Search Results for: lter

History of Data Nuggets

Because Data Nuggets originated from a partnership of teachers and scientists, they address both the needs of scientists to share their research broadly while developing their communication skills, and of teachers who need resources that address education reform and teach science in an authentic way.

Data Nuggets are designed and developed by Elizabeth Schultheis and Melissa Kjelvik from Michigan State University. They have been under development since 2011 and originated through conversations between science teachers and graduate students during the NSF GK-12 project “New GK-12: Using the STEM Dimensions of Bioenergy Sustainability to Bring Leading-edge Graduate Research to K-12 Learning Settings”. This unique opportunity for collaboration between teachers and scientists led to the creation of teacher-inspired resources. Teachers shared that they were lacking educational resources that helped their students practice working with real, messy data like that collected during classroom inquiry-based projects. Graduate students in the sciences, not surprisingly, have lots of practice working with messy data and surprising results. Through this collaboration, Data Nuggets were created to bring real data from current and ongoing research into the classroom and take students through the process of science, from the inception of ideas to the analysis and interpretation of data.

Melissa Kjelvik and teacher Connie High working together to collect scientific data.

From 2013-2015, Data Nuggets were funded with seed grants from the NSF BEACON Center Study of Evolution in Action. These funds allowed us to greatly expand Data Nuggets as a resource, with activities now being developed in response to workshops held across the BEACON consortium. The funding has also provided opportunities to collaborate with science educators at Understanding Science (UCMP), National Institute for Mathematical and Biological Synthesis (NIMBioS), and Biological Sciences Curriculum Study (BSCS) to further refine the template and to align Data Nuggets with current science standards and reform, making them easier to integrate into existing curriculum.

Data Nuggets are currently funded by a 4-year NSF DRK-12 grant, awarded to MSU and BSCS in 2015, to conduct a research study to evaluate the effectiveness of integrating Data Nuggets into science curriculum. This research will help to determine whether these short activities can increase the mathematical skills of students and their ability to think scientifically and support claims using data.

Liz Schultheis working with teachers to collect herbivory data.

We will continue to develop and revise Data Nuggets to help teachers bring sets of data from graduate student research into their classroom, and help students become comfortable working with messy data and unexpected results. Data Nuggets have gone through an iterative development process, where materials developed by scientists were used in the classroom and modified based on teacher and student experiences and feedback. We continue to present Data Nuggets at national and local education conferences where teachers and science educators can provide feedback on the structure and content of each activity. Our innovative and iterative development approach has led to a product that teachers and students find easy to work with and integrate into existing curriculum.

For more information on Data Nuggets, see our paper in the American Biology Teacher: Click here for a PDF!

