Performing Department
Ecology & Evolutionary Biology
Non Technical Summary
Climate change is affecting many insect species, including those of major agricultural and conservation interest. Understanding the ability of insect populations to adapt to changing environments is important for assessing and predicting the varied effects climate change will have, and will permit better informed resource management decisions. This work focuses specifically on the question of how seasonal adaptation in insects may (or may not) be responding to climate change.Virtually all economically important species, including pollinators and pests, use seasonal cues during development to "pre-adapt" to future conditions, allowing them to physically and behaviorally optimize themselves for specific seasons. As the climate changes, however, these insects face the challenge of retuning their environmental response norms in order to ensure expression of their proper seasonal forms at the proper times. It is the purpose of this work to advance our basic understanding of how, and to what extent, insect populations can adapt their environmental response mechanisms to changing climates. There are three components to this work: (1) A survey of historical insect collections in the context of climate data to assess how environmental responses have been changing over time, (2) a survey of current insect populations across a latitudinal gradient to determine how, and to what extent, populations of the same species can genetically adapt to extremely different climates, and (3) genetic mapping work to identify regions of the insect genome that control seasonal variation. This work will provide an important initial baseline for modeling the effects of climate change on insect populations, especially in regions with dramatic seasonal variation.
Animal Health Component
0%
Research Effort Categories
Basic
90%
Applied
0%
Developmental
10%
Goals / Objectives
Objective 1: How has J. coenia seasonal coloration changed over the last 100 years in New York?Using museum specimens and climate data from the last 100 years, we aim to determine how the expression of environmentally-induced coloration has changed over time, and how this change relates to climate.Objective 2: What are the physiological mechanisms underlying variation in seasonal plasticity?To assess how seasonal adaptation is regulated across different climates, we will use butterflies collected in the field along a latitudinal gradient spanning New York, North Carolina, and Florida. Climates in these states vary by temperature and day length, and it is expected that physiological regulation of seasonal color patterns will be affected as well. In these three populations we will assess (1) the extent of regional variation in seasonal plasticity, and (2) differences in hormonal regulation underlying these different response norms.Objective 3: What is the genetic basis of variation in seasonal response norms?Using butterflies from our lab colony, we will study in more detail how butterflies may regulate their plastic response by identifying genomic regions underlying seasonally responsive and non-responsive selection lines.
Project Methods
Objective 1: Change in color plasticity over timeWe will use museum collections to study recent historical changes in color plasticity norms. Because J. coenia is a widespread butterfly, many specimens are available in various natural history collections in New York. We are specifically interested in the collection at the American Museum of Natural History in New York City, as well as the Cornell Insect Collection in Ithaca, New York. We will score wing color according to, and compare this to temperature and day length conditions from two weeks prior (i.e. the critical period of phenotype determination). Thus, we can assess how environment has affected phenotype. Preliminary data suggest that seasonal response norms have evolved over the last 100 years, although we seek more data to better define trends in relation to climate change.Objective 2: Seasonal response along a latitudinal gradientTo assess seasonal response in different conditions, we will use butterflies from three populations along a latitudinal gradient to (1) determine the range of variation in seasonal response norms, and (2) determine associated differences in hormone regulation during development.First, we will establish lab colonies of butterflies from New York, North Carolina, and Florida. It is already known that Florida and North Carolina populations have diverged in their environmental response mechanisms, and we believe that New York populations have as well. We will rear larvae from these different populations under different day length and temperature conditions representing spring and fall, and then measure wing phenotypes in adults in order to quantify responses to these different conditions. Next, we will determine differences in ecdysone hormone regulation between these populations. Earlier work shows that the hormone ecdysone plays a pivotal role in formation of seasonal colors, where a signalling peak is shifted in different seasons. We will assess how this is hormone signal is regulated in populations from different climates. We will use HPLC to measure ecdsyone levels at several time points throughout development, and determine the timing and height of the signaling peak.Next, we will determine whether timing of, or sensitivity to, the ecdysone peak explains regional variation in seasonal response norms. Depending on the results of the first part of this project (i.e. ecdysone measurements), we will perform a series of timed ecdysone injections. If we see a change in timing or height of the ecdysone peak between different populations, we will determine whether this is sufficient to alter phenotype by performing timed injections of an ecdysone analog or an ecdysone inhibitor. Thus, we can change ecdysone regulation in one population to mimic ecdysone regulation in another population, and determine whether this is sufficient to reproduce seasonal phenotypes. If we don't see any change in timing or height of the ecdysone signaling peak in the different populations it could be because either the sensitive period has changed, or the ecdysone responsiveness has changed. We can test the first hypothesis by doing timed injections throughout development and determining when the phenotype will change, and we can test the second hypothesis by increasing the ecdysone level when the signaling peak occurs.Objective 3: Genetic mechanisms underlying seasonal response?In order to determine the genetic basis of a seasonal response we will use selection lines created from our lab colony that are either responsive or unresponsive to environmental variation. This objective has three phases.First, we will determine genomic regions of interest involved in the seasonal response. We have a plastic line (PL), with a tan wing under warm conditions and a red wing under cold conditions, as well as two lines that either constitutively express red (CR), or tan (CT), regardless of conditions. We will conduct a series of full-sib CR x PL and CT x PL crosses and raise F1, F2, and F3 progeny under conditions opposing the phenotype of their C-line grandparent. Wing color will be determined with a spectrometer, and average reflectance will be used to segregate and quantify intermediate, red, and tan phenotypes. These segregated individuals from both crosses will be sequenced. We will map these sequences back to our reference genome. Thus, we can identify regions in the genome that vary along with our phenotype of interest (i.e. seasonally responsive or not).Next, we will use gene expression data to determine what genes are differentially expressed during development between the different selection lines, and are thus likely involved in determining a seasonal response. We will rear the selection lines under different conditions, collect wing tissue at several times during development and extract RNA. We will sequence RNA and map these reads back to our reference transcriptome. Then we will determine which genes are differentially expressed between different lines under the different conditions, and thus assess which genes are potentially involved in generating the different phenotypes.Last, we will combine our genomic and expression data. By determining which differentially expressed genes are located in the genomic regions of interest found in the mapping component the objective, we can identify genes that are likely involved in determining whether an organism is plastic or not.