PROJECT SUMMARY

Overview:Understanding how species evolve in response to environmental change is of broad theoretical andapplied interest. The Hawaiian avian malaria system is an exceptional model for studying co-evolutionarydynamics of parasite, hosts and vectors because they are all strongly affected by a steep environmentalgradient of decreasing temperature with increasing elevation. The introduced Culex quinquefasciatus isthe only competent vector of Plasmodium relictum, the agent of avian malaria in Hawaii. Avian malariacauses high mortality in native Hawaiian birds that results in strong selection for disease tolerance orresistance, which is already apparent in some native species. In addition, although American strains ofCx. quinquefasciatus arrived first, preliminary analyses suggest an Australasian strain introduced laterenabled transmission of P. relictum in Hawaii. Importantly, hosts and vectors can exert selection on theparasite for changes in virulence. Until recently, methods for determining mechanisms of parasitevirulence, host disease tolerance/resistance and vector refractoriness have been broadly unfeasible, butadvances in sequencing technologies have revolutionized the field. The objectives of this study are: 1)Characterize the genomic signatures of parasites, hosts and vectors at different elevations replicatedacross islands; 2) Perform common-garden experiments and experimental infections to assess differencesin competence or virulence among strains of vectors and parasites, respectively; 3) Integrate Aims 1 and2 in predictive models of the impact of co-evolutionary changes on vector-borne disease transmissionunder current and future climate scenarios. We will use comparative genomics and transcriptomics atmultiple spatial, temporal and experimental scales, and combine Susceptible-Infected-Resistant (SIR)models with evolutionary game theory to capture the reciprocal influence of changing populations.

Intellectual Merit:One of the major challenges in predicting disease risk in dynamic infectious disease systems isunderstanding how the system can change over evolutionary time based on the adaptive potential of thehosts, vectors, and parasite, and on external forces such as climate change. The Hawaiian honeycreepersare a group of closely related but spectacularly divergent passerine birds that have been decimated by theintroduction of P. relictum and Cx. quinquefasciatus to Hawaii. Many species are now on the brink ofextinction, but a few have recently evolved varying degrees of resistance or tolerance to the disease. Wepropose to generate one of the first comprehensive datasets detailing the evolutionary potential of themajor players in a complex multi-host disease system. We will integrate this unprecedentedunderstanding of the hidden evolutionary aspects underpinning avian malaria dynamics into a modelingframework that addresses how the system can change over space and time. In doing so we will provide anoriginal abstract mathematical tool for predicting long-term co-evolutionary dynamics in a host-vector-parasite/pathogen system.

Broader Impacts:The research proposed here has ramifications for mitigation of anthropogenic impacts associated withinvasive species and climate change, and can be translated directly into practical managementrecommendations. We find that the public readily appreciates adaptation to virulent parasites, allowingfor a better general comprehension of the outcomes of evolutionary and climate change. The academicinstitutions involved have a successful record of research, outreach and teaching. Sixteen high school,undergraduate and graduate students will be supported by the project, either integrated in researchprojects in the lab or field or by attending programs designed to bring high school students fromdisadvantaged local schools (primarily from Hawaii) to remote forest bird sanctuaries. The PIs willbroadly disseminate results through K-12, cooperative extension and adult education, and outreach viaexhibits, print and electronic media. Two collaborators are high school teachers that will develop web-based video tutorials and associated teaching materials on applications of mathematical models toepidemiology, evolutionary biology, invasive species, and wildlife conservation. For cultural andeconomic reasons, there is widespread public interest in how organisms can rapidly evolve in response todisease and/or climate. Our work will inspire the next generation of scientists to pursue biologicalresearch, while also being accessible to the general public.

TABLE OF CONTENTSFor font size and page formatting specifications, see GPG section II.B.2.

Total No. of Page No.*Pages (Optional)*

Cover Sheet for Proposal to the National Science Foundation

Project Summary (not to exceed 1 page)

Table of Contents

Project Description (Including Results from Prior

NSF Support) (not to exceed 15 pages) (Exceed only if allowed by aspecific program announcement/solicitation or if approved inadvance by the appropriate NSF Assistant Director or designee)

References Cited

Biographical Sketches (Not to exceed 2 pages each)

Budget (Plus up to 3 pages of budget justification)

Current and Pending Support

Facilities, Equipment and Other Resources

Special Information/Supplementary Documents(Data Management Plan, Mentoring Plan and Other Supplementary Documents)

Appendix (List below. )

(Include only if allowed by a specific program announcement/solicitation or if approved in advance by the appropriate NSFAssistant Director or designee)

Appendix Items:

*Proposers may select any numbering mechanism for the proposal. The entire proposal however, must be paginated.Complete both columns only if the proposal is numbered consecutively.

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Fig. 1. Changes in prevalence of Plasmodium infection in three honeycreeper species along elevation transects in Hawaii (redrawn from Samuel et al 20155). This graph summarizes patterns of exposure to malaria but not the abundance of each bird species. Amakihi are abundant at low elevation, whereas Apapane are rare and Iiwi non-existent.

D. PROJECT DESCRIPTION Conceptual Framework Vector-borne disease dynamics are driven by interactions among environmental, host, vector and parasite characteristics that can vary across space and change over time due to evolutionary processes. Selection pressures experienced by hosts and vectors depend on the disease risk in a given location, which fluctuates with environmental factors such as climate, ultimately influencing disease dynamics in ways that are challenging to predict1-3. To understand disease dynamics in a changing world, it is necessary to understand the interaction between environmental, ecological and evolutionary processes in hosts, parasites and vectors. The transmission of the introduced avian malaria parasite, Plasmodium relictum, by the introduced mosquito Culex quinquefasciatus among Hawaiian honeycreepers is an excellent system to examine environmental influences on host-vector-pathogen co-evolution. In Hawaii, elevational gradients on each island generate gradients in vector abundance and P. relictum prevalence4-

7 and provide an elegant replicated natural experiment. P. relictum is highly virulent in most Hawaiian birds, such as the Iiwi (Drepanis coccinea), which are restricted to high elevations. However, populations of one species, the Hawaii Amakihi (Chlorodrepanis virens) exist at low elevation and most survive infection8,9 (Fig. 1; scientific bird names follow AOU13). Others, like the Apapane (Himatione sanguinea) survive at the cooler intermediate elevations (Fig. 1) where transmission still occurs but is moderate due to smaller vector populations4-7 . Differences among elevations and islands in birds’ response to P. relictum suggest underlying genetic differences8,9 shaped by elevational influences on temperature, vector abundance and parasite development. However, the interplay of evolutionary and ecological factors remains undescribed. Several decades of research in the Hawaiian avian malaria system has quantified many of the host and vector

demographic characteristics14-19 and several models have been developed to predict the effects of climate change on disease dynamics4,5,20. Our proposed research takes advantage of this body of knowledge to examine outstanding problems at the interface of evolution and climate change with implications for public health: We aim to quantify co-evolutionary interactions among parasite, vector and avian hosts along an environmental gradient to build a predictive model of the influence of evolutionary change on disease transmission. The objectives of this study are threefold: 1) Characterize the genomic signatures of parasites, hosts and vectors at different elevations, replicated across other distinct populations; 2) Perform common-garden experiments and experimental infections to assess differences in cold tolerance/competence or virulence among different lineages of the vectors and strains of parasites, respectively; 3) Integrate Aims 1 and 2 in predictive models of the impact of co-evolutionary changes on vector-borne disease transmission under current and future climate scenarios. The strength of the proposed work lies in our extensive experience in this system, in the new genomic resources and modeling methodologies we have developed, and in the multifaceted nature of the research. We will use comparative genomic and transcriptomic approaches at multiple geographic, temporal and experimental scales and combine compartmental Susceptible-Infected-Resistant (SIR) models with models of evolutionary game theory to ultimately capture the reciprocal influence of changing populations of parasites, hosts and vectors over generations. Response to Reviewers’ Comments on 2015 Submission: We were pleased with the enthusiasm of prior reviewers for this proposal. In response to the request for a clearer explanation of how empirical data will be integrated into the modeling framework, we now provide explicit reference throughout the text

