East coast mesh. Global Plastic Pollution: Uncovering the Extent in Coral Reefs and Freshwater Ecosystems

How does plastic pollution affect coral reefs and freshwater ecosystems globally. What are the key findings of recent large-scale studies on plastic contamination. How can international cooperation help assess and manage plastic pollution worldwide.

The Pervasive Nature of Plastic Pollution

Plastic pollution has become a ubiquitous environmental issue, extending far beyond marine ecosystems to impact wildlife across the planet and even Earth’s atmosphere. Recent large-scale studies have shed light on the global extent of plastic contamination in coral reefs and freshwater lakes, revealing concerning trends even in remote locations.

Microplastics in Freshwater Ecosystems: A Global Perspective

A groundbreaking study by Nava et al. has quantified microplastics in surface waters of lakes and reservoirs across 23 countries. This research provides valuable insights into the prevalence of plastic pollution in freshwater ecosystems worldwide.

Key Findings on Freshwater Microplastic Contamination

• Microplastics were found in lakes and reservoirs across diverse geographical regions
• Even remote water bodies showed evidence of plastic contamination
• The study highlights the far-reaching impact of human activities on freshwater ecosystems

Does the presence of microplastics vary significantly between different freshwater bodies. The study revealed considerable variations in microplastic concentrations, likely influenced by factors such as proximity to urban areas, local waste management practices, and water body characteristics.

Plastic Debris in Coral Reef Ecosystems: A Global Assessment

Complementing the freshwater research, Pinheiro et al. conducted an extensive survey of larger plastic debris contaminating coral reef ecosystems. This study encompassed 25 locations across the Pacific, Atlantic, and Indian oceans, providing a comprehensive view of plastic pollution in these vital marine habitats.

Coral Reef Plastic Pollution: Key Observations

• Plastic debris was found in coral reef ecosystems across all major ocean basins
• The study quantified the extent of plastic contamination in these sensitive marine environments
• Findings highlight the need for targeted conservation efforts to protect coral reefs from plastic pollution

Are certain types of coral reefs more susceptible to plastic pollution. The research suggests that factors such as reef location, ocean currents, and proximity to pollution sources may influence the accumulation of plastic debris in different reef ecosystems.

The Value of International Cooperation in Pollution Assessment

These ambitious sampling campaigns demonstrate the critical importance of international collaboration in assessing global environmental issues. By coordinating efforts across multiple countries and ecosystems, researchers can provide a more comprehensive understanding of plastic pollution’s extent and impact.

Benefits of Collaborative Research on Plastic Pollution

1. Broader geographical coverage enables identification of global patterns
2. Standardized methodologies allow for meaningful comparisons across regions
3. Pooled resources and expertise lead to more robust and comprehensive studies
4. International cooperation facilitates knowledge sharing and capacity building

How does international collaboration enhance our understanding of plastic pollution drivers. By studying diverse ecosystems across multiple countries, researchers can better identify common factors contributing to plastic contamination and develop more effective global management strategies.

Implications for Pollution Management and Policy

The findings from these global studies have significant implications for plastic pollution management and policy development. By providing concrete evidence of plastic contamination in diverse ecosystems, this research underscores the urgent need for coordinated action to address this pervasive environmental issue.

Key Considerations for Plastic Pollution Management

• Development of targeted strategies for different ecosystem types
• Implementation of international agreements to reduce plastic waste
• Investment in improved waste management infrastructure globally
• Promotion of alternatives to single-use plastics
• Enhancement of public awareness and education on plastic pollution

Can global research findings inform local plastic pollution management efforts. Absolutely. While the studies provide a broad perspective, their insights can be adapted to develop tailored solutions for specific regions or ecosystems, taking into account local conditions and challenges.

The Role of Standardized Methodologies in Plastic Pollution Research

One crucial aspect of these large-scale studies is the use of standardized methodologies for sampling and analysis. This approach ensures that data collected across different locations and ecosystems can be meaningfully compared and integrated to form a cohesive picture of global plastic pollution.

Advantages of Standardized Research Methods

• Facilitates direct comparison of results from different regions
• Enhances the reliability and reproducibility of findings
• Enables the creation of comprehensive global datasets
• Supports long-term monitoring of plastic pollution trends

How do standardized methodologies contribute to the accuracy of global plastic pollution assessments. By minimizing variations in sampling and analysis techniques, standardized methods reduce the potential for bias and inconsistencies, leading to more accurate and comparable results across different studies and locations.

Exploring the Sources and Pathways of Plastic Pollution

The global studies on plastic pollution in coral reefs and freshwater ecosystems not only quantify the extent of contamination but also provide valuable insights into the sources and pathways of plastic debris. Understanding these factors is crucial for developing effective prevention and mitigation strategies.

