Interactions between natural-occurring landscape conditions and land use influencing the abundance of riverine smallmouth bass, Micropterus dolomieu

2011 ◽  
Vol 68 (11) ◽  
pp. 1922-1933 ◽  
Author(s):  
Shannon K. Brewer ◽  
Charles F. Rabeni
Keyword(s):  
Land Use ◽  
Decision Tree ◽  
Smallmouth Bass ◽  
Urban Stream ◽  
Micropterus Dolomieu ◽  
Soil Permeability ◽  
Group Designation ◽  
Natural Landscape ◽  
Population Potential ◽  
Tree Models

This study examined how interactions between natural landscape features and land use influenced the abundance of smallmouth bass, Micropterus dolomieu , in Missouri, USA, streams. Stream segments were placed into one of four groups based on natural-occurring watershed characteristics (soil texture and soil permeability) predicted to relate to smallmouth bass abundance. Within each group, stream segments were assigned forest (n = 3), pasture (n = 3), or urban (n = 3) designations based on the percentages of land use within each watershed. Analyses of variance indicated smallmouth bass densities differed between land use and natural conditions. Decision tree models indicated abundance was highest in forested stream segments and lowest in urban stream segments, regardless of group designation. Land use explained the most variation in decision tree models, but in-channel features of temperature, flow, and sediment also contributed significantly. These results are unique and indicate the importance of natural-occurring watershed conditions in defining the potential of populations and how finer-scale filters interact with land use to further alter population potential. Smallmouth bass has differing vulnerabilities to land-use attributes, and the better the natural watershed conditions are for population success, the more resilient these populations will be when land conversion occurs.

scholarly journals Perfluoroalkyl Substances in Plasma of Smallmouth Bass from the Chesapeake Bay Watershed

2021 ◽  
Vol 18 (11) ◽  
pp. 5881
Author(s):  
Vicki S. Blazer ◽  
Stephanie E. Gordon ◽  
Heather L. Walsh ◽  
Cheyenne R. Smith
Keyword(s):  
Land Use ◽  
Chesapeake Bay ◽  
Plasma Concentrations ◽  
Fish Tissue ◽  
Smallmouth Bass ◽  
Perfluoroalkyl Substances ◽  
Micropterus Dolomieu ◽  
Population Declines ◽  
Chesapeake Bay Watershed ◽  
Perfluorodecanoic Acid

Smallmouth bass Micropterus dolomieu is an economically important sportfish and within the Chesapeake Bay watershed has experienced a high prevalence of external lesions, infectious disease, mortality events, reproductive endocrine disruption and population declines. To date, no clear or consistent associations with contaminants measured in fish tissue or surface water have been found. Therefore, plasma samples from two sites in the Potomac River and two in the Susquehanna River drainage basins, differing in land-use characteristics, were utilized to determine if perfluoroalkyl substances were present. Four compounds, perfluorooctane sulphonic acid (PFOS), perfluoroundecanoic acid (PFUnA), perfluorodecanoic acid (PFDA) and perfluorododecanoic acid (PFDoA), were detected in every fish. Two additional compounds, perfluorooctane sulphonamide (PFOSA) and perfluorononanoic acid (PFNA), were less commonly detected at lower concentrations, depending on the site. Concentrations of PFOS (up to 574 ng/mL) were the highest detected and varied significantly among sites. No seasonal differences (spring versus fall) in plasma concentrations were observed. Concentrations of PFOS were not significantly different between the sexes. However, PFUnA and PFDoA concentrations were higher in males than females. Both agricultural and developed land-use appeared to be associated with exposure. Further research is needed to determine if these compounds could be affecting the health of smallmouth bass and identify sources.

scholarly journals Restoring steppe landscapes: patterns, drivers and implications in Russia’s steppes

2020 ◽  
Author(s):  
Robert Pazur ◽  
Alexander V. Prishchepov ◽  
Ksenya Myachina ◽  
Peter H. Verburg ◽  
Sergey Levykin ◽  
...  
Keyword(s):  
Land Use ◽  
Agricultural Land ◽  
Landsat Imagery ◽  
Regression Tree ◽  
Agricultural Land Use ◽  
Virgin Land ◽  
Human Footprint ◽  
Steppe Belt ◽  
Tree Models ◽  
Southern Russia

