Data usePhD Thesis
RationaleClimate change and rising temperatures are threatening global biodiversity, with ectotherms potentially particularly vulnerable. Species in low latitudes could suffer significantly as air temperatures are already near their critical thermal limits . To cope with the heat, many species in the tropics must use behavioral thermoregulation, such as seeking cooler microhabitats and changing activity times . It is reasonable then to hypothesize that with rising temperatures, tropical species would spend more time undergoing thermoregulation avoiding heat and lose activity time for foraging and breeding . However, the potential of changing activity time and thermoregulation behaviors in mediating rising temperature have only been discussed theoretically using biophysical models, and has never been explicitly examined in the field.
Meanwhile, deforestation is another threat to biodiversity facing tropical regions. In addition to changing forest structure directly, logging and forest transformation to plantations will also likely create more clearings, increasing forest floor insolation and raising temperatures inside forests . In response to these temperature increases from unlogged to logged forests, species will also likely need to adjust their thermoregulatory behaviors. This behavioral reaction is similar to what we would expected for species under climate change. In this way, comparing species thermoregulation and behavioral plasticity in a logged landscape could provide insights into how species might respond to warming.
We will use butterflies as a focal taxa. Abundant in the forest, butterfly thermoregulatory behaviors are relatively easy to observe and record in the field, communities as also relatively familiar as from previous studies . Although butterfly communities differ in different habitat, some species persist, By monitoring and comparing diel activity times and behaviors of same species of butterflies across different habitats, we will examine the extent and potential of behavioral plasticity to cope with relatively fast changing thermal environments, and what it means for tropical ectotherms under climate change.
MethodsField sampling: We will sample butterflies within two habitat types: old growth forest (OG1) and fragmented forest (from A-F), for each habitat type, we chose 4-5 locations are replicates and select one transect within each locations. In each habitat, we will walk each transect in two consecutive days and use abundance to quantify activity time. We will walk transects at 1 hour intervals at a constant pace (approximately 1km/h) and record butterfly species and numbers that are observed with 2.5m of on each side of the transects. We will also record behaviors of butterflies and micro-habitat they stayed in in detail (behavior: basking/touring/territory/oviposition/resting; microhabitat: in shade/ in sun/near streams).
Only species shared among habitat types are including in our study from a previous published community study in central Kalimantan with similar elevation and forest type. We will consider family Nymphalidae only as they are easy to observe. We will also place data loggers (HOBO UA-002-64) that record temperature and light intensity every 5 min along transects to quantify microclimates in each habitat.
From each habitat, we will also make 5 individual of our focal species into specimens and photograph under same conditions to get morphological information for further biophysical model building (see below).
Biophysical model building and validation: With the assumption that only active individuals will be seen, we will use biophysical models to estimate operative body temperatures of butterflies encountered during transects with behavioral information and microclimate data measured. We here listed 8 focal species that will be monitor and are also likely to occur in both habitats.
Biophysical models were developed and modified by Kingslover (1983) and Bonebrake (2014), and have been validated from butterflies in Hong Kong. Models will also be adjusted to obtain the relationship between light intensity (Lux) to solar radiation (w/h) to account for the difference cause by the latitude difference between Sabah (~5°) and Hong Kong (~22°) with a HOBO U30-NRC weather station.
The biophysical models we use include three behavioral scenarios were modeled for butterflies as: a) Basking, in which a butterfly tries to maximize heat intake in sunlight, heat intake by solar radiation (Rs), radiation reflected by the environment (Re) and air conduction (Ca), heat loss from body radiation(Rb); b) Heat avoidance, in which a butterfly is exposed to directed sunlight but with heat avoidance behavior, heat intake by radiation reflected by the environment (Re) and air conduction (Ca), heat loss from body radiation(Rb); c) Heat avoidance in shade or cloudy weather, in which a butterfly evade from sun, heat intake by air conduction (Ca), heat loss from body radiation(Rb).
Statistical analysis: We will compare air temperature, time spent in each microhabitat and activity time among three habitat types, and combine operative body temperature using biophysical models to project how butterflies might cope with future climate change given behavioral plasticity measured in this study.