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NiCHE has archived 15 audio presentations from this event Between June 11 and 15, 2009, a group of students, faculty, and northern community members gathered under the midnight sun to consider the intersections of northern and environmental history. Citation : Bocking, Stephen. "Sketching a Political and Environmental History of Science in Northern Canada." Northern Environmental History Workshop. 13 June 2009. Bio : Stephen Bocking, Environmental & Resource Studies Program, Trent University. Abstract : I will present some ideas relating to understanding the political and environmental history of science in northern Canada since the 1940s. These ideas are tentative, representing one possible way of thinking about the history of northern science, and I will be eager for advice on how to work with them. Several themes that seem relevant to this history will be mentioned, including the intersection of scientific knowledge and cultural and political views of the north; and also the political history of northern science, particularly in terms of the way that shifting political priorities have been expressed through institutions for science. I will spend the most time surveying implications and questions that flow from viewing northern science in terms of concepts of situated science, with a focus on its material practice, using various examples from the history of the science over the last 60 years. Some of these questions include: how and why scientists (most based in the south) have defined the north as scientifically interesting; how features of the northern environment itself have influenced scientific work; how scientists have placed themselves: as "northern" scientists, or as representatives of disciplines that are mainly defined by scientific communities based in the south; how knowledge has moved in and out of the north; and how the authority of this knowledge has been asserted.

Zoomable full resolution image available at davidrumsey.com . This image 14359.070 is a part of image group 14359.000 . Three physical maps representing the United States, featuring the mean annual sunshine, mean annual evaporation and mean May-October evaporation, based upon the period from 1931 to 1960. Maps also show political boundaries, bodies of water, drainage, coastlines and islands. Maps include a legend, as well as a bar scale and scale statements (scales differ). Presented with Albers Equal Area Projection. With two inset maps within each map: Principal islands of Hawaii -- Alaska. Colored lithograph. Together, maps are 42 x 31 cm, on sheet 49 x 35 cm. Maps appear in Special subject maps section, subsection Physical : Climate. The national atlas of the United States of America, by the United States Geological Survey; published in Washington D. C., 1970. Bound in navy blue board, with title printed in silver on both front cover and spine. Accompanied by envelope with six overlay sheets, tucked between final page and back cover of volume. Collation: [i-vi], vii-xiii, [1], 2-417, A1, A2, B1, B2, C, D. Atlas contains 770 maps and 18 charts. Includes a dedication, foreward, list of contributors, introduction, table of contents and index to map subjects. Topic covered: physical geography, history, economics, culture, administrative boundaries and cartography. In addition, atlas also provides maps of the world, as related to the United States. Maps show political boundaries, cities, railways, roads, topography, bodies of water, glaciers, drainage, coastlines, islands, water depths and time zones. Topical maps feature other details, such as history, geology, climate, agriculture, population, racial demographics (including indigenous peoples), religion, language and transportation. Some maps use data visualization to further illustrate geographical information, with charts overlaid upon the landscape. "Adapted from "About The National Atlas of the United States of America," by the U.S. Geological Survey: The National Atlas of the United States of America was published in 1970. It was designed to be of practical use to decision makers in government and business, and for planners and research scholars as well as others needing to visualize country-wide distributional patterns and relationships between environmental phenomena and human activities. The National Atlas represents the principal characteristics of the country in 1970, including its physical features, historical evolution, economic activities, sociocultural conditions, administrative subdivisions, and place in world affairs. Various federal agencies, professional organizations, and commercial firms had advocated producing a National Atlas of the United States of America, but the magnitude of the task and the scope of the research required deterred those who would begin it. Late in 1954, the National Academy of Sciences-National Research Council established a Committee on the National Atlas of the United States, with representatives from several federal mapmaking agencies. The committee's primary responsibilities were to coordinate all federal agencies that would be involved in producing the atlas and to ensure uniform quality in its cartography. This proved to be a nearly impossible task, and consequently in 1961 the committee terminated itself. In so doing it recommended that the atlas be completed by one federal agency, preferably the Geological Survey in the U.S. Department of the Interior. In March of 1961, the Secretary of the Interior accepted the challenge. Congress appropriated funds to begin work on the National Atlas in 1963, and on reimbursable loan the Library of Congress made available the chief of its Geography and Map Division, Dr. Arch C. Gerlach, to serve as editor. Eighty-four agencies and bureaus appointed liaison officers to the National Atlas Project, base maps were prepared at four scales, and an advisory group of eminent cartographers and geographers collaborated to formulate fundamental design principles and specifications. The first part of the National Atlas is devoted to general reference maps that contain most of the forty-one thousand place names recorded in the index. These maps were included for the convenience of readers wanting basic locational information. In the thematic section of the National Atlas, separate subdivisions deal with the country's physical, historical, economic, and socio-cultural characteristics. The maps in this portion of the atlas represent the relationships between human beings and their environment while offering scientific bases for analyzing the nation's economic development in 1970. The National Atlas proved to be the last paper atlas of this magnitude produced by the federal government."

