequently, a deeper understanding of the hazards and risks related to the degradation of permafrost is fundamental for science and society.</p><p>To address climate change effects on infrastructure and human activities, we (i) mapped circumpolar permafrost hazard areas and (ii) quantified critical engineering structures and population at risk by mid-century. We used observations of ground thermal regime, geospatial environmental data, and statistically-based ensemble methods to model the current and future near-surface permafrost extent at ca. 1 km resolution. Using the forecasts of ground temperatures, a consensus of three geohazard indices, and geospatial data we quantified the amount and proportion of infrastructure elements and population at risk owing to climate change. We show that ca. 70% of current infrastructure and population in the permafrost domain are in areas with high potential for thaw of near-surface permafrost by 2050. One-third of fundamental infrastructure is located in high hazard regions where the ground is susceptible to thaw-related ground instability. Owing to the observed data-related and methodological limitations we call for improvements in the circumpolar hazard mappings and infrastructure risk assessments.</p><p>To successfully manage climate change impacts and support sustainable development in the Arctic, it is critical to (i) produce high-resolution geospatial datasets of ground conditions (e.g., content of organic material and ground ice), (ii) develop further high-resolution permafrost modelling, (iii) comprehensively map permafrost degradation-related hazards, and (iv) quantify the amount and economic value of infrastructure and natural resources at risk across the circumpolar permafrost area.</p>

scholarly journals Characterisation of extreme events waves in marine ecosystems: the case of Mediterranean Sea

2020 ◽  
Author(s):  
Valeria Di Biagio ◽  
Gianpiero Cossarini ◽  
Stefano Salon ◽  
Cosimo Solidoro
Keyword(s):  
Cluster Analysis ◽  
Mediterranean Sea ◽  
Extreme Events ◽  
Marine Ecosystems ◽  
Horizontal Resolution ◽  
Ecosystem Functions ◽  
Biogeochemical Model ◽  
Open Sea ◽  
Basin Scale ◽  
The Mediterranean

Abstract. We propose a new method to identify and characterise the occurrence of prolonged extreme events in marine ecosystems on the basin scale. There is a growing interest about events that can affect ecosystem functions and services in a changing climate. Our method identifies extreme events as peak occurrences over 99th percentile thresholds computed from local time series and defines an Extreme Events Wave (EEW) as a connected region including these events. The EEWs are characterised by a set of novel indexes, referred to initiation, extent, duration and strength. The indexes, associated to the areas covered by each EEW, are then statistically analysed to highlight the main features of the EEWs on the considered domain. We applied the method to the winter-spring daily chlorophyll field of a validated multidecadal hindcast provided by a coupled hydrodynamic-biogeochemical model of the Mediterranean open-sea ecosystem, with 1/12° horizontal resolution. This allowed to identify the maxima of chlorophyll as exceptionally high and prolonged blooms and to characterise their phenomenology in the period 1994–2012. A fuzzy k-means cluster analysis on the EEWs indexes provided a bio-regionalisation of the Mediterranean Sea associated to the occurrence of chlorophyll EEWs with different regimes.

scholarly journals Spatial Multivariate Cluster Analysis for Defining Target Population of Environments in West Africa for Yam Breeding

2019 ◽  
Vol 10 (3) ◽  
pp. 1-30 ◽  
Author(s):  
Tunrayo R. Alabi ◽  
Patrick Olusanmi Adebola ◽  
Asrat Asfaw ◽  
David De Koeyer ◽  
Antonio Lopez-Montes ◽  
...  
Keyword(s):  
Cluster Analysis ◽  
West Africa ◽  
Poverty Reduction ◽  
Principal Component ◽  
Environmental Data ◽  
Wealth Creation ◽  
Multivariate Cluster Analysis ◽  
Breeding Research ◽  
Multivariate Cluster ◽  
The Impact

Yam (Dioscorea spp.) is a major staple crop with high agricultural and cultural significance for over 300 million people in West Africa. Despite its importance, productivity is miserably low. A better understanding of the environmental context in the region is essential to unlock the crop's potential for food security and wealth creation. The article aims to characterize the production environments into homologous mega-environments, having operational significance for breeding research. Principal component analysis (PCA) was performed separately on environmental data related to climate, soil, topography, and vegetation. Significant PCA layers were used in spatial multivariate cluster analysis. Seven clusters were identified for West Africa; four were country-specific; the rest were region-wide in extent. Clustering results are valuable inputs to optimize yam varietal selection and testing within and across the countries in West Africa. The impact of breeding research on poverty reduction and problems of market accessibility in yam production zones were highlighted.

