Lecture Set 1: Harnessing Diverse Data for Ecological Insights Across Scales

Task A

Author

AJ Smit

Published

June 28, 2020

Lecture Series Assignment: Harnessing Diverse Data for Ecological Insights Across Scales

We increasingly rely on a rich ‘landscape’ of data sources to untangle the complexities of ecosystems at local, regional, and global scales. This assessment task requires the class to critically examine the wide array of ecological data, their acquisition, integration, and the transformative role of technology in driving ecological research.

Objective: Develop a comprehensive understanding of the diverse data sources available to ecologists, their strengths and limitations, and how to harness them effectively to address research questions across scales.

Approach: You will prepare a set of lectures that will explore the landscape of ecological data, from open data repositories to field campaign datasets, and discuss the methodologies for integrating and analysing these diverse sources. The role of technology in advancing ecological research and the principles of open science will also be highlighted.

Due Date: 27 June 2024

Lecture Series Structure

Create a lecture set comprised of a textbook (approx. 40-50 pages in Quarto, MS Word format, but presented as HTML) and Quarto slides that addresses the following key areas:

Topic 1: Defining the Data Landscape

Clearly define and contrast open data, field campaign data and other data (?) within the ecological context.
Delve into the strengths and limitations of each type of data. Consider aspects like data quality, biases, accessibility, cost, and the specific research questions they are best suited for.

Topic 2: Typology of Ecological Data

Develop a detailed typology of the different types of data ecologists utilise. Categorise data based on its nature (e.g., observational, experimental, spatiotemporal), source (e.g., remote sensing, citizen science), and level of organisation (e.g., individual, population, community, ecosystem).
Discuss how this typology helps us select appropriate data sources for our research questions and integrate diverse datasets effectively.

Topic 3: Data Repositories and Examples

Provide concrete examples of prominent open data repositories (e.g., PANGEA, GBIF, NEON, LTER) and platforms facilitating access to field campaign data (e.g., DataONE, specific research project websites).
Critically assess the strengths and weaknesses of these platforms, considering factors like data discoverability, metadata quality, and user-friendliness.

Topic 4: Data Integration Methodologies

Describe the challenges and opportunities associated with integrating disparate data sources. Explain the importance of data standardisation, cleaning, harmonisation, and alignment in time and space.
Discuss various data integration methods, such as data fusion, data assimilation, and meta-analysis. Explain how these methods enhance ecological research by combining information from multiple sources.

Topic 5: Case Studies Across Scales

Choose three specific case studies or research scenarios that exemplify the use of open data and field campaign data to address ecological questions across different spatial and temporal scales.
For each case study:
- Briefly describe the research question and ecological context.
- Identify the specific data sources used (both open and field campaign).
- Explain how the data was integrated and analysed.
- Summarise the key findings and their broader ecological implications.

Topic 6: The Role of Technology

Explore the advancements in data analytics, machine learning, and computational modeling that have revolutionised the way ecologists access, analyse, and integrate data.
Discuss how these technologies facilitate the extraction of patterns, identification of drivers, and forecasting of ecological dynamics.
Provide examples of how technology has enabled ecological research that was previously not feasible (e.g., large-scale species distribution modeling, ecosystem service assessments).

Topic 7: Open Science and FAIR Principles

Explain the principles of open science, with a focus on open data and the FAIR principles (Findable, Accessible, Interoperable, Reusable).
Discuss how open science fosters collaboration, accelerates scientific discovery, and enhances the reproducibility of ecological research.
Critically reflect on the potential of open science to democratize access to ecological data and empower researchers in under-resourced regions or disciplines.

Topic 8: Future Directions

Speculate on the future of data-driven ecological research. How might advancements in technology and the adoption of open science further transform the field?
Identify emerging challenges and opportunities, such as the need for robust data management practices, ethical considerations surrounding data use, and the potential for citizen science to contribute valuable ecological data.

Assessment Criteria

The class’ essay will be evaluated on:

Depth of understanding of ecological data sources and their applications.
Critical evaluation of the strengths and limitations of different data types and platforms.
Clarity and coherence in explaining data integration methods and technological advancements.
Relevance and depth of the case studies chosen.
Reflection on the broader implications of open science and technology for ecological research.
A weighted individual mark will be generated based on your personal contributions (volume and quality) to the the essay.