Title	Content Level	Science Concepts / Keywords	Quantitative Concepts / Statistics	Graph Type(s)	Variable Type(s)	Data Type(s)
Dangerously bold	1	animals, animal behavior, tradeoff, fish, predation, biological significance	percent, standard error (SE), predictions	bar	categorical	summarized, Digital Data Nugget
Coral bleaching and climate change	1	climate change, coral reef, marine, mutualism, temperature, animals, algae, adaptation, evolution	ratio	bar	categorical	summarized, Digital Data Nugget
Won’t you be my urchin?	1	coral reef, herbivory, marine, sea urchin, water, animals, competition, food web	mean, models, standard error (SE), standard deviation (SD)	bar	categorical	raw
Springing forward	1 & 3	climate change, phenology, plants, temperature	mean, standard error (SE), Julian date	bar	categorical	summarized, full dataset available, Digital Data Nugget
Do urchins flip out in hot water?	1 & 3	animals, climate change, marine, heatwaves, urchins, behavior, invertebrates, environmental change	average, mean, standard error (SE), calculation	bar	categorical, continuous	summarized, two levels available,
Do insects prefer local or foreign foods?	2	herbivory, invasive species, plants, insects, enemy release, ecology	mean, variance, standard deviation (SD), standard error (SE), confidence intervals (CI), predictions	bar	categorical	summarized, full dataset available, Digital Data Nugget
Spiders under the influence	2	animals, invertebrates, habitat, chemical pollution, aquatic, streams, scientist profile	mean, multiple variables	multiple bar	categorical	full dataset, students summarize
Do invasive species escape their enemies?	2	herbivory, invasive species, plants, insects, enemy release, ecology	mean, percent	bar	categorical	summarized
Lake Superior Rhythms	2	amplitude, aquatic, atmosphere, environmental, physics, student research, wave period, waves	cycle, sine wave, amplitude, change over time	sine wave	continuous	summarized, full dataset available
All washed up? The effect of floods on cutthroat trout	2	animals, disturbance, ecology, fish, water, stream, floods, alternative hypotheses, limnology	regression, ratio, rate, graph choice, unnecessary variables, long-term data	scatter	continuous	raw, Digital Data Nugget
Float down the Kalamazoo River	2	Kalamazoo River, water, suspended solids, dam, reservoir, limnology	mean, ratio, rate, standard deviation (SD), standard error (SE), Julian date, unnecessary variables	bar, line	categorical, continuous	summarized, Digital Data Nugget
Finding a foothold	2	animals, ecology, marine, substrate, water	frequency, proportion	bar	categorical	summarized
Is chocolate for the birds?	2	experimental design, agriculture, animals, birds, biodiversity, rainforest, succession, disturbance, transect, habitat	addition, unnecessary variables	bar	categorical	raw, full dataset available, Digital Data Nugget
Fish fights	2	animal behavior, animals, fish, mating	mean, proportion, regression	scatter	continuous	summarized, Digital Data Nugget
Marvelous mud	2	ecology, environmental, fertilization, mud, phosphorus, substrate, water, wetland, limnology	percent, regression, graph choice	scatter	continuous	summarized
Which guy should she choose?	2	animal behavior, animals, fish, mating	frequency, regression, correlation vs. causation	scatter	continuous	raw, summarized
Sexy smells	2	adaptation, animal behavior, animals, birds, mating	percent, regression, correlation vs. causation	scatter	continuous	raw, Digital Data Nugget
Shooting the poop	2	adaptation, animal behavior, animals, insects, predation, alternative hypotheses	mean, standard error (SE)	bar	categorical	raw
Invasive reeds in the salt marsh	2	disturbance, invasive species, plants, wetland, limnology, transect	mean, percent	bar	categorical	raw, summarized
A tail of two scorpions	2	animal behavior, animals, predation	addition, proportion, ratio, graph choice	bar, stacked bar, pie chart	categorical	raw, Digital Data Nugget
Green crabs: invaders in the Great Marsh	2	animals, invasive species, substrate, wetland, erosion, limnology	addition, range, map	map	categorical, spatial	raw, summarized
Guppies on the move	2	animals, aquatics, behavior, ecology, genetics, migration, movement, tropics	regression	line, scatter	categorical, continuous	raw, full dataset available
The birds of Hubbard Brook, Part I	2	animals, biodiversity, birds, climate change, succession, disturbance, ecology	count, long-term data	line, scatter	continuous	raw, full dataset available, Digital Data Nugget
Beetle battles	2	adaptation, animals, behavior, competition, evolution, insects, mating	standard error (SE)	bar	categorical	summarized
How do brain chemicals influence who wins a fight?	2	animals, behavior, competition, insects, aggression, brain chemistry, physiology	mean	bar	categorical	raw, summarized
Deadly windows	2	animals, animal behavior, birds, environmental, urban, alternative hypotheses	addition, proportion	bar	categorical	summarized
Which would a woodlouse prefer?	2	experimental design, animals, behavior, ecology, predation	count, Chi-square test, replication, sample size	bar	categorical	raw, Digital Data Nugget
Tree-killing beetles	2	animals, biodiversity, disturbance, ecology, environmental, insects, plants	mean, percent, proportion, regression	scatter	continuous	summarized
Alien life on Mars – caught in crystals?	2	astrobiology, salt, solution, Mars, extraterrestrial life, chemistry, physical science	mean, time series	line	continuous	summarized, visual, full dataset available
Beetle, it’s cold outside!	2	animals, climate change, ectotherm, insects, temperature	mean, standard error (SE), models	line	continuous	summarized, Digital Data Nugget
Can a salt marsh recover after restoration?	2	disturbance, salinity, transect, invasive species, plants, wetland, restoration, limnology	mean, percent, frequency	bar, line	continuous	summarized
Fast weeds in farmer’s fields	2	evolution, adaptation, agriculture, plants, fitness, heredity, genetics	frequency, percent, mean, replication, sample size, unnecessary variables	bar, scatter	continuous, categorical	summarized
The carbon stored in mangrove soils	2	carbon, climate change, disturbance, ecology, environmental, nutrients, greenhouse gasses, plants, transect	proportion, mean, unnecessary variables	bar	continuous, categorical	summarized
Where to find the hungry, hungry herbivores	2	herbivory, plants, insects, ecology, latitude, longitude	regression, standard deviation (SD), standard error (SE)	scatter	continuous	summarized
A window into a tree’s world	2	climate change, dendrochronology, ecology, plants, temperature	mean, relative growth, graph choice, regression, correlation vs. causation, trend line,	line, scatter	continuous, categorical	summarized
Corals in a strange place	2	adaptation, coral reef, mangrove, morphology, structure and function	visual data, count	bar, stacked bar, pie chart	continuous	summarized, full dataset available
Mangroves on the move	2	climate change, disturbance, ecology, environmental, fertilization, nitrogen, nutrients, phosphorus, plants	mean, standard error (SE)	bar	categorical, continuous	summarized
Getting to the roots of serpentine soil	2	soil, plasticity, limiting factors, plants, ecology, scientist profile	mean, range, standard deviation	bar	continuous, categorical	summarized
Little butterflies on the prairie	2	butterflies, prairie strips, prairie, agriculture, crops, farmers, animals, ecology, scientist team	Pollard Walk, transect, abundance, count, mean, long-term data, T-test	bar	continuous	summarized, full dataset available
Blinking out?	2	agriculture, insects, population, ecology, biodiversity, fireflies, scientist profile	moving window, long-term data, standardize, sampling effort, division, count, unnecessary variables	line, scatter	continuous, categorical	summarized, full dataset available, Digital Data Nugget
PFAS: Our forever problem	2	PFAS, water, teacher, pollution, watershed, Human impact	concentration, sampling, dilution, bar plot	bar	continuous, categorical	raw, full dataset available
Buried seeds, buried treasure	2	germination, plants, seed bank, seed viability, scientist profile	long-term data, trend	scatter	continuous	raw
Mowing for monarchs, Part I	2	community science, citizen science, animals, behavior, biodiversity, community science, disturbance, ecology, plants, insects, alternative hypotheses	average, time, rate, fraction	bar	categorical	summarized, full dataset available
A difficult drought	2	agriculture, biofuels, climate change, plants, carbon, fermentation, ethanol, chemistry	mean, range, variability, replication, sample size	bar	continuous, categorical	summarized, full dataset available
Farms in the fight against climate change	2	Carbon, Soil, LTER, climate change	average, standard deviation, percent, bar plot	bar	categorical, continuous	summarized, raw
Mowing for monarchs, Part II	2	community science, citizen science, animals, behavior, biodiversity, community science, disturbance, ecology, plants, insects, predation, alternative hypotheses	average, time, rate, fraction	bar	categorical	summarized, full dataset available
Does more rain make healthy bison babies?	2	animals, ecology, keystone species, plants, prairie, precipitation	mean, time, regression, long-term data, unnecessary variables	line, scatter	continuous	summarized, full dataset available
Benthic buddies	2	adaptation, animals, arctic, biodiversity, ecology, environmental, invertebrates, lagoons, marine	mean	bar	categorical	summarized
Did you hear that? Inside the world of fruit fly mating songs	2	animals, insect, process of science, reproducibility, communication, volume, social, behavior	calculations, index, standard deviation, average, replicate	bar	categorical, continuous	summarized
A burning question	2	biodiversity, canopy, ecology, fire ecology, forest, human impact, keystone species, land management, natural resources	average, time	bar	categorical, continuous	summarized
What grows when the forest goes?	2	fire, forest, invasive species, long-term, plants	average, percent, proportion, error bars	bar	categorical, continuous	summarized
Anole’s new niche	2	adaptation, animals, evolution, niche, population, introduced species, native species, behavior, habitat, competition	mean, grand mean, standard deviation (SD), count, unnecessary variables	bar	categorical, continuous	summarized
Salmonberries in our future	2	Arctic, wetlands, climate change, ecology, disturbance, water, marine	mean, standard deviation (SD)	multiple bar	categorical, continuous	summarized