Reciprocal Averaging and Polar Ordination as Techniques for Analyzing Lotic Macroinvertebrate Communities

1980 ◽  
Vol 37 (9) ◽  
pp. 1358-1364 ◽  
Author(s):  
Joseph M. Culp ◽  
Ronald W. Davies
Keyword(s):  
Cluster Analysis ◽  
Field Data ◽  
Environmental Gradient ◽  
Environmental Data ◽  
Macroinvertebrate Communities ◽  
Reciprocal Averaging ◽  
Spatial And Temporal Patterns ◽  
Polar Ordination ◽  
Ordination Techniques ◽  
Group Relationships

Reciprocal averaging and polar ordination techniques were applied to lotic macroinvertebrate field data to determine the relative performance of these techniques in lotic benthic community analyses. It was found that, because of inherent problems with endpoint determinations, polar ordination should only be used where a well-defined environmental gradient exists. Reciprocal averaging ordination produced interpretable axes and was preferred over polar ordination because endpoint determination was objective and simultaneous species–site ordinations were produced. Reciprocal averaging ordination allowed groupings of sites similar to those determined through cluster analysis to be recognized, while providing a visual representation of between-group relationships superior to that of cluster dendrograms. Combined with subsequent analyses of environmental data, reciprocal averaging ordination can be an excellent technique for summarizing spatial and temporal patterns of lotic macroinvertebrate communities.Key words: ordination, reciprocal averaging, benthic, lotic, communities, clustering

Ecoregionalization classification of wetlands based on a cluster analysis of environmental data

2016 ◽  
Vol 19 (4) ◽  
pp. 724-735 ◽  
Author(s):  
Alex M. Lechner ◽  
Nic McCaffrey ◽  
Phill McKenna ◽  
William N. Venables ◽  
John T. Hunter
Keyword(s):  
Cluster Analysis ◽  
Environmental Data

scholarly journals Intra-lake response of Arcellinida (testate lobose amoebae) to gold mining-derived arsenic contamination in northern Canada: Implications for environmental monitoring

PeerJ ◽  
2020 ◽  
Vol 8 ◽  
pp. e9054 ◽  
Author(s):  
Nawaf A. Nasser ◽  
R. Timothy Patterson ◽  
Jennifer M. Galloway ◽  
Hendrik Falck
Keyword(s):  
Cluster Analysis ◽  
Gold Mining ◽  
Spatial Gradient ◽  
Near Surface ◽  
Gold Mines ◽  
Olsen P ◽  
Ore Processing ◽  
High Calcium ◽  
Species Richness And Abundance ◽  
The Impact

Arcellinida (testate lobose amoebae) were examined from 40 near-surface sediment samples (top 0.5 cm) from two lakes impacted by arsenic (As) contamination associated with legacy gold mining in subarctic Canada. The objectives of the study are two folds: quantify the response of Arcellinida to intra-lake variability of As and other physicochemical controls, and evaluate whether the impact of As contamination derived from two former gold mines, Giant Mine (1938–2004) and Tundra Mine (1964–1968 and 1983–1986), on the Arcellinida distribution in both lakes is comparable or different. Cluster analysis and nonmetric multidimensional scaling (NMDS) were used to identify Arcellinida assemblages in both lakes, and redundancy analysis (RDA) was used to quantify the relationship between the assemblages, As, and other geochemical and sedimentological parameters. Cluster analysis and NMDS revealed four distinct arcellinidan assemblages in Frame Lake (assemblages 1–4) and two in Hambone Lake (assemblages 5 and 6): (1) Extreme As Contamination (EAC) Assemblage; (2) High calcium (HC) Assemblage; (3) Moderate As Contamination (MAC) assemblages; (4) High Nutrients (HN) Assemblage; (5) High Diversity (HD) Assemblage; and (6) Centropyxis aculeata (CA) Assemblage. RDA analysis showed that the faunal structure of the Frame Lake assemblages was controlled by five variables that explained 43.2% of the total faunal variance, with As (15.8%), Olsen phosphorous (Olsen-P; 10.5%), and Ca (9.5%) being the most statistically significant (p < 0.004). Stress-tolerant arcellinidan taxa were associated with elevated As concentrations (e.g., EAC and MAC; As concentrations range = 145.1–1336.6 mg kg−1; n = 11 samples), while stress-sensitive taxa thrived in relatively healthier assemblages found in substrates with lower As concentrations and higher concentrations of nutrients, such as Olsen-P and Ca (e.g., HC and HM; As concentrations range = 151.1–492.3 mg kg−1; n = 14 samples). In contrast, the impact of As on the arcellinidan distribution was not statistically significant in Hambone Lake (7.6%; p-value = 0.152), where the proportion of silt (24.4%; p-value = 0.005) and loss-on-ignition-determined minerogenic content (18.5%; p-value = 0.021) explained a higher proportion of the total faunal variance (58.4%). However, a notable decrease in arcellinidan species richness and abundance and increase in the proportions of stress-tolerant fauna near Hambone Lake’s outlet (e.g., CA samples) is consistent with a spatial gradient of higher sedimentary As concentration near the outlet, and suggests a lasting, albeit weak, As influence on Arcellinida distribution in the lake. We interpret differences in the influence of sedimentary As concentration on Arcellinida to differences in the predominant As mineralogy in each lake, which is in turn influenced by differences in ore-processing at the former Giant (roasting) and Tundra mines (free-milling).