Additional Instructions

Please work as a class on this essay/lecture series. Provide a schema that shows me how work has been allocated to individuals within the class. This schema should be included as a separate document and I will use it to generate a weighting for individual marks. All tasks must selected so that they contribute to the overall coherence and quality of the document, and each much carry equal weight in terms of the final mark and time required to complete the task.

Your goal is to provide a professional, well-structured, and information-rich document. Here, professional applies to presentation (formatting and appearance) and content (quality of content, narrative, and language).

The maximum length of the essay should not exceed 40-50 pages, excluding references.

At the end, five or six individuals will present the material to the class as a series of three 30-minute lectures. These individuals will be chosen based on their contributions to the essay and their ability to present the material in a clear and engaging manner.

The points below will address some of the written presentation aspects:

Use citations and footnotes (including bibliography files and the automatic generation of bibliographies)—through collective effort by the class, you will learn how these tools work. To this end, 10% of the marks will assess your ability to use these facilities to their fullest extent.
The typology of data types can be presented as flow diagrams. Should you wish to include diagrams, please use Mermaid Diagrams within Quarto. Again, the combined class effort will quickly bring you towards grasping and understanding the concepts.
Should diagrams not be to your liking or not suited to your specific requirement, markdown tables might be a better option for presenting structured information.
Figures can also be inserted into Quarto documents if needs be.
To ensure easy use, provide your html file as a self-contained document by inserting the necessary options in your Quarto document’s YAML header.

Content

To arrive at professional content (emphasis on the language component of professional content), please feel free to use ChatGPT. However, I want to see two versions of your document:

the first version will show the essay in your own words, prior to applying ChatGPT polish
the second version will have the grammatical, punctuation, grammar, and language checked by ChatGPT

For example, consider the following text produced by a student:

Thin and elongated structures are essential for plants, this structures increase the surface area of the plants. Having a large surface area ensures that the mass f the plant is exposed to the sun and the environment around it. The plants will have large sa/v ratios, the plants will be dominated with physiological processes thus increasing their of photosynthesis because the ability oof diffusion is much faster.

In ChatGPT, construct the following prompt:

Correct the language and grammar: “Thin and elongated structures are essential for plants, this structures increase the surface area of the plants. Having a large surface area ensures that the mass f the plant is exposed to the sun and the environment around it. The plants will have large sa/v ratios, the plants will be dominated with physiological processes thus increasing their of photosynthesis because the ability oof diffusion is much faster.”

It will return the improved text:

Thin and elongated structures are vital for plants, as these structures augment the plant’s surface area. A larger surface area ensures that a substantial portion of the plant mass is exposed to the sun and its surrounding environment. As a result, plants will exhibit large surface area to volume (SA/V) ratios. Such plants will be characterized by dominant physiological processes, thereby enhancing their photosynthesis rates due to faster diffusion capabilities.

Submission instructions

Submit an essay structured under well-defined and logical headings by Tuesday, 27 June 2024, by no later than 23:59.

Provide your essay as a professional Quarto-generated html files.

Please label the Quarto and resulting HTML files as follows:

BCB743_2024_Task_A1_text.html — the textbook will have one submission for the class.

In addition, the presenters (different people to those who will present Task A2) will please submit their Quarto slides as follows:

BCB743_2024_<first_name>_<last_name>_Task_A1_slides.html

(the < and > must be omitted as they are used in the example as field indicators only).

Failing to follow these instructions carefully, precisely, and thoroughly will cause you to lose marks, which could cause a significant drop in your score as formatting counts for 15% of the final mark (out of 100%).

Submit your assignments on iKamva when ready.

Reuse

CC BY-NC-SA 4.0

Citation

BibTeX citation:

@online{j._smit2020,
  author = {J. Smit, Albertus and Smit, AJ},
  title = {Lecture {Set} 1: {Harnessing} {Diverse} {Data} for
    {Ecological} {Insights} {Across} {Scales}},
  date = {2020-06-28},
  url = {http://tangledbank.netlify.app/BCB743/assessments/Task_A1.html},
  langid = {en}
}

For attribution, please cite this work as:

J. Smit A, Smit A (2020) Lecture Set 1: Harnessing Diverse Data for Ecological Insights Across Scales. http://tangledbank.netlify.app/BCB743/assessments/Task_A1.html.

