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Tracking butterfly responses to climate change using citizen science data
Leslie RiesUniversity of Maryland, Biology
National Socio-environmental Synthesis Center
Focus on the monarch as a model for understanding climate and ecological models
Stage 1: Overwintering
Stage 2: Spring
migration and breeding
Stage 3: Summer expansion and breeding
Stage 4: Fall migration
Journey Northstarted ‘99
Monarch Larvae Monitoring
Projectstarted ‘99
WWF-Mexico• started ’96
• started tracking overwinter mortality in 2003
N. American Bfly Assoc.started 1975
Ohio BMSstarted ’96
How does climate impact butterflies? Changing climates can challenge the physiological
tolerances of species Increased heat can allow more growth (in juveniles) or activity
(in adults), but can also be harmful at excessive temperatures Changing climates can shift the distribution or emergence
timing of interacting species host or nectar plants natural enemies or mutualists
These dynamics can combine to shift range distributions or impact population numbers Species Distribution Models help us understand range dynamics Population models help us understand how performance at each
stage impacts population trajectories
• Mechanistic models translate environmental conditions (often thermal constraints to growth or energetics) into biologically relevant metrics (survivorship or fecundity) and can be used to predict distributions at large scales.
• BENEFITS: • Specific mechanisms are identified a
priori • Allows independent distribution data
to test predictions and identify specific weaknesses and strengths of the models
• DRAWBACKS:• Lack of data for most organisms • Short history of model development• Lack of model transferability between
organisms
Species Distribution Models: Mechanistic Approach
0
500
1000
1500
2000
2500
3000
3500
0 100 200 300 400Acc
umul
ated
deg
ree
days
Julian Date
Degree days through the year
Growing Degree Days (GDD)• Growing degree days are used to estimate the
amount of thermal energy available for growth. • A minimum temperature at which growth can
begin is determined (DZmin), and each degree above that is considered a “degree day”• In some cases, a maximum temperature is set
(DZmax) after which degree days are no longer accumulated
June
Apr
Oct
0
5
10
15
20
25
5 10 15 20 25 30 35 40 45
Dai
ly d
egre
e da
ys
(Tmin+Tmax)/2
Calculating daily degree days
DZmin = 11.5C
(52.7F) DZmax = 33C (91.4F)
?
Total GDD required:~323DD
Zalucki 1982
44DD
31DD
27DD
25DD
34DD
58DD
104DD
Goal: Predict current (and future) distributions
Take laboratory-measured temperature tolerances to develop GDD calculations
Obtain climate data to estimate number of generations possible within a region of interest
Determine if the predicted range overlaps with the known distribution
+ =
Building the distribution modelTake laboratory-measured temperature tolerances and intersect with spatial patterns of heat accumulation throughout eastern North America to predict number of generations that could be produced in spring and summer
Predicted number of generations on averageSpring (Mar-Apr) Summer (May-Aug)
Testing the distribution model:spring distributions
Data source: Journey North All records: Mar-Apr
Testing the distribution model:summer distributions
Data source: NABA Average observations: July
1 year
35 year
Modeling the distribution of the sachem butterfly using mechanistic models
The sachem butterfly (Atalopedes campestris) recently expanded its range into Washington state.
Winter temperatures had been rising in the area
Natural history notes: a common, open-area species that uses several grasses, including common grasses such as Bermuda and crab grass
Leslie Ries1, Jessica Turner1, Lisa Crozier2, and Thomas Mueller1
1University of Maryland 2NOAA NW Fisheries Center
Summer recruitment Recruitment predictions are based on growing degree days
In this case, the lower development threshold (DZmin) was 15.5C (60F) with no upper temperature threshold (Crozier 2001)
Number of growing degree days necessary for a single generation was estimated at 417
Predictedgenerations:
Predicted number of generations based on NOAA weather station data (1990-2009 average)
Overwinter survival Predicted rates of overwinter survival are based on mean
January temperature
Predicted overwinter survival based on NOAA weather station data (1990-2009 average)
Predictedsurvival:
Predicted growth rates The model predicts lambda based on summer recruitment
and overwinter survival Clearly, the scaling of the model predictions seem off…
Predicted lambda based on NOAA weather station data (1990-2009 average)
Predictedlambda:
The model does well at capturing the northern range limits (limited by cold), but
overestimates growth in warmer regions
GDD models have historically focused on cold limitations rather than physiological detriments of excessive heat
Predictedlambda:
Observed abundances:
Another study showing the sachem increasing in MA
*
GDD models have historically focused on cold limitations rather than physiological detriments of excessive heat
Lethal and sub-lethal temperature effects were tested in a laboratory
setting (Betalden et al., in prep) Larvae at various stages were exposed to potentially
lethal or sublethal temperatures for a different number of days 38C (100.4F), 40C (104F), 42C (107.6F), 44C (111.2F) and
a control (30C, 86F) First, Third, Fifth instars exposed Exposed for 1, 2, 4, or 6 days Nighttime temperatures were kept at 25C
Larvae were reared to determine survivorship rates and total development time (in degree days)
Results: Survivorship rates (Betalden et al., in prep)
• Survivorship begins to decline for the 40C treatment only when larvae are exposed for 6 days (and only for 3rd and 5th instars)
• Survivorship is very low overall at 42C
• No individuals in the 44C treatment survived
Results: Development Time (Betalden et al., in prep)
• Development time increases as individuals are exposed to higher temperatures for longer periods of time
• There is a treatment effect even for individuals exposed for 1 day (suggesting sublethal effects may occur at lower temperatures)
So how should GDD be calculated?