Can kelp help the plovers?	2	marine, beach, herbivory, kelp, preference, behavior, invertebrate, student research, food web	average, multiple trials, calculations	multiple bar	categorical, continuous	summarized
The science of stamen loss	2	adaptation, animals, evolution, plants, pollination, traits, natural selection, flowers	percent change, rate, unnecessary variables	bar	categorical, continuous	summarized
Growing kelp for community	2	environmental, growth, human impacts, kelp, mariculture, marine, photosynthesis, traditional knowledge	average, time	multiple line	categorical, continuous	summarized
Testing the waters for oyster farming	2	applied research, environmental, mariculture, marine, oceanography, oyster, salinity, chemistry	mean, average, parts per thousand	multiple bar	categorical, quantitative	summarized, full dataset available
What wakes the squirrels?	2	animal behavior, animals, arctic, behavior, climate change, ecology, environmental, mammals, permafrost, phenology	average, correlation vs. causation, Julian date, long-term data, mark-recapture, missing data, trendline	scatter	quantitative	summarized, full dataset available
Are plants more toxic in the tropics?	3	herbivory, diversity, plants, insects, ecology, adaptation, chemistry	standard deviation (SD), standard error (SE), index, formula	bar	categorical	summarized
Does a partner in crime make it easier to invade?	3	legume, plants, mutualism, rhizobia, invasive species, soil, scientist profile	mean	bar	categorical	summarized
Fair traders or freeloaders?	3	evolution, legume, plants, mutualism, rhizobia, nitrogen, fertilization	mean, standard error (SE)	bar	categorical	summarized
Fertilizing biofuels may cause release of greenhouse gasses	3	agriculture, biofuels, climate change, fertilization, greenhouse gases, nitrogen, plants	regression	scatter	continuous	summarized, full dataset available, Digital Data Nugget
The ground has gas!	3	climate change, temperature, greenhouse gases, nitrogen, plants, chemistry	regression	scatter	continuous	raw, summarized, full dataset available
Growing energy: comparing biofuel crop biomass	3	agriculture, biofuels, climate change, fertilization, plants, carbon	mean, standard error (SE)	bar	categorical	summarized
Microbes facing tough times	3	drought, enzymes, microbes, mutualist, agriculture, climate change, crops	mean, standard deviation, negative values	bar	continuous	summarized
How the cricket lost its song, Part I	3	adaptation, animal behavior, animals, rapid evolution, mating, parasitism, scientist profile	percent	bar	categorical	raw, summarized, Digital Data Nugget
The mystery of Plum Island Marsh	3	fertilization, fish, food web, marine, mollusk, water, wetland, limnology	mean	bar	categorical	raw
Invasion meltdown	3	climate change, ecology, invasive species, plants, temperature	mean, range, replication, sample size	bar	categorical	summarized, full dataset available
Is your salt marsh in the zone?	3	climate change, ecology, plants, sea level rise, substrate, wetland, limnology	mean	bar	categorical	raw
Lizards, iguanas, and snakes! Oh my!	3	animals, biodiversity, disturbance, restoration, urban, transect	count, addition	bar	categorical	raw
What do trees know about rain?	3	climate change, dendrochronology, ecology, plants, precipitation, temperature, water	mean, formula, equation, addition, multiplication	line	continuous	raw, full dataset available
CSI: Crime Solving Insects	3	animals, insects, parasitism	weighted mean	bar	categorical	raw, Digital Data Nugget
Does sea level rise harm saltmarsh sparrows?	3	animals, birds, sea level rise, climate change, disturbance, ecology, wetland, limnology	mean, standard deviation (SD)	line	continuous	summarized
Keeping up with the sea level	3	climate change, disturbance, ecology, sea level rise, plants, substrate, wetland, limnology	formula, equation, rate	line, scatter	continuous, categorical	raw
The birds of Hubbard Brook, Part II	3	animals, biodiversity, birds, climate change, succession, disturbance, habitat, ecology	count, long-term data	line, scatter	continuous, categorical	raw, full dataset available, Digital Data Nugget
How the cricket lost its song, Part II	3	adaptation, animal behavior, animals, rapid evolution, mating, parasitism, scientist profile	mean	bar	categorical	raw, summarized. Digital Data Nugget
Feral chickens fly the coop	3	adaptation, animals, behavior, birds, ecology, evolution, invasive species, mating, heredity, genetics	proportion, percent	bar	categorical	raw, summarized
Raising Nemo: Parental care in the clown anemonefish	3	animals, behavior, coral reef, ecology, fish, marine, mating, tradeoff, plasticity, scientist profile	mean, standard error (SE)	bar	categorical	raw
When a species can’t stand the heat	3	animals, climate change, disturbance, ecology, environmental, mating, temperature, sex ratio	addition, percent, ratio, regression	scatter	continuous	raw, full dataset available, Digital Data Nugget
Are you my species?	3	adaptation, animals, behavior, biodiversity, competition, evolution, fish, mating	formula, equation, addition, subtraction, division, regression	scatter	continuous	raw, Digital Data Nugget
Marsh makeover	3	bodiversity, disturbance, ecology, greenhouse gases, mud, plants, restoration, wetland, limnology	standard error (SE)	bar, line	categorical	raw, summarized
To bee or not to bee aggressive	3	animals, behavior, genes, insects, tradeoff, plasticity, aggression	mean, effect size, percent change, range	bar	categorical	summarized, full dataset available, Digital Data Nugget
Why are butterfly wings colorful?	3	adaptation, animals, insects, models, predation, alternative hypotheses	fraction, proportion, probability	bar	categorical	summarized, Digital Data Nugget
City parks: wildlife islands in a sea of cement	3	animals, biodiversity, ecology, urban, island biogeography, parks, camera trap	Shannon Wiener Index, formula, equation, sum, proportion, regression	scatter	continuous	summarized, full dataset available, Digital Data Nugget
Is it better to be bigger?	3	adaptation, animals, evolution, predation, natural selection	mean, percent, rate, regression	scatter	continuous	summarized, Digital Data Nugget
Is it dangerous to be a showoff?	3	adaptation, animals, evolution, predation, tradeoff, natural selection	percent, rate, regression	scatter	continuous, categorical	summarized
What big teeth you have! Sexual selection in rhesus macaques	3	animals, evolution, sexual selection, sexual dimorphism, anatomy, form and function, primate, scientist profile	mean, standard deviation (SD)	bar	continuous, categorical	raw, Digital Data Nugget
Bringing back the Trumpeter Swan	3	animals, biodiversity, birds, ecology, environmental, restoration	mean, long-term data, count	line	continuous, categorical	raw, full dataset available, Digital Data Nugget
Are forests helping in the fight against climate change?	3	climate change, carbon, ecology, greenhouse gasses, photosynthesis, plants, decomposition, respiration	regression, long-term data	scatter	continuous	raw, Digital Data Nugget
Can biochar improve crop yields?	3	agriculture, environmental, fertilization, plants, soil, water, biochar, carbon	percent, mean, standard deviation (SD), yield, replication, sample size, randomization	bar	continuous, categorical	summarized
Hold on for your life! Part I	3	adaptation, animals, disturbance, evolution, natural selection, genetic drift, hurricane, biological significance, alternative hypotheses	argumentation, mean, standard error (SE)	bar	continuous, categorical	summarized
Hold on for your life! Part II	3	adaptation, animals, disturbance, evolution, natural selection, genetic drift, hurricane	argumentation, visual data		visual	raw, photo, video
Testing the tolerance of invasive plants	3	ecology, herbivory, invasive species, plants, tolerance	statistical interaction, mean, standard error (SE)	bar	categorical	summarized, full dataset available
Picky eaters: Dissecting poo to examine moose diets	3	animal behavior, animals, ecology, foraging, herbivory, parks, predator-prey	1:1 line, proportion, mean, unnecessary variables	scatter	continuous, categorical	summarized, full dataset available
Candid camera: capturing the secret lives of carnivores	3	animals, biodiversity, carnivores, ecology, island biogeography, richness, camera trap, parks	regression	map, scatter	continuous	summarized, Digital Data Nugget
Crunchy or squishy? How El Niño events change zooplankton	3	algae, animals, marine, El Niño	outlier, correlation vs. causation, unnecessary variables	line, scatter	continuous	raw, Digital Data Nugget
Streams as sensors: Arctic watersheds as indicators of change	3	climate change, ecology, environmental, carbon, nitrogen, permafrost, limnology	unnecessary variables, regression, long-term data	scatter	continuous	summarized
The end of winter as we’ve known it?	3	climate change, ice cover, student research	Julian date, mean, regression, messiness, variability	scatter	continuous	summarized, full dataset available, Digital Data Nugget
Working to reduce the plastics problem	3	plastics, synthetic materials, chemistry, biodegradable, elastomer, polymer, monomer, stress, strain, physical science	percent, ratio	line	continuous	summarized
Limit by limit: Nutrients control algal growth in Arctic streams	3	nitrogen, nutrients, phosphorus, nutrient limitation, law of the minimum, Arctic, limnology	response ratio, graph choice, standard deviation (SD)	bar	categorical	summarized
To reflect, or not to reflect, that is the question	3	albedo, arctic, climate change, environmental, ice, temperature, water	equation, unnecessary variables, regression	line, scatter	continuous	summarized
How milkweed plants defend against monarch butterflies	3	herbivory, evolution, coevolution, plants, insects, ecology, scientist profile	mean, regression, best fit line, trend line, multiple dependent variables, messiness, outlier	line, scatter	continuous	summarized
Purring crickets: The evolution of a new cricket song	3	adaptation, animal behavior, animals, rapid evolution, mating, parasitism, scientist profile	mean, percent, Chi-square test	bar	categorical	raw, Digital Data Nugget
Round goby, skinny goby	3	local adaptation, animals, biodiversity, rapid evolution, fish, Great Lakes, habitat, invasive species, Kalamazoo River	mean, standard error, replication, sample size	bar	categorical	summarized, full dataset available
David vs. Goliath	3	aggression, animals, behavior, brain chemistry, competition, insects, physiology, biological significance	frequency, proportion, percent, unnecessary variables	bar	categorical	raw, summarized
Size matters - and so does how you carry it!	3	adaptation, animals, evolution, insects, sexual selection, tradeoffs	residuals, trend, multiple graphs, standardize	scatter, line	continuous	raw, summarized, full dataset available