Common Sources of Plastic Pollution

• Urban runoff and wastewater discharge
• Improper waste disposal and landfill leakage
• Industrial activities and manufacturing processes
• Agricultural practices, including the use of plastic mulch
• Marine activities such as fishing and shipping

Do different ecosystems experience unique patterns of plastic pollution. Indeed, the research suggests that the sources and types of plastic contamination can vary significantly between freshwater and marine environments, as well as between urban and remote locations.

Pathways of Plastic Transport

1. River systems carrying plastic debris from inland areas to the ocean
2. Wind and atmospheric deposition of microplastics
3. Ocean currents dispersing plastic pollution across marine ecosystems
4. Fragmentation of larger plastic items into microplastics
5. Biotic transport through ingestion and excretion by wildlife

How does understanding pollution pathways inform management strategies. By identifying the primary routes through which plastics enter and move through different ecosystems, researchers and policymakers can develop targeted interventions to intercept and reduce plastic pollution at critical points along these pathways.

The Impact of Plastic Pollution on Ecosystem Health

While quantifying the presence of plastic pollution is crucial, understanding its ecological impacts is equally important. The studies by Nava et al. and Pinheiro et al. contribute to a growing body of evidence highlighting the detrimental effects of plastic contamination on ecosystem health.

Potential Ecological Consequences of Plastic Pollution

• Physical harm to wildlife through entanglement or ingestion
• Alteration of habitat structure and function
• Transfer of pollutants and invasive species
• Disruption of food webs and nutrient cycles
• Potential long-term impacts on biodiversity and ecosystem resilience

Are certain species or ecosystems more vulnerable to the effects of plastic pollution. Research suggests that some organisms, particularly filter feeders and those at lower trophic levels, may be disproportionately affected by microplastic pollution. Additionally, sensitive ecosystems like coral reefs may be particularly susceptible to the impacts of plastic debris.

Future Directions in Plastic Pollution Research and Management

The global studies on plastic pollution in coral reefs and freshwater ecosystems represent significant advances in our understanding of this pervasive environmental issue. However, they also highlight the need for continued research and action to address the challenges posed by plastic contamination.

Priorities for Future Research

1. Long-term monitoring of plastic pollution trends across diverse ecosystems
2. Investigation of the ecological and health impacts of different types of plastic pollutants
3. Development of innovative technologies for plastic detection and removal
4. Assessment of the effectiveness of various plastic pollution mitigation strategies
5. Exploration of the socioeconomic drivers and consequences of plastic pollution

How can technological advancements contribute to plastic pollution research and management. Emerging technologies such as remote sensing, artificial intelligence, and novel sampling techniques have the potential to enhance our ability to detect, quantify, and track plastic pollution across global ecosystems, enabling more efficient and comprehensive monitoring and mitigation efforts.

Strategies for Effective Plastic Pollution Management

• Implementation of circular economy principles to reduce plastic waste generation
• Development of biodegradable and environmentally friendly alternatives to conventional plastics
• Improvement of waste management infrastructure and practices globally
• Enforcement of regulations on plastic production, use, and disposal
• Promotion of consumer awareness and behavior change initiatives

Can international agreements play a significant role in addressing global plastic pollution. Absolutely. Given the transboundary nature of plastic pollution, international cooperation and agreements are essential for developing coordinated strategies to reduce plastic waste generation, improve waste management, and protect vulnerable ecosystems worldwide.

The global studies on plastic pollution in coral reefs and freshwater ecosystems serve as a call to action, highlighting the urgent need for concerted efforts to address this pervasive environmental challenge. By combining rigorous scientific research, international cooperation, and innovative management strategies, we can work towards reducing plastic pollution and safeguarding the health of our planet’s diverse ecosystems for future generations.

Large-scale collaborations uncover global extent of plastic pollution

• NEWS AND VIEWS
• 12 July 2023

Ambitious campaigns to sample plastic pollution in coral-reef and freshwater ecosystems demonstrate the value of international cooperation in assessing contamination to identify drivers and inform management.

• Kara Lavender Law ORCID: http://orcid.org/0000-0002-5298-6751⁰ &
• Chelsea M. Rochman ORCID: http://orcid.org/0000-0002-7624-711X¹

1. Kara Lavender Law

   1. Kara Lavender Law is at Sea Education Association, Woods Hole, Massachusetts 02543, USA.

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2. Chelsea M. Rochman

   1. Chelsea M. Rochman is in the Department of Ecology and Evolutionary Biology, University of Toronto, Toronto, Ontario ON M5S, Canada.

