Making Effective Figures

•

0 likes•184 views

Zachary Labe

Professional development series for CSU's Department of Atmospheric Science REU program in 2021

Science

MAKING
EFFECTIVE FIGURES
ZACHARY LABE | 20 JULY 2021 | REU PROFESSIONAL DEVELOPMENT | COLORADO STATE UNIVERSITY

Polar Amplification: acceleration of
warming in high latitudes relative to
the rest of the globe

Warmer
Colder
NOW
Start of
satellite-era

DON’T BE
SUCH A
SCIENTIST
WE ARE
DATA
SCIENTISTS
ART BY JILL PELTO

Landscape of Change uses data
about sea level rise, glacier volume
decline, increasing global
temperatures, and the increasing use
of fossil fuels. These data lines
compose a landscape shaped by
the changing climate, a world in
which we are now living.
Jill Pelto|http://www.jillpelto.com/landscape-of-change
“
”

Senator Sheldon Whitehouse (D-CT) - Time to Wake Up: Climate Progress Speech (3/21/2018)

#endrainbow
Check out: https://betterfigures.org/2018/06/04/playing-hunt-the-discontinuity/

Adapted from Ed Hawkins at betterfigures.org

Crameri, F. (2018). Scientific colour maps.
Zenodo. http://doi.org/10.5281/zenodo.1243862
Crameri, F. (2018), Geodynamic diagnostics, scientific
visualisation and StagLab 3.0, Geosci. Model Dev., 11, 2541-
2562, doi:1 0.5194/gmd-11-2541-2018
Crameri, F., G.E. Shephard, and P.J. Heron (2020), The
misuse of colour in science communication, Nature
Communications, 11, 5444. doi:10.1038/s41467-020-19160-7
Palettable:
Color palettes for Python

OTHER OPTIONS
THYNG ET AL. 2016; OCEANOGRAPHY

CMASHER
“Scientific colormaps for making accessible,
informative and cmashing plots”

1. Seaborn.
2. Plotly.
3. ggplot.
4. Matplotlib v3.
ALTERNATIVES

1. https://betterfigures.org/
2. https://www.climate-lab-book.ac.uk/
3. http://colorbrewer2.org/
RESOURCES

Future minus Pre-Industrial PEINGS ET AL. 2021, JCLI
Bring drama to your data story

2-m
TEMPERATURE
Future minus Pre-Industrial PEINGS ET AL. 2021, JCLI

ACCESSIBILITY
No jargon
Tell a story
Alternative text
Color contrast ratio
Label data directly
Avoid flashing GIFs
Include figure titles
Avoid data overlays
Provide data references

PLOT BY ED HAWKINS
DON’T BE
SUCH A
SCIENTIST
WE ARE
DATA
SCIENTISTS

https://showyourstripes.info/
PLOT BY ED HAWKINS

CHECK:
Simple.
Bold.
Stories.
@ZLabe
Questions!
ZACHARY LABE | 20 JULY 2021 | REU PROFESSIONAL DEVELOPMENT | COLORADO STATE UNIVERSITY

What's hot

2018 Machine Learning and Physical Sciences Symposium

Zachary Labe

Linking the Quasi-Biennial Oscillation and Projected Arctic Sea-Ice Loss to S...

Zachary Labe

Dissertation Defense: Zachary Labe

Zachary Labe

Refining projections of the 'warm Arctic, cold Siberia' pattern in climate mo...

Zachary Labe

Communicating Arctic climate change through data-driven stories

Zachary Labe

Trends and regional variability of observed Arctic sea-ice thickness

Zachary Labe

Decadal warming slowdown predictions by an artificial neural network

Zachary Labe

Why is it difficult to resolve future projections of Arctic-midlatitude linka...

Zachary Labe

Visioning Future Landscapes of Climate Change: Cotswolds ‘Best and Worst'

Countryside and Community Research Institute

Ramage GEO-CRADLE March 2018 Istanbul

Steven Ramage

Abstract

Kaylee Lawrence

IGARSSoral_Zhang_July.ppt

grssieee

GIS as a Land Planning Resource

International Map Industry Association

A.StrobridgeAssign5

Ashley Strobridge

PRICIP_poster_2008_Dec

Lisa Benham

Climate Modelling, Predictions and Projections

ipcc-media

WGI: The Physical Science Basis - Overview Presentation, Thomas Stocker

ipcc-media

Green Day 2016 - Earth Observation satellites support climate change monitoring

Leonardo

MERBE_leaflet_2015

Grant Matthews PhD

Soil for Africa - the role of sustainable soil management for restoration of ...

World Agroforestry (ICRAF)

What's hot (20)

2018 Machine Learning and Physical Sciences Symposium

Linking the Quasi-Biennial Oscillation and Projected Arctic Sea-Ice Loss to S...

Dissertation Defense: Zachary Labe

Refining projections of the 'warm Arctic, cold Siberia' pattern in climate mo...