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Fig. 2. Current (left) and future (65-80 years from now, right) forest bird number of species based on modeled range and available primary habitat of all extant species. In just 65 years, multiple species per island are projected to go extinct (remnant number of species is summarized by color, from green = 8 species to red = 1 species). From Fortini et al. 201511.

to how specific model parameters will be obtained and expand on the proposed strategy to integrate empirical results with the different modeling approaches in Table 1 in the Research Synthesis section.

Background Studies of avian malaria transmission and epidemiology represent an exceptional model for vector-borne disease, especially human malaria (reviewed in Cox et al. 201022), which is still the deadliest vector-borne disease in the world23. In addition, studies of birds on islands have resulted in some of the best-known illustrations of speciation, biogeography, and adaptation24-27. The Hawaiian honeycreepers are a striking case of adaptive radiation where at least 55 species diversified from a single colonization event28-30. Unfortunately, habitat destruction, introduced predators and diseases have decimated this diverse endemic community. In particular, avian malaria, whose agent is vectored only by introduced Culex quinquefasciatus mosquitoes31-33, has caused dramatic declines and extinctions in many native birds. Most native birds are highly susceptible to avian malaria and are restricted to elevations above the distribution of Cx. quinquefasciatus, a tropical species limited by temperature6. However, some native avian species now occur at lower elevations where disease is seasonal or year-round, suggesting an evolved ability to survive infection, either by reducing the replication of the malaria agent (resistance) or by surviving despite high infection levels (tolerance)34. Specifically, increased survival following malaria infection has been shown experimentally, or inferred from modeling, for the Hawaii and Oahu Amakihi (C. virens and C. flava, respectively, but not the Kauai Amakihi, C. stejnegeri) and Apapane5,8,35. In contrast, the majority of remaining native Hawaiian birds are highly sensitive to avian malaria, restricting them to elevations above the “mosquito zone”, and predicted increases in local temperatures that would drive mosquitoes upslope are forecasted to cause catastrophic extinctions11 (Fig. 2). Research Approach: We propose an integrated approach to examine the roles of parasite, host and vector co-evolution along a climatic gradient of transmission intensity of P. relictum in the Hawaiian Islands. We address a fundamental challenge in predicting disease risk in dynamic infectious disease systems—understanding how the system can change over time based on the adaptive potential of the hosts, vectors, and parasite, and due to external forces, such as climate change. Research Components 2-4 will generate one of the first comprehensive datasets detailing the evolutionary potential of the major players in a complex multi-host vector-borne disease system. We will integrate this unprecedented understanding of the hidden evolutionary aspects underpinning avian malaria dynamics into a modeling framework that addresses how the system can change over space and time. The Hawaiian system provides a unique opportunity for examining disease dynamics in an evolutionary framework because tolerant or resistant avian hosts, multiple strains of the mosquito vector and unique parasite virulence patterns have been observed in the islands. We will develop a modeling framework that combines standard compartmental SIR models and models of evolutionary game theory to capture the influence of changing populations on host, vector and pathogen fitness over generations. Evolutionary

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game theory has a long and rich history of generating fundamental insights into how hosts may evolve resistance to pathogens/parasites34,36-40, or how competing strains/pathogen circulating in a common host population may select for particular patterns of epidemiological characteristics over time41,42. However, these methods have only rarely been leveraged to study co-evolutionary dynamics among hosts, vectors, and pathogens in infectious disease systems (cf.41-45 and references contained therein). We will use this modeling framework to determine the relative effects of genetic vs. environmental parameters on transmission dynamics. This will provide a mathematical framework for predicting long-term co-evolutionary dynamics in a host-vector-parasite/pathogen system over space and time. 1. Modeling host, vector and parasite evolution to predict malaria occurrence in a changing world We will use a combination of traditional SIR and Game Theory models to understand interactions in both ecological (SIR) and evolutionary (Game Theory) time. This model framework will then be applied across spatially realistic landscapes to understand disease dynamics across elevation gradients. We will then simulate changes to disease risk and avian population dynamics likely to occur under various evolutionary or climate change scenarios, broadening the application to other disease-host systems. Questions and Objectives for Research Component 1: 1.i) How do parasite prevalence and population sizes of avian species differ among elevations under realistic evolutionary scenarios determined by the genetic findings in Research Components 2–4? 1.ii) How will host/vector/parasite evolution (e.g., host resistance or tolerance, vector competence, and parasite infectivity or virulence) alter the dynamics of the system? 1.iii) How will projected warming associated with anthropogenic climate change alter host-vector-pathogen co-evolution and transmission dynamics? Methodological Approach for Research Component 1: The SIR Model: We will adapt a well-parameterized and field-tested SIR multi-host-vector model developed for the Hawaiian avian malaria system4 to evaluate interactions among the parasite, the mosquito vector, and 5 Hawaiian forest birds with differing susceptibility to malaria: Kauai, Oahu, and Hawaii Amakihi, Apapane, and Iiwi. We will model juvenile and adult Susceptible (S), Infected (I), and Recovered (R) individuals of each host species, and Unexposed (Um), Exposed (Em), and Infectious (Im) adult mosquitoes.

Mosquitoes

Juvenile Birds Adult Birds

In these equations, t and Env are time and environmental conditions in the habitat, respectively. Because the model involves multiple bird species, bird density (B) represents the total density of both age classes for all species, respectively. H, L, and denote the percent of birds (B) that are highly and less infectious, or recovered (regardless of age), respectively, and the transmission probabilities from birds to mosquitoes (c) are subscripted to reflect these levels of infectivity. The model also includes maturation rates for the parasite developing in the mosquito vector ( ), and juvenile birds ( ). In our model natural

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birth and death rates will be included as population projections in the game-theory portion of our models. Therefore, new individuals are introduced here only by the terms, and , of mosquitoes and birds, respectively, calculated as part of intrinsic growth (part of below). Because the probability of a successful blood meal may vary, we include a dilution term (g) to reduce the bite rate by up to 50% as ; we can also vary the transmission probability from mosquitoes to birds (q), the disease-induced avian mortality rate ( ), and the avian recovery rate (γ) as needed. Field and experimental data from past research, and Components 2–4 of this proposal will allow us to fully parameterize the model and explore the range of variation in the system (see Research Synthesis). The Game Theory (using SIR) Model: We will use the SIR model as part of a larger, game theoretic evolutionary model that will integrate host, vector, and parasite ecology (as influenced by climatic variables) with epidemiological dynamics over time as all populations are allowed to evolve. Our approach uses the SIR disease dynamics with the empirical ecological and genetic data (generated from Components 2–4; see Research Synthesis) to project the size of each genotypic group in the next generation as the game theoretic payoffs for each “player” (i.e., host genotype, parasite genotype, or vector genotype) in each habitat patch. Payoffs for the hosts and vectors will be based on observed inter- and intra-group/species ecological interactions as captured by tailoring of the standard N-species generalization of the competitive Lotka-Volterra equations (cf. Levin et al. 200946) in the following way:

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In this formulation, the are the genetic types for each set of species (e.g., all host genotypes in the patch) determined by the genetic analyses described below. The are the competitive interactions among players (neutrally assumed to be 1 unless empirical findings suggest otherwise) and is the carrying capacity in that patch as a function of environmental/climatic habitat conditions (e.g., temperature, rainfall), based for hosts on surveys of breeding birds in largely disease-free areas47,48. Finally, is the intrinsic growth rate for each genetic type i as a function of both the environmental conditions in the patch (Env) and the prevalence of infection (Prev). This dependence of on the prevalence of infection will be the weighted average of survival for individuals in that player group based on their infection status (as determined by challenge studies), where the proportion of individuals of each infection status will be determined by the SIR model above. For the parasite, rather than logistic population growth with competition, we will use the number of new infections caused by that genotype as predicted by the SIR model in that patch at that time, which is the familiar pathogen reproductive ratio Reff. To thus inform the game theoretic model, the SIR model will be stratified to include each host/vector/ parasite genetic type by incorporating a set of equations for each genotype of each species. Infection duration, mortality rate, and fecundity may vary in the hosts; vector competence, survival and fecundity changes may vary in the vector, and replication rate and virulence may vary in the parasite. While we will measure some of these rates in the challenge studies (see below), we will obtain other rates from published data (e.g., Atkinson et al. 20138) and from previous work by our group (e.g., Fonseca and Fleischer, see below, have previously estimated some of the epidemiological transmission probabilities associated with American- or Hawaiian-origin vector genotypes). Despite this, some parameters will still be unknown, and will therefore be estimated by fitting the SIR model to prevalence estimates from proposed and previous research4,5 for each patch by maximum likelihood via iterated particle filtering49. We will also analyze the sensitivity of model projections under different relative rate scenarios to determine how different the epidemiological rates would have to be from our estimates for each player in order to constitute novel co-evolutionary selective pressure on the system. In linking the SIR to the Game Theoretic model in this way, we will have constructed two continuous time models, with potentially different natural rate parameterizations (i.e., SIR models are traditionally formulated over days, weeks, or years, whereas game theory models are traditionally formulated as generations). We will therefore be careful to integrate the game theory model with the SIR model appropriately to ensure the correct relative passage of time in both models. Initially we will characterize patch dynamics in isolation and then incorporate between-patch migration by incorporating arrival and departure rates for each genotypic group in each patch, v, to/from each other:

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where is the size of genotypic group i in patch v, and is the rate of successful migration for genotypic group i from patch v to patch u. We will use this expression to build models linking patches along an elevation/temperature gradient that influences several vector and pathogen parameters. 2. Evolution of the parasite: Variation in Plasmodium genomics and virulence Plasmodium is a group of globally distributed parasites that infect all major terrestrial vertebrate groups, and in birds there is a high degree of species diversity worldwide, with lineages often specializing on particular host taxa50-56. Some Plasmodium lineages appear limited to warmer climates and with predicted warming under future climate scenarios a major constraint to their development may be lifted in cooler regions, allowing the pathogen to invade currently disease-free refugia57,58; in Hawaii this is predicted to cause extinctions of several endemic bird species20. Despite the globally high genetic variation and broad phylogenetic diversity found in most localities worldwide, there has been only one species (P. relictum) and one lineage, GRW4, found in the Hawaiian Islands50. However, genetic variation in this lineage exists in at least one gene involved in evasion of host immune response (TRAP)59, and we propose to perform genomic analyses to more fully assess the extent of variation across the parasite genome. We will implement a synthetic approach to examine genomic variation associated with host resistance, with specific host species, with elevation/temperature, and with changes in virulence in the GRW4 strain that colonized Hawaii. Recently, we developed a 6,000-bait Single Nucleotide Polymorphism (SNP) capture assay to assess variation in neutral markers and functional genes across the genome (McClure, Fleischer, unpubl.; Fig. 3). With this greatly expanded set of genomic markers, and the transcriptome analyses proposed here, we will be able to determine whether cryptic lineages exist that specialize on specific Hawaiian birds or vary by elevation (Ki for each elevation in the game theory model) possibly driven by locally adapted mosquito populations. Although prior experiments using a single lineage of GRW4 found that above 1800m elevation the temperatures are too low for complete sporogony60, (Ki=0), variation in developmental rates (mp and mj in the SIR model) with temperature may vary among low, mid and high elevation GRW4 lineages. In addition, because increases in refractoriness in hosts and/or vectors may influence the evolution of Plasmodium, we will characterize differences among GRW4 strains circulating in areas differing in the proportion of refractory vs. permissive avian hosts. We will also compare isolates of GRW4 from the Old World and elsewhere to ones currently in Hawaii to determine how virulence and genetic variation have changed following introduction to Hawaii. Questions/ Objectives for Research Component 2: 2.i) Is there an association among variants of GRW4 and vector lineages, host species, or host susceptibility? 2.ii) Are GRW4 strains associated with elevation, and do higher-elevation strains contain temperature-associated adaptive diversity?

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Fig. 3. Top: Nucleotide diversity in 76 SNP markers in Big Island (n=5), other Hawaiian Islands (n=5) and non-Hawaiian (n=4 from Sweden, Indian Ocean Islands (IOI), and Bermuda) isolates of P. relictum GRW4 lineage. Lines indicate mean values across each set of isolates, with higher variation in non-Hawaiian and lowest in Big Island isolates. Bottom: Mitogenomic variation within the GRW4 lineage. Hawaiian (and Bermuda) isolates cluster together but differ from IOI.