Abstract Context Agricultural land abandonment across the steppe belt of Eurasia has provided an opportunity for the restoration of steppe landscapes in recent decades. However, global food demands are about to revert this trajectory and put restored steppe landscapes at risk. Objectives We analysed steppe development in southern Russia in the last 40 years, assessed its spatial patterns and drivers of change for several periods. Methods Using Landsat imagery, we mapped the permanent steppe and steppe restoration from 1990 to 2018. Based on regression tree models, we evaluate and explain its dynamics. Results were compared with district-level trends in land-use intensities of cropland. Results We found 70% of the steppe in 2018 represented permanent steppe and 30% of former cropland dominantly abandoned in the postsocialism (1990–2000). The permanent steppe and steppe restored in the postsocialism (1990–2000) were located far from settlements, on rough terrain and in districts of the Virgin Land Campaign (1954–1963). In recent decades, the patterns of steppe restoration (2000–2018) were mostly determined by unfavourable agroclimatic conditions and distance from grain storage facilities. The restoration pattern reflects regional differences in land-use intensities, e.g., isolated steppe patches mostly appeared in areas of intensive agricultural land-use. Conclusions Steppe restoration has appeared in areas marginal for agricultural production, with poor natural conditions and little human footprint. Consequently, the permanent steppe became less fragmented and a more continuous steppe landscape resulted. The remaining isolated steppe patches require attention in restoration programs as they are mostly located in areas of intensive agricultural land-use.

A Practical Tutorial for Decision Tree Induction

2021 ◽  
Vol 54 (1) ◽  
pp. 1-38
Author(s):  
Víctor Adrián Sosa Hernández ◽  
Raúl Monroy ◽  
Miguel Angel Medina-Pérez ◽  
Octavio Loyola-González ◽  
Francisco Herrera
Keyword(s):  
Decision Tree ◽  
Decision Trees ◽  
Machine Learning Techniques ◽  
Evaluation Measures ◽  
Decision Tree Induction ◽  
Learning Techniques ◽  
Tree Models ◽  
Evaluation Measure ◽  
Main Components ◽  
Support Decision Making

Experts from different domains have resorted to machine learning techniques to produce explainable models that support decision-making. Among existing techniques, decision trees have been useful in many application domains for classification. Decision trees can make decisions in a language that is closer to that of the experts. Many researchers have attempted to create better decision tree models by improving the components of the induction algorithm. One of the main components that have been studied and improved is the evaluation measure for candidate splits. In this article, we introduce a tutorial that explains decision tree induction. Then, we present an experimental framework to assess the performance of 21 evaluation measures that produce different C4.5 variants considering 110 databases, two performance measures, and 10× 10-fold cross-validation. Furthermore, we compare and rank the evaluation measures by using a Bayesian statistical analysis. From our experimental results, we present the first two performance rankings in the literature of C4.5 variants. Moreover, we organize the evaluation measures into two groups according to their performance. Finally, we introduce meta-models that automatically determine the group of evaluation measures to produce a C4.5 variant for a new database and some further opportunities for decision tree models.

scholarly journals Evolutionary Algorithm for Improving Decision Tree with Global Discretization in Manufacturing

Sensors ◽  
2021 ◽  
Vol 21 (8) ◽  
pp. 2849
Author(s):  
Sungbum Jun
Keyword(s):  
Decision Tree ◽  
Evolutionary Algorithm ◽  
Decision Trees ◽  
Manufacturing Systems ◽  
Ensemble Methods ◽  
Machine Learning Techniques ◽  
Learning Techniques ◽  
Industrial Internet ◽  
Tree Models ◽  
Real World Datasets

Due to the recent advance in the industrial Internet of Things (IoT) in manufacturing, the vast amount of data from sensors has triggered the need for leveraging such big data for fault detection. In particular, interpretable machine learning techniques, such as tree-based algorithms, have drawn attention to the need to implement reliable manufacturing systems, and identify the root causes of faults. However, despite the high interpretability of decision trees, tree-based models make a trade-off between accuracy and interpretability. In order to improve the tree’s performance while maintaining its interpretability, an evolutionary algorithm for discretization of multiple attributes, called Decision tree Improved by Multiple sPLits with Evolutionary algorithm for Discretization (DIMPLED), is proposed. The experimental results with two real-world datasets from sensors showed that the decision tree improved by DIMPLED outperformed the performances of single-decision-tree models (C4.5 and CART) that are widely used in practice, and it proved competitive compared to the ensemble methods, which have multiple decision trees. Even though the ensemble methods could produce slightly better performances, the proposed DIMPLED has a more interpretable structure, while maintaining an appropriate performance level.