Zoomable full resolution image available at davidrumsey.com . This image 14359.070 is a part of image group 14359.000 . Three physical maps representing the United States, featuring the mean annual sunshine, mean annual evaporation and mean May-October evaporation, based upon the period from 1931 to 1960. Maps also show political boundaries, bodies of water, drainage, coastlines and islands. Maps include a legend, as well as a bar scale and scale statements (scales differ). Presented with Albers Equal Area Projection. With two inset maps within each map: Principal islands of Hawaii -- Alaska. Colored lithograph. Together, maps are 42 x 31 cm, on sheet 49 x 35 cm. Maps appear in Special subject maps section, subsection Physical : Climate. The national atlas of the United States of America, by the United States Geological Survey; published in Washington D. C., 1970. Bound in navy blue board, with title printed in silver on both front cover and spine. Accompanied by envelope with six overlay sheets, tucked between final page and back cover of volume. Collation: [i-vi], vii-xiii, [1], 2-417, A1, A2, B1, B2, C, D. Atlas contains 770 maps and 18 charts. Includes a dedication, foreward, list of contributors, introduction, table of contents and index to map subjects. Topic covered: physical geography, history, economics, culture, administrative boundaries and cartography. In addition, atlas also provides maps of the world, as related to the United States. Maps show political boundaries, cities, railways, roads, topography, bodies of water, glaciers, drainage, coastlines, islands, water depths and time zones. Topical maps feature other details, such as history, geology, climate, agriculture, population, racial demographics (including indigenous peoples), religion, language and transportation. Some maps use data visualization to further illustrate geographical information, with charts overlaid upon the landscape. "Adapted from "About The National Atlas of the United States of America," by the U.S. Geological Survey: The National Atlas of the United States of America was published in 1970. It was designed to be of practical use to decision makers in government and business, and for planners and research scholars as well as others needing to visualize country-wide distributional patterns and relationships between environmental phenomena and human activities. The National Atlas represents the principal characteristics of the country in 1970, including its physical features, historical evolution, economic activities, sociocultural conditions, administrative subdivisions, and place in world affairs. Various federal agencies, professional organizations, and commercial firms had advocated producing a National Atlas of the United States of America, but the magnitude of the task and the scope of the research required deterred those who would begin it. Late in 1954, the National Academy of Sciences-National Research Council established a Committee on the National Atlas of the United States, with representatives from several federal mapmaking agencies. The committee's primary responsibilities were to coordinate all federal agencies that would be involved in producing the atlas and to ensure uniform quality in its cartography. This proved to be a nearly impossible task, and consequently in 1961 the committee terminated itself. In so doing it recommended that the atlas be completed by one federal agency, preferably the Geological Survey in the U.S. Department of the Interior. In March of 1961, the Secretary of the Interior accepted the challenge. Congress appropriated funds to begin work on the National Atlas in 1963, and on reimbursable loan the Library of Congress made available the chief of its Geography and Map Division, Dr. Arch C. Gerlach, to serve as editor. Eighty-four agencies and bureaus appointed liaison officers to the National Atlas Project, base maps were prepared at four scales, and an advisory group of eminent cartographers and geographers collaborated to formulate fundamental design principles and specifications. The first part of the National Atlas is devoted to general reference maps that contain most of the forty-one thousand place names recorded in the index. These maps were included for the convenience of readers wanting basic locational information. In the thematic section of the National Atlas, separate subdivisions deal with the country's physical, historical, economic, and socio-cultural characteristics. The maps in this portion of the atlas represent the relationships between human beings and their environment while offering scientific bases for analyzing the nation's economic development in 1970. The National Atlas proved to be the last paper atlas of this magnitude produced by the federal government."