Communicating Arctic climate change through data-driven stories

Trends and regional variability of observed Arctic sea-ice thickness

Decadal warming slowdown predictions by an artificial neural network

Why is it difficult to resolve future projections of Arctic-midlatitude linka...

Visioning Future Landscapes of Climate Change: Cotswolds ‘Best and Worst'

Ramage GEO-CRADLE March 2018 Istanbul

Abstract

IGARSSoral_Zhang_July.ppt

GIS as a Land Planning Resource

A.StrobridgeAssign5

PRICIP_poster_2008_Dec

Climate Modelling, Predictions and Projections

WGI: The Physical Science Basis - Overview Presentation, Thomas Stocker

Green Day 2016 - Earth Observation satellites support climate change monitoring

MERBE_leaflet_2015

Soil for Africa - the role of sustainable soil management for restoration of ...

Similar to Making Effective Figures

Using data visualization for effective science (communication) - April 2022

Zachary Labe

23 November 2022… GFDL Lunchtime Seminar Series Creating visualizations of complex data structures and patterns is an important part of our jobs. We use figures for journal publications, presentations, posters, lab group meetings, science communication, and more. However, creating suitable figures for the task can sometimes be an afterthought during the extensive scientific process. In this seminar, I’ll share examples from climate science to discuss a network of resources available for designing accessible figures in both publications and presentations by leveraging resources that support open science practices. I will also share examples of what not to do, which goes beyond only considering interpretable colormaps, and how to improve these figures moving forward. Finally, by using global mean surface temperature as a case study, I will share some creative instances of using data visualization as a form of storytelling for communicating climate change.

Using data visualization for accessible science (communication)

Zachary Labe

Monitoring indicators of climate change through data-driven visualization

Zachary Labe

Contrasting polar climate change in the past, present, and future

Zachary Labe

Making effective science figures

Zachary Labe

Geospatial as an Accelerator of Impact: Already Converging!

Dawn Wright

Career pathways and research opportunities in the Earth sciences

Zachary Labe

World Connections Climate Change App by Ilisagvik College STEM students

Brian Fuchs

GEOtop Sisef presentation

Riccardo Rigon

The 14th Summer Environmental Health Sciences Institute took place in Houston, TX the week of 7/14/2014. This workshop on climate change, comes from educational designers from the National Center for Atmospheric Research. While you may not have been able to join us, you can still review content and download all the activities at our website: https://scied.ucar.edu/events/clone-climate-change-connections-2014

2014 Climate Change Connections - Workshop Content & Activities

Teresa Eastburn

Anthropomorphic, climate change

nybergjohn

Making effective and accessible figures

Zachary Labe

Scales and Hydrology in 2020

Riccardo Rigon

This webinar to the Ecosystem Based Management Tools Network, May 17, 2017, reported progress on the Ecological Marine Units (EMU) project, a new undertaking commissioned by the Group on Earth Observations, to develop a standardized and practical global ecosystems classification and map for the oceans. The EMU is comprised of a global point mesh framework, created from 52,487,233 points from the NOAA World Ocean Atlas. Each point has x, y, z, as well as six attributes of chemical and physical oceanographic structure (temperature, salinity, dissolved oxygen, nitrate, silicate, phosphate) that are likely drivers of many ecosystem responses. We identify and map 37 environmentally distinct 3D regions (candidate ‘ecosystems’) within the water column. These units can be attributed according to their productivity, direction and velocity of currents, species abundance, global seafloor geomorphology, and more. A series of data products for open access will share the 3D point mesh and EMU clusters at the surface, bottom, and within the water column, as well as 2D and 3D web apps for exploration of the EMUs and the original World Ocean Atlas data. This webinar provided an overview of the EMU project and cover recent developments and future plans for the EMUs. Webinar recording at https://www.openchannels.org/webinars/2017/ecological-marine-units-3-d-mapping-ocean-based-noaas-world-ocean-atlas

Ecological Marine Units: A 3-D Mapping of the Ocean Based on NOAA’s World Oce...

Dawn Wright

Modeling the Climate System: Is model-based science like model-based engineer...

Steve Easterbrook

GIS Day is a special occasion, whereby we express what we are thinking and doing in our GIS research, education, training, and applications activities. And, it is also is a time to set forth what we wish others would think about and do, such as providing answers to the question: “What contribution is Geography making to support and encourage the development and use of GIS technology and GIScience methods, techniques, and operations by governments, NGOs, business, researchers, academe, the media, and interest groups?” The impending Research Colloquium on Using the Retrospective Approach to Mine for GIS Nuggets is one such contribution by Geography to GIS. This GIS Day 2014 presentation includes a selection of figures and tables from several Colloquium papers which illustrate how Geography can contribute to both parts of the title, that is, GIS: Bringing Geography to the World and, GIS: Bringing the World to Geography.