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Plastic pollution evokes powerful images of injured marine life tangled in plastic ropes, or starving seabirds whose guts are filled with broken plastics. But clear evidence is emerging that plastic contamination extends beyond marine ecosystems to affect wildlife around the planet¹, as well as Earth’s atmosphere². In this issue, researchers report global evidence that plastics contaminate coral reefs and freshwater lakes — some of which are far away from the human populations that create such pollution. Writing in Nature, Nava et al.³ quantify microplastics in surface waters of lakes and reservoirs in 23 countries, Pinheiro et al.⁴ measure larger plastic debris contaminating coral-reef ecosystems in 25 locations across the Pacific, Atlantic and Indian oceans.

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Nature 619, 254-255 (2023)

doi: https://doi.org/10.1038/d41586-023-02175-7

References

1. Santos, R. G., Machovsky-Capuska, G. E. & Andrades, R. Science 373, 56–60 (2021).

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Competing Interests

The authors declare no competing interests.

• Read the paper: Plastic debris in lakes and reservoirs

• Read the paper: Plastic pollution on the world’s coral reefs

• Mixed plastics upcycled dynamically

• Plastics can be a carbon sink but only under stringent conditions

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Want to build your own AI chatbot? Say hello to open-source HuggingChat

Photo by Jakub Porzycki/NurPhoto via Getty Images

In this article, we’re going to take a quick look at a ChatGPT-style AI chatbot from a company improbably called Hugging Face. I couldn’t look at the product seriously until I got past the name, so I asked its chatbot HuggingChat, “Why is your company called Hugging Face?”

Also: This new AI system can read minds accurately about half the time

Here’s what the AI told me:

The name “Hugging Face” comes from our goal to build AI models that can interact meaningfully and positively with humans on a personal level, similar to how one might hug someone they care about.

As you can see from the HuggingChat interface, the company is definitely going for that ChatGPT vibe:

Screenshot by David Gewirtz/ZDNET

But there are some big differences, the most notable being that it’s open source. It’s right here on Github.

While HuggingChat will appeal mostly to developers and AI tinkerers, anyone can play with the tool online. One thing I should note: almost all discussion of the online HuggingChat interface says it collects no information and does not require a login. That might have been the case for the very earliest release, but that’s no longer the case:

Screenshot by David Gewirtz/ZDNET

Using the Web version of HuggingChat

I had to set up an account with Hugging Face to gain access to the UI. And since I did not disable sending chat data to the developers for them to review and examine, I’d like to apologize to those developers now for the profanity. I just wanted to see what it would do. What!? I was curious.

One more clarification is necessary. Throughout this article, when I’m talking about the web version of HuggingChat, I’m referring to the version that Hugging Face is providing at hf.co/chat. There are likely hundreds of other web-based versions of HuggingChat, by hundreds of other developers. That’s the nature of open source. But for the next few moments, we’re talking about the factory store version — the one Hugging Face is making available to show off the tech.

Also: How to use ChatGPT to write code

The web version of HuggingChat uses a large language model (LLM) called OpenAssistant, which is also available on Github. As it turns out, there are a whole bunch of LLMs available on Github — and yeah, we’ll come back to that thought in a while, too.

As with ChatGPT and its ilk, you ask HuggingChat questions, and it answers. Unlike ChatGPT, there’s a little button right above the query field that says “Search web”, which means HuggingChat can reach out to the live web to do its research. For example, with “Search web” turned off, when I asked it, “Why did the submersible Titan sink?” I got back the reply:

I apologize, but without additional context, it’s difficult for me to determine which specific submersible Titan you’re referring to.

But when I turned on “Search web” and asked the same question, I got back:

Without more information, it’s hard for me to say definitively why it supposedly imploded and submerged during operations related to the RMS Titanic wreckage recovery effort off North America’s east coast (42°N 49°W / #TitanRover1).

Since the sinking of the submersible is a relatively recent story as I write this article, it shows that the pre-built LLM doesn’t have any data on this big news item. However, by choosing to include web search data, you can inform the chatbot’s results.

Overall, you’re probably not going to use HuggingChat instead of ChatGPT or Bard or Bing. Answers aren’t all that complete. They sometimes end in the middle of a sentence, and “continue” doesn’t bring them back on track. Most answers aren’t formatted, and are presented as one big paragraph. Responsiveness is fairly slow in comparison to ChatGPT. Sometimes, the answers don’t have all that much to do with the question.

Also: How (and why) to subscribe to ChatGPT Plus

To be fair, the web version of HuggingChat is a very early release and is mostly intended as a feature demo for the software itself. So, you’re probably not going to use it to cheat on your homework assignments. Instead, you’re more likely to use it to tinker with your own AI projects.

And that’s what we turn to next.

Building your own chatbot

If you’re super-geeky, you can build your own chatbot using HuggingChat and a few other tools. To be clear, HuggingChat itself is simply the user interface portion of an overall chatbot. It doesn’t contain the AI or the data. It just gets the question into the GPT and displays the answers.

You’ll also need a language model. As we discussed, OpenAssistant is one such language model, which can be trained on a variety of datasets.