Zoomable full resolution image available at davidrumsey.com . This image 14359.070 is a part of image group 14359.000 . Three physical maps representing the United States, featuring the mean annual sunshine, mean annual evaporation and mean May-October evaporation, based upon the period from 1931 to 1960. Maps also show political boundaries, bodies of water, drainage, coastlines and islands. Maps include a legend, as well as a bar scale and scale statements (scales differ). Presented with Albers Equal Area Projection. With two inset maps within each map: Principal islands of Hawaii -- Alaska. Colored lithograph. Together, maps are 42 x 31 cm, on sheet 49 x 35 cm. Maps appear in Special subject maps section, subsection Physical : Climate. The national atlas of the United States of America, by the United States Geological Survey; published in Washington D. C., 1970. Bound in navy blue board, with title printed in silver on both front cover and spine. Accompanied by envelope with six overlay sheets, tucked between final page and back cover of volume. Collation: [i-vi], vii-xiii, [1], 2-417, A1, A2, B1, B2, C, D. Atlas contains 770 maps and 18 charts. Includes a dedication, foreward, list of contributors, introduction, table of contents and index to map subjects. Topic covered: physical geography, history, economics, culture, administrative boundaries and cartography. In addition, atlas also provides maps of the world, as related to the United States. Maps show political boundaries, cities, railways, roads, topography, bodies of water, glaciers, drainage, coastlines, islands, water depths and time zones. Topical maps feature other details, such as history, geology, climate, agriculture, population, racial demographics (including indigenous peoples), religion, language and transportation. Some maps use data visualization to further illustrate geographical information, with charts overlaid upon the landscape. "Adapted from "About The National Atlas of the United States of America," by the U.S. Geological Survey: The National Atlas of the United States of America was published in 1970. It was designed to be of practical use to decision makers in government and business, and for planners and research scholars as well as others needing to visualize country-wide distributional patterns and relationships between environmental phenomena and human activities. The National Atlas represents the principal characteristics of the country in 1970, including its physical features, historical evolution, economic activities, sociocultural conditions, administrative subdivisions, and place in world affairs. Various federal agencies, professional organizations, and commercial firms had advocated producing a National Atlas of the United States of America, but the magnitude of the task and the scope of the research required deterred those who would begin it. Late in 1954, the National Academy of Sciences-National Research Council established a Committee on the National Atlas of the United States, with representatives from several federal mapmaking agencies. The committee's primary responsibilities were to coordinate all federal agencies that would be involved in producing the atlas and to ensure uniform quality in its cartography. This proved to be a nearly impossible task, and consequently in 1961 the committee terminated itself. In so doing it recommended that the atlas be completed by one federal agency, preferably the Geological Survey in the U.S. Department of the Interior. In March of 1961, the Secretary of the Interior accepted the challenge. Congress appropriated funds to begin work on the National Atlas in 1963, and on reimbursable loan the Library of Congress made available the chief of its Geography and Map Division, Dr. Arch C. Gerlach, to serve as editor. Eighty-four agencies and bureaus appointed liaison officers to the National Atlas Project, base maps were prepared at four scales, and an advisory group of eminent cartographers and geographers collaborated to formulate fundamental design principles and specifications. The first part of the National Atlas is devoted to general reference maps that contain most of the forty-one thousand place names recorded in the index. These maps were included for the convenience of readers wanting basic locational information. In the thematic section of the National Atlas, separate subdivisions deal with the country's physical, historical, economic, and socio-cultural characteristics. The maps in this portion of the atlas represent the relationships between human beings and their environment while offering scientific bases for analyzing the nation's economic development in 1970. The National Atlas proved to be the last paper atlas of this magnitude produced by the federal government."

Pacific Science Center Teen Interns - Teen environmental stewardship interns at the Mercer Slough Environmental Education Center;

Pacific Science Center Teen Interns - Teen environmental stewardship interns at the Mercer Slough Environmental Education Center;

Pacific Science Center Teen Interns - Teen environmental stewardship interns at the Mercer Slough Environmental Education Center;

Pacific Science Center Teen Interns - Teen environmental stewardship interns at the Mercer Slough Environmental Education Center;

Pacific Science Center Teen Interns - Teen environmental stewardship interns at the Mercer Slough Environmental Education Center;

Pacific Science Center Teen Interns - Teen environmental stewardship interns at the Mercer Slough Environmental Education Center;

Pacific Science Center Teen Interns - Teen environmental stewardship interns at the Mercer Slough Environmental Education Center;

Pacific Science Center Teen Interns - Teen environmental stewardship interns at the Mercer Slough Environmental Education Center;

This book contains a 10-year outlook for the National Science Foundation (NSF) and addresses critical environmental challenges and develops environmental syntheses to frame integrated interdisciplinary research questions and activities to merge data, approaches, and ideas across spatial, temporal, and societal scales. It focuses on three interrelated areas: (1) coupled human and natural systems; (2) coupled biological and physical systems; and (3) people and technology. (KHR)

We describe an interactive collaborative environmental education project that makes advanced laboratory facilities at Brookhaven National Laboratory accessible for one-year or multi-year science projects for the high school level. Cyber-enabled Environmental Science (CEES) utilizes web conferencing software to bring multi-disciplinary, inquiry-based research opportunities to Districts who wish to participate. CEES serves as a model to show how students involved in distance learning and experimentation can engage in exciting, state-of-the-art research that enhances their skills for future Science, Technology, Engineering, and Math (STEM) careers. High school research opportunities through CEES support all seven New York State Standards for mathematics, science and technology (MST), Common Core and 12 of the National Geography Standards.