Do you feel the urban heat?	3	urban, climate change, extreme heat, environmental justice, human impacts, socioeconomic, sensors	maximum, minimum, averages, time, baseline	multiple line	continuous, categorical	summarized
Ant wars!	3	aggression, animals, behavior, competition, insects	density, ratio, percent, regression, count	bar, line, scatter	continuous	raw, summarized
Salty sediments? What bacteria have to say about chloride pollution	3	bacteria, chemistry, disturbance, environmental, microbes, pollution, salt, urban, water, habitat, time, toxicity	mean, concentration	bar	categorical	summarized
Going underground to investigate carbon locked in soils	3	climate change, ecology, environmental, greenhouse gasses, soil carbon, microbes, chemistry	mean, standard deviation (SD), regression, best fit line, trend line, correlation vs. causation	line, scatter	continuous	summarized
Nitrate: Good for plants, bad for drinking water	3	agriculture, environmental, fertilization, nitrogen, soil, water, plants, human health	mean, time, date, Julian date, concentration	line, scatter	continuous, categorical	summarized, full dataset available
Trees and the city	3	biodiversity, ecology, environmental justice, social demographics, urban	spatial data analysis, percent, binned data, average, median, histogram	multiple scatter, spatial map	continuous	spatial, summarized, full dataset available
Collaborative cropping: Can plants help each other grow?	3	agriculture, environmental, plants, crops	replicates, correlation vs. causation, regression, trend	multiple scatter	continuous	raw
The sound of seagrass	3	acoustics, sound, photosynthesis, marine, productivity, decibels, physics	average, mean, standard deviation, trend, time	multiple scatter, line	continuous	summarized
Which tundra plants will win the climate change race?	3	climate change, nutrients, long-term data, competition, plants, ecology	mean, trend, time, series, control, long-term data	line	continuous	summarized
The prairie burns with desire	3	ecology, prairie, plants, fire ecology, human impact, reproduction, land management	trend, time, multiple plots, multiple variables, long-term data, proportion, average	scatter, line	continuous	summarized, full dataset available
Seagrass survival in a super salty lagoon	3	climate change, ecology, environmental, long-term, marine, plants, salinity	double y-axis, trend, time, multiple variables	scatter	continuous	summarized
Sink or source? How grazing geese impact the carbon cycle	3	carbon cycle, Arctic, wetlands, primary production, photosynthesis, respiration, climate change, birds, ecosystem	equation, calculation, subtraction, negative values, source, sink	bar	categorical, continuous	summarized
Poop, poop, goose!	3	wetlands, Arctic, carbon cycle, climate change, disturbance, ecology, environmental, greenhouse gasses, birds	mean, standard deviation (SD), flux	bar	categorical	summarized
Too hot to help? Friendship in a changing climate	3	mutualism, algae, coral, genotype, photosynthesis, respiration, climate change	calculations, negative values, net, mean, average, standard error	bar	categorical, continuous	summarized
Does the heat turn caterpillars into cannibals?	3	animal behavior, insect, virus, disease ecology, temperature, cannibalism, caterpillar	calculation, percents	bar	categorical, continuous	summarized
climate change, disturbance, ecology, environmental, growth, human impact, plants, water, wetlands	3	climate change, disturbance, ecology, environmental, growth, human impact, plants, water, wetlands	mean, average, mass,	bar	quantitative, qualitative	summarized
A plant breeder’s quest to improve perennial grain	4	genetics, artificial selection, DNA, selective breeding, phenotype, genotype, nucleotides, sequencing	calculations, average, predictions, standard error, standard deviation,	bar	continuous, categorical	supplemental activity available,
Cheaters in nature – when is a mutualism not a mutualism?	4	evolution, legume, plants, mutualism, parasitism, rhizobia, nitrogen, fertilization	mean, standard error (SE)	bar	categorical	summarized
Dangerous aquatic prey: can predators adapt to toxic algae?	4	adaptation, algae, evolution, marine, predation	mean	bar	categorical	summarized
Salmon in hot water	4	adaptation, animals, climate change, evolution, fish, genes, genome, temperature, DNA, heredity, genetics, QTL	mean	line	continuous	summarized
Urbanization and estuary eutrophication	4	algae, eutrophication, fertilization, marine, nitrogen, phosphorus, wetland, urban, photosynthesis, respiration, limnology	mean, standard error (SE), subtraction, model	bar	categorical	raw
How to escape a predator	4	adaptation, animal behavior, animals, predation, physiology, evolution	mean, standard error (SE), unnecessary variables	bar	categorical	raw, summarized
The flight of the stalk-eyed fly	4	physics, moment of intertia, adaptation, animals, flight, physiology	mean, standard error (SE), formula, equation, multiplication		continuous	summarized
Make way for mummichogs	4	animals, biodiversity, disturbance, fish, restoration, wetland, limnology, student research	mean	bar, line	continuous	raw, summarized
The Arctic is melting – so what?	4	climate change, marine, temperature, water, weather, ice, Arctic, albedo	percent, models	diagram	categorical, modeled data	summarized
Gene expression in stem cells	4	gene expression, genes, stem cells, DNA, genetics, human health	mean	bar	categorical	summarized, Digital Data Nugget
Bon Appétit! Why do male crickets feed females during courtship?	4	adaptation, animals, behavior, competition, insects, mating, feeding, alternative hypotheses, scientist profile	count, proportion, regression, multiple regression, unnecessary variables	scatter	continuous	raw, Digital Data Nugget
Winter is coming! Can you handle the freeze?	4	ecology, evolution, genes, plants, local adaptation, QTL	percent, standard deviation (SD), standard error (SE)	bar, line	categorical	raw, summarized
Finding Mr. Right	4	animals, animal behavior, biodiversity, birds, evolution, genes, mating, local adaptation	mean	bar	categorical	raw
Why so blue? The determinants of color pattern in killifish, Part I	4	adaptation, animals, biodiversity, evolution, fish, genes, mating, heredity, genetics, close reading activity	mean, standard deviation (SD), standarad error (SE)	bar	categorical	raw, summarized
Why so blue? The determinants of color pattern in killifish, Part II	4	adaptation, animals, biodiversity, evolution, fish, genes, mating, heredity, genetics	mean, standard deviation (SD), standarad error (SE)	bar	categorical	raw, summarized
Sticky situations: big and small animals with sticky feet	4	adaptation, animals, biomimicry, chemistry, physics, scale	mean, ratio, multiplication, formula, equation, surface area, mass, volume	scatter - logarithmic axes	continuous	summarized
When whale I sea you again?	4	climate change, marine, temperature, water, whales, DNA, PCR, sex ratio	fraction, percent, ratio	line, stacked bar	continuous, categorical	raw, Digital Data Nugget
The case of the collapsing soil	4	climate change, carbon, ecology, plants, phosphorus, sea level rise, respiration, substrate, wetland, limnology	regression, concentration	scatter	continuous	raw, Digital Data Nugget
Clique wars: social conflict in daffodil cichlids	4	animal behavior, animals, competition, fish	count, standard deviation (SD), standarad error (SE)	bar	categorical	summarized, Digital Data Nugget
Fishy origins	4	community science, citizen science, DNA, evolution, fish, PCR, marine, microsatellites	percent, proportion, addition, division	bar, stacked bar	continuous, categorical	raw
Fertilizer and fire change microbes in prairie soil	4	biodiversity, diversity, grassland, microbes, plants, prairie, soil	unnecessary variables, Shannon Wiener Index, mean	bar	continuous, categorical	summarized
Breathing in, Part I	4	photosynthesis, carbon accumulation, carbon sequestration, climate change, forest, habitat	mean, confidence, global database	bar	continuous, categorical	summarized, full dataset available
Breathing in, Part 2	4	climate change, photosynthesis, respiration, carbon, climate model	precision, percent, model prediction, mean, calculation, equation	bar	continuous, categorical	summarized, full dataset available
Stop that oxidation! What fruit flies teach us about human health	4	insects, model species, cell biology, genetics, cellular processes, oxidation, genetics, scientist profile	mean	bar	continuous, categorical	raw, summarized
Love that dirty water	4	environmental, urban, water, GIS, landscapes, impervious surfaces, ecosystem services, land acknowledgement, human health	model, web-tool, simulation, percent change, calculation, map	bar, line, map	categorical, continuous	summarized
Trees and bushes, home sweet home for warblers	4	animals, biodiversity, disturbance, ecology, birds, succession, transect, habitat	regression, best fit line, trend line, percent	scatter	continuous	summarized
Changing climates in the Rocky Mountains	4	citizen science, climate change, community science, ecology, environmental, plants, precipitation, temperature	mean, trend, time	line, double y-axis	continuous, categorical	summarized, photo
Surviving the flood	4	disturbance, urban, stream, floods, photosynthesis, respiration, stormwater	reference line, percent, negative values, additional variables, difference, unnecessary variables, outlier	scatter, line	continuous	raw, summarized
Eavesdropping on the ocean	4	acoustic ecology, physics, whales technology, mammals, marine biology, renewable energy, population, human impact	proportions, calculation, detections	scatter, bar	categorical, continuous	summarized, full dataset available
Reconstructing the behaviour of ancient animals	4	anatomy, animals, behavior, form and function, fossils, nocturnal, paleobiology, primate	mean, average, range, maximum, minimum, box and whisker plot	bar, box and whisker plot	categorical, continuous	summarized
CO2 and trees, too much of a good thing?	4	Carbon dioxide, climate change, photosynthesis, plants, respiration	mass, average	bar	categorical, continuous	summarized
Catching fish with sound	4	climate change, fish, ocean, sound	volume, depth, temperature	scatter	continuous	summarized
Bear Necessities: A genetic panel for bear identification	4	animals, DNA, Genetics, Conservation	genotype	NA	categorical	summarized
Toxic legacy	4	chemical pollution, community, human health, superfund	geometric mean, average, reference population	multiple bar	categorical, quantitative	summarized