GIS: Bringing Geography to the World & the World to Geography

Barry Wellar

RemoteSensingProjectPaper

James Sherwood

Global Warming and the Polar Regions

The Ohio State University, College of Education and Human Ecology

April 2010, Tri-State EPSCoR Meeting, Incline Village

Jeff Dozier

Department of Geography and Geoinformation Science Seminar, George Mason University, Falls Church, VA, September 2015. Increasingly, GIS is part of the collaboration between computer scientists, information scientists, and domain scientists to solve complex scientific questions. Successfully addressing scientific problems, such as informing regional decision- and policy-making for coastal zone management and marine spatial planning, requires integrative and innovative approaches to analyzing, modeling, and developing extensive and diverse data sets. The current chaotic distribution of available data sets, lack of documentation about them, and lack of easy-to-use access tools and computer modeling and analysis codes are still major obstacles for scientists and educators alike. Contributing solutions to these problems is part of an emerging science agenda at Esri for a range of environmental, conservation, climate and ocean sciences that will be discussed. The talk will highlight some recent projects in progress, including a new global map of ecological land units, new tools to support multidimensional scientific data, continued work on an ocean basemap, and more.

Esri and the Scientific Community

Dawn Wright

Similar to Making Effective Figures (20)

Using data visualization for effective science (communication) - April 2022

Using data visualization for accessible science (communication)

Monitoring indicators of climate change through data-driven visualization

Contrasting polar climate change in the past, present, and future

Making effective science figures

Geospatial as an Accelerator of Impact: Already Converging!

Career pathways and research opportunities in the Earth sciences

World Connections Climate Change App by Ilisagvik College STEM students

GEOtop Sisef presentation

2014 Climate Change Connections - Workshop Content & Activities

Anthropomorphic, climate change

Making effective and accessible figures

Scales and Hydrology in 2020

Ecological Marine Units: A 3-D Mapping of the Ocean Based on NOAA’s World Oce...

Modeling the Climate System: Is model-based science like model-based engineer...

GIS: Bringing Geography to the World & the World to Geography

RemoteSensingProjectPaper

Global Warming and the Polar Regions

April 2010, Tri-State EPSCoR Meeting, Incline Village

Esri and the Scientific Community

More from Zachary Labe

Welcome to GFDL for Take Your Child To Work Day

Zachary Labe

Labe, Z.M., T.L. Delworth, N.C. Johnson, and W.F. Cooke. Explainable AI for distinguishing future climate change scenarios, EGU General Assembly 2024, Vienna, Austria (Apr 2024). Abstract... https://meetingorganizer.copernicus.org/EGU24/EGU24-9110.html References... Labe, Z.M., T.L. Delworth, N.C. Johnson, and W.F. Cooke (2024). Exploring a data-driven approach to identify regions of change associated with future climate scenarios. (submitted; preprint - https://doi.org/10.22541/essoar.171288901.17027965/v1)

Explainable AI for distinguishing future climate change scenarios

Zachary Labe

10 May 2024… Atmospheric and Oceanic Sciences Student/Postdoc Seminar (Presentation): Reexamining future projections of Arctic climate linkages, Princeton University, USA. References... Labe, Z.M., Y. Peings, and G. Magnusdottir (2018), Contributions of ice thickness to the atmospheric response from projected Arctic sea ice loss, Geophysical Research Letters, DOI:10.1029/2018GL078158 Labe, Z.M., Y. Peings, and G. Magnusdottir (2019). The effect of QBO phase on the atmospheric response to projected Arctic sea ice loss in early winter, Geophysical Research Letters, DOI:10.1029/2019GL083095 Labe, Z.M., Y. Peings, and G. Magnusdottir (2020). Warm Arctic, cold Siberia pattern: role of full Arctic amplification versus sea ice loss alone, Geophysical Research Letters, DOI:10.1029/2020GL088583 Labe, Z.M., May 2020: The effects of Arctic sea-ice thickness loss and stratospheric variability on mid-latitude cold spells. University of California, Irvine. Doctoral Dissertation. Peings, Y., Z.M. Labe, and G. Magnusdottir (2021), Are 100 ensemble members enough to capture the remote atmospheric response to +2°C Arctic sea ice loss? Journal of Climate, DOI:10.1175/JCLI-D-20-0613.1

Reexamining future projections of Arctic climate linkages

Zachary Labe

Techniques and Considerations for Improving Accessibility in Online Media

Zachary Labe

26 March 2024… GFDL Polar Climate Interest Group (Presentation): An intro to explainable AI for polar climate science, NOAA GFDL, Princeton, NJ. References: Labe, Z.M. and E.A. Barnes (2022), Comparison of climate model large ensembles with observations in the Arctic using simple neural networks. Earth and Space Science, DOI:10.1029/2022EA002348, https://doi.org/10.1029/2022EA002348 Labe, Z.M. and E.A. Barnes (2021), Detecting climate signals using explainable AI with single-forcing large ensembles. Journal of Advances in Modeling Earth Systems, DOI:10.1029/2021MS002464, https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/2021MS002464