0
5
10
15
20
25
5 10 15 20 25 30 35 40 45
Daily
deg
ree
days
(Tmin+Tmax)/2
Calculating daily degree days
DZmin = 11.5C (52.7F)
DZmax = 31.5C (88.7F)
?
Sub-lethal and lethal
effects
?
Mapping out lethal and sub-lethal zones:Average from 1990-2009
ABOVE 42ABOVE 40ABOVE 38
AVG NUMBER OF DAYS
• Lethal and sub-lethal temperatures seem to correspond to limits in population densities, especially in the midwest
• Next up:• Comparing lethal temperatures to
larval development observed in the field
MLMP SITES
Preference and performance relative to mean number of days >38C
Mean number of days with temps >38C
0
0.2
0.4
0.6
0.8
1
June July Aug
Prop
orti
on E
ggs
Month
Performance
0-1
1-5
>5
In zones where caterpillars are more likely to experience sub-lethal temperatures, there appears to be less development
But climate differs from year to year – so did temperature really drive those patterns?
Accumulated sub-lethal degree days:
1999 2000 2001
2002 2003 2004
• These are accumulated over the main summer growing season (2 months)
• To truly test the impacts of sub-lethal and lethal temperatures, we need to tie temperature events to survey dates
Relationship between development and accumulated sub-lethal degree days
0
0.02
0.04
0.06
0.08
0.1
0.12
0.14
0.16
None 0-1 1-10 >10
Prop
orti
on la
te in
star
larv
ae
Number of accumulated sub-lethal degree days
n=518
n=267n=70
n=24
• Conclusions• Monarch distributions are limited by cold temperatures in the
spring and both cold and hot temperatures in the summer• But what stage is the most crucial for monarch populations?
Understanding monarch population dynamics is critical for their conservation
Notable population patterns: Eastern monarchs may be declining,
but examining different life stages suggests different patterns
Monarch populations show large fluctuations from year to year
Underlying mechanisms REGIONAL CONNECTIONS: How
do dynamics in one phase of the migratory cycle influence dynamics in subsequent phases?
ENVIRONMENTAL INFLUENCE: How much do environmental factors influence the connection between these phases?
SUMMER MONITORING DATA
WINTER MONITORING DATA
Focus on climate impacts during migration and breeding
Stage 1: Overwintering
Stage 2: Spring
migration and breeding
Stage 3: Summer expansion and breeding
Stage 4: Fall migration
Journey Northstarted ‘99
Monarch Larvae Monitoring
Projectstarted ‘99
WWF-Mexico• started ’96
• started tracking overwinter mortality in 2003
N. American Bfly Assoc.started 1975
Ohio BMSstarted ’96
Data Available for Analysis
Monarch Larvae Monitoring Project (MLMP)
North American Butterfly Association Counts (NABA)
Ohio Butterfly Monitoring Scheme (OH)
Mexican sites
WWF: Mexico
Data Available for Analysis
Monarch Larvae Monitoring Project (MLMP)
North American Butterfly Association Counts (NABA)
Mexican sites
South
N-Central
N-East
Ohio Butterfly Monitoring Scheme (OH)
WWF: Mexico
South
N-Central
N-East
Tracking the population through each region and stage
1. Do the number of adults surviving the winter in Mexico relate to the number of adults arriving in the
Texas area in spring?2. Do the number of spring arriving
adults relate to the number of 1st gen eggs that are recorded?