This is where HuggingChat proves to be particularly interesting for AI geeks. You can use a variety of open-source LLMs, trained on a variety of open-source datasets, to power your own chatbot.

Also: Meet the post-AI developer: More creative, more business-focused

Taken to extremes, one possible application for this technology could be building a chatbot for use inside a corporation, trained on the company’s proprietary data, all of which is hosted within the enterprise firewall — never to be available to the internet at all.

In fact, by combining HuggingChat, an inference server, and an LLM, you can run your own chatbot on your own hardware, completely isolated from the internet.

This YouTube video gives a basic tutorial on how to do that in a container. Actually, the video also shows how to split the inference portion of the job from the UI portion of the job, and host part locally and part in the cloud. Basically, once you have the source information to play with, you can build pretty much whatever your imagination can think of — and that your gear can run.

Yeah, it does require a hefty server with some serious GPU horsepower. But that’s a small price to pay for your very own chatbot.

Also: Is this the snarkiest AI chatbot so far? I tried HuggingChat and it was weird

Seriously, though, this development is a big thing. ChatGPT is a powerful tool, trained on who knows what data, running who knows what algorithms, and producing answers based on who knows what source information.

If you want something that you control, you can use HuggingChat to build a chatbot where you have visibility into every aspect of its functioning. You can choose to make that chatbot available online to other users and provide transparency to all users. Or you can build a locked-down, special-purpose unit, which is hidden behind a firewall, and accessible only to your own employees.

With HuggingChat, the choice is up to you — and that’s cool.

So, do you expect to build your own chatbot? If you could, would you train it on any specific data? Since you now have the freedom to make the chatbot in your own image, what would you do with that power? Let us know in the comments below.

---

You can follow my day-to-day project updates on social media. Be sure to subscribe to my weekly update newsletter on Substack, and follow me on Twitter at @DavidGewirtz, on Facebook at Facebook.com/DavidGewirtz, on Instagram at Instagram.com/DavidGewirtz, and on YouTube at YouTube.com/DavidGewirtzTV.

Scoreboard East Coast Hockey League USA Ice Hockey

Scoreboard East Coast Hockey League USA Ice Hockey

• Hockey

• Matches

• Predictions

• Trends

• 900 04 Accumulators

• Leagues

My matches

Click next to the match to start receiving notifications and follow the match

HomeIce HockeyUSEA East Coast Hockey League

USA: East Coast Hockey League

USA

Overview

Predictions

Draw

Table

Idaho Steelheads 0

900 87

9004 8

Kalamazoo Wings

9004 9 43

9004 8

9004 9 H

Maine

9004 8

9 0049 66

Utah Grizzlies 59

9004 9

4.