Lizards, iguanas, and snakes! Oh my!

The Common Side-blotched Lizard

The activities are as follows:

Throughout history people have settled mainly along rivers and streams. Easy access to water provides resources to support many people living in one area. In the United States today, people have settled along 70% of rivers.

Today, rivers are very different from what they were like before people settled near them. The land surrounding these rivers, called riparian habitats, has been transformed into land for farming, businesses, or housing for people. This urbanization has caused the loss of green spaces that provide valuable services, such as water filtration, species diversity, and a connection to nature for people living in cities. Today, people are trying to restore green spaces along the river to bring back these services. Restoration of disturbed riparian habitats will hopefully bring back native species and all the other benefits these habitats provide.

Scientist Mélanie searching for reptiles in the Central Arizona-Phoenix LTER.

Scientists Heather and Mélanie are researchers with the Central Arizona-Phoenix Long-Term Ecological Research (CAP LTER) project. They want to know how restoration will affect animals living near rivers. They are particularly interested in reptiles, such as lizards. Reptiles play important roles in riparian habitats. Reptiles help energy flow and nutrient cycling. This means that if reptiles live in restored riparian habitats, they could increase the long-term health of those habitats. Reptiles can also offer clues about the condition of an ecosystem. Areas where reptiles are found are usually in better condition than areas where reptiles do not live.

Heather and Mélanie wanted to look at how disturbances in riparian habitats affected reptiles. They wanted to know if reptile abundance (number of individuals) and diversity (number of species) would be different in areas that were more developed. Some reptile species may be sensitive to urbanization, but if these habitats are restored their diversity and abundance might increase or return to pre-urbanization levels. The scientists collected data along the Salt River in Arizona. They had three sites: 1) a non-urban site, 2) an urban disturbed site, and 3) an urban rehabilitated site. They counted reptiles that they saw during a survey. At each site, they searched 21 plots that were 10 meters wide and 20 meters long. The sites were located along 7 transects, or paths measured out to collect data. Transects were laid out along the riparian habitat of the stream and there were 3 plots per transect. Each plot was surveyed 5 times. They searched for animals on the ground, under rocks, and in trees and shrubs.

Featured scientists: Heather Bateman and Mélanie Banville from Arizona State University. Written by Monica Elser from Arizona State University.

Flesch–Kincaid Reading Grade Level = 9.8

Check out this video of Heather and her lab out in the field collecting lizards:

Virtual field trip to the Salt River biodiversity project:

Additional resources related to this Data Nugget:

For more background on the importance of biodiversity, students can eat this article in The Guardian – What is biodiversity and why does it matter to us?

SaveSave

10.21.15

Is your salt marsh in the zone?

Scientist James collecting plants in a Massachusetts marsh, part of the Plum Island Ecosystems Long Term Ecological Research site

The activities are as follows:

Tides are the rise and fall of ocean water levels, and happen every day like clockwork. Gravity from the moon and sun drive the tides. There is a high tide and a low tide, and the average height of the tide is called the mean sea level. The mean sea level changes seasonally due to the warming and cooling of the ocean throughout the year. It also changes annually due to a long-term trend of ocean warming and the melting of glaciers. Scientific evidence shows that climate change is causing the sea level to rise faster now than it has in the past. As the climate continues to warm, it is predicted that the sea level will continue to rise.