An intro to explainable AI for polar climate science

Zachary Labe

Using accessible data to communicate global climate change

Zachary Labe

Water in a Frozen Arctic: Cross-Disciplinary Perspectives

Zachary Labe

27 March 2024… IARPC Collaborations, Modelers’ Community of Practice (Presentation): Explainable AI approach for evaluating climate models in the Arctic. Remote Presentation. References... Labe, Z. M., & Barnes, E. A. (2022). Comparison of climate model large ensembles with observations in the Arctic using simple neural networks. Earth and Space Science, 9(7), e2022EA002348, https://doi.org/10.1029/2022EA002348

Explainable AI approach for evaluating climate models in the Arctic

Zachary Labe

12 March 2024… Sharing Science – North American Webinar, Young Earth System Scientists (YESS) Community (Presentation): Explainable neural networks for evaluating patterns of climate change and variability. Remote Presentation. References... Labe, Z.M., E.A. Barnes, and J.W. Hurrell (2023). Identifying the regional emergence of climate patterns in the ARISE-SAI-1.5 simulations. Environmental Research Letters, DOI:10.1088/1748-9326/acc81a

Explainable neural networks for evaluating patterns of climate change and var...

Zachary Labe

23 February 2024… Department of Environmental Sciences Seminar (Presentation): Applications of machine learning for climate change and variability, Rutgers University, New Brunswick, NJ. References: Labe, Z.M. and E.A. Barnes (2021), Detecting climate signals using explainable AI with single-forcing large ensembles. Journal of Advances in Modeling Earth Systems, DOI:10.1029/2021MS002464 Labe, Z.M. and E.A. Barnes (2022), Predicting slowdowns in decadal climate warming trends with explainable neural networks. Geophysical Research Letters, DOI:10.1029/2022GL098173 Labe, Z. M., Johnson, N. C., & Delworth, T. L. (2024). Changes in United States summer temperatures revealed by explainable neural networks. Earth's Future, DOI:10.1029/2023EF003981

Applications of machine learning for climate change and variability

Zachary Labe

data-driven approach to identifying key regions of change associated with fut...

Zachary Labe

Distinguishing the regional emergence of United States summer temperatures be...

Zachary Labe

Researching and Communicating Our Changing Climate

Zachary Labe

16 November 2023… Department Seminar (Presentation): Revisiting projections of Arctic climate change linkages, Tongji University, Shanghai, China. Remote Presentation. References: Labe, Z.M., Y. Peings, and G. Magnusdottir (2018), Contributions of ice thickness to the atmospheric response from projected Arctic sea ice loss, Geophysical Research Letters, DOI: 10.1029/2018GL078158 Labe, Z.M., Y. Peings, and G. Magnusdottir (2019). The effect of QBO phase on the atmospheric response to projected Arctic sea ice loss in early winter, Geophysical Research Letters, DOI: 10.1029/2019GL083095 Labe, Z.M., Y. Peings, and G. Magnusdottir (2020). Warm Arctic, cold Siberia pattern: role of full Arctic amplification versus sea ice loss alone, Geophysical Research Letters, DOI: 10.1029/2020GL088583 Peings, Y., Z.M. Labe, and G. Magnusdottir (2021), Are 100 ensemble members enough to capture the remote atmospheric response to +2°C Arctic sea ice loss? Journal of Climate, DOI: 10.1175/JCLI-D-20-0613.1 Labe, Z.M. and E.A. Barnes (2022), Comparison of climate model large ensembles with observations in the Arctic using simple neural networks. Earth and Space Science, DOI: 10.1029/2022EA002348

Revisiting projections of Arctic climate change linkages

Zachary Labe

18 November 2023… NJ State Museum Planetarium (Presentation): Visualizing climate change through data, Trenton, NJ. References... Eischeid, J.K., M.P. Hoerling, X.-W. Quan, A. Kumar, J. Barsugli, Z.M. Labe, K.E. Kunkel, C.J. Schreck III, D.R. Easterling, T. Zhang, J. Uehling, and X. Zhang (2023). Why has the summertime central U.S. warming hole not disappeared? Journal of Climate, DOI:10.1175/JCLI-D-22-0716.1, https://journals.ametsoc.org/view/journals/clim/36/20/JCLI-D-22-0716.1.xml

Visualizing climate change through data

Zachary Labe

5 October 2023… Atmosphere and Ocean Climate Dynamics Seminar (Presentation): Using explainable machine learning to evaluate climate change projections, Yale University, New Haven, CT. Remote Presentation. References... Labe, Z.M., E.A. Barnes, and J.W. Hurrell (2023). Identifying the regional emergence of climate patterns in the ARISE-SAI-1.5 simulations. Environmental Research Letters, DOI:10.1088/1748-9326/acc81a, https://iopscience.iop.org/article/10.1088/1748-9326/acc81a