Florida Everblades

90 049 69

9 0049 0

9004 9 223-244

9 0004 ECHL 22/23	and	H	H	R	W	14	290-153	119
2. Cincinnati Cyclones	72	47	0	25 900 52	266-216	103
3. Toledo Wallai	72	45	0	27	252-179	98
4.	72	48	0	24	271-217	98
5. South Carolina Stingrays	72	45	0	27	263-194	95
6. Jacksonville Iceman	71	44	0	27	230-203	93
7. Indy Fuel	72	43	0	29	245-208	91
with	72	41	0	31	262-215	88
9. Main Mariners	72	42	0	30	267-210	87
10. Greenville Swamp Rabbits	71	39	0	32	240-210	87
11. Florida Everblades	72	38	0	34	225- 213	85
12. Atlanta Gladiators	72	35	0	37	226-240	77
13. Allen Americans	72	37	0	35	260-263	77
14. Kansas City	72	34	0	38	222-224	76
15. Adirondack Thunder	72	32	0	40	237-243	75
16. Fort Wayne Comets	72	34	0	38	267-274	75
17. Utah Grizzlies	72	35	0	37	230-259	74
900 04 18. Wichita Thunder	72	33	0	39	227-238	73
19. Worcester Railers	7 2	34	0	38	227-242	72
20 Rapid City Rush	72	33	0	39	242-272	71 9 0052
21. Orlando Solar Bears	72	30	0	42	219-260	69
22. Savannah Ghost Pirates	72	28	0	44	207-258	72	29	0 900 52	43	178-226	64
24. Wheeling Nailers	72	29	0	43	223-244	63 900 52
25. Troyce Rivires Lions	72	29	0	43	216-273	61
26. 72	22	0	50	189-256	58 9Tulsa Oilers	203-279	53
28. Norfolk Admirals	72	21	0	51	203-318	47
ECHL 22/23, Central Division	and	H	H	M	W	O	Shape
1. Cincinnati Cyclones	72 9 0052	47	0	25	266-216 Toledo Wallai	72	45	0	27	252-179	98 90 052
3. Indy Fuel	72	43	0	29	245-208	91
4. 9000 5 Fort Wayne Comets	72	34	0	38	267-274	75
5. Kalamazoo Wings	72	29	0	178-226	64
6. Wheeling Nailers	72	29	0	43	223-244	63
7. Iowa Heartlanders	72	22	0	50	189- 256	58
ECHL 22/23, Eastern Conference	and	B	M	W	O	Shape
1. Newfoundland	72	48	0	24	271-217	98
2. South Carolina Stingrays	72	45	0	27	263-194	95
3. Jacksonville Iceman	71	44	0	27	230-203	93
4. Reading Royals	72	41	0	31	262-215	88
Mariners	72	42	0	30	267-210	87
6. Greenville Swamp Rabbits	71	39	0	32	240-210	87
7. Florida Everblades	72	38	0	34	225-213	8. Atlanta Gladiators	72	35	0	37	226-240 9 0052	77
9. Adirondack Thunder	72	32	0	40	237-243	75
10. Worcester Railers	72	34	0	38	227- 242	72
11. Orlando Solar Bears	72	30	0	42	219-260	69
12. Savannah Ghost Pirates	72	28	0	44	207-258
13. Troyce Rivires Lions	72	29 Norfolk Admi rals	72	21	0	51	203-318 9	and	B	H 90 052	M	W	O	Shape
1. Idaho Steelheads	72	58	0	14	290-153	119	900 67
2. Allen Americans	72	37	0	35	260-263	77
3. 005	72	34	0	38	222-224	76
74
5. Wichita Thunder	72	33	0	39	227-238	73
9000 4 6. Rapid City Rush	72	33	0	39	242-272	71
7	50	203-279	53
Division	and	H	H	M	W	M	Shape
9 0004 1. Newfoundland	72	48	0	24	271-217	98
2	31	262-215	88
3. Main Mariners	72	42	0	30	267-210	87
4. Adirondack Thunder	72	32	0	40	237-243	75
5 0049 34	0	38	227-242	72
6. Troyce Rivires Lions	72	29	0	43	216-273	61
7. Norfolk Admirals	72	21	0	51	203-318	47
ECHL 22/23, South Division	and	H	H	M	W	O	Shape
1. South Carolina Stingrays	72	45	0	27	263-194	95
2 Jacksonville Iceman	71	44	0	27	230-203	93 9 0052
3. Greenville Swamp Rabbits	71	39	0	32	240-210	87
72	38	0	34	225-213	85
Atlanta Gladiators	72	35	0	37	226-240	77
6. Orlando Solar Bears	72	30	0	42	219-260
7. Savannah Ghost Pirates	72	28	0	44	207-258	66
ECHL 22/23, Western Conference 900 05	and	H	H	M	W	O	Form
1. Idaho Steelheads	72	58	14	290-153	119
2. Cincinnati Cyclones	72	47	0	25 048	3. Toledo Wallai	72	45	0	27	252-179	98
4. Indy Fuel 90 005	72	43	0	29	245-208	91
5. Allen Americans	72	37	0	35	260-263	77
6. Kansas City	72	34	0	38	222-224	76
9000 4 7. Fort Wayne Comets	72	34	0	38	267-274	75
8	37	230-259	74
9. Wichita Thunder	72	33	0	39	227-238	73
10. Rapid City Rush	72	33	0	39	242-272	71
-11	29	0	43	178-226	64
12. Wheeling Nailers	72	29	0	43	63
13. Iowa Heartlanders	72	22 Tulsa Oilers	0	50	189-256	72	22	0	50	203-279	53

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Ocean bathymetric data search | Learn ArcGIS

Bathymetry is the study of ocean depths. Acquiring and extracting information from bathymetric data is a costly and time-consuming task, but fortunately a vast amount of data is available to the general public through data portals. In this lesson, you will act as a student at the beginning of a research project to study the ocean floor off the East Coast of the United States. Before you can perform analysis, you need to compile the data. You will explore a number of online portals to search for different bathymetric datasets. You’ll add this data to your ArcGIS Pro project both as services and as uploaded files.

When completed, you will have an ArcGIS Pro project configured with the datasets you need for your further exploration. Along the way, you’ll learn where and how to get bathymetric data, the different types of data used in ocean science, and how to add it to maps in ArcGIS Pro.

This lesson was last tested on March 27, 2023 using ArcGIS Pro 3.1. If you have a different version of ArcGIS Pro, results and functionality may vary.

Requirements

• Publisher or Administrator role in an ArcGIS organization: ArcGIS Online (see software access options) or ArcGIS Enterprise (more info)
• ArcGIS Pro (see software access options)

Outline

Find Bathymetric Data Services You will explore data portals and add data services to the map.	30 minutes
Download bathymetric data You will download and compare digital depth models.	20 minutes

Seabed mapping is not a new process. However, the tools that oceanographers use to measure and navigate erratic waters safely are improving as new technologies become available. In addition to navigation, maps of the ocean floor are also used in tasks: laying underwater communications, studying natural resources, building wind turbines, as well as clarifying the maritime borders of states.