With the dramatic growth of environmental science as an elective in high schools over the last decade, educators have the opportunity to realistically consider the possibility of incorporating environmental science into the core high school curriculum. Environmental science has several characteristics that make it a candidate for the core curriculum. It is: (1) important for students and society; (2) an opportunity for students to experience an applied science; and (3) a particularly engaging context for learning fundamental science. In this paper, the author considers the possibility of a reform with the goal of achieving widespread adoption of environmental science as a required subject for high school by arguing for the value of environmental science, examining the rationale for the status quo, exploring what a high school core curriculum that includes environmental science might look like, and considering which of the elements that would be required to implement this reform are in place. The author concludes that many of the elements to support broad adoption of this reform are in place, but several are not, so additional groundwork would need to be laid before a large-scale reform effort targeted at integrating environmental science into the core high school curriculum could be successful. (Contains 2 footnotes.)

With the dramatic growth of environmental science as an elective in high schools over the last decade, educators have the opportunity to realistically consider the possibility of incorporating environmental science into the core high school curriculum. Environmental science has several characteristics that make it a candidate for the core curriculum. It is: (1) important for students and society; (2) an opportunity for students to experience an applied science; and (3) a particularly engaging context for learning fundamental science. In this paper, the author considers the possibility of a reform with the goal of achieving widespread adoption of environmental science as a required subject for high school by arguing for the value of environmental science, examining the rationale for the status quo, exploring what a high school core curriculum that includes environmental science might look like, and considering which of the elements that would be required to implement this reform are in place. The author concludes that many of the elements to support broad adoption of this reform are in place, but several are not, so additional groundwork would need to be laid before a large-scale reform effort targeted at integrating environmental science into the core high school curriculum could be successful. (Contains 2 footnotes.)

With the dramatic growth of environmental science as an elective in high schools over the last decade, educators have the opportunity to realistically consider the possibility of incorporating environmental science into the core high school curriculum. Environmental science has several characteristics that make it a candidate for the core curriculum. It is: (1) important for students and society; (2) an opportunity for students to experience an applied science; and (3) a particularly engaging context for learning fundamental science. In this paper, the author considers the possibility of a reform with the goal of achieving widespread adoption of environmental science as a required subject for high school by arguing for the value of environmental science, examining the rationale for the status quo, exploring what a high school core curriculum that includes environmental science might look like, and considering which of the elements that would be required to implement this reform are in place. The author concludes that many of the elements to support broad adoption of this reform are in place, but several are not, so additional groundwork would need to be laid before a large-scale reform effort targeted at integrating environmental science into the core high school curriculum could be successful. (Contains 2 footnotes.)

With the dramatic growth of environmental science as an elective in high schools over the last decade, educators have the opportunity to realistically consider the possibility of incorporating environmental science into the core high school curriculum. Environmental science has several characteristics that make it a candidate for the core curriculum. It is: (1) important for students and society; (2) an opportunity for students to experience an applied science; and (3) a particularly engaging context for learning fundamental science. In this paper, the author considers the possibility of a reform with the goal of achieving widespread adoption of environmental science as a required subject for high school by arguing for the value of environmental science, examining the rationale for the status quo, exploring what a high school core curriculum that includes environmental science might look like, and considering which of the elements that would be required to implement this reform are in place. The author concludes that many of the elements to support broad adoption of this reform are in place, but several are not, so additional groundwork would need to be laid before a large-scale reform effort targeted at integrating environmental science into the core high school curriculum could be successful. (Contains 2 footnotes.)

With the dramatic growth of environmental science as an elective in high schools over the last decade, educators have the opportunity to realistically consider the possibility of incorporating environmental science into the core high school curriculum. Environmental science has several characteristics that make it a candidate for the core curriculum. It is: (1) important for students and society; (2) an opportunity for students to experience an applied science; and (3) a particularly engaging context for learning fundamental science. In this paper, the author considers the possibility of a reform with the goal of achieving widespread adoption of environmental science as a required subject for high school by arguing for the value of environmental science, examining the rationale for the status quo, exploring what a high school core curriculum that includes environmental science might look like, and considering which of the elements that would be required to implement this reform are in place. The author concludes that many of the elements to support broad adoption of this reform are in place, but several are not, so additional groundwork would need to be laid before a large-scale reform effort targeted at integrating environmental science into the core high school curriculum could be successful. (Contains 2 footnotes.)