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2.iii) Do GRW4 strains of P. relictum from different islands and other parts of its range (e.g., Europe, Africa) differ genetically and in their ability to infect and replicate in avian hosts? Methodological Approach for Research Component 2: Using high-throughput sequencing of targeted genes and genome-wide variation, we will infer specific transmission pathways from the mosquito vector through the bird hosts. To do so, we will take a population genomics approach to determine whether vector-associated strains appear in different host species. In parallel, we will identify P. relictum genes that are differentially expressed in the host and the vector to enhance our understanding of the genes involved in successful infection of both (i.e., genes that influence Reff in host/vector). To complement this work, we will examine blood slides for each bird host, and squashes of mosquito guts and salivary glands, to assess life cycle completion across the elevational gradient. Next, we will determine whether there are specific associations between GRW4 strains and elevation. We will also assess genomic differences among GRW4 isolates from different islands and between Hawaii and the mainland to identify and characterize genes that are distinct in sequence or differentially expressed among strains. Sampling: Plasmodium DNA will be obtained from different elevations and Hawaiian Islands and from relevant locations outside Hawaii. Parasite DNA will be extracted simultaneously with that of its bird host or mosquito vector. Plasmodium will also be obtained from infected avian museum specimens. Challenge experiments: We will perform experimental infections of P. relictum to quantify relative measures of virulence of multiple GRW4 strains, including from: 1) low elevations on the island of Hawaii, 2) its upper elevational limit on the island of Hawaii, 3) Oahu (all low-elevation), 4) low-elevations onMaui, 5) Kauai (all low-elevation), 6) its native range in Europe/ Africa, 7) an isolate from French-Polynesia and 8) a closely related Old World non-GRW4 lineage such as SGS1 (P22 in Beadell 200650). The domestic canary (Serinus canaria domestica) will be used as a model first, because it is a cardueline finch (as are Hawaiian honeycreepers); second, prior experiments have shown it is susceptible to Hawaiian GRW4 (Fleischer, Fonseca unpubl.) with variation in parasite load among individuals; third, it is easy to obtain and work with. A complementary challenge study in amakihi is underway, but due to logistical and ethical considerations related to infecting native species, that experiment is limited to testing a single strain of GRW4 in 15 birds. We will assess differences in infection parameters among GRW4 and related strains. Specifically, we will quantify parasitemia, proportion of gametocytes (collectively, contributing to parasite maturation rate in juvenile birds, mj), hematocrit, white blood cell count, and changes to host body weight during the course of infection. Juvenile canaries will be purchased and shipped to the aviaries and screened to ensure no prior infection. These experiments will quantify functional differences within Hawaii and between Hawaiian and other P. relictum lineages. For each challenge, 20 birds will be infected with one of the seven isolates of P. relictum plus a sham-infected control group of 20 birds (180 birds total). Blood will be collected from birds prior to exposure and every two days thereafter. In addition to assessing replication rate of each strain, we will characterize the transcriptome of P. relictum during the course of infection by either subtracting the avian transcriptome (e.g. Videvall et al. 201561, Sackett & Fleischer unpubl.) from the total (avian + parasite) transcriptome expressed in blood, or mapping to the GRW4 parasite genome we are currently obtaining (see below). If we fail to find variation in virulence among parasite strains we will develop challenges in other species present in Hawaii (e.g. house sparrows (Passer domesticus) or house finches (Haemorhous mexicanus))62. Genomic resources: Our SNP assay (Fig. 3) contains genome-wide markers as well as a suite of coding genes thought to be important in the infection process and in response to temperature stress (e.g., DHFR50,63, TRAP59; msp164; CSP65). We will specifically look for SNPs associated with particular host and vector lineages. We will also use this assay to assess whether unique strains of GRW4 exist, both within and outside of Hawaii (largely using samples that we and others have obtained50,66-70). We will use the GATK pipeline for genomic variants, with P. gallinaceum (McCutchan and Vinetz unpubl.) as a closely related reference and supplementing with the well-annotated P. falciparum reference71. The transcriptome will be assembled with Trinity72, and differential gene expression will be assessed in DESeq73. We will explore gene ontology using the PlasmoDB online database74. Analyses and Synthesis for Research Component 2: For the genome-wide SNP data, we will perform association analyses to determine whether certain parasite strains or SNPs are associated with host tolerance or resistance, host species, or mosquito genotypes. We may observe host specialization of

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certain strains; alternatively, it may be the case that all strains infect the vector, but only certain strains can be effectively transmitted from the vector to the native avian hosts—such that the vector acts as a sieve for genetic diversity of the pathogen (as seen in WNV75 and human malaria76). We will use multiple association methods in parallel, validating any signal of association in order to minimize false inference. For gene expression data, we will employ gene ontology analyses to characterize which types of genes are most heavily regulated during the host- and vector-infection process. These will be compared to available online resources for other Plasmodium lineages (e.g., http://plasmodb.org) to ascertain the degree of conservation of infection genes. We will assay temporal changes in Plasmodium genomic diversity in our samples of bird museum specimens from the 1940s on, and of temporally collected samples from our previous fieldwork (1986– 2014) to determine whether allele frequencies have changed during the period during which the evolution of host tolerance occurred. Additionally, we will strive to sample mosquitoes housed at the Bishop Museum to obtain P. relictum genomic information from early strains. Collectively, these complementary approaches will allow us to determine whether GRW4 is characterized by neutral and/or functional variation across islands, elevation, vector and host species, and its extensive range. 3. Evolution of the host: Genomic mechanisms of malaria response across avian hosts and spaceThe high malaria-associated mortality in native Hawaiian bird species7,77-79 is an extraordinarily strong selective force, suggesting that signatures of selection in avian genomes should be evident80. Traits under strong selection, including disease resistance, often enable the most straightforward detection of selection events81,82 and the evolution of resistance or tolerance to malaria in humans are among the best examples83. In the Hawaiian honeycreepers, the Amakihis exhibit mixed morbidity in response to infection by GRW4, with contemporary low elevation populations showing greatly reduced mortality relative to their high elevation counterparts5,8 leading several authors to suggest increased immunogenetic capacity against the malaria agent9,84,85. Amakihi populations currently occur across the islands in habitats from wet forests at sea level to dry/mesic shrublands at >2000m elevation, encountering a wide range of O2 levels and climatic conditions. In contrast, the Apapane is less abundant at low elevations and shows an intermediate response to malaria infection, and the Iiwi is largely restricted to high elevations and suffers very high mortality from GRW4 infection5,86. Each species thus has its own disease-induced mortality rate ( in the SIR model) and recovery rate (γ) estimated from challenge experiments8,77,78,86,87. Juveniles of all species disperse farther within than across elevations92, and populations show genetic structure across elevations9, suggesting that honeycreepers may have become adapted to local conditions. Because both disease presence and other biotic and abiotic factors vary by elevation, we can study both aspects of natural selection with replication among related species and different island populations (Fig. 4). Importantly, we can also assay temporal change in host genotypes to dissect host responses to selective forces. Avian malaria was apparent in the islands no more than ~80 years ago (Fleischer et al. unpubl.), and so could only have exerted selective pressure since the 1930s. Comparison of genomic variants from museum specimens collected prior to 1930—of which there are dozens to hundreds from each species across the islands—will allow identification of genes that have changed since introduction of the disease. Conversely, genomic responses to climate should be evident in both pre-malaria avian genomes as well as those collected more recently, allowing us to infer genes important for adaptation to local

Fig 4. Collection sites for 3 Amakihi species on 5 islands; phylogenetic tree indicates relationships and divergence times in Chlorodrepanis.