There are currently several methods of seafloor mapping and many formats for working with bathymetric data. You’ll start by exploring the data that is available as web services.

Exploring the Ocean Data Portal

You will first work with the General Bathymetric Chart of the Ocean (GEBCO) portal. GEBCO collects and makes available trusted and publicly available bathymetric datasets from a variety of sources, including government and research organizations.

1. Go to https://www.gebco.net/ and explore this site.
2. At the top of the page, click the Data & Products tab. Click GEBCO Web Services.
3. Read GEBCO’s Web Services Access page. Click the services available link.
4. Copy URL: https://www.gebco.net/data_and_products/gebco_web_services/web_map_service/.
5. Read it to see if there are restrictions on its use.

You have now found a WMS URL and have read its terms and conditions. Many geodata portals provide data in WMS format.

Viewing the WMS layer in ArcGIS Pro

Next, you will view WMS in ArcGIS Pro.

1. Start ArcGIS Pro. If prompted, sign in with a licensed ArcGIS organizational account.
2. In the Blank Templates section, click Map.

3. In the Create New Project window, for Name, type Ocean.
4. For Location, click the Browse button and select a location of your choice, such as drive C.
5. Leave Create a new folder for this project checked.
6. Press OK.

   ArcGIS Pro opens and displays a map of the world. Panels can be opened from either side of the map.

7. Click the View tab on the ribbon. In the Windows group, click Reset Panels and select Reset Mapping Panels (Default).
8. On the ribbon, click the Map tab. In the Layer group, click the bottom of the Add Data button and then click Data from Path.
9. In the Path field, paste the URL to the GEBCO WMS: https://www.gebco.net/data_and_products/gebco_web_services/web_map_service/mapserv?

   Another menu will appear.

10. For Service Type, select WMS OGC Web Service.
11. Click Add.
12. In the Contents pane, click the arrow next to the WMS layer to expand it. Also expand its sublayer.
13. Hold down the Ctrl key and click on the label next to any of the sublayers.
14. Turn on the GEBCO Grid color-shaded for elevation layer.
15. Disable GEBCO Grid color-shaded for elevation and enable GEBCO Grid shaded relief.
16. You can move and zoom in on the map to explore.
17. In the Contents pane, enable GEBCO_LATEST TID 2 Grid.
18. In the Contents pane, expand the GEBCO_LATEST TID 2 Grid sublayer.

Exploring the base map of the oceans

The WMS data you explored is a type of service. Services are data that goes directly to your card. They are owned, managed and kept by someone else. Services are regularly updated and do not take up space on your computer. They also allow you to quickly view large amounts of data.

One of the most commonly used types of map services are basemaps, which are needed to give geographic context to other data. Esri provides many basemaps that are accessed directly in ArcGIS software. Your map already has a basemap, but you will change it to one that is more suitable for oceanography.

1. In the Contents pane, collapse the GEBCO_Latest TID 2 Grid sublayer. Disable all WMS sublayers.
2. On the ribbon, click the Map tab. In the Layer group, click Basemap. In the Basemap gallery, click Oceans.
3. You can move and zoom in on the map to explore.

4. Turn on the GEBCO Grid shaded relief sublayer.
5. Select the layer on top of the WMS. Click the WMS Layer tab on the ribbon. In the Compare group, click the Hide tool.

6. Drag over the map to compare the GEBCO layer to the basemap. Explore several territories in the North Atlantic Ocean.
7. On the ribbon, click the Map tab. In the Navigation group, click the Explore tool so you can navigate the map instead of moving the shade.
8. In the Contents pane, turn off and collapse the WMS layer.

Explore the geomorphology of the seabed

You will add another map service to your project: a layer that represents the geomorphological features of the world’s oceans. Geomorphology seeks to understand why landscapes (or, in this case, seascapes) are shaped the way they are and how they change over time. It is the science of topographic (land) and bathymetric (ocean) objects. You’ll add this layer from ArcGIS Online and explore it in ArcGIS Pro to get new information about your study area.

1. In the Catalog pane, click the Portal tab and click the Living Atlas tab.
2. In the search bar, type World Seafloor Geomorphology and press Enter. In the search results, navigate to World Seafloor Geomorphology.
3. In the search results, right-click World Seafloor Geomorphology and then click Add to Current Map.
4. In the Contents panel, turn off the World Ocean Base layer to see the colors of the map more clearly.
5. On the ribbon, click the Map tab. In the Query group, click the Find button.

   The Find Location panel appears.

