Biology subjects

Skrotzki, J.

Publications and source records attributed to Skrotzki, J..

3 recordsLinked to original sources

bioRxiv2026

The Effects of Mean Temperature and Diurnal Temperature Range on West Nile Virus Transmission

Temperature is a major driver of arbovirus transmission, and a changing climate is expected to affect this process significantly. Most experimental studies rely on constant temperatures and overlook realistic daily temperature fluctuations that impact vector-pathogen interactions. The nonlinear relationship between temperature and vector traits responsible for pathogen transmission suggests that daily fluctuating temperatures produce phenotypes important for transmission distinct from those at constant temperatures. Here, we tested whether realistic variations in mean temperature and diurnal temperature range (DTR) influence West Nile virus (WNV) transmission. We experimentally infected colonized Culex tarsalis with WNV-infectious blood meals and maintained them under constant and fluctuating temperature regimes. We quantified how temperature, DTR, and incubation time shaped several outcomes (infection, dissemination, infectiousness, WNV loads in mosquito saliva and mosquito survival). We also integrated survival and infectiousness probabilities to infer implications for transmission. We observed strong effects of temperature on the WNV infection dynamics, viral loads and mosquito survival. Although the probability of initial infection was similar among all temperature regimes, dissemination and infectiousness were constrained by temperature. Dissemination and infectiousness were highest at 26{degrees}C and reduced at cooler (22{degrees}C) and warmer (30{degrees}C) temperatures. Fluctuating temperatures significantly decreased infection and dissemination probabilities, while the probability of becoming infectious was driven primarily by mean temperature rather than DTR. Mosquito survival probability was temperature dependent, and fluctuating regimes increased mortality risk by 1.95-fold. Integrating mosquito survival and infectiousness dynamics demonstrated that, although at higher temperatures the extrinsic incubation period is shorter, reduced mosquito lifespan can limit viral transmission. Together, these results indicate that overall WNV transmission is affected by temperature-dependent viral dynamics and host physiological constraints. Fluctuating temperature regimes significantly delay viral dissemination within the host, especially at the optimal temperature (26{degrees}C). Measurement of infection outcomes under constant temperatures treatments may lead to over/under estimation of transmission parameters in epidemiological models, therefore integrating fluctuating temperature treatments into mechanistic models of transmission can improve estimates of when and where WNV transmission is most likely to occur.

ecology↗

bioRxiv2026

Humidity shapes the thermal niche of Anopheles stephensi,an invasive malaria vector

Vector-borne pathogens cause 17% of all human infectious diseases, and rising global temperatures are shifting the distribution and abundance of mosquito vectors. Because mosquitoes are ectotherms, temperature strongly governs biological rates and physiology; however, mosquitoes also experience other environmental factors that may interact with temperature to shape the thermal performance of traits driving population dynamics. Here, we use a factorial life-table experiment spanning five relative humidities (30-90%) and seven temperatures (16-38{whitebullet}C) to show that humidity modifies the thermal performance of key fitness traits in adult Anopheles stephensi, an invasive urban malaria vector. When integrated into a demographic model, humidity markedly reshapes projections of population fitness relative to temperatureonly models, suppressing growth and contracting year-round suitability in hot, arid regions while enhancing fitness in more humid or high-elevation climates characteristic of South Asia and Africa. Together, these results highlight the need to integrate multiple environmental drivers into projections of climatic suitability, as temperature-only approaches may mischaracterize both the magnitude and spatial structure of mosquito population fitness. More broadly, our findings demonstrate how moisture availability reshapes thermal niches, population fitness, and climate-driven projections of vector distributions.

ecology↗

bioRxiv2025

Field-validation of multiple species distribution models shows variation in performance for predicting Aedes albopictus distributions at the invasion edge

Climate and land use changes have resulted in range expansion of many species. In this shifting disease landscape, it is important to leverage tools that can predict the potential distributions of invading vectors to target surveillance and control efforts and identify at risk populations. Species Distribution Models (SDMs) are widely used to predict ranges of invasive species; however, invasive species often violate assumptions of equilibrium and niche conservatism. Moreover, these studies are rarely validated using independent data. Here, we use long-term mosquito surveillance data for Aedes albopictus, a highly invasive mosquito capable of transmitting several arboviruses, at its range-edge to evaluate a variety of SDMs (MaxEnt, GAM, Random Forest, Boosted Regression Tree) in predicting Ae. albopictus range. We identify key environmental drivers of distributions and areas where models tended to disagree in predicting occurrence. At sites where models disagree, we sampled for Ae. albopictus to generate an independent dataset for field-validation of models in addition to the common practice of cross-validation. Finally, we determine if models based on early invasion data can predict later stage invasion ranges. We found that landscape and climatic variables are important drivers of population distributions. SDM methods varied in predictive accuracy between models and across validation methods (i.e. cross-vs. field-validation). GAM and MaxEnt best predicted later-stage invasion distributions, requiring fewer years of training data. Our work shows that SDMs can be useful tools to predict the ranges of invasive species and highlights the importance of comparing predictions of invasive species range. Author SummaryMosquitoes are greatly impacted by their surrounding environment. Environmental changes such as those driven by climate change or changes in land use (i.e. urbanization, etc.) can have profound impacts on mosquito ranges. Species distribution models (SDMs), which use the occurrence data of a species in combination with environmental data (e.g., landscape characteristics, temperature, etc.) to estimate suitable habitats for the species, are helpful tools to understand how species ranges can change with the environment through time and space. There are many different species distribution models to choose from - each with different methods for estimating suitable habitat - making it important to compare the performance of different models. Furthermore, because invasive species often violate assumptions of SDMs, it is important to rigorously explore how different methods perform when predicting invasive species ranges in newly invaded areas. In this study, we tested the predictive accuracy of different species distribution models, and we found it varied across modeling and validation method. We also tested whether models could use early-stage invasion data to predict the late-stage invasion distributions of Ae. albopictus. We found that some modeling methods performed well while others needed more data to improve accuracy of late-stage invasion range predictions. In summary, when modeling species ranges using SDMs, it is important to use multiple methods and compare results because methods will likely disagree, and further sampling may be required to determine which model is most accurate.

ecology↗