Salt marshes are wetlands with plains of grass that grow along much of the ocean’s coast worldwide. These marshes are important habitats for many plants and animals, and protect our shores from erosion during storms. They grow between mean sea level and the level of high tide. Marshes flood during high tide and are exposed to the air during low tide. The health of a salt marsh is determined by where it sits relative to the tide (the “zone”). A healthy marsh is flooded only part of the time. Too much flooding and too little flooding are unhealthy. Because they are so important, scientists want to know if salt marshes will keep up with sea level rise caused by climate change.

A picture of James’ “marsh organ” which holds plants at different elevations relative to mean sea level. He gave it that name because it resembles organ pipes!

In the 1980s, scientist James began measuring the growth of marsh grasses. He was surprised to find that there was a long-term trend of increasing grass growth over the years. James wanted to know if grasses could continue to keep up with rising sea levels. If he could experimentally manipulate the height of the grasses, relative to mean sea level, he might be able to figure out how grasses will do when sea levels are higher. To test this, James invented a way to experimentally grow a marsh at different elevations relative to mean sea level. He built a device he called the “marsh organ”. This device is made of tubes that stand at different elevations and are filled with marsh mud and planted with marsh grasses. He measured the growth of the grass in each of the pipes. If grasses will continue to grow taller in the future with higher water levels, then plants growing in pipes at lower elevations should grow more than plants growing in pipes with higher elevations.

Featured scientist: James Morris from the University of South Carolina

Additional teacher resource related to this Data Nugget: Jim has created an interactive salt marsh model called the “marsh equilibrium model”. This online tool allows you to plug in different marsh levels to explore potential impacts to the salt marsh. To explore this tool click here.

To read more about Jim’s research on “tipping points” beyond which sediment accumulation fails to keep up with rising sea level and the marshes drown, click here.

There are two publications related to the data included in this activity:

Morris, J.T., Sundberg, K., and Hopkinson, C.S. 2013. Salt marsh primary production and its responses to relative sea level and nutrients in estuaries at Plum Island, Massachusetts, and North Inlet, South Carolina, USA. Oceanography 26:78-84.
Morris, J.T., P.V. Sundareshwar, C.T. Nietch, B. Kjerfve, D.R. Cahoon. 2002. Responses of coastal wetlands to rising sea level. Ecology 83:2869-2877.

SaveSave

10.19.15

Green crabs: invaders in the Great Marsh

Scientist Alyssa holding a non-native green crab, introduced from Europe to the American Atlantic Coast. This crab causes many problems in its new range, including the loss of native eelgrass.

The activities are as follows:

Marshes, areas along the coast that flood with each tide, are incredibly important habitats. They act as homes to large number of species, protect the coast from erosion during storms, and act as a filter for nutrients and pollution. Many species are unique to these habitats and provide crucial support to the marsh. For example, native eelgrass, a type of plant, minimizes erosion by holding sediments in place with their roots.

In an effort to help protect and restore marshes, we must understand current-day issues that are affecting their health. The introduction of non-native species, species that are not originally from this ecosystem, into a marsh may disrupt the marsh ecosystem and threaten the survival of native species. One species that has recently caused a lot of trouble is the European green crab. This crab species was accidentally carried to the Atlantic coast back in the early 1800s from Europe. Since then, they have become extremely invasive and their numbers have exploded! Compared to native crabs, the green crab digs a lot when it searches for food and shelter. This digging uproots eelgrass and causes its population numbers to fall. In many spots where green crabs have been introduced, marshes are now bare and no more grass can grow.

Non-native green crabs caught in trap that has been underwater for 25 hours

The Great Marsh is one of the coastal habitats affected by invasive green crabs. Located on the North Shore of Massachusetts, the Great Marsh is known for being the longest continuous stretch of salt marsh in all of New England. Alyssa is a restoration ecologist who is very concerned with the conservation of the Great Marsh and other important coastal ecosystems. She and other scientists are trying to maintain native species while also reducing the effects of non-native species.

A major goal for Alyssa is to restore populations of a native eelgrass. Eelgrass does more than just prevent erosion. It also improves water quality, provides food and habitat for native animal species, and acts as an indicator of marsh health. If green crabs are responsible for the loss of eelgrass from the marsh, then restorations where eelgrass is planted back into the marsh should be more successful where green crab numbers are low. Alyssa has been measuring green crab populations in different areas by laying out green crab traps for 24 hours. Alyssa has set these traps around Essex Bay, an area within the Great Marsh. She recorded the total number of green crabs caught at each location (as well as their body size and sex).

Native eelgrass growing in Essex Bay, an area within the Great Marsh

Featured scientist: Alyssa Novak, Center for Coastal Studies/Boston University. Written by: Hanna Morgensen

Flesch–Kincaid Reading Grade Level = 8.8

8.24.15

Urbanization and estuary eutrophication

Charles Hopkinson out taking dissolved O2 measurements.

The activities are as follows:

An estuary is a habitat formed where a freshwater river or stream meets a saltwater ocean. Many estuaries can be found along the Atlantic coast of North America. Reeds and grasses are the dominant type of plant in estuaries because they are able to tolerate and grow in the salty water. Where these reeds and grasses grow they form a special habitat called a salt marsh. Salt marshes are important because they filter polluted water and buffer the land from storms. Salt marshes are the habitat for many different kinds of plants, fish, shellfish, and birds.

Hap Garritt removing an oxygen logger from Middle Road Bridge in winter.

Scientists are worried because some salt marshes are in trouble! Runoff from rain washes nutrients, usually from lawn fertilizers and agriculture, from land and carries them to estuaries. When excess nutrients, such as nitrogen or phosphorus, enter an ecosystem the natural balance is disrupted. The ecosystem becomes more productive, called eutrophication. Eutrophication can cause major problems for estuaries and other habitats.

With more nutrients in the ecosystem, the growth of plants and algae explodes. During the day, algae photosynthesize and release O₂ as a byproduct. However, excess nutrients cause these same algae grow densely near the surface of the water, decreasing the light available to plants growing below the water on the soil surface. Without light, the plants die and are broken down by decomposers. Decomposers, such as bacteria, use a lot of O₂because they respire as they break down plant material. Because there is so much dead plant material for decomposers, they use up most of the O₂ dissolved in the water. Eventually there is not enough O₂for aquatic animals, such as fish and shellfish, and they begin to die-off as well.

Two features can be used to identify whether eutrophication is occurring. The first feature is low levels of dissolved O₂ in the water. The second feature is when there are large changes in the amount of dissolved O₂ from dawn to dusk. Remember, during the day when it’s sunny, photosynthesis converts CO₂, water, and light into glucose and O₂. Decomposition reverses the process, using glucose and O₂ and producing CO₂ and water. This means that when the sun is down at night, O₂ is not being added to the water from photosynthesis. However, O₂ is still being used for decomposition and respiration by animals and plants at night.

The scientists focused on two locations in the Plum Island Estuary and measured dissolved O₂ levels, or the amount of O₂in the water. They looked at how the levels of O₂ changed throughout the day and night. They predicted that the upper part of the estuary would show the two features of eutrophication because it is located near an urban area. They also predicted the lower part of the estuary would not be affected by eutrophication because it was farther from urban areas.

A view of the Plum Island estuary

Featured scientists: Charles Hopkinson from University of Georgia and Hap Garritt from the Marine Biological Laboratory Ecosystems Center

Flesch–Kincaid Reading Grade Level = 9.6

5.6.15

Invasive reeds in the salt marsh

Culverts run under roads and allow water from the ocean to enter a marsh. Phragmites can be seen growing in the background.