Using explainable machine learning to evaluate climate change projections

Zachary Labe

11 September 2023… Hershey Horticulture Society (Presentation): Climate change extremes by season in the United States, Hershey, PA, USA. References... Eischeid, J.K., M.P. Hoerling, X.-W. Quan, A. Kumar, J. Barsugli, Z.M. Labe, K.E. Kunkel, C.J. Schreck III, D.R. Easterling, T. Zhang, J. Uehling, and X. Zhang (2023). Why has the summertime central U.S. warming hole not disappeared? Journal of Climate, DOI:10.1175/JCLI-D-22-0716.1 Labe, Z.M., T.R. Ault, and R. Zurita-Milla (2016), Identifying Anomalously Early Spring Onsets in the CESM Large Ensemble Project, R. Clim Dyn, DOI:10.1007/s00382-016-3313-2 Labe, Z.M., N.C. Johnson, and T.L Delworth (2023). Changes in United States summer temperatures revealed by explainable neural networks. Preprint. DOI: 10.22541/essoar.168987129.98069596/v1

Climate change extremes by season in the United States

Zachary Labe

22 August 2023… Guest lecture for “Introduction to Global Climate Change (ESS 15)” (Invited): Our changing Arctic in the past and future, University of California, Irvine, CA. Remote Presentation. References... Delworth, T. L., Cooke, W. F., Adcroft, A., Bushuk, M., Chen, J. H., Dunne, K. A., ... & Zhao, M. (2020). SPEAR: The next generation GFDL modeling system for seasonal to multidecadal prediction and projection. Journal of Advances in Modeling Earth Systems, 12(3), e2019MS001895, https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/2019MS001895 Labe, Z.M. and E.A. Barnes (2022), Comparison of climate model large ensembles with observations in the Arctic using simple neural networks. Earth and Space Science, DOI:10.1029/2022EA002348, https://doi.org/10.1029/2022EA002348 Labe, Z.M., Y. Peings, and G. Magnusdottir (2020). Warm Arctic, cold Siberia pattern: role of full Arctic amplification versus sea ice loss alone, Geophysical Research Letters, DOI:10.1029/2020GL088583, https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2020GL088583

Guest Lecture: Our changing Arctic in the past and future

Zachary Labe

Climate Projections - What Really is Business as Usual?

Zachary Labe

Sea Ice Anomalies

Zachary Labe

More from Zachary Labe (20)

Welcome to GFDL for Take Your Child To Work Day

Explainable AI for distinguishing future climate change scenarios

Reexamining future projections of Arctic climate linkages

Techniques and Considerations for Improving Accessibility in Online Media

An intro to explainable AI for polar climate science

Using accessible data to communicate global climate change

Water in a Frozen Arctic: Cross-Disciplinary Perspectives

Explainable AI approach for evaluating climate models in the Arctic

Explainable neural networks for evaluating patterns of climate change and var...

Applications of machine learning for climate change and variability

data-driven approach to identifying key regions of change associated with fut...

Distinguishing the regional emergence of United States summer temperatures be...

Researching and Communicating Our Changing Climate

Revisiting projections of Arctic climate change linkages

Visualizing climate change through data

Using explainable machine learning to evaluate climate change projections

Climate change extremes by season in the United States

Guest Lecture: Our changing Arctic in the past and future

Climate Projections - What Really is Business as Usual?

Sea Ice Anomalies

Recently uploaded

Zoology 5th semester notes( Sumit_yadav).pdf

Sumit Kumar yadav

SCIENCE-4-QUARTER4-WEEK-4-PPT-1 (1).pptx

RizalinePalanog2

Kochi CALL GIRL 84099*07087 ❤CALL GIRLS IN Kochi ESCORT SERVICE❤CALL GIRL IN We are Providing :- ● – Private independent collage Going girls . ● – independent Models . ● – House Wife’s . ● – Private Independent House Wife’s ● – Corporate M.N.C Working Profiles . ● – Call Center Girls . ● – Live Band Girls . ●- Foreigners & Many More . Service type: 1.In call 2.out call 3. full Lip to Lip kiss 4.69 5.b-job without Condom 6. Hard Core sex & Much More. 7 Body to Body Touch 8 Kissing 9 Sucking Boobs and More 10 Enjoy by Hand 11 Relax By Oral 12 Sex with Happy Ending • In Call and Out Call Service • 3* 5* 7* Hotels Service • 24 Hours Available • Indian, Russian, Punjabi, Kashmiri Escorts • Real Models, College Girls, House Wife, Also Available • Short Time and Full Time Service Available • Hygienic Full AC Neat and Clean Rooms Avail. In Hotel 24 hours • Daily Escorts Staff Available • Minimum to Maximum Range Available.

Kochi ❤CALL GIRL 84099*07087 ❤CALL GIRLS IN Kochi ESCORT SERVICE❤CALL GIRL

kantirani197

Introduction,importance and scope of horticulture.pptx

Bhagirath Gogikar

Seismic Method Estimate velocity from seismic data.pptx

AlMamun560346

GBSN - Microbiology (Unit 2)

Areesha Ahmad

Clean In Place(CIP).pptx .