Philip Morris Records; report; extr, extra; marg, marginalia

Philip Morris Records; report; drft, draft

Philip Morris Records; report; extr, extra

Philip Morris Records; report; extr, extra

xi, 375 p. : 28 cm

xi, 375 p. : 28 cm

Model climate patterns, weather simulations, and environmental predictions with the GPU4Host AI server. Website:- https://www.gpu4host.com/gpu-cloud

This document presents a project that attempts to increase awareness of natural resources and surface and ground water in the Miami Valley region among elementary and middle school teachers and their students. The Miami Valley (Ohio) Environmental Science Education Teacher Enhancement Project Summer Workshop involved 33 teachers investigating a combination of field-based activities, exploration of environmental curricular materials, and the development of integrated units related to water resources and environmental topics. Annual follow-ups and quarterly meetings after the workshop indicate that teachers continued to use the water resource curricular materials in their instructional practices. (YDS)

This document presents a project that attempts to increase awareness of natural resources and surface and ground water in the Miami Valley region among elementary and middle school teachers and their students. The Miami Valley (Ohio) Environmental Science Education Teacher Enhancement Project Summer Workshop involved 33 teachers investigating a combination of field-based activities, exploration of environmental curricular materials, and the development of integrated units related to water resources and environmental topics. Annual follow-ups and quarterly meetings after the workshop indicate that teachers continued to use the water resource curricular materials in their instructional practices. (YDS)

This document presents a project that attempts to increase awareness of natural resources and surface and ground water in the Miami Valley region among elementary and middle school teachers and their students. The Miami Valley (Ohio) Environmental Science Education Teacher Enhancement Project Summer Workshop involved 33 teachers investigating a combination of field-based activities, exploration of environmental curricular materials, and the development of integrated units related to water resources and environmental topics. Annual follow-ups and quarterly meetings after the workshop indicate that teachers continued to use the water resource curricular materials in their instructional practices. (YDS)

This document presents a project that attempts to increase awareness of natural resources and surface and ground water in the Miami Valley region among elementary and middle school teachers and their students. The Miami Valley (Ohio) Environmental Science Education Teacher Enhancement Project Summer Workshop involved 33 teachers investigating a combination of field-based activities, exploration of environmental curricular materials, and the development of integrated units related to water resources and environmental topics. Annual follow-ups and quarterly meetings after the workshop indicate that teachers continued to use the water resource curricular materials in their instructional practices. (YDS)

The Speciality of Journal [Asian Journal of Environmental Science (AJES)] that it is an International Journal publication in the field of Environmental Science and Allied Sciences. Our high qualities International Journal are published with highly qualified Reviewers, Scholarly Scientists to ensure the originality, relevance, and readability. The International Journal published by us, aims to contribute to the constant scientific research and training in the field of Environmental Science and Allied Sciences.

The Speciality of Journal [Asian Journal of Environmental Science (AJES)] that it is an International Journal publication in the field of Environmental Science and Allied Sciences. Our high qualities International Journal are published with highly qualified Reviewers, Scholarly Scientists to ensure the originality, relevance, and readability. The International Journal published by us, aims to contribute to the constant scientific research and training in the field of Environmental Science and Allied Sciences.

AP Environmental Science By Advanced Placement

AP Environmental Science By Advanced Placement

Data Mining (DM) is a fundamental component of the Data Science process. Over recent years a huge library of DM algorithms has been developed to tackle a variety of problems in fields such as medical imaging and traffic analysis. Many DM techniques are far more flexible than more classical numerial simulation or statistical modelling approaches. These could be usefully applied to data-rich environmental problems. Certain techniques such as artificial neural networks, clustering, case-based reasoning or Bayesian networks have been applied in environmental modelling, while other methods, like support vector machines among others, have yet to be taken up on a wide scale. There is greater scope for many lesser known techniques to be applied in environmental research, with the potential to contribute to addressing some of the current open environmental challenges. However, selecting the best DM technique for a given environmental problem is not a simple decision, and there is a lack of guidelines and criteria that helps the data scientist and environmental scientists to ensure effective knowledge extraction from data. This paper provides a broad introduction to the use of DM in Data Science processes for environmental researchers. Data Science contains three main steps (pre-processing, data mining and post-processing). This paper provides a conceptualization of Environmental Systems and a conceptualization of DM methods, which are in the core step of the Data Science process. These two elements define a conceptual framework that is on the basis of a new methodology proposed for relating the characteristics of a given environmental problem with a family of Data Mining methods. The paper provides a general overview and guidelines of DM techniques to a non-expert user, who can decide with this support which is the more suitable technique to solve their problem at hand. The decision is related to the bidimensional relationship between the type of environmental system and the type of DM method. An illustrative two way table containing references for each pair Environmental System-Data Mining method is presented and discussed. Some examples of how the proposed methodology is used to support DM method selection are also presented, and challenges and future trends are identified.

