Implications of taxonomic resolution and sample habitat for stream classification at a broad geographic scale

2000 ◽  
Vol 19 (2) ◽  
pp. 352-361 ◽  
Author(s):  
Rebecca Hewlett
Keyword(s):  
Taxonomic Resolution ◽  
Geographic Scale ◽  
Stream Classification

scholarly journals Comparing the performance of different stream classification systems using aquatic macroinvertebrates

2013 ◽  
Vol 25 (4) ◽  
pp. 406-417 ◽  
Author(s):  
Márlon de Castro Vasconcelos ◽  
Adriano Sanches Melo ◽  
Albano Schwarzbold
Keyword(s):  
Randomization Test ◽  
Classification Systems ◽  
Data Type ◽  
Taxonomic Resolution ◽  
Stream Classification ◽  
Environment Variables ◽  
Family Level ◽  
Community Data ◽  
Performance Results ◽  
Classification Strength

AIM: We evaluated five stream classification systems observing: 1) differences in richness, abundance and macroinvertebrates communities among stream classes within classification systems; and 2) whether classification systems present better performance using macroinvertebrates. Additionally, we evaluated the effects of taxonomic resolution and data type (abundance and presence) on results. METHODS: Five stream classification systems were used, two based on hydroregions, one based on ecoregions by FEOW, a fourth one based on stream orders and the last one based on clusters of environment variables sampled in 37 streams at Rio Grande do Sul state, Brazil. We used a randomization test to evaluate differences of richness and abundance, a db-MANOVA to evaluate the differences of species assemblages and Classification Strength (CS) to evaluate the classifications performance. RESULTS: There were differences of richness and abundance among stream classes within each stream classification. The same result was found for community data, except for stream order classifications in family level. We observed that stream classes obtained for each stream classification differed in terms of environment variables (db-MANOVA). The classification based on environment variables showed higher CS values than other classification systems. The taxonomic resolution was important to the observed results. Data on genera level presented CS values 12% higher than family level for cluster classification, and the data type was dependent on the classification system and taxonomic resolution employed. CONCLUSION: Our results indicate that classifications based on cluster of environment variables was better than other stream classification systems, and similar results using genera level can be obtained for management programs using family resolution in a geographical context similar to this study.

Nutrient Cycling and Energy Flow in Grasslands

2018 ◽  
Author(s):  
Brian J. Wilsey
Keyword(s):  
Energy Flow ◽  
Animal Species ◽  
Net Primary Productivity ◽  
Growing Season ◽  
C4 Plant ◽  
Geographic Scale ◽  
Organic C ◽  
Natural Forms ◽  
Belowground Productivity ◽  
Remote Sensing Techniques

Net primary productivity (NPP) is the amount of C or biomass that accumulates over time and is photosynthesis—autotroph respiration. Annual NPP is estimated by summing positive biomass increments across time periods during the growing season, including offtake to herbivores, which can be high in grasslands. Remote sensing techniques that are used to assess NPP are discussed by the author. Belowground productivity can be high in grasslands, and it is important to carbon storage. Across grasslands on a geographic scale, NPP, N mineralization, and soil organic C all increase with annual precipitation. Within regions, NPP can be strongly affected by the proportion of C4 plant species and animal species composition and diversity. Humans are adding more N to the environment than all the natural forms of addition (fixation and lightning) combined. Animals, especially herbivores, can have strong effects on how plants respond to changes in changes in resource availability.

Analyzing and repairing concept drift adaptation in data stream classification

2021 ◽  
Author(s):  
Ben Halstead ◽  
Yun Sing Koh ◽  
Patricia Riddle ◽  
Russel Pears ◽  
Mykola Pechenizkiy ◽  
...  
Keyword(s):  
Data Stream ◽  
Concept Drift ◽  
Stream Classification ◽  
Data Stream Classification

Reference frames and geographic scale: understanding their relationship in environmental learning

2021 ◽  
pp. 1-15
Author(s):  
Jiayan Zhao ◽  
Xiaochuan Ma ◽  
Mark Simpson ◽  
Pejman Sajjadi ◽  
Jan Oliver Wallgrün ◽  
...  
Keyword(s):  
Reference Frames ◽  
Geographic Scale ◽  
Environmental Learning

scholarly journals Community structure of aquatic insects (Ephemeroptera, Plecoptera, and Trichoptera) in Cerrado streams of Paraguay, Paraná, and São Francisco river basins

2013 ◽  
Vol 13 (1) ◽  
pp. 97-107 ◽  
Author(s):  
Renato de Mei Romero ◽  
Mônica Ceneviva-Bastos ◽  
Gustavo Henrique Baviera ◽  
Lilian Casatti
Keyword(s):  
Community Structure ◽  
Aquatic Insects ◽  
Regional Differences ◽  
River Basins ◽  
Taxonomic Composition ◽  
Taxonomic Resolution ◽  
Sao Francisco River ◽  
Original Distribution ◽  
São Francisco River

We evaluated qualitatively and quantitatively the community structure of aquatic insects (Ephemeroptera, Plecoptera, and Trichoptera) in 19 streams in areas of Cerrado in the Paraguay, Paraná, and São Francisco river basins. The number of genera and taxonomic composition were compared at spatial (at the hydrographic basins level) and conservation levels (more preserved and less preserved areas). The influence of spatial and environmental factors in richness and abundance was also evaluated. The geographical distribution of Grumicha, Coryphorus, and Austrotinodes was expanded. The highest Trichoptera richness was found in the São Francisco river basin (F = 5,602, p = 0,004) and a higher number of Ephemeroptera genera occurred in the relatively less preserved sites (F = 6,835, p = 0,009). The pattern of genera distribution was different among basins (R = 0,0336, p = 0,001), but it was similar among relatively less and more preserved areas (R = -0,039, p = 0,737). These findings can be explained by the low impact level in these streams and also by the taxonomic resolution used in this study. Latitude and instream diversity were the most important factors to explain the variation in genera richness and abundance (p = 0.004 and p = 0.026, respectively). Hence, the regional differences can be attributed to spatial influences, quantity or quality of habitats and the original distribution of taxa within each basin.

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