Poonam Aher Patil

GBSN - Microbiology (Unit 1)

Areesha Ahmad

Bollworms are among the most damaging pests in cotton cultivation, affecting the bolls where the cotton fibers are formed. There are several species of bollworms, each capable of causing significant yield loss and quality degradation if not effectively managed. Here’s a detailed look at the primary bollworm species affecting cotton: Cotton Bollworm (Helicoverpa armigera): Also known as the corn earworm or the Old World bollworm, this pest is found in many regions around the world. It is highly polyphagous (feeds on many different plants) and poses a threat not only to cotton but also to maize, tomatoes, and legumes. The larvae bore into the cotton bolls, feeding on the developing seeds and fibers, which can lead to boll rot. Pink Bollworm (Pectinophora gossypiella): A significant pest of cotton, the pink bollworm larvae infest the cotton bolls, feeding on the seeds and lint. This can severely damage or destroy the bolls. In regions where pink bollworms are prevalent, they have been a major driver for the adoption of genetically engineered Bt cotton, which expresses a bacterium gene toxic to certain insects. Tobacco Budworm (Heliothis virescens): Closely related to the cotton bollworm, the tobacco budworm primarily attacks tobacco but is also a common pest in cotton. It primarily damages the flowers and bolls of the cotton plant. Differentiating between the tobacco budworm and the cotton bollworm based on appearance can be challenging, but it is crucial for effective management. American Bollworm (Helicoverpa zea): Known in some regions as the corn earworm, it is similar in behavior to Helicoverpa armigera and poses a threat to a variety of crops, including cotton. The larvae attack the cotton bolls, leading to direct damage to the cotton lint and seeds. Management Strategies: Cultural Controls: Crop rotation, destruction of crop residues, and deep plowing can help break the pest’s life cycle. Timing of planting can also be adjusted to avoid peak pest infestation. Biological Controls: Natural enemies like Trichogramma wasps, which parasitize bollworm eggs, and predators such as lacewings and ladybugs can be encouraged. Bacillus thuringiensis (Bt) products can also be sprayed, which are particularly effective against young larvae. Chemical Controls: Insecticides may be required when infestation levels exceed economic thresholds. However, resistance management must be considered, alternating modes of action to avoid developing resistance. Genetic Approaches: Bt cotton, genetically modified to express Bacillus thuringiensis toxin, has been highly effective in controlling bollworms and has dramatically reduced the reliance on chemical insecticides. Monitoring and Scouting: Regular field scouting and using pheromone traps to monitor adult populations can help in timely and targeted application of control measures. The effective management of bollworms often requires an integrated approach

Pests of cotton_Borer_Pests_Binomics_Dr.UPR.pdf

PirithiRaju

low price Call me 7857803690 100%genuine sexy VIP call girl safe service WhatsApp chat. 785780369 Normal call kijiye 7857803690 100% genuine young college girl and housewife Full enjoy open minded girl provide 24hour full cooperative model and full satisfactions☎️*78578//03690*⭐Escorts service █▬█⓿▀█▀ call girls and bhabhi available for room Sex and video call service A-1 HIGH CLASS CALL GIRLS TOP MODEL 24X7 HOME/HOTEL Call Girls Safe & Secure High Class Sm Affordable Rate 100% Satisfaction, Unlimited Enjoyment. Any Time for Model/Escort in High class luxury and premium

SAMASTIPUR CALL GIRL 7857803690 LOW PRICE ESCORT SERVICE

ayushi9330

(Vivek)Call Us, 8448380779,Call girls in Delhi NCr – We Offer best in class call girls. escort Service At Affordable Price At low Rate with Space Night 8000 We Are One Of The Oldest Escort and Call girls Agencies in Delhi. You Will Find That Our Female Escorts Are Full Of Fun, Sexy And They Would Love Enjoy Your Company. We Have A Fantastic Selection Of Escort Ladies Available For In-Calls As Well As Out-Calls. Our Escorts Are Not Only Beautiful But All Have Great Personalities Making Them The Perfect Companion For Any Occasion. In-Call:- You Can Come At Our Place in Delhi Our place Which Is Very Clean Hygienic 100% safe Accommodation. Out-Call:- You have To Come Pick The Girl From My Place We Are Also Provide Door Step Services (Delhi Ncr, Noida, Gurgaon, Faridabad, Ghaziabad Note:- Pic Collectors Time Passers Bargainers Stay Away As We Respect The Value For Your Money Time And Expect The Same From You Hygienic:- Full Ac room And Clean Rooms Available In Hotel 24 * 7 Hourly In Delhi NCR More Details, With WhatsApp Number, +91-8448380779

Connaught Place, Delhi Call girls :8448380779 Model Escorts | 100% verified

Delhi Call girls

GBSN - Microbiology (Unit 3)

Areesha Ahmad

fruit fly, this slide mainly made for pumpkin fruit fly, this is also known as drosophila melangastor, this type of fruit fly destroyed the mainly vegetables crops. if you want to known examples this types of fly which is destroy the pumpkin, tomato, brinjal, potato, bottle guard, ridge guard, bitter guard, cucumber, water melon, musk melon, bean, long bean and other many vegetables which has fruits. they distryed fruit fly. thank you...

pumpkin fruit fly, water melon fruit fly, cucumber fruit fly

PRADYUMMAURYA1

Feature-aligned N-BEATS with Sinkhorn divergence (ICLR '24)