Mexican sites
South
N-Central
N-East
Tracking the population through each region and stage
Mexican sites
1. Do the number of adults surviving the winter in Mexico relate to the number of adults arriving in the
Texas area in spring?2. Do the number of spring arriving
adults relate to the number of 1st gen eggs that are recorded?
3. How do the number of spring adults or eggs relate to the number of 1st generation arrivals in the northern
regions?
South
N-Central
N-East
Tracking the population through each region and stage
Mexican sites
1. Do the number of adults surviving the winter in Mexico relate to the number of adults arriving in the
Texas area in spring?2. Do the number of spring arriving
adults relate to the number of 1st gen eggs that are recorded?
3. How do the number of spring adults or eggs relate to the number of 1st generation arrivals in the northern
regions?4. Can the number of 1st generation
adults / 2nd generation eggs predict numbers in subsequent generations?
Q1 and Q2. How do overwintering numbers relate to the number of arriving adults and how do arriving adults influence the
number of eggs we see in the spring?
0
0.1
0.2
0.3
0.4
0.5
0.6
0 1 2 3
2nd
gen
MLM
P eg
g de
nsit
y (N
-Cen
tral
)
1st gen MLMP egg density (South)
00.20.40.60.81
1.21.41.61.82
0 0.5 1 1.5 2 2.5N
ABA
1st
Gen
adu
lts (
N-E
ast)
NABA spring migrants (South)
Q3. How do the number of spring adults or eggs relate to the number of 1st generation arrivals in the northern regions?
A weak, or non-existent, relationship between the spring generation and summer arrivals in the north could be due to lack of data, or swamping out by environmental
factors.
1st gen eggs in south to 2nd gen eggs North Migrant adults in south to 1st gen adult arrivals
r=0.5 p=0.13 r=0.69 p=0.12
0
1
2
3
4
5
6
7
8
0 1 2 3
Sum
mer
NA
BA d
etec
tions
(N-C
entr
al)
1st Gen Spring arrivals NABA (N-Central)
0
0.1
0.2
0.3
0.4
0.5
0.6
0.01 0.1 1
Sum
mer
MLM
P eg
g de
ns (N
-Cen
tral
)
2nd gen MLMP egg density (N-Central)
Q3. Can the number of 1st generation adults / 2nd generation eggs predict numbers in subsequent generations?
YES: This suggests that the number of arrivals in the northern breeding grounds from the southern spring generation has a strong influence on the ultimate size of that year’s population.
0
1
2
3
4
5
6
0.001 0.01 0.1 1Su
mm
er N
ABA
det
ectio
ns (N
-Eas
t)2nd gen MLMP egg density (N-East)
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.001 0.01 0.1 1
Sum
mer
MLM
P eg
g de
nsit
y (N
-Eas
t)
2nd gen MLMP egg density (N-East)
N-East: r=0.899 p=<0.0001 r=0.85 p=0.004
r=0.7925 p=<0.0001 r=0.73 p=0.005
N-Central:
Tracking climate’s impacts on the migratory monarch butterfly
We examined the impacts on population growth in Ohio of:
1. Spring temperature (in Texas)2. Spring precipitation (in Texas)3. Summer temperature (in Ohio)
4. Summer precipitation (in Ohio)
Patterns based on simple climate metrics aren’t informative
Meaningful patterns emerge when patterns are evaluated in a multiple regression framework
The story so far… • No relationship between adults leaving Mexico, arriving in the South, and
laying eggs
• Weak (or non-existent) relationship between adults arriving in the South, next generation arrivals in the North
and egg-laying• The disconnect may be due to the importance of spring climate on the
ultimate population size (and/or health) of migrants to the North
• A strong relationship between the numbers arriving in the North and
laying eggs and the size of the population at the end of the summer.• This suggests that the size of that
first generation produced in the spring that arrives in the North is an
important contributor to yearly population sizes and (again) that
spring climate is important
But are climate impacts direct or indirect?
South
N-Central
N-East
Could climate impact the phenological linkage between milkweeds and monarchs
Data source: Journey North
Arrival dates - 2001
Arrival mismatches are leading to at least anecdotal incidents of egg loading
Take home messages
Climate is impacting butterfly populations Using models that link physiological tolerance data to
large-scale distributions is a powerful way to tease out the complex interactions between climate and ecology
We could not possibly explore these questions in a rigorous way without a data stream from dedicated citizen-science networks, so public participation in scientific research is CRUCIAL to answer the most relevant questions in today’s world.
So THANK YOU!!!
Questions?
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