Data Mining (DM) is a fundamental component of the Data Science process. Over recent years a huge library of DM algorithms has been developed to tackle a variety of problems in fields such as medical imaging and traffic analysis. Many DM techniques are far more flexible than more classical numerial simulation or statistical modelling approaches. These could be usefully applied to data-rich environmental problems. Certain techniques such as artificial neural networks, clustering, case-based reasoning or Bayesian networks have been applied in environmental modelling, while other methods, like support vector machines among others, have yet to be taken up on a wide scale. There is greater scope for many lesser known techniques to be applied in environmental research, with the potential to contribute to addressing some of the current open environmental challenges. However, selecting the best DM technique for a given environmental problem is not a simple decision, and there is a lack of guidelines and criteria that helps the data scientist and environmental scientists to ensure effective knowledge extraction from data. This paper provides a broad introduction to the use of DM in Data Science processes for environmental researchers. Data Science contains three main steps (pre-processing, data mining and post-processing). This paper provides a conceptualization of Environmental Systems and a conceptualization of DM methods, which are in the core step of the Data Science process. These two elements define a conceptual framework that is on the basis of a new methodology proposed for relating the characteristics of a given environmental problem with a family of Data Mining methods. The paper provides a general overview and guidelines of DM techniques to a non-expert user, who can decide with this support which is the more suitable technique to solve their problem at hand. The decision is related to the bidimensional relationship between the type of environmental system and the type of DM method. An illustrative two way table containing references for each pair Environmental System-Data Mining method is presented and discussed. Some examples of how the proposed methodology is used to support DM method selection are also presented, and challenges and future trends are identified.

Data Mining (DM) is a fundamental component of the Data Science process. Over recent years a huge library of DM algorithms has been developed to tackle a variety of problems in fields such as medical imaging and traffic analysis. Many DM techniques are far more flexible than more classical numerial simulation or statistical modelling approaches. These could be usefully applied to data-rich environmental problems. Certain techniques such as artificial neural networks, clustering, case-based reasoning or Bayesian networks have been applied in environmental modelling, while other methods, like support vector machines among others, have yet to be taken up on a wide scale. There is greater scope for many lesser known techniques to be applied in environmental research, with the potential to contribute to addressing some of the current open environmental challenges. However, selecting the best DM technique for a given environmental problem is not a simple decision, and there is a lack of guidelines and criteria that helps the data scientist and environmental scientists to ensure effective knowledge extraction from data. This paper provides a broad introduction to the use of DM in Data Science processes for environmental researchers. Data Science contains three main steps (pre-processing, data mining and post-processing). This paper provides a conceptualization of Environmental Systems and a conceptualization of DM methods, which are in the core step of the Data Science process. These two elements define a conceptual framework that is on the basis of a new methodology proposed for relating the characteristics of a given environmental problem with a family of Data Mining methods. The paper provides a general overview and guidelines of DM techniques to a non-expert user, who can decide with this support which is the more suitable technique to solve their problem at hand. The decision is related to the bidimensional relationship between the type of environmental system and the type of DM method. An illustrative two way table containing references for each pair Environmental System-Data Mining method is presented and discussed. Some examples of how the proposed methodology is used to support DM method selection are also presented, and challenges and future trends are identified.

Data Mining (DM) is a fundamental component of the Data Science process. Over recent years a huge library of DM algorithms has been developed to tackle a variety of problems in fields such as medical imaging and traffic analysis. Many DM techniques are far more flexible than more classical numerial simulation or statistical modelling approaches. These could be usefully applied to data-rich environmental problems. Certain techniques such as artificial neural networks, clustering, case-based reasoning or Bayesian networks have been applied in environmental modelling, while other methods, like support vector machines among others, have yet to be taken up on a wide scale. There is greater scope for many lesser known techniques to be applied in environmental research, with the potential to contribute to addressing some of the current open environmental challenges. However, selecting the best DM technique for a given environmental problem is not a simple decision, and there is a lack of guidelines and criteria that helps the data scientist and environmental scientists to ensure effective knowledge extraction from data. This paper provides a broad introduction to the use of DM in Data Science processes for environmental researchers. Data Science contains three main steps (pre-processing, data mining and post-processing). This paper provides a conceptualization of Environmental Systems and a conceptualization of DM methods, which are in the core step of the Data Science process. These two elements define a conceptual framework that is on the basis of a new methodology proposed for relating the characteristics of a given environmental problem with a family of Data Mining methods. The paper provides a general overview and guidelines of DM techniques to a non-expert user, who can decide with this support which is the more suitable technique to solve their problem at hand. The decision is related to the bidimensional relationship between the type of environmental system and the type of DM method. An illustrative two way table containing references for each pair Environmental System-Data Mining method is presented and discussed. Some examples of how the proposed methodology is used to support DM method selection are also presented, and challenges and future trends are identified.