Joonhun Lee

Choose Our GTB Nagar Call Girls Through Our WhatsApp Number: - 8250077686 Easy & Fast Booking Procedure of GTB Nagar Call Girls Call girls are ready and waiting to provide the quality essentialness that will help ease away life's tensions GTB Nagar Call Girls are regular companions of elite gentlemen. They can take them places they could only dream of visiting. These ladies take great care in maintaining themselves to look appealing; visiting salons and spas regularly keeps them looking their best; their portfolios can be found online via an escort agency website. Visit our website: https://www.prishagill.com/ Visit our website: https://www.dighacallgirls.com/ Visit our website: https://www.sheetalarora.com/ Visit our website: https://www.streetgirls69.in/

High Profile 🔝 8250077686 📞 Call Girls Service in GTB Nagar🍑

Damini Dixit

IDENTIFICATION OF THE LIVING- forensic medicine

sherlingomez2

Unit5-Cloud.pptx for lpu course cse121 o

ManavSingh202607

Call Girls In Safdarung Enclave Arjun Nagar Whatsapp +91 9654467111 Delhi ⛟ Open 24 Hrs, ☎ Booking Short 2000 Night 6000 ALL HOME/HOTEL SERVICE DOORSTEP SERVICE IN/CALL & OUT/CALL SERVICE WITH MANY OPTIONS AVAILABLE DELHI GURGAON & NOIDA SERVICE IN REASONABLE RATES FROM LOW TO HIGH PROFILE STAFF’S. Call Girl Number~24X7~Call Girl Services, New Delhi, Delhi OutCall Rate Call Girl Mahipalpur,Call Girl Connaught Place,Call Girl Nehru Place,Call Girl Chanakyapuri,Call Girl Paharganj,Call Girl Dhaula Kuan,Call Girl Moti Bagh,Call Girl Karol Bagh,Call Girl Greater Kailash,Call Girl Naraina, Call Girl Katwaria Sarai,Call Girl Janakpuri,Call Girl Kalkaji,Call Girl Lajpat Nagar,Call Girl Palam,Call Girl Malviya Nagar,Call Girl Mehrauli,Call Girl Govindpuri,Call Girl Sarojini Nagar ,Call Girl Neb Sarai,Call Girl South Ex,Call Girl Munirka,Call Girl Saket,Call Girl Chattarpur

9654467111 Call Girls In Raj Nagar Delhi Short 1500 Night 6000

Sapana Sha

Module for Grade 9 for Asynchronous/Distance learning

levieagacer

biology HL practice questions IB BIOLOGY

1301aanya

Recently uploaded (20)

Zoology 5th semester notes( Sumit_yadav).pdf

SCIENCE-4-QUARTER4-WEEK-4-PPT-1 (1).pptx

Kochi ❤CALL GIRL 84099*07087 ❤CALL GIRLS IN Kochi ESCORT SERVICE❤CALL GIRL

Introduction,importance and scope of horticulture.pptx

Seismic Method Estimate velocity from seismic data.pptx

GBSN - Microbiology (Unit 2)

Clean In Place(CIP).pptx .

GBSN - Microbiology (Unit 1)

Pests of cotton_Borer_Pests_Binomics_Dr.UPR.pdf

SAMASTIPUR CALL GIRL 7857803690 LOW PRICE ESCORT SERVICE

Connaught Place, Delhi Call girls :8448380779 Model Escorts | 100% verified

GBSN - Microbiology (Unit 3)

pumpkin fruit fly, water melon fruit fly, cucumber fruit fly

Feature-aligned N-BEATS with Sinkhorn divergence (ICLR '24)

High Profile 🔝 8250077686 📞 Call Girls Service in GTB Nagar🍑

IDENTIFICATION OF THE LIVING- forensic medicine

Unit5-Cloud.pptx for lpu course cse121 o

9654467111 Call Girls In Raj Nagar Delhi Short 1500 Night 6000

Module for Grade 9 for Asynchronous/Distance learning

biology HL practice questions IB BIOLOGY

Making Effective Figures

1. MAKING EFFECTIVE FIGURES ZACHARY LABE | 20 JULY 2021 | REU PROFESSIONAL DEVELOPMENT | COLORADO STATE UNIVERSITY

3. Polar Amplification: acceleration of warming in high latitudes relative to the rest of the globe

6. Warmer Colder NOW Start of satellite-era

7. Polar Amplification: acceleration of warming in high latitudes relative to the rest of the globe

8. DATA VISUALIZATION IS STORY-TELLING.

9. DON’T BE SUCH A SCIENTIST WE ARE DATA SCIENTISTS ART BY JILL PELTO

10. Landscape of Change uses data about sea level rise, glacier volume decline, increasing global temperatures, and the increasing use of fossil fuels. These data lines compose a landscape shaped by the changing climate, a world in which we are now living. Jill Pelto|http://www.jillpelto.com/landscape-of-change “ ”

11. BEGINNING WITH OUR DATA.

12.