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environments. Genomic regions identified as important in malaria susceptibility will be validated by sequencing these candidate regions in birds with known survivorship outcome from experimental Plasmodium challenges as part of an ongoing parallel study with collaborators (Paxton, Sackett, Atkinson, Fleischer, unpubl.). Questions / Objectives for Research Component 3: 3.i) Are genomic responses to selection consistent or divergent (i.e., parallel or convergent evolution) across replicate lineages with known evolutionary relationships? 3.ii) Do genomic signatures differ between response to disease and response to climate? 3.iii) Are there differences among species in their genomic signatures of response to avian malaria? Methodological Approach for Research Component 3: We are taking a comprehensive approach to identify adaptive responses of Hawaiian honeycreepers to both avian malaria and climatic conditions. We are currently analyzing genomic differences between 6, and transcriptomic differences between 2, low- and high-elevation amakihi populations on the island of Hawaii that have had limited gene exchange since the introduction of malaria9,14,88. These populations differ in the proportion of highly/less infectious (H and L, respectively, in the SIR model) and recovered (Rtot) birds (B), which we will estimate from existing and ongoing experimental challenges and fieldwork89,90, including from this proposal. We will assess adaptation in different honeycreeper species, subspecies, and geographically distinct populations that occur on five islands isolated for hundreds of thousands to millions of years. This will allow us to assess whether similar adaptations are conferred by consistent or unique genomic mechanisms. To distinguish between response to climate and response to malaria, we will complement our spatial approach in two main ways. First, we will analyze birds from museum collection in our ancient DNA lab as we have successfully done in the past91-93, to evaluate temporal differences between contemporary amakihi and those present before the introduction of malaria9. Incorporation of museum specimens allows direct detection of changes over time. The majority of changes in the genome over the last 80–100 years are likely a response to the strong selective pressure of introduced disease and not to climate, which has changed relatively little over the last century in Hawaii. Second, to confirm that previously identified genomic changes are indeed adaptations to malaria, we will compare the genomes and transcriptomes of survivors and fatalities from ongoing and planned challenge experiments. Experimental challenges are important to validate the role of identified genomic changes as a response to malaria, rather than other selective or demographic forces. Sampling: We will sample geographically distinct sites on the islands of Hawaii, Maui, Molokai, Oahu and Kauai, establishing elevational transects with 3 sites per transect. Mist-nets will be set for one week at each site, and blood will be collected from captured birds by experienced handlers using University of Hawaii IACUC approved protocols for blood sampling. Blood smears will be made to determine infection status and intensity, providing population estimates of Prev for the game theory model, and the remaining blood will be separated into aliquots for DNA and RNA extraction. We will also obtain DNA from our previous collection efforts, which include hundreds of amakihi samples from the island of Hawaii and dozens of samples from other islands from the last ~25 years. We will extract DNA from museum specimens of Amakihi, Apapane and Iiwi collected prior to the introduction of malaria (our Hawaii Amakihi collection contains 14 samples from the 1890s and 12 from the 1940s9. Additional museum specimen samples will be processed in our dedicated Ancient DNA Lab, and Illumina library preparation will follow our successful ancient DNA protocols94-96. Importantly, blood collection enables sampling of host DNA/RNA in addition to DNA/RNA from Plasmodium. Therefore, we will characterize genetic variation and gene expression in P. relictum for each infected bird. Genomic resources: We have developed genomic resources for Hawaiian honeycreepers (Fig. 5), including the genome sequence of a low-elevation Hawaii Amakihi via hybrid assembly of a long read Roche 454 ~2.5x sequence and a ~60x Illumina short-read sequence21. Over 4 million SNPs spread across the genome were identified, of which 400,000 were polymorphic in Amakihi. We used these to develop capture assays with 40,000 baits, each containing 1–2 SNPs. We have used these assays to characterize SNP variation in Amakihi museum specimens sampled prior to the introduction of malaria, with reasonable recovery (10–20%) of SNPs. In addition, we can preferentially target certain genomic regions (e.g., those found to be important in comparisons of modern birds) for enrichment of ancient

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samples. We use the GATK pipeline to select high-quality SNPs and reduce the influence of sequencing error on our inferences. Analyses and synthesis for Research Component 3: We will perform genome-wide association and outlier tests to identify loci associated with a response to natural selection. We will minimize Type I and II error rates97 by employing multiple algorithms to perform FST outlier analysis for detecting loci that are highly divergent across elevations, while controlling for genetic background98. Within populations, selection will be inferred using Tajima’s D99, Dn/Ds and Long Runs of Homozygosity100 and we will use TESS3101 distinguish adaptive from non-adaptive genetic variation. We will focus on loci identified under multiple methods102 with replication and further refinement103 and identify monomorphic regions of the genome possibly associated with selective sweeps.

These analyses are already underway for a subset of amakihi populations on the island of Hawaii (Sackett et al. unpubl). Coding regions will be mapped and selected as candidates for further study. As mentioned, we will use replicated transects across the islands to assess convergence in evolutionary processes. Employing similar methods, we will compare the genomes of low-elevation birds prior to malaria introduction with those of contemporary populations that have evolved in the presence of malaria. Loci that are divergent in these analyses will be candidates for genes related to malaria tolerance. SNPs associated with tolerance will influence both the transition rate from infected to recovered individuals and the transmission probability (c) from birds to mosquitoes in the SIR model. These SNPs are also expected to increase in frequency (i.e., the size of this genotypic group, xi, will increase) each generation in the game theory model. Genotypic data, along with infection prevalence information (Prev, determined above), will contribute to parameterization of ri in the game theory model. In a complementary study (described above), we will also characterize differences between live and dead birds after experimental malaria challenges8. To infer adaptations to climatic factors, we will focus on loci that were highly divergent across elevations but were not significant in temporal comparisons (within the same elevation) and divergent between dead and live birds in the challenge experiments. Resistance or tolerance to malaria may be related to differences in gene expression in addition to genomic variation. We will test for transcriptional differences using RNA-seq with RNA extracted from blood samples collected in the field. Due to the complexity involved in transcriptional work, we will use multiple analytical approaches and within-individual replicates. We will use both reference-guided (using the Hawaii amakihi genome21) and de novo assembly approaches to generate transcriptomes for each species. Each subsequent transcriptome will be sequenced to ≥500X coverage from a subset of all sampled populations on three of the islands (40 birds total). The Tuxedo suite of open-source software (Bowtie, Tophat, Cufflinks104) will be used on a local GenePattern server (Broad Institute105,106). Evolution of the vector: Effects of strain replacement and genomics of vector competence. The pantropical and subtropical southern house mosquito, Culex (Culex) quinquefasciatus Say 1823107, is considered a classic example of worldwide human-assisted range expansion12. Notably, this species is often the primary vector of human periodic filariasis (Wuchereria bancrofti), avian malaria108, and several

Fig. 5. Genomic reconstruction of the Amakihi and Akiapolaau effective population sizes over time using Pairwise Sequentially Markovian Coalescent10 from recent samples. Although the population histories conform to expectations, the algorithm is unable to reconstruct the last ~10,000 years of genomic history due to the lack of phylogenetically informative variants. Inclusion of older specimens from museum collections will address this limitation. Inset: Proportion of heterozygous sites in the Amakihi genome21 across chromosomes (each color; Z at right). Chromosomes 1

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Fig. 6. Results of a Bayesian cluster analysis of multilocus microsatellite genotypes of 735 individuals. Geographic locations of all samples with associated location numbers are shown in the world map. Reproduced from Fonseca et al. 200612.