The activities are as follows:

Phragmites australis is an invasive reed, a type of grass that grows in water. Phragmites is taking over saltwater marshes in New England, or wetland habitats near the Atlantic Ocean coast. Phragmites does so well it crowds out native plants that once served as food and homes for marsh animals. Once Phragmites has invaded, it is sometimes the only plant species left! Phragmites does best where humans have disturbed a marsh, and scientists were curious why that might be. They thought that perhaps when a marsh is disturbed, the salinity, or amount of salt in the water, changes. Phragmites might be able to survive after disturbances that cause the amount of salt in the water to drop, but becomes stressed when salinity is high.

Students collecting data on the plant species present in the marsh using transects. Every 1m along the tape, students observe which plants are present. Phragmites is the tall grass that can be seen growing behind the students.

Fresh water in a marsh flows from the upstream source to downstream. Saltwater marshes end at the ocean, where freshwater mixes with salty ocean water. One type of disturbance is when a road is cut through a marsh. Upstream of the road, the marsh is cut off from the salt waters from the ocean, so only fresh water will enter and salinity will drop. Downstream of the road, the marsh is still connected to the ocean and salinity should be unaffected by the disturbance. Often, a culvert (a pipe that runs under the road) is placed to allow salt water to pass from the ocean into the marsh. The amount of ocean water flowing into the marsh is dependent on the diameter of the culvert.

Students at Ipswich High School worked with scientists from the Mass Audubon, a conservation organization, to look at the Phragmites in the marsh. They looked at an area where the salinity in the marsh changed after a road was built. They wanted to know if this change would affect the amount of Phragmites in that marsh. In 1996, permanent posts were placed 25 meters apart in the marsh. That way, scientists could collect data from the same points each year. At these posts, students used transects, a straight line measured from a point to mark where data is collected. Then they collected data on all the plants that were found every meter along the transects. Data has been collected at these same points since 1996. In 2005, an old 30cm diameter culvert was replaced with two 122cm culverts. These wider culverts allow much more salty ocean water to flow under the road and into the marsh. Students predicted that after the culverts were widened, more ocean water would enter the marsh. This would make salinity go up, making it harder for Phragmites to grow, and it would decline in numbers. Students continued to survey the plants found along transects at each permanent post and documented their findings.

Featured scientists: Lori LaFrance from Ipswich High School, Massachusetts and Liz Duff from Mass Audubon. This study was part of the PIE-LTER funded by the NSF.

Flesch–Kincaid Reading Grade Level = 9.0

To access the original data presented in this activity, and collected by students, access Mass Audubon’s Vegetation Data, available online. To access the salinity data related to this activity, and collected by students, access Mass Audubon’s Salinity Data, available online. Scroll down to “Ipswich, MA, Town Farm Road” for data from the site discussed here.

View of the two new culverts.

The old pipe that was removed, and the new culvert.

Arial view of the upstream and downstream research sites.

4.23.15

Growing energy: comparing biofuel crop biomass

The activities are as follows:

Éste Data Nugget también está disponible en Español:

Most of us use fossil fuels every day to power our cars, heat and cool our homes, and make many of the products we buy. Fossil fuels like coal, oil, and natural gas come from plants and animals that lived and died hundreds of millions of years ago – this is why they’re called “fossil” fuels! These ancient energy sources have many uses, but they also have a major problem. When we use them, fossil fuels release carbon dioxide into the atmosphere. As a greenhouse gas, carbon dioxide traps heat and warms the planet. To avoid the serious problems that come with a warmer climate, we need to transition away from fossil fuels and think of new, cleaner ways to power our world.

Biofuels are one of these alternatives. Biofuels are made out of the leaves and stems (called biomass) of plants that are alive and growing today. When harvested, the biomass can be converted into fuel. Plants take in carbon dioxide from the atmosphere to grow. It’s part of the process of photosynthesis. In that way, biofuels can create a balance between the carbon dioxide taken in by plants and what is released when burning fuels.

At the Great Lakes Bioenergy Research Center, scientists and engineers work together to study how to grow plants that take in as much carbon as possible while also producing useful biofuels. Gregg is one of these scientists and he wants to find out how much biomass can be harvested from different plants like corn, grasses, trees, and even weeds. Usually, the bigger and faster a plant grows, the more biomass they make. When more biomass is grown, more biofuels can be produced. Gregg is interested in learning how to produce the most biomass while not harming the environment.

While biofuels may sound like a great solution, Gregg is concerned with how growing them may affect the environment. Biofuels plants come with tradeoffs. Some, like corn, are great at quickly growing to huge heights – but to do this, they often need a lot of fertilizer and pesticides. These can harm the environment, cost farmers money, and may even release more of the greenhouse gasses we are trying to reduce. Other plants might not grow so fast or so big, but also don’t require as many chemicals to grow, and can benefit the environment in other ways, such as by providing habitat for animals. Many of those plants are perennials, meaning that they can grow back year after year without replanting (unlike corn). Common biofuel perennials like switchgrass, Miscanthus grass, prairie grasses, and poplar trees require fewer fertilizers and pesticides to grow, and less fossil fuel-powered equipment to grow and harvest them. Because of this, perennials might be a smart alternative to corn as a source of biofuels.

Gregg out in the WI experimental farm.

Believing in the power of perennials, Gregg thought that it might even be possible to get the same amount of biomass from perennials as is normally harvested from corn, but without using all of the extra chemicals and using less energy. To investigate his ideas, Gregg worked together with a team to design a very big experiment. The team grew many plots of biofuel plants on farms in Wisconsin and Michigan, knowing that the soils at the site in Wisconsin were more nutrient-rich and better for the plants they were studying than at the Michigan site. At each farm, they grew plots of corn, as well as five types of perennial plots: switchgrass, Miscanthus grass, a mix of prairie plant species, young poplar trees, and weeds. For five years, the scientists harvested, dried, and weighed the biomass from each plot every fall. Then, they did the math to find the average amount of biomass produced every year by each plot type at the Wisconsin and Michigan sites.

Featured scientist: Dr. Gregg Sanford from University of Wisconsin-Madison. Written with Marina Kerekes.

Flesch–Kincaid Reading Grade Level = 8.9

This Data Nugget was adapted from a data analysis activity developed by the Great Lakes Bioenergy Research Center (GLBRC). For a more detailed version of this lesson plan, including a supplemental reading, biomass harvest video and extension activities, click here.

This lesson can be paired with The Science of Farming research story to learn a bit more about the process of designing large-scale agricultural experiments that need to account for lots of variables.

For a classroom reading, click here to download an article written for the public on these research findings. Click here for the scientific publication. For more bioenergy lesson plans by the GLBRC, check out their education page.

Aerial view of GLBRC KBS LTER cellulosic biofuels research experiment; Photo Credit: KBS LTER, Michigan State University

For more photos of the GLBRC site in Michigan, click here.

SaveSave

SaveSaveSaveSave

SaveSave

3.20.15

Springing forward

Scientist Shaun collecting phenology data in the climate change experiment. He is recording the date that the first flowers emerge for dame’s rocket.