Data Mining (DM) is a fundamental component of the Data Science process. Over recent years a huge library of DM algorithms has been developed to tackle a variety of problems in fields such as medical imaging and traffic analysis. Many DM techniques are far more flexible than more classical numerial simulation or statistical modelling approaches. These could be usefully applied to data-rich environmental problems. Certain techniques such as artificial neural networks, clustering, case-based reasoning or Bayesian networks have been applied in environmental modelling, while other methods, like support vector machines among others, have yet to be taken up on a wide scale. There is greater scope for many lesser known techniques to be applied in environmental research, with the potential to contribute to addressing some of the current open environmental challenges. However, selecting the best DM technique for a given environmental problem is not a simple decision, and there is a lack of guidelines and criteria that helps the data scientist and environmental scientists to ensure effective knowledge extraction from data. This paper provides a broad introduction to the use of DM in Data Science processes for environmental researchers. Data Science contains three main steps (pre-processing, data mining and post-processing). This paper provides a conceptualization of Environmental Systems and a conceptualization of DM methods, which are in the core step of the Data Science process. These two elements define a conceptual framework that is on the basis of a new methodology proposed for relating the characteristics of a given environmental problem with a family of Data Mining methods. The paper provides a general overview and guidelines of DM techniques to a non-expert user, who can decide with this support which is the more suitable technique to solve their problem at hand. The decision is related to the bidimensional relationship between the type of environmental system and the type of DM method. An illustrative two way table containing references for each pair Environmental System-Data Mining method is presented and discussed. Some examples of how the proposed methodology is used to support DM method selection are also presented, and challenges and future trends are identified.

Data Mining (DM) is a fundamental component of the Data Science process. Over recent years a huge library of DM algorithms has been developed to tackle a variety of problems in fields such as medical imaging and traffic analysis. Many DM techniques are far more flexible than more classical numerial simulation or statistical modelling approaches. These could be usefully applied to data-rich environmental problems. Certain techniques such as artificial neural networks, clustering, case-based reasoning or Bayesian networks have been applied in environmental modelling, while other methods, like support vector machines among others, have yet to be taken up on a wide scale. There is greater scope for many lesser known techniques to be applied in environmental research, with the potential to contribute to addressing some of the current open environmental challenges. However, selecting the best DM technique for a given environmental problem is not a simple decision, and there is a lack of guidelines and criteria that helps the data scientist and environmental scientists to ensure effective knowledge extraction from data. This paper provides a broad introduction to the use of DM in Data Science processes for environmental researchers. Data Science contains three main steps (pre-processing, data mining and post-processing). This paper provides a conceptualization of Environmental Systems and a conceptualization of DM methods, which are in the core step of the Data Science process. These two elements define a conceptual framework that is on the basis of a new methodology proposed for relating the characteristics of a given environmental problem with a family of Data Mining methods. The paper provides a general overview and guidelines of DM techniques to a non-expert user, who can decide with this support which is the more suitable technique to solve their problem at hand. The decision is related to the bidimensional relationship between the type of environmental system and the type of DM method. An illustrative two way table containing references for each pair Environmental System-Data Mining method is presented and discussed. Some examples of how the proposed methodology is used to support DM method selection are also presented, and challenges and future trends are identified.