arboviruses including West Nile virus109,110. Cx. quinquefasciatus belongs to the Cx. pipiens complex, a morphologically homogeneous group of species, subspecies and forms exhibiting a wide array of behaviors and physiologies linked to unique genotypes111-113. Cx. quinquefasciatus shows intraspecific variation in refractoriness, or the ability to resist infection, with the agents of avian malaria114 (Fleischer and Fonseca unpubl. see below) and lymphatic filariasis115,116. Ten years ago, we used a panel of 12 microsatellite loci to examine 28 populations of Cx. quinquefasciatus from across the world (Fig. 6) and found that continental populations of Cx. quinquefasciatus flanking Hawaii (American and Australasian) are genetically differentiated12. Although

historical records pinpoint an original introduction of Cx. quinquefasciatus from the New World (hereafter the ‘American’ strain), we found that currently Hawaiian Cx. quinquefasciatus have an ‘Australasian’ signature. This conclusion is significant because changes in the dynamics of avian malaria in Hawaii might be associated with the arrival of the Australasian strain. Critically, the mechanisms underlying the quasi-replacement of the first strain with the second12 are still unclear. We hypothesize they may be associated with extraordinary insecticidal campaigns in the 1930-40’s developed to control dengue and yellow fever7,117 If Australasian Culex brought in insecticide resistant alleles118 they could have changed the vector competence of local Cx. quinquefasciatus (as proposed by Alout et al 2014119). Indeed, in preliminary experiments we have observed that populations of American Cx. quinquefasciatus are refractory to GRW4 while Hawaiian Cx. quinquefasciatus are highly competent (Fig. 7; Fleischer, Fonseca et al. unpubl.). Unfortunately, at the time, we were unable to test Australasian strains so we do not know if vector competence to Hawaiian GRW4 arose in Hawaii or is simply a characteristic of the Australasian strain. Population genetic analyses of Cx. quinquefasciatus also indicated differences among islands15 while across elevations in the island of Hawaii there were signatures of isolation with unique non-panmictic (temporary) populations at high elevation (~1500m)16. These high elevation temporary populations are likely created by diffusion during warmer periods and were predicted by elevation patterns of temperature and humidity31. Likewise, we have observed a patchwork of genetic mixing associated with temperature in populations of the globally invasive mosquito and latest addition to the Hawaiian fauna, Aedes japonicus japonicus120,121. Further, we have recently successfully developed protocols and reagents to identify metabolic pathways associated with cold tolerance in another mosquito, Ae. albopictus (Armbruster, Fonseca, et al. unpubl.) that we will also test in Cx. quinquefasciatus. Questions/ Objectives for Research Component 4: 4.i) Test vector competence of genetically distinct strains of Cx. quinquefasciatus for Hawaiian GRW4 and related

Fig. 7. Comparison of the susceptibility of two genetically distinct strains of Cx. quinquefasciatus for GRW4. The Hawaiian strain was started from specimens collected in Hilo in 2010. The American strain was started from Florida specimens. The y-axis is the proportion of tested mosquitoes of each strain that became infected.

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Plasmodium strains. 4.ii) What genes or patterns of gene expression differ between competent and refractory Cx. quinquefasciatus? 4.iii) Does Cx. quinquefasciatus competence to Plasmodium GRW4 vary among elevations in Hawaii? Methodological approach for Research Component 4: We are taking a multi-pronged approach to characterize the evolution of Cx. quinquefasciatus as a vector of the Hawaiian GRW4 strain of P. relictum. First, we will experimentally assess the relative vector competence and cold tolerance of Australasian and New World strains of Cx. quinquefasciatus from French Polynesia/Guam and California/Mexico. We will compare them with Hawaiian Cx. quinquefasciatus sampled at low and high elevation (providing estimates of intrinsic growth rate ri and transmission probability to birds (q) for each strain at low and high elevations). Second, we will compare the genome and transcriptome (before and after challenge) of relevant strains and identify genes, gene expression and genetic pathways associated with vector competence or cold tolerance. Third, we will curate these genomic resources, compare them with existing data, and optimize an in-solution capture assay (see below). Fourth, we will perform genomic analyses to understand the global ancestry and putative evolution of Cx. quinquefasciatus in Hawaii. Collections will come from broad sampling across the distribution of the species to enable genome-wide inferences of ancestry, recent evolution among Hawaiian populations, and assessment of genes involved in colonization of new environments. We will identify genes that are differentially expressed at high vs. low elevations and genes that are differentially expressed in GRW4-infected vs. refractory mosquitoes. Sampling: We already have hundreds of specimens of Hawaiian Cx. quinquefasciatus obtained from multiple elevations and islands12,15,16. We will also strive to obtain historical Hawaiian specimens to ascertain whether evolutionary changes can be observed. Of note, we have examined Cx. quinquefasciatus specimens collected in Hawaii in 1919 and 1931 and found they lack the Australasian signature evident in a 1944 specimen12 (all specimens were obtained from the Bishop Museum). Challenge experiments: We will obtain egg masses of Cx. quinquefasciatus from three populations each in Hawaii, French Polynesia/Guam and California/Mexico, representative of the relevant genetic strains. We will create minimally inbred mosquito lines to use in experiments. As experimental controls we will also test GRW4-refractory American Cx. quinquefasciatus from available colonies (Fig. 7). Mosquitoes will be reared in incubators under 12:12 L:D (Light:Dark), 80% RH at 25°C using standard protocols122. First, we will examine cold-tolerance with a standard “chill-response” assay where adults are exposed briefly to 0°C and recovery times are measured123. Next, we will test at least 100 females of each strain against Hawaiian GRW4 (see Research Component 2 for more details regarding Plasmodium strain and infected birds). Groups of 20 females of each mosquito strain will be given simultaneous access to infected blood. After the challenge, engorged female mosquitoes will be kept at 25°C and 70-80% relative humidity for 2 weeks for optimal parasite development. Then, guts and salivary glands will be examined for the presence of oocysts and sporozoites, respectively, and this will inform the rate of transition from exposed (Em) to infectious (Im) mosquitoes for each strain in the SIR model. We will optimize rapid assays to strain-ID each individual female using known fixed microsatellite sequences among mosquito strains12,124 and perform PCRs to confirm infection status and parasite strain125. With this information, we will estimate the mp parameter for each Cx. quinquefasciatus strain. We will then prepare indexed RNA-seq libraries to obtain ≥50X coverage from infected and uninfected Cx. quinquefasciatus. Genomic resources: We have designed an in-solution capture assay targeting 131 rapidly evolving Culex genes obtained from a recent comparison of de novo whole transcriptomes from Cx. pipiens f. pipiens and f. molestus126 using the Cx. quinquefasciatus genome (CpipJ1.3 Johannesburg, South Africa127) as a reference. Of the seven enriched GO terms identified, five terms (chitin metabolic process, chitin binding, serine-type endopeptidase activity, proteolysis and odorant binding) were also enriched along the ‘fly’ branch128 indicating they may represent a genetic ‘core’ for adaptive evolution within the Diptera. To estimate genotyping error rates we included 28 slow-evolving ‘housekeeping’ genes126. Of note, we covered complete exonic and intronic regions for simultaneous investigation of both adaptive and neutral evolution. We now propose to add capture probes for genes involved in insecticide resistance: P450s, alpha and beta esterases, sodium channel, and acetylcholinesterase129 and any additional loci in Culex

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found associated with cold tolerance or refractoriness to Plasmodium. To ensure optimal capture, the assay includes 20,000 120-bp baits, tiling every 40 bp, so that each gene has a final coverage of ~3X. Analyses and synthesis for Research Component 4: First, we will analyze genomic and transcriptomic data from the different strains and from the challenges. For the genes inferred to be differentially associated with cold tolerance and/or refractoriness, we will implement selection tests to assess whether these genes—and which regions of the genes—are under selection in Hawaiian Cx. quinquefasciatus. To do so, we will calculate the ratio of non-synonymous to synonymous mutations along a sliding window. New genes/GO terms identified in these analyses will be added to the capture assay (in-solution capture assays are adaptable, so newly identified targets can easily be added to future improvements of the bait set). Data from the capture assays will be analyzed in the program fastStructure130. An FST-outlier approach will be used to determine which genes are more readily exchanged between lineages versus those under divergent selection. Loci under divergent selection will contribute to mosquito genotypes xi in the game theory model. As in Research Component 3, we will use Tuxedo (Bowtie, Tophat, Cufflinks104) on a local GenePattern server (Broad Institute105,106) to identify genes that are differentially expressed. Research Synthesis The four research components proposed will provide the needed tools to develop a predictive model of a complex vector-borne disease system. In Hawaii, avian hosts vary in their responses to P. relictum across elevation gradients and among islands, likely the result of significant and variable selective pressure. Some variation in transmission is driven by climatic factors such as temperature, but traits of vectors and parasites are not “fixed parameters” and likely are evolving. Our ultimate aim is to describe the genomic characteristics of all components of the system and combine them into a model that predicts co-evolutionary change and its effects on disease dynamics under a changing environment. Table 1 summarizes the different empirical tasks we propose to develop represented by the different section designations, and where they will be incorporated into the different modeling approaches. Table 1. How the empirical work relates to modeling efforts. (The information in each cell refers to the sections of the proposal; Pub Lit = Relying primarily on Published Literature; NA = Not applicable due to scope of question.*Estimates of patterns of abundance will rely on prior ecological studies, along with additional analyses).