--- title: "Lecture Set 1: Harnessing Diverse Data for Ecological Insights Across Scales" subtitle: "Task A" author: - "AJ Smit" date: '2020/06/28 (updated: `r Sys.Date()`)' --- ## Lecture Series Assignment: Harnessing Diverse Data for Ecological Insights Across Scales We increasingly rely on a rich 'landscape' of data sources to untangle the complexities of ecosystems at local, regional, and global scales. This assessment task requires the class to critically examine the wide array of ecological data, their acquisition, integration, and the transformative role of technology in driving ecological research. **Objective**: Develop a comprehensive understanding of the diverse data sources available to ecologists, their strengths and limitations, and how to harness them effectively to address research questions across scales. **Approach**: You will prepare a set of lectures that will explore the landscape of ecological data, from open data repositories to field campaign datasets, and discuss the methodologies for integrating and analysing these diverse sources. The role of technology in advancing ecological research and the principles of open science will also be highlighted. **Due Date**: 27 June 2024 ### Lecture Series Structure Create a lecture set comprised of a textbook (approx. 40-50 pages in Quarto, MS Word format, but presented as HTML) and Quarto slides that addresses the following key areas: #### Topic 1: Defining the Data Landscape - Clearly define and contrast *open data*, *field campaign data* and other data (?) within the ecological context. - Delve into the strengths and limitations of each type of data. Consider aspects like data quality, biases, accessibility, cost, and the specific research questions they are best suited for. #### Topic 2: Typology of Ecological Data - Develop a detailed typology of the different types of data ecologists utilise. Categorise data based on its nature (e.g., observational, experimental, spatiotemporal), source (e.g., remote sensing, citizen science), and level of organisation (e.g., individual, population, community, ecosystem). - Discuss how this typology helps us select appropriate data sources for our research questions and integrate diverse datasets effectively. #### Topic 3: Data Repositories and Examples - Provide concrete examples of prominent open data repositories (e.g., PANGEA, GBIF, NEON, LTER) and platforms facilitating access to field campaign data (e.g., DataONE, specific research project websites). - Critically assess the strengths and weaknesses of these platforms, considering factors like data discoverability, metadata quality, and user-friendliness. #### Topic 4: Data Integration Methodologies - Describe the challenges and opportunities associated with integrating disparate data sources. Explain the importance of data standardisation, cleaning, harmonisation, and alignment in time and space. - Discuss various data integration methods, such as data fusion, data assimilation, and meta-analysis. Explain how these methods enhance ecological research by combining information from multiple sources. #### Topic 5: Case Studies Across Scales - Choose *three* specific case studies or research scenarios that exemplify the use of open data and field campaign data to address ecological questions across different spatial and temporal scales. - For each case study: - Briefly describe the research question and ecological context. - Identify the specific data sources used (both open and field campaign). - Explain how the data was integrated and analysed. - Summarise the key findings and their broader ecological implications. #### Topic 6: The Role of Technology - Explore the advancements in data analytics, machine learning, and computational modeling that have revolutionised the way ecologists access, analyse, and integrate data. - Discuss how these technologies facilitate the extraction of patterns, identification of drivers, and forecasting of ecological dynamics. - Provide examples of how technology has enabled ecological research that was previously not feasible (e.g., large-scale species distribution modeling, ecosystem service assessments). #### Topic 7: Open Science and FAIR Principles - Explain the principles of open science, with a focus on open data and the FAIR principles (Findable, Accessible, Interoperable, Reusable). - Discuss how open science fosters collaboration, accelerates scientific discovery, and enhances the reproducibility of ecological research. - Critically reflect on the potential of open science to democratize access to ecological data and empower researchers in under-resourced regions or disciplines. #### Topic 8: Future Directions - Speculate on the future of data-driven ecological research. How might advancements in technology and the adoption of open science further transform the field? - Identify emerging challenges and opportunities, such as the need for robust data management practices, ethical considerations surrounding data use, and the potential for citizen science to contribute valuable ecological data. ### Assessment Criteria The class' essay will be evaluated on: - Depth of understanding of ecological data sources and their applications. - Critical evaluation of the strengths and limitations of different data types and platforms. - Clarity and coherence in explaining data integration methods and technological advancements. - Relevance and depth of the case