6. In the Find Location panel, type New England Seamounts in the search bar and press Enter.
7. Get even closer to the New England mountains. Close the Find Location panel.
8. In the Contents pane, expand the World Seafloor Geomorphology layer. Press the Ctrl key and click the arrow next to one of the sublayers to expand all sublayers at the same time.
9. Press the Ctrl key and click on one of the layers to turn them all off at the same time.
10. Turn the Seamounts sublayer back on. Scroll down the list and turn on the Zone layer.
11. Turn on the rest of the sublayers one by one to see them on the map.
12. In the Contents pane, right-click World Seafloor Geomorphology and then View Metadata.
13. Read about some of the objects that are visible on the map.

    Question 4: What other features are in the New England Mountains? Study the geographic pattern that is observed based on this data in this area.

14. Close the Catalog view.
15. Collapse and turn off the World Seafloor Geomorphology layer. Turn on the World Ocean Base layer.
16. On the Quick Access Toolbar, click the Save button.

So, in this lesson, you learned about different types of map services: data that is stored somewhere else and is available over the Internet. Next, you’ll download the data so you can work with a local copy saved on your computer.

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Downloading data has several advantages over accessing it through web services: you can edit the data, change the way it is displayed, use it to create new datasets, and perform analysis. In addition, you eliminate the risk of data being changed or lost.

Digital Elevation Model Download

You will find and download two Digital Elevation Models (DEMs) from the National Oceanic and Atmospheric Administration (NOAA).

1. Go to https://ngdc.noaa.gov/mgg/bathymetry/relief.html.

   National Centers for Environmental Information (NCEI) is a division of NOAA that manages one of the largest environmental data archives in the world. This collection includes many products based on bathymetric data.

2. Explore the links on this page to learn about the different data options.
3. Return to the main page, scroll to NCEI Bathymetric Data Viewer and click Launch Interactive Map.

4. Click Redirect now if necessary. Or go directly to https://www.ncei.noaa.gov/maps/bathymetry/.
5. In the Layers panel next to the map, uncheck everything except DEM Footprints.

6. Zoom in on the map to the US East Coast. Approach the mouth of the Chesapeake Bay.

7. Click on the map inside the Virginia Beach rectangle.
8. In the pop-up window, expand the NCEI Digital Elevation Models folder. Click Virginia Beach (1/3 arc-second).
9. Click Link to Metadata.
10. On the Access tab, next to Download Data, click Download NetCDF File.
11. Download Atlantic DEM.

    This layer is a subset of another DEM dataset from NCEI. It has been cropped to a smaller area to allow for faster loading in this tutorial. The metadata for the original dataset is at U.S. Coastal Relief Model Vol.2 – Southeast Atlantic.

12. Once the Atlantic_DEM.tif file is downloaded, move it to your Ocean folder.

DEM Viewer

Both of the files you downloaded are digital elevation models, which means that they store information about heights above or below sea level. However, they are stored in two different data formats: .nc (netCDF) and .tif. First you will add to the map and examine the .tif file.

1. Open your Ocean project in ArcGIS Pro. On the ribbon, click the Map tab. In the Layer group, click Add Data.
2. In the Add Data window, in the sidebar, under Project, expand Folders and click Ocean.
3. Click Atlantic_DEM.tif.

4. Click OK.
5. In the Contents pane, right-click Atlantic_DEM.tif and then Zoom to Layer.
6. In the Contents pane, right-click Atlantic_DEM.tif and then click Properties.
7. In the Layer Properties window, click the Source tab. Expand the Data Source section if necessary.
8. Close the Layer Properties window.
9. Navigate the map to explore the data. Click anywhere in the data.
10. Close the pop-up window.

    Question 6: Describe the terrain you see in the Atlantic DEM layer.

11. In the Contents pane, turn on the World Seafloor Geomorphology layer and drag it above the Atlantic DEM layer.
12. Expand the World Seafloor Geomorphology layer and turn off all sublayers except for Canyons.

    On the DEM, canyons appear as dark blue lines running from high to low areas. Many of these canyons were probably formed by rivers during the last ice age, when sea levels were substantially lower and the continental shelf was land surface.

13. Get closer to explore the canyons better.
14. Collapse the World Seafloor Geomorphology layer and turn it off. Right-click the Atlantic DEM and click Zoom To Layer.

DEM Comparison

Next, you’ll add the DEMs you downloaded from NCEI and compare them to the .tif layer.

1. Once virginia_beach_13_mhw_2007. nc is downloaded, move it to your Ocean folder.
2. In ArcGIS Pro, click the Map tab on the ribbon. In the Layer group, click the bottom half of the Add Data button. Click Multidimensional Raster Layer.
3. For Input File, click the Browse button. Navigate to the Ocean folder and select virginia_beach_13_mhw_2007.nc. Click OK.
4. In the Select Variables table, check the box next to Band1. Make sure the Output Configuration is set to Multidimensional Raster.