Task Parameterize SIR Model to reflect habitat patches/sites

Parameterize Game Theoretic Model for each patch / sampled site

Host Vector Parasite Host Vector Parasite Patterns of abundance

(Elevation, Islands, Climate) 3.ii Pub Lit* 2.ii Initial values taken from Pub Lit and 2.ii

Genomic Variability Across Sites

Avian hosts Not Relevant for

Model Type

3.i, 3.ii NA 2.iVector NA 4.iii 2.iParasite NA NA 2.ii, 2.iii

Parasite Genomics

Host susceptibility Not Relevant for Model Type

2.ii, 2.iii NA 2.ii, 2.iiiVector competence NA 2.ii, 2.iii 2.ii, 2.iii

Parasite Challenge

of Vector Lineages NA 4.i NA NA 4.ii 4.i, 4.iiUsing Avian model 2.iii NA NA 2.iii NA 2.iii

Avian Host Genomics

By parasite Not Relevant for Model Type

3.ii, 3iii NA NA By elevation 3.i, 3.ii NA NA

A logical next step for these models is to work towards integrating them into a GIS framework to provide a spatial representation of anticipated changes in genotype composition/population abundance for both birds and vectors across space. Recently developed down-scaled climate models for 2100 (Hawaiian Regional Climate Model with 1 km spatial resolution for Maui and 3 km spatial resolution for all other islands131,132), which indicate 2.2–3.4 oC change in temperature across the islands, will be used to project changes in the system under predicted climate change effects at each sample site. We will use our game theoretic population projections over time to predict species abundance and relative shifts in the balance of genotypic representation in each of the habitat patches as disease and climatic conditions change. We expect that the results of this proposal may alter the way disease dynamics are modeled. Most available epidemiological models are static systems that do not account for evolution of the host, vector

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or pathogen, despite the awareness that these organisms evolve in response to each other. Avian malaria in Hawaii provides a tractable system for studying the multidimensional influences of evolution on the distribution of disease under present and future climatic conditions. First, both vector and pathogen are distributed in predictable ways—depending on temperature—along a linear gradient in elevation. Second, decades of study provide needed empirical data for reasonable parameterization. Third, each island represents a unique natural experiment, replicating the evolutionary process. We will capitalize on newly available genomic and transcriptomic tools and this elegant natural experiment to inform our understanding of avian malaria dynamics in Hawaii and vector-borne disease in general. Results from Prior Support Award: DEB-1115895 Amount: $1,999,999 Period of Support: 7/1/11–6/31/16 Title: The effect of sociality on transmission and spread of a multi-host pathogen, NSF-EEID. Kilpatrick (PI), Foster (Co-PI) Results: Intellectual Merit—We used theory and data to predict which species will be driven extinct by white-nose syndrome and tested these predictions. We developed novel molecular assays, disease severity metrics, surveillance strategies, and mathematical approaches for analyzing disease dynamics. We quantified seasonal, local, and continental patterns and drivers of disease dynamics during pathogen invasion and establishment, determined drivers of population impacts, and discovered how some species now persist with disease in endemic and emerging regions. Broader Impacts—We trained 30 undergraduate students, 11 graduate students, 3 postdocs, and 4 high school students. We have given 108 presentations, including conference talks, invited university seminars, local and national NPR station interviews, and K-12 classes. Numerous members of our team have participated USFWS working groups for disease management and an NCEAS workshop on disease-induced extinctions. Evidence of Research Products: 39 publications from project including several papers in top tier journals133-171. For PI’s Fonseca, Fefferman, and Fleischer of their respective prior NSF awards the most directly relevant work to this proposal for each of them is the currently ongoing EAGER award: Award: NSF-DEB 1547168, Amount: $130,000 Period of Support: 07/15/2015-06/30/2017 Title: EAGER: New genomic resources and models for predicting evolving vector-borne disease dynamics in a changing world. Fonseca (PI), Fefferman, Fleischer, Kilpatrick, Paxton (Co-PI’s). Results: Intellectual Merit—We developed theory and genomic resources in support of our larger program on understanding the processes and interactions in the Hawaiian avian malaria system. In particular we: (1) developed a method of correlational analysis that can integrate multiple data sources, measured in different scales/dimensions, and allow for insight into the potential different suites of factors likely to influence evolution in coevolutionary biological systems (especially host-pathogen-parasite systems); (2) developed a pipeline for genome assembly for the malaria parasite Plasmodium relictum and analyzed captured Plasmodium libraries from 71 mosquitoes and 105 birds to assay variation within and outside of Hawaii; (3) developed a custom capture array to target 159 adaptive Culex quinquefasciatus genes, successfully tested on 16 individuals; and (4) obtained and used a new, better assembled Hawaiian honeycreeper genome (Hemignathus wilsoni) to re-assemble the amakihi genome. Broader Impacts—We conducted a 3 day workshop in 2015 of all PI’s and postdocs to determine state of knowledge of the Hawaiian malaria system and design new models and research. We have trained two post docs, and given 1 symposium talk and 3 invited seminars. We have one publication submitted and two in prep.

Broader Impacts of the Proposed Work We recognize the urgent need for scientists to incorporate public interest in their research and effectively disseminate our results to broad audiences. The proposed project will help develop the next generation of scientists, while also engaging the public in ways that will create meaningful connections to science. In an era of increasing public scrutiny of science and many voices fighting to be heard on an expanding variety of media outlets, we believe our research on avian malaria and evolutionary responses of vertebrate hosts and vectors will have a receptive audience. Adaptation to climate and disease are tangible ideas that are readily understood by the public, allowing for a better general understanding of the outcomes of evolutionary change. In addition, the results of our research will help us to understand a vexing and complex conservation problem for Hawaiian birds, and potentially lead to successful mitigation of these threats. Our collaborative group integrates broader impacts directly into our research programs in unique ways. Below, we detail how we propose to successfully address several aspects of these impacts.