Childhood asthma and land‐use characteristics in school and residential neighborhoods: A decision tree learning approach

2021 ◽  
Author(s):  
Inês Paciência ◽  
João Cavaleiro Rufo ◽  
Ana Isabel Ribeiro ◽  
Milton Severo ◽  
André Moreira
Keyword(s):  
Land Use ◽  
Decision Tree ◽  
Childhood Asthma ◽  
Learning Approach ◽  
Decision Tree Learning

Impacts of road access on lake trout (Salvelinus namaycush) populations: regional scale effects of overexploitation and the introduction of smallmouth bass (Micropterus dolomieu)

2009 ◽  
Vol 66 (2) ◽  
pp. 212-223 ◽  
Author(s):  
Scott D. Kaufman ◽  
Ed Snucins ◽  
John M. Gunn ◽  
Wayne Selinger
Keyword(s):  
Lake Trout ◽  
Scale Effects ◽  
Regional Scale ◽  
Winter Season ◽  
Salvelinus Namaycush ◽  
Smallmouth Bass ◽  
Micropterus Dolomieu ◽  
Excessive Pressure ◽  
Fishing Activity ◽  
Remote Lakes

In lake trout ( Salvelinus namaycush ) lakes of northeastern Ontario, Canada, aerial surveys of fishing activity on individual lakes (N = 589) and quantitative gillnet surveys (N = 65) were used to assess the effects of road access on angling effort and the presence of introduced smallmouth bass ( Micropterus dolomieu ). Angling effort, particularly during the open-water season, was highest and often exceeded estimated sustainable levels on lakes with good road access. Approximately 25% of the remote lakes also received excessive pressure during the winter season. Angler numerical responses to lake trout abundance were detected in remote lakes, but not in road-accessible lakes. Smallmouth bass were more prevalent in lakes with road access and human settlement (either cottages or lodges), supporting the theory that they were introduced into these lakes. Lake trout populations were depleted throughout much of the study range. Even without road access or smallmouth bass, lake trout abundance was still 47% lower than in unexploited reference lakes. When bass and (or) road access were present, lake trout abundance decreased by 77%. Remote lake trout populations in this area are clearly vulnerable to the negative impacts of improved access, a vector for both overexploitation and species introductions.

scholarly journals River Otter, Lontra canadensis, Food Habits in the Missouri Ozarks

2008 ◽  
Vol 122 (4) ◽  
pp. 303 ◽  
Author(s):  
Nathan M. Roberts ◽  
Charles F. Rabeni ◽  
John S. Stanovick ◽  
David A. Hamilton
Keyword(s):  
Smallmouth Bass ◽  
Lontra Canadensis ◽  
Micropterus Dolomieu ◽  
Widespread Occurrence ◽  
River Otters ◽  
Lepomis Megalotis ◽  
Rock Bass ◽  
Longear Sunfish ◽  
The Mean ◽  
Ambloplites Rupestris

The reintroduction of River Otters (Lontra canadensis) between 1982 and 1992 resulted in widespread occurrence of the species throughout the Missouri Ozarks. This study examined otter diets from the vicinity of two Ozark streams in relation to seasonal and spatial trends. Otter scats (N = 4750) were collected and analyzed from the Osage Fork River and Big Piney River during the summer and winter seasons of 2001 and 2002. During the winter (January-March), fish occurred in 86% of the samples. During the summer (June–August), occurrence of fish dropped to approximately 15% for both rivers. Seven families of fish were identified in the diets, with Centrarchidae being most common regardless of river or season. Within the Centrarchidae, the genus Lepomis (mostly Longear Sunfish, Lepomis megalotis) was most common, with Micropterus (mostly Smallmouth Bass, Micropterus dolomieu) and Rock Bass (Ambloplites rupestris) also well represented. The mean age of Ambloplites consumed (mean = 3.3 years) was consistently older than that of either Micropterus (mean = 2.54 years) or Lepomis (mean = 2.78 years). Crayfish were recovered from a mean of 85.2% of scats in the winter and 99% in the summer. Smaller fish and crayfish were more common from the upper reaches of the streams while larger fish were prevalent in the lower reaches.

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