Sean Mooney, a high school researcher, collecting phenology data in the climate change experiment. He is recording the date that the first flowers emerge for dame’s rocket.

The Reading Level 1 activities are as follows:

The Reading Level 3 activities are as follows:

Éste Data Nugget también está disponible en Español:

Every day we add more greenhouse gases to our air when we burn fossil fuels like oil, coal, and natural gas. Greenhouse gasses trap the sun’s heat, so as we add more the Earth is heating up! What does climate change mean for the species on our planet? The timing of life cycle events for plants and animals, like flowering and migration, is largely determined by cues organisms take from the environment. The timing of these events is called phenology. Scientists studying phenology are interested in how climate change will influence different species. For example, with warming temperatures and more unpredictable transitions between seasons, what can we expect to happen to the migration timings of birds, mating seasons for animals, or flowering times of plants?

Scientists collecting phenology data in the climate change experiment.

Plants are the foundation for almost all life on Earth. Through photosynthesis, plants produce the oxygen (O₂) that we breathe, food for their own growth and development, food for animals and microbes, and crops that provide food and materials for human society. Because plants are so important to life, we need to find out how climate change could affect them. One good place to start is by looking at flowering plants, guided by the question, how will increased temperatures affect the phenology of flowering? One possible answer to this question is that the date that flowers first emerge for a species is driven by temperature. If this relationship is real, we would expect flowers to emerge earlier each year as temperatures increase due to climate change. But if flowers come out earlier and earlier each year, this could greatly impact plant reproduction and could cause problems for pollinators who count on plants flowering at the same time the pollinators need the pollen for food.

Shaun, Mark, Elizabeth, and Jen are scientists in Michigan who wanted to know if higher temperatures would lead to earlier flowering dates for plants. They chose to look at flowers of dame’s rocket, a leafy plant that is related to the plants we use to make mustard! Mark planted dame’s rocket in eight plots of land. Plots were randomly assigned to one of two treatments. Half of the plots were left to experience normal temperatures (normal), while the other four received a heating treatment to simulate climate change (heated). Air temperatures in heated plots increased by 3°C, which mimics climate change projections for what Michigan will experience by the end of the century. Mark, Elizabeth, and Jen measured the date that each plant produced its first flower, and the survival of each plant. The scientists predicted that dame’s rocket growing in the heated plots would flower earlier than those in the normal plots.

Featured scientists: Shaun Davis from Thornapple Kellogg Middle School and Mark Hammond, Elizabeth Schultheis, and Jen Lau from Michigan State University

Flesch–Kincaid Reading Grade Level = The Reading Level 3 activity has a score of 9.2; the Level 1 has a 6.4.

Flowers of Hesperis matronalis (dame’s rocket), a species of mustard that was introduced to the U.S. from Eurasia.

Additional teacher resources related to this Data Nugget include:

If you would like your students to interact with the raw data, we have attached the original data here. The file also includes weather data over the course of the experiment if students want to ask and explore independent questions.

For a lesson plan that uses citizen science phenology datasets to examine changes in phenology over 30+ year timespans, and address the scientific question, “Do we see evidence for climate change in the phenology of plants and animals?”, click here.
Many phenology datasets are freely available online (many collected by citizen scientists). These datasets are extremely useful because scientists (and your students!) can examine average trends in timing shifts over periods of decades and often in different regions. Phenology datasets available online:
- Lilac flowering phenology dataset
- Ice cover duration for two Michigan lakes
- Nature’s Notebook: A national plant and animal phenology observation program, where students can contribute their phenology data
- ebird: A global bird observation program through Cornell University, students can become citizen scientists and enter data on local bird counts
- hummingbird.net: A place to learn about attracting, watching, feeding, and studying the hummingbirds that breed in North America
NY Times article on research showing what happens when climate change shifts phenology – “5 Plants and Animals Utterly Confused by Climate Change“
Webinar, hosted by Data Nuggets and DataClassroom, exploring the research and data behind this activity.
Webinar exploring how plants respond to climate change, featuring this Data Nugget and LTER scientists!

SaveSave

10.24.14

Shooting the poop

The activities are as follows:

Imagine walking through a forest in the middle of summer. You can hear birds chirping, a slight breeze rustling the leaves, and a faint pinging noise like rain. However, what you hear is not rain – it is the sound of millions of forest insects pooping!

If we look closer to see who is making all this frass (insect poop) you’ll notice there are tons of caterpillars amongst the leaves. You might see caterpillars eating plants and hiding from predators. Some caterpillars might camouflage themselves, while others build shelters from leaves to avoid being seen. Others are brightly colored to warn predators that they have chemicals that make them taste awful.

The silver-spotted skipper is a caterpillar that lives in the forest. They have a variety of defense strategies against enemies, including building leaf shelters for protection. For these insects, the sight and smell of poop might alert predators that there is a tasty meal nearby. Usually caterpillars keep moving and leave their frass behind, but this species builds shelters and isn’t able to keep moving because they need their shelters for protection.

Martha is a behavioral biologist who studies these insects. While raising silver-spotted skipper caterpillars in the lab, Martha noticed that they were making a pinging noise in their containers. Upon further observation, she discovered that they “shoot their poop”, sometimes launching their frass over 1.5m! Martha wanted to figure out why these caterpillars might have this very strange behavior. Perhaps launching their frass is a way to avoid being found by predators.

To evaluate whether the smell of frass helps predators find and locate silver-spotted skippers, Martha conducted an experiment with a wasp predator that eats these caterpillars. She allowed two silver-spotted skippers to build shelters on a leaf and then carefully removed the caterpillars. She then inserted 6 frass pellets into one of the shelters, and 6 beads designed to look like frass but with no smell (control treatment) into the other shelter. She placed the leaf with the two shelters in a cage containing an actively foraging wasp colony (n = 10 wasps). She recorded how many times the wasps visited each shelter (control beads or frass) and how much time the wasps spent exploring each shelter. She expected wasps would spend more time exploring the shelters with the frass than they would the control shelters.

Featured scientist: Martha Weiss from Georgetown University. Written by Kylee Grenis.

Flesch–Kincaid Reading Grade Level = 9.6

Additional teacher resources related to this Data Nugget include:

The paper published using this data and testing alternative hypotheses: Weiss, M. R. (2003) Good housekeeping: why do shelter-dwelling caterpillars fling their frass? Ecology Letters 6(4): 361–370

YouTube videos of the silver-spotted skipper (Epargyreus clarus) “shooting its poop” (aka. ballistic defecation). These videos would be great to show in class after students have read the Research Background section to help engage them with the system.

SaveSave

SaveSaveSaveSave

SaveSave

Search Results for: lter

History of Data Nuggets

For more information on Data Nuggets, see our paper in the American Biology Teacher: Click here for a PDF!

BY MATH & SCIENCE CONCEPTS

If you are looking for additional data to use with your students, search “full dataset available” to find Data Nuggets where the scientists have provided the full datasets behind the research in the activity. Email datanuggetsK16@gmail.com to get a copy of these data!

To help introduce these science and math concepts to your students, check out this set of resources.

Lizards, iguanas, and snakes! Oh my!

Is your salt marsh in the zone?

Green crabs: invaders in the Great Marsh

Urbanization and estuary eutrophication

Invasive reeds in the salt marsh

Growing energy: comparing biofuel crop biomass

Springing forward

Shooting the poop