scholarly journals Toward Improved Model Capacities for Assessment of Climate Impacts on Coastal Bentho-Pelagic Food Webs and Ecosystem Services

2021 ◽  
Vol 8 ◽  
Author(s):  
Sabine Horn ◽  
Cédric L. Meunier ◽  
Vera Fofonova ◽  
Karen H. Wiltshire ◽  
Subrata Sarker ◽  
...  
Keyword(s):  
Climate Change ◽  
Sustainable Development ◽  
Food Web ◽  
Marine Ecosystems ◽  
Coastal Ecosystems ◽  
Climate Impacts ◽  
Trophic Levels ◽  
Environmental Data ◽  
Detailed Knowledge ◽  
Fish And Shellfish

Global climate change is a key driver of change in coastal waters with clear effects on biological communities and marine ecosystems. Human activities in combination with climate change exert a tremendous pressure on marine ecosystems and threaten their integrity, structure, and functioning. The protection of these ecosystems is a major target of the 14th United Nations sustainable development goal “Conserve and sustainably use the oceans, seas and marine resources for sustainable development.” However, due to the complexity of processes and interactions of stressors, the status assessment of ecosystems remains a challenge. Holistic food web models, including biological and environmental data, could provide a suitable basis to assess ecosystem health. Here, we review climate change impacts on different trophic levels of coastal ecosystems ranging from plankton to ecologically and economically important fish and shellfish species. Furthermore, we show different food web model approaches, their advantages and limitations. To effectively manage coastal ecosystems, we need both a detailed knowledge base of each trophic level and a holistic modeling approach for assessment and prediction of future scenarios on food web-scales. A new model approach with a seamless coupling of physical ocean models and food web models could provide a future tool for guiding ecosystem-based management.

The Analysis and Applying of Industrial Enterprises Contaminative Source Based on SuperMap GIS

2011 ◽  
Vol 383-390 ◽  
pp. 3734-3738
Author(s):  
Min Tao Ma ◽  
Yan Yan Zhang ◽  
Meng Meng Lu
Keyword(s):  
Environmental Management ◽  
Cluster Analysis ◽  
Clustering Analysis ◽  
Statistical Information ◽  
Environmental Data ◽  
Pollution Monitoring ◽  
Industrial Enterprises ◽  
Total Amount Control ◽  
Supermap Gis ◽  
Point Pollution

Finding out different situation of area environmental and instructing management, which to advance the using efficiency of environmental data information. This paper constructs clustering analysis module on point pollution analysis module based on SuperMap, beyond which, using the information of environmental pollution monitoring data at some typical area in Beijing, and employing 6 major indexes of National total Amount Control as variable, and 18 Industrial Enterprises as object which picked up from national statistical information system registered in typical district. According to pollution distributing, character and economic situation, obtaining the accurate interpretation for the formal results in the ordered sample cluster analysis at present. This paper gives a new method and way in environmental management of Industrial Enterprises.

Modelling marine diseases

2020 ◽  
pp. 233-256
Author(s):  
Tal Ben-Horin ◽  
Gorka Bidegain ◽  
Giulio de Leo ◽  
Maya L. Groner ◽  
Eileen Hofmann ◽  
...  
Keyword(s):  
Ocean Circulation ◽  
Life Histories ◽  
Marine Ecosystems ◽  
Environmental Data ◽  
Disease Dynamics ◽  
Epidemiological Modeling ◽  
Modeling Methods ◽  
Local Host ◽  
Disease Risks ◽  
Host Parasite

The unique characteristics of marine ecosystems have pushed investigators to refine well-tested and widely applied epidemiological modeling methods to understand marine disease dynamics. This chapter begins by reviewing models used to quantify within-host parasite dynamics in open marine ecosystems where infection is near universal. These models are powerful tools for quantifying how diseases respond to changing environmental conditions and, when reliable environmental data are available, can forecast marine disease risks into the future. This chapter then describes epidemiological models that consider transmission processes and parasite life histories unique to marine systems, and then incorporates disease processes in fisheries assessment models. Finally, because disease dynamics vary across local host populations, this chapter concludes by overviewing ocean circulation models and their use in understanding parasite dispersal and spread in marine ecosystems.

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