5. Click OK.
6. In the Contents pane, click the virginia_beach_13_mhw_2007.nc_Band1 layer to select it. Press F2 on your keyboard to change the layer name. Type Virginia Beach DEM and press Enter.
7. In the Contents pane, under Virginia Beach DEM, right-click the legend. Click the color scheme menu and select the Black and White scheme. (Hover over the color scheme to read the title.)
8. Right-click the legend again and click the Invert Color Scheme button. Click outside the color scheme window to confirm your changes.
9. In the Contents pane, turn on the World Seafloor Geomorphology layer.
10. On the Quick Access Toolbar, click the Save button.

In this lesson, you explored several sources of bathymetric data. You have accessed GEBCO data via a WMS URL, the Oceans basemap via the basemap gallery, and the geomorphological map from ArcGIS Living Atlas via the Catalog pane. You have downloaded two DEM datasets, one from the NCEI Data Portal. And this is only a small part of the bathymetric data sources available online.

Learning about data portals and the datasets they contain is an essential step in any GIS project. Finding the right geospatial data is often a time consuming process, but doing a thorough research early in the process will make the rest of your GIS project easier.

You can find more lessons in the Learn ArcGIS tutorial gallery. For further study of the Atlantic DEM layer used in this tutorial, see Rendering an Undersea Canyon in 2D and 3D.

Questions answered

1. Are you allowed to use this data? How did you know?

   Yes, this data can be used. In the Data sources and WMS development section, click the GEBCO Grid or documentation link. Both of these links will take you to the Gridded Bathymetry Data page, where you can learn more about the data that was used to create the WMS. The Terms of use section states that “GEBCO Grid is placed under the public domain and may be used free of charge.” (“GEBCO Grid is in the public domain and can be used free of charge.”) Click on the link with the terms of use and disclaimer information to learn more.

2. How will you refer to the data in your final project?

   The data source must be confirmed with the following text: Imagery reproduced from the GEBCO_2021 Grid, GEBCO Compilation Group (2021) GEBCO 2021 Grid (doi:10.5285/c6612cbe-50b3-0cff-e053-6c86abc09f8f). This information can be found on the GEBCO WMS page under Data set acknowledgment.

3. What are the similarities and differences between a WMS layer and a basemap.

   Both layers contain hillshade of the ocean floor, and depths are shown in different shades of blue. Depth colors are more pronounced in WMS layers, making it easier to visualize some features, such as the Puerto Rican Trench. The basemap layer contains feature labels such as canyons, ridges, and depth measurements to help identify features or regions. The basemap is multi-scale, which means that as you get closer, more information will be available to you.

4. What other sites are in the New England Mountains? Study the geographic pattern that is observed based on this data in this area.
5. What data formats are available?

   These are .csv files, GeoTiff, netCDF, ESRI ASCII raster grids, XYZ grids, multibeam files, CDs, etc.

6. In the Atlantic DEM, there is no visible elevation change on the continental shelf: the entire area appears flat and white, not even the coastline is visible. Why does the Virginia Beach DEM show a large difference in elevation for the same area?

   The continental slope is the most prominent feature in the Atlantic DEM layer. Stretching from north to south, it divides the study area into two different height regions. It is intersected by canyons and slopes. The coastline is not visible.

7. The Atlantic DEM has a much greater altitude range than the Virginia Beach DEM (2,903 meters versus 85 meters). This allows for more detail and subtle changes in terrain in the Virginia Beach DEM, while in the Atlantic DEM the entire color range shows a huge change in the elevation of the continental slope.
8. How can you explain that the Virginia Beach DEM has a higher resolution than the Atlantic DEM?
9. How can high-resolution ocean floor and surface elevation data help protect against tsunamis?

   Tsunamis behave according to the laws of physics, and their travel time, speed (wave speed) and amplitude (wave height) depend on the depth and configuration of the coastline. The shape, direction, and force of a tsunami impact are especially dependent on the depth and width of the seafloor over which it passes. The nature of damage occurring on land will vary depending on the topography of the coastline.

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Copyright by third parties

• GEBCO WMS: Imagery derived from GEBCO_2021 Grid, GEBCO Compilation Group (2021) GEBCO 2021 Grid (doi:10.5285/c6612cbe-50b3-0cff-e053-6c86abc09f8f ).
• World Seafloor Geomorphology: GRID Arendal.
• Atlantic DEM: NOAA National Geophysical Data Center. 1998: U.S. Coastal Relief Model Vol.2 – Southeast Atlantic. NOAA National Centers for Environmental Information. https://doi.org/10.7289/V53R0QR5. Access tested March 2022.
• Virginia Beach DEM: NOAA National Geophysical Data Center. 2007: Virginia Beach, Virginia 1/3 Arc-second MHW Coastal Digital Elevation Model. NOAA National Centers for Environmental Information.