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Discovery and Education — Our approach to education centers on hands-on and student-centered learning172. The Smithsonian’s Center for Conservation Genomics (CCG) annually trains ~15-25 students and postdoctoral researchers in lab-based genetic work. Students and postdoctoral mentees will be involved in multiple aspects of the research, from sample collection to lab work, data analysis, manuscript preparation, and presentation of results. CCG is a collaborative and supportive environment for developing skills in genetics across taxa. The students and postdoctoral researchers on this project, including those in the collaborating institutions, will be immersed in this creative atmosphere and will be deeply involved in all project aspects. In addition, CCG will host summer interns for this project. Fefferman has a strong history of publishing teaching materials integrating mathematics with biology curricula for use in high school and university settings, and has participated in online course development efforts at Rutgers. Informed by these experiences, Fefferman will continue an ongoing collaboration with two high school teachers, Kathleen Gabric and James Kupetz, nationally recognized and published experts in science education and outreach. Both have excellent records in the production of widely utilized teaching materials in bio-math and computational thinking and have been involved for 8 years in NSF-funded activities to pair researchers with educators to integrate cutting edge science into national curricular goals. This collaboration will produce a set of web-based video tutorials and associated teaching materials ($14K budgeted) on applications of mathematical models to epidemiology, evolutionary biology, invasive species, and wildlife conservation, targeting an educational range from middle-school to advanced-undergraduates; we will make these freely available for public use. Previous STEM-related videos released by or about Fefferman have attracted over 4,000 views on YouTube. These activities will not only increase the visibility for this interdisciplinary work, but will also highlight how basic research can be translated directly into practical management recommendations. Foster emphasizes undergraduate education and training. His undergraduates present their research at national meetings. In peer-reviewed publications over the past three years, the Foster group has had 19 undergraduate and 7 graduate student coauthors, illustrating strong student involvement in publication. At least 4 undergraduates from his lab will work on generating and analyzing genomic data for this project. PI Kilpatrick has a consistent record of involving students in high-impact research, and will train at least two undergraduate students each year and one graduate student during the Plasmodium challenge experiments. PI Fefferman will train a graduate student in game theory modeling approaches, and PI Fonseca, who also has multiple publications with undergraduate and graduate students, will train multiple work-study students in mosquito sampling, experimental challenges, and molecular genetics. Students and postdocs will travel to at least one other PI institution to receive additional training. Participation of Underrepresented Groups — We involve underrepresented groups in our science in several ways, including implementing education programs for native Hawaiian youth, training local students from UH Hilo, and recruiting students from programs designed to increase participation of underrepresented groups. The CCG run by PI Fleischer has an excellent record of providing opportunities for women and minorities in science; currently, the lab comprises 78% women and 41% members from underrepresented groups. Nearly all of the 68 CCG postdoctoral fellows (over half of whom were women) have stayed in academic and research science. As a researcher living in Hawaii, PI Paxton will integrate our research activities into local education, where it may be especially meaningful. He currently works with several youth education programs, including Teaching Change from the Hawaii Science Teachers Association, to bring high school students from disadvantaged local schools to remote forest bird sanctuaries such as Hakalau Forest National Wildlife Refuge. In addition, through Imi Pono, Paxton brings students to the bird banding sites to demonstrate conservation and science in action. Paxton also trains UH Hilo undergraduate and graduate students in banding and other field activities; most are local Hawaiians. PI Foster has an extensive track record in involving students from underrepresented groups in his research: Five of his six prior undergraduate students came from underrepresented groups (3 Hispanics, 2 Native Americans) and he actively recruits from these groups. PI Fonseca has a strong history of training minority students pursuing PhDs in Medical Entomology. One of her former PhD students, then supported by a fellowship in Graduate Assistance in Areas of National Need (GAANN), is currently at James Cook University, Australia. Fonseca is also advising a Latino student veteran of the Iraq war developing his PhD at Rutgers on invasive species ecology. PI Sackett has a history of recruiting underrepresented students, including 3 first-generation college students, veterans and women. The University of South Florida comprises 41% racial minorities, providing opportunities to increase the

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participation of women and students from underrepresented groups in science. Broad Dissemination — The PIs are dedicated to disseminating results to the public and scientific communities through presentations, publications, K–12 and adult education, and outreach via museum and zoo exhibits and television, print, and electronic media. For cultural, economic and health reasons, there is widespread public interest in how organisms can adapt to disease and climate change. This work can inspire the next generation of scientists while being accessible and of interest to the general public. PI Fleischer will continue his substantial outreach efforts as part of his position at the National Zoo, where his program engages the public about current research in zoo activities (e.g., the annual Autumn Conservation Festival), lab tours, K–12 and adult education. The National Zoo attracts roughly 2 million visitors annually, so an exhibit on avian malaria will have substantial public exposure. In addition, Fleischer and Campana will develop a module on pathogens and conservation for a genetics course at the Smithsonian-George Mason University School for Conservation in Front Royal, Virginia. PI Paxton gives numerous talks each year to public groups on the ecology and conservation of Hawaiian forest birds, with a particular focus on the effects of malaria on these species. Audiences for these talks include Hawaii Volcanoes National Park volunteers, public groups like Friends of Hakalau Forest, Rotary Club, U.S. Forest Service Natural History Seminar Series, and local Audubon Society Chapters. We will integrate results from this research into these talks, providing prompt dissemination of research findings. PI Sackett will develop a teaching module that centers on avian malaria in Hawaii for the annual Teaching Controversial Topics Workshop at the University of Colorado (CU). This workshop draws 50–100 high school educators from the Mountain West region, collectively teaching over 4,000 students per year. Teaching modules, scientific presentations and panels are used to discuss best practices for teaching publicly controversial science topics such as climate change and evolution. Many of the lesson plans developed are available online through CU’s Evolution Outreach Committee to an extended audience. In addition, PI Sackett seeks to extend the Evolution Outreach network to USF, to host a similar workshop. PI Fonseca works extensively with the Rutgers Cooperative Extension program on outreach about mosquitoes and disease to professional mosquito control professionals and directly with the public. In 2016 she was featured in “You Bet your Garden” an NPR radio show regarding Zika virus control. She teaches in the Rutgers Environmental Stewards program to develop science-based effective action communities and will develop an additional course on the evolution of vector-borne diseases using the proposed research as the centerpiece. Dr. Fonseca presents at national and international meetings of mosquito control professionals developing collaborative research. In 2013-2015 Fonseca coauthored 6 publications with a mosquito control professional as the first author173-178, is a member of the Zika Action Committees in NJ and NYC. Fonseca maintains a website dedicated to information dissemination and has collaborated with economists to quantify the costs of invasive mosquitoes to Public Health179,180. Benefits to Society — Malaria is among the world’s most important human diseases but despite substantial resources dedicated to its research, many aspects of the evolution of the host, vector, and parasite remain poorly known. Malaria in birds of Hawaii is a model system to study these evolutionary processes, providing exceptional opportunities to examine malaria effects under much more tractable conditions (e.g., small land area; avoiding the challenges of working with human subjects; limited pool of hosts, vectors, and parasites). The avian malaria system will provide insights into how vectors and parasites in human malaria systems may be affected by climate change. Moreover, study of rapid evolution in this system provides substantive merit in its own right. Invasive species and climate change pose considerable threats to native species, and research on malaria in Hawaii allows one to see how rapidly some species can respond to these threats—and what genetic factors contribute to their ability to respond. Can native species adapt to devastating infectious diseases before extinction? This is not just an important scientific question, but one that touches the future existence of many species imperiled by introduced pathogens and climate change.

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9 Foster, J. T., Woodworth, B. L., Eggert, L. E., Hart, P. J., Palmer, D., Duffy, D. C. & Fleischer, R. C. Genetic structure and evolved malaria resistance in Hawaiian honeycreepers. Mol Ecol 16, 4738-4746 (2007).

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