studies chosen. - Reflection on the broader implications of open science and technology for ecological research. - A weighted individual mark will be generated based on your personal contributions (volume and quality) to the the essay. ### Additional Instructions Please work as a class on this essay/lecture series. Provide a schema that shows me how work has been allocated to individuals within the class. This schema should be included as a separate document and I will use it to generate a weighting for individual marks. All tasks must selected so that they contribute to the overall coherence and quality of the document, and each much carry equal weight in terms of the final mark and time required to complete the task. Your goal is to provide a **professional, well-structured, and information-rich** document. Here, professional applies to presentation (formatting and appearance) *and* content (quality of content, narrative, and language). The maximum length of the essay should not exceed 40-50 pages, excluding references. At the end, five or six individuals will present the material to the class as a series of three 30-minute lectures. These individuals will be chosen based on their contributions to the essay and their ability to present the material in a clear and engaging manner. The points below will address some of the written presentation aspects: 1. Use [**citations and footnotes**](https://quarto.org/docs/authoring/footnotes-and-citations.html) (including bibliography files and the automatic generation of bibliographies)---through collective effort by the class, you will learn how these tools work. To this end, 10% of the marks will assess your ability to use these facilities to their fullest extent. 2. The typology of data types can be presented as flow diagrams. Should you wish to include diagrams, please use [**Mermaid Diagrams**](https://quarto.org/docs/authoring/diagrams.html) within Quarto. Again, the combined class effort will quickly bring you towards grasping and understanding the concepts. 3. Should diagrams not be to your liking or not suited to your specific requirement, [**markdown tables**](https://quarto.org/docs/authoring/tables.html) might be a better option for presenting structured information. 4. [**Figures**](https://quarto.org/docs/authoring/figures.html) can also be inserted into Quarto documents if needs be. 5. To ensure easy use, provide your html file as a [**self-contained**](https://quarto.org/docs/output-formats/html-basics.html#self-contained) document by inserting the necessary options in your Quarto document's YAML header. ### Content To arrive at professional content (emphasis on the language component of professional content), please feel free to use ChatGPT. However, I want to see two versions of your document: * the **first version** will show the essay in your own words, prior to applying ChatGPT polish * the **second version** will have the grammatical, punctuation, grammar, and language checked by ChatGPT For example, consider the following text produced by a student: > Thin and elongated structures are essential for plants, this structures increase the surface area of the plants. Having a large surface area ensures that the mass f the plant is exposed to the sun and the environment around it. The plants will have large sa/v ratios, the plants will be dominated with physiological processes thus increasing their of photosynthesis because the ability oof diffusion is much faster. In ChatGPT, construct the following prompt: > Correct the language and grammar: "Thin and elongated structures are essential for plants, this structures increase the surface area of the plants. Having a large surface area ensures that the mass f the plant is exposed to the sun and the environment around it. The plants will have large sa/v ratios, the plants will be dominated with physiological processes thus increasing their of photosynthesis because the ability oof diffusion is much faster." It will return the improved text: > Thin and elongated structures are vital for plants, as these structures augment the plant's surface area. A larger surface area ensures that a substantial portion of the plant mass is exposed to the sun and its surrounding environment. As a result, plants will exhibit large surface area to volume (SA/V) ratios. Such plants will be characterized by dominant physiological processes, thereby enhancing their photosynthesis rates due to faster diffusion capabilities.                    ::: callout-important ## Submission instructions Submit an essay structured under well-defined and logical headings by Tuesday, 27 June 2024, by no later than 23:59. Provide your essay as a **professional** Quarto-generated html files. Please label the Quarto and resulting HTML files as follows: - `BCB743_2024_Task_A1_text.html` --- the textbook will have one submission for the class. In addition, the presenters (different people to those who will present Task A2) will please submit their Quarto slides as follows: - `BCB743_2024_<first_name>_<last_name>_Task_A1_slides.html` (the `<` and `>` must be omitted as they are used in the example as field indicators only). Failing to follow these instructions carefully, precisely, and thoroughly will cause you to lose marks, which could cause a significant drop in your score as formatting counts for 15% of the final mark (out of 100%). Submit your assignments on iKamva when ready. :::