13. LINE GRAPHS Temperature Anomaly (°C)

14.

15.

16.

17.

18.

19. :)

20.

21.

22.

23. MAP PLOTS

24. YIKES!

25. YIKES – FONT IS BLEH!

26. YIKES – COLOR!

27. MAP PROJECTION!

28. :)

29. HAVE FUN!

30.

31.

32.

33.

34.

35.

36. SURPRISINGLY EFFECTIVE.

37. Senator Sheldon Whitehouse (D-CT) - Time to Wake Up: Climate Progress Speech (3/21/2018)

38. DANISH METEOROLOGICAL INSTITUTE

39.

40. SCIENCE OF DESIGN.

41. #endrainbow Check out: https://betterfigures.org/2018/06/04/playing-hunt-the-discontinuity/

42.

43.

44.

45.

46.

47. SCHNEIDER AND NOCKE, 2017

48. SCHNEIDER AND NOCKE, 2017

49. SCHNEIDER AND NOCKE, 2017

50. SCHNEIDER AND NOCKE, 2017

51. SCHNEIDER AND NOCKE, 2017

52. Adapted from Ed Hawkins at betterfigures.org

53. Crameri, F. (2018). Scientific colour maps. Zenodo. http://doi.org/10.5281/zenodo.1243862 Crameri, F. (2018), Geodynamic diagnostics, scientific visualisation and StagLab 3.0, Geosci. Model Dev., 11, 2541- 2562, doi:1 0.5194/gmd-11-2541-2018 Crameri, F., G.E. Shephard, and P.J. Heron (2020), The misuse of colour in science communication, Nature Communications, 11, 5444. doi:10.1038/s41467-020-19160-7 Palettable: Color palettes for Python

54. Crameri, F. (2018). Scientific colour maps. Zenodo. http://doi.org/10.5281/zenodo.1243862 Crameri, F. (2018), Geodynamic diagnostics, scientific visualisation and StagLab 3.0, Geosci. Model Dev., 11, 2541- 2562, doi:1 0.5194/gmd-11-2541-2018 Crameri, F., G.E. Shephard, and P.J. Heron (2020), The misuse of colour in science communication, Nature Communications, 11, 5444. doi:10.1038/s41467-020-19160-7

55. OTHER OPTIONS THYNG ET AL. 2016; OCEANOGRAPHY

56. CMOCEAN

57. CMASHER “Scientific colormaps for making accessible, informative and cmashing plots”

58. Adjusting axes (spines)

59. Changing font styles

60. https://github.com/zmlabe

61. 1. Seaborn. 2. Plotly. 3. ggplot. 4. Matplotlib v3. ALTERNATIVES

62. 1. https://betterfigures.org/ 2. https://www.climate-lab-book.ac.uk/ 3. http://colorbrewer2.org/ RESOURCES

63. Future minus Pre-Industrial PEINGS ET AL. 2021, JCLI Bring drama to your data story

64. 2-m TEMPERATURE Future minus Pre-Industrial PEINGS ET AL. 2021, JCLI

65. 2-m TEMPERATURE Future minus Pre-Industrial PEINGS ET AL. 2021, JCLI

66. 2-m TEMPERATURE Future minus Pre-Industrial PEINGS ET AL. 2021, JCLI

67. 2-m TEMPERATURE Future minus Pre-Industrial PEINGS ET AL. 2021, JCLI

68. 2-m TEMPERATURE Future minus Pre-Industrial PEINGS ET AL. 2021, JCLI

69. 2-m TEMPERATURE Future minus Pre-Industrial PEINGS ET AL. 2021, JCLI

70. 2-m TEMPERATURE Future minus Pre-Industrial PEINGS ET AL. 2021, JCLI

71. MAKING ACCESSIBLE FIGURES.

72. ACCESSIBILITY

73. ACCESSIBILITY

74. ACCESSIBILITY

75.

76.

77.

78.

79.

80. ACCESSIBILITY No jargon Tell a story Alternative text Color contrast ratio Label data directly Avoid flashing GIFs Include figure titles Avoid data overlays Provide data references

81. VISUALIZING GLOBAL TEMPERATURE CHANGE

82.

83. PLOT BY ED HAWKINS

84. 2016 RIO OLYMPICS OPENING CEREMONY

85.

86.

87. PLOT BY ED HAWKINS DON’T BE SUCH A SCIENTIST WE ARE DATA SCIENTISTS

88.

89. https://showyourstripes.info/ PLOT BY ED HAWKINS

90. CHECK: Simple. Bold. Stories. @ZLabe Questions! ZACHARY LABE | 20 JULY 2021 | REU PROFESSIONAL DEVELOPMENT | COLORADO STATE UNIVERSITY

Making Effective Figures

Recommended

Recommended

More Related Content

What's hot

What's hot (20)

Similar to Making Effective Figures

Similar to Making Effective Figures (20)

More from Zachary Labe

More from Zachary Labe (20)

Recently uploaded

Recently uploaded (20)

Making Effective Figures