Data Mining (DM) is a fundamental component of the Data Science process. Over recent years a huge library of DM algorithms has been developed to tackle a variety of problems in fields such as medical imaging and traffic analysis. Many DM techniques are far more flexible than more classical numerial simulation or statistical modelling approaches. These could be usefully applied to data-rich environmental problems. Certain techniques such as artificial neural networks, clustering, case-based reasoning or Bayesian networks have been applied in environmental modelling, while other methods, like support vector machines among others, have yet to be taken up on a wide scale. There is greater scope for many lesser known techniques to be applied in environmental research, with the potential to contribute to addressing some of the current open environmental challenges. However, selecting the best DM technique for a given environmental problem is not a simple decision, and there is a lack of guidelines and criteria that helps the data scientist and environmental scientists to ensure effective knowledge extraction from data. This paper provides a broad introduction to the use of DM in Data Science processes for environmental researchers. Data Science contains three main steps (pre-processing, data mining and post-processing). This paper provides a conceptualization of Environmental Systems and a conceptualization of DM methods, which are in the core step of the Data Science process. These two elements define a conceptual framework that is on the basis of a new methodology proposed for relating the characteristics of a given environmental problem with a family of Data Mining methods. The paper provides a general overview and guidelines of DM techniques to a non-expert user, who can decide with this support which is the more suitable technique to solve their problem at hand. The decision is related to the bidimensional relationship between the type of environmental system and the type of DM method. An illustrative two way table containing references for each pair Environmental System-Data Mining method is presented and discussed. Some examples of how the proposed methodology is used to support DM method selection are also presented, and challenges and future trends are identified.

Includes bibliographical references and index

Includes bibliographical references and index

Current research provides a limited understanding of the life long influence of nonformal place-based environmental and science education programs on past participants. This study looks to address this gap, exploring the ways in which these learning environments have contributed to environmental identity and stewardship. Using Dorothy Holland's approach to social practice theory's understanding of identity formation, this study employed narrative interviews and a close-ended survey to understand past participants' experience over time. Participants from two place-based environmental education programs and one science-inquiry program were asked to share their reflections on their program experience and the influence they attribute to that experience. Among all participants, the element of hands-on learning, supportive instructors, and engaging learning environments remained salient over time. Participants of nature-based programs demonstrated that these programs in particular were formative in contributing to an environmental stewardship identity. Social practice theory can serve as a helpful theoretical framework for significant life experience research, which has largely been missing from this body of research. This study also holds implications for the fields of place-based environmental education, conservation psychology, and sustainability planning, all of which look to understand and increase environmentally sustainable practices.

Current research provides a limited understanding of the life long influence of nonformal place-based environmental and science education programs on past participants. This study looks to address this gap, exploring the ways in which these learning environments have contributed to environmental identity and stewardship. Using Dorothy Holland's approach to social practice theory's understanding of identity formation, this study employed narrative interviews and a close-ended survey to understand past participants' experience over time. Participants from two place-based environmental education programs and one science-inquiry program were asked to share their reflections on their program experience and the influence they attribute to that experience. Among all participants, the element of hands-on learning, supportive instructors, and engaging learning environments remained salient over time. Participants of nature-based programs demonstrated that these programs in particular were formative in contributing to an environmental stewardship identity. Social practice theory can serve as a helpful theoretical framework for significant life experience research, which has largely been missing from this body of research. This study also holds implications for the fields of place-based environmental education, conservation psychology, and sustainability planning, all of which look to understand and increase environmentally sustainable practices.

William Paterson University Galleries director Kristen Evangelista worked with WP environmental science professor Nicole Davi to create a special project with professional artist Tattfoo Tan. Tan's artistic focus is sustainability and WP students worked with him to create mobile gardens that will be incorporated into his upcoming exhibition. For more info: http://www.wpunj.edu/coac/gallery and http://www.wpunj.edu/cosh/departments/environmental-science.

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This report considers the following issues, trends, and recent activities in science, mathematics, and environmental education: (1) inadequate achievement in knowledge, concepts, skills, and processes pertaining to these subjects; (2) curricula which do not provide the content needed for current and future academic and personal needs, do not reflect existing knowledge of learning and instruction, are not considered relevant by many students, and do not encourage the use of instructional materials besides textbooks; (3) lack of time devoted to problem-solving in mathematics and science; (4) inadequate emphasis on environmental education in terms of curriculum development, materials, and time devoted to the topic; (5) recent research describing effective instructional techniques; and (6) recruitment and retention of qualified teachers. In addition, recommendations for needed action are provided, as is a list of references. (PS)

This bibliography cites sources to assist middle, junior, and senior high school students and teachers in planning, preparing, and executing science fair projects in the environmental sciences. In addition, a few books with experiments suitable for elementary grade students are included. The listing includes: (1) 5 introductory texts; (2) 31 subject headings used by the Library of Congress under which books on environmental science projects can be located; (3) 9 basic texts; (4) 10 specialized titles; (5) 12 classroom experiments and activities in books and pamphlets; (6) 9 classroom experiments and activities in journal articles; (7) 15 handbooks, manuals, and reference tools; (8) 14 bibliographies and project indexes; (9) 7 book/film reviews and "best books" sources; (10) 6 abstracting and indexing services; (11) 20 journals; (12) 8 representative journal articles; (13) 13 selected materials; and (14) 4 additional sources of information. The listing is not intended to be comprehensive. (LZ)