Presentation is loading. Please wait.

Presentation is loading. Please wait.

Tracking butterfly responses to climate change using citizen science data Leslie Ries University of Maryland, Biology National Socio-environmental Synthesis.

Similar presentations


Presentation on theme: "Tracking butterfly responses to climate change using citizen science data Leslie Ries University of Maryland, Biology National Socio-environmental Synthesis."— Presentation transcript:

1 Tracking butterfly responses to climate change using citizen science data Leslie Ries University of Maryland, Biology National Socio-environmental Synthesis Center

2 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 North started ‘99 Monarch Larvae Monitoring Project started ‘99 WWF-Mexico started ’96 started tracking overwinter mortality in 2003 N. American Bfly Assoc. started 1975 Ohio BMS started ’96

3 How does climate impact butterflies? Changing climates can challenge the physiological tolerances of species 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 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 Changing climates can shift the distribution or emergence timing of interacting species host or nectar plants host or nectar plants natural enemies or mutualists natural enemies or mutualists These dynamics can combine to shift range distributions or impact population numbers These dynamics can combine to shift range distributions or impact population numbers Species Distribution Models help us understand range dynamics Species Distribution Models help us understand range dynamics Population models help us understand how performance at each stage impacts population trajectories Population models help us understand how performance at each stage impacts population trajectories

4 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

5 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 DZmin = 11.5C (52.7F) DZmax = 33C (91.4F) ? Total GDD required: ~323DD Zalucki DD 31DD 27DD 25DD 34DD 58DD 104DD

6 Goal: Predict current (and future) distributions Take laboratory-measured temperature tolerances to develop GDD calculations Take laboratory-measured temperature tolerances to develop GDD calculations Obtain climate data to estimate number of generations possible within a region of interest Obtain climate data to estimate number of generations possible within a region of interest Determine if the predicted range overlaps with the known distribution Determine if the predicted range overlaps with the known distribution + =

7 Building the distribution model Take 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 average Spring (Mar-Apr)Summer (May-Aug)

8 Testing the distribution model: spring distributions Data source: Journey North All records: Mar-Apr

9 Testing the distribution model: summer distributions Data source: NABAAverage observations: July 1 year 35 year

10 Modeling the distribution of the sachem butterfly using mechanistic models The sachem butterfly (Atalopedes campestris) recently expanded its range into Washington state. The sachem butterfly (Atalopedes campestris) recently expanded its range into Washington state. Winter temperatures had been rising in the area 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 Ries 1, Jessica Turner 1, Lisa Crozier 2, and Thomas Mueller 1 Leslie Ries 1, Jessica Turner 1, Lisa Crozier 2, and Thomas Mueller 1 1 University of Maryland 1 University of Maryland 2 NOAA NW Fisheries Center 2 NOAA NW Fisheries Center

11 Summer recruitment Recruitment predictions are based on growing degree days 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) 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 Number of growing degree days necessary for a single generation was estimated at 417 Predicted generations: Predicted number of generations based on NOAA weather station data ( average)

12 Overwinter survival Predicted rates of overwinter survival are based on mean January temperature Predicted rates of overwinter survival are based on mean January temperature Predicted overwinter survival based on NOAA weather station data ( average) Predicted survival:

13 Predicted growth rates The model predicts lambda based on summer recruitment and overwinter survival The model predicts lambda based on summer recruitment and overwinter survival Clearly, the scaling of the model predictions seem off… Clearly, the scaling of the model predictions seem off… Predicted lambda based on NOAA weather station data ( average) Predicted lambda:

14 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 Predicted lambda: Observed abundances:

15 Another study showing the sachem increasing in MA * GDD models have historically focused on cold limitations rather than physiological detriments of excessive heat

16 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 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) 38C (100.4F), 40C (104F), 42C (107.6F), 44C (111.2F) and a control (30C, 86F) First, Third, Fifth instars exposed First, Third, Fifth instars exposed Exposed for 1, 2, 4, or 6 days Exposed for 1, 2, 4, or 6 days Nighttime temperatures were kept at 25C Nighttime temperatures were kept at 25C Larvae were reared to determine survivorship rates and total development time (in degree days) Larvae were reared to determine survivorship rates and total development time (in degree days)

17 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 3 rd and 5 th instars) Survivorship is very low overall at 42C No individuals in the 44C treatment survived

18 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)

19 So how should GDD be calculated? DZmin = 11.5C (52.7F) DZmax = 31.5C (88.7F) ? Sub-lethal and lethal effects ?

20 Mapping out lethal and sub-lethal zones: Average from 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

21 Preference and performance relative to mean number of days >38C Mean number of days with temps >38C In zones where caterpillars are more likely to experience sub-lethal temperatures, there appears to be less development

22 But climate differs from year to year – so did temperature really drive those patterns? Accumulated sub- lethal degree days: 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

23 Relationship between development and accumulated sub-lethal degree days n=518 n=267 n=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?

24 Understanding monarch population dynamics is critical for their conservation Notable population patterns: Notable population patterns: Eastern monarchs may be declining, but examining different life stages suggests different patterns Eastern monarchs may be declining, but examining different life stages suggests different patterns Monarch populations show large fluctuations from year to year Monarch populations show large fluctuations from year to year Underlying mechanisms Underlying mechanisms REGIONAL CONNECTIONS: How do dynamics in one phase of the migratory cycle influence dynamics in subsequent phases? 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? ENVIRONMENTAL INFLUENCE: How much do environmental factors influence the connection between these phases? SUMMER MONITORING DATA WINTER MONITORING DATA

25 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 North started ‘99 Monarch Larvae Monitoring Project started ‘99 WWF-Mexico started ’96 started tracking overwinter mortality in 2003 N. American Bfly Assoc. started 1975 Ohio BMS started ’96

26 Data Available for Analysis Monarch Larvae Monitoring Project (MLMP) North American Butterfly Association Counts (NABA) Ohio Butterfly Monitoring Scheme (OH) Mexican sites WWF: Mexico

27 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

28 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 1 st gen eggs that are recorded? Mexican sites

29 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 1 st generation arrivals in the northern regions?

30 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 1 st generation adults / 2 nd generation eggs predict numbers in subsequent generations?

31 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?

32 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. 1 st gen eggs in south to 2 nd gen eggs NorthMigrant adults in south to 1 st gen adult arrivals r=0.5 p=0.13r=0.69 p=0.12

33 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. N-East: r=0.899 p=<0.0001r=0.85 p=0.004 r= p=<0.0001r=0.73 p=0.005 N-Central:

34 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)

35 Patterns based on simple climate metrics aren’t informative

36 Meaningful patterns emerge when patterns are evaluated in a multiple regression framework

37 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

38 Could climate impact the phenological linkage between milkweeds and monarchs Data source: Journey North

39 Arrival dates

40 Arrival mismatches are leading to at least anecdotal incidents of egg loading

41 Take home messages Climate is impacting butterfly populations 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 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. 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!!! So THANK YOU!!!

42 Questions?


Download ppt "Tracking butterfly responses to climate change using citizen science data Leslie Ries University of Maryland, Biology National Socio-environmental Synthesis."

Similar presentations


Ads by Google