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\begin{document}

\title{Humidity - The Overlooked Variable in Thermal Biology of Mosquito-Borne
Disease}



\author[1]{Joel Brown}%
\author[2]{Mercedes Pascual}%
\author[3]{Michael Wimberly}%
\author[4]{Leah Johnson}%
\author[1]{Courtney Murdock}%
\affil[1]{Cornell University}%
\affil[2]{University of Chicago}%
\affil[3]{University of Oklahoma}%
\affil[4]{Virginia Polytechnic Institute and State University}%


\vspace{-1em}



  
  \date{May 17, 2024}


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\selectlanguage{english}
\begin{abstract}
Vector-borne diseases cause significant financial and human loss, with
billions of dollars spent on control. Arthropod vectors experience a
complex suite of environmental factors that affect fitness, population
growth, and species interactions across multiple spatial and temporal
scales. Temperature and water availability are two of the most important
abiotic variables influencing their distributions and abundances. While
extensive research on temperature exists, the influence of humidity on
vector and pathogen parameters affecting disease dynamics are less
understood. Humidity is often underemphasized, and when considered, is
often treated as independent of temperature even though desiccation
likely contributes to declines in trait performance at warmer
temperatures. This Perspectives explores how humidity shapes the thermal
performance of mosquito-borne pathogen transmission. We summarize what
is known about its effects and propose a conceptual model for how
temperature and humidity interact to shape the range of temperatures
across which mosquitoes persist and achieve high transmission potential.
We discuss how failing to account for these interactions hinders efforts
to forecast transmission dynamics and respond to epidemics of
mosquito-borne infections. We outline future research areas that will
ground the effects of humidity on the thermal biology of pathogen
transmission in a theoretical and empirical framework to improve spatial
and temporal prediction of vector-borne pathogen transmission.%
\end{abstract}%



\sloppy


\textbf{1. Introduction}

Vector-borne parasites are common, important biological enemies of
humans, animals, and plants, transmitted by one living organism to
another. Despite the recent gains in reducing the overall global burden
for parasites like malaria (Gething \emph{et al.} 2010; Bhatt \emph{et
al.} 2015; Ashepet \emph{et al.} 2021), vector-borne diseases still
account for 17\% of all infectious diseases and cause 700,000 deaths in
humans annually (W.H.O. 2020). Livestock and crop systems are also
plagued by vector-borne diseases, which place serious constraints on
agricultural production globally (D\selectlanguage{ngerman}öring 2017; Garros \emph{et
al.}2017), and vector-borne diseases can be devastating in wildlife
populations, particularly when introduced to new areas. Collectively,
tens of billions of dollars are spent every year on control, medical
interventions, and mitigating loss of productivity (Warner 1968;
George\emph{et al.} 2015; Stuchin \emph{et al.} 2016; Aguirre 2017;
Weaver\emph{et al.} 2018).

The dependence of many pathogens on ectothermic arthropod vectors for
transmission means that vector-borne diseases are highly sensitive to
variation in the environment. Arthropod vectors experience a complex
suite of environmental factors, both abiotic (e.g., temperature,
rainfall, humidity, salinity) and biotic (e.g., biological enemies,
inter- and intra-specific interactions, and variation in habitat
quality). These factors vary in their relative effects on organismal
fitness, can synergize (Kleynhans \& Terblanche 2011; Huxley \emph{et
al.} 2021, 2022; Liu \& Gaines 2022), and exert their effects at
different spatial scales (Cohen \emph{et al.} 2016) with important
consequences for the abundance and distribution of arthropod vectors
(Ryan \emph{et al.} 2015; Evans \emph{et al.} 2019), vector population
dynamics (Murdock \emph{et al.} 2017), and pathogen transmission
(Samuel\emph{et al.} 2011; Mordecai \emph{et al.} 2013; Murdock \emph{et
al.}2014a, 2016; Mordecai \emph{et al.} 2017; Huber \emph{et al.} 2018;
Shocket \emph{et al.} 2018b; Tesla \emph{et al.} 2018; Wimberly \emph{et
al.} 2020; Ngonghala \emph{et al.} 2021).

In vector ecology, there has been a strong emphasis on studying the
effects of temperature on mosquito-borne pathogen transmission (reviewed
in Mordecai \emph{et al.} 2019). In addition to temperature, water
availability is another critical abiotic variable influencing ectotherm
biology, and both play important roles determining the distribution and
abundance of ectotherms (Chown \& Nicolson 2004; Deutsch \emph{et
al.}2008; Steiner \emph{et al.} 2008; Kearney \& Porter 2009;
Roura-Pascual\emph{et al.} 2011; Lenhart \emph{et al.} 2015;
Rozen-Rechels \emph{et al.} 2019; González-Tokman \emph{et al.} 2020;
Klink \emph{et al.} 2020) and species richness (Jamieson \emph{et al.}
2012; Calatayud \emph{et al.} 2016; Beck \emph{et al.} 2017; Cardoso
\emph{et al.} 2020; Pilotto\emph{et al.} 2020; Hamann \emph{et al.}
2021). Body temperature has important effects on the rates of enzymatic
processes as well as the structural integrity of cellular membranes and
proteins (Angilletta 2009), while all cellular processes rely on water
as a solvent for biochemical reactions and for trafficking nutrients
into, within, and out of cells (Chown \& Nicolson 2004; Chaplin 2006).
Temperature also affects the amount of desiccation stress an organism
experiences due to the fundamental relationship between ambient
temperature and the amount of water the surrounding air can hold
(Lawrence 2005; Romps 2021). Other fields at the climate-health
interface have explored the effects of wet heat vs dry heat on the
energy budgets of endotherms in the context of human heat stress and
climate change (Buzan \& Huber 2020). We anticipate that variation in
relative humidity is also an important force shaping the thermal
performance of ectotherms, including mosquitoes. Whereas metabolic
theory has been well developed and widely applied in ecology to
understand temperature effects (Brown \emph{et al.} 2004; Dell \emph{et
al.} 2011; Corkrey \emph{et al.} 2016) we currently lack a similar
framework for understanding how humidity and temperature interact to
influence mosquitoes and their pathogens.

In this Perspectives, we explore the effects of humidity on the thermal
performance of mosquito-borne pathogen transmission. We begin by
summarizing what is currently known about how temperature and humidity
affects mosquito fitness, population dynamics, and pathogen
transmission, whilst highlighting current knowledge gaps. We present a
conceptual framework for understanding the interaction between
temperature and humidity and how it shapes the range of temperatures
across which mosquitoes persist and achieve high transmission potential.
We then discuss how failing to account for these interactions across
climate variables hinders efforts to forecast transmission dynamics and
to respond to epidemics of mosquito-borne infections. We end by
outlining future research areas that will ground the effects of humidity
on thermal performance of pathogen transmission in a theoretical and
empirical basis to improve spatial and temporal prediction of
vector-borne pathogen transmission. Such a framework will inform
multiple fields (thermal, disease, and landscape ecology and
epidemiology) and a diversity of vector-borne disease systems (human,
wildlife, domestic animals, and plants).

\textbf{2. The effects of temperature on mosquito population dynamics
and pathogen transmission}

Numerous studies have demonstrated that mosquito-borne pathogen
transmission is both seasonally and geographically limited at various
spatial scales by variation in ambient temperature (e.g., malaria
(Siraj\emph{et al.} 2014; Ryan \emph{et al.} 2015; Villena \emph{et
al.}2022), Zika (Siraj \emph{et al.} 2018; Tesla \emph{et al.} 2018;
Ryan\emph{et al.} 2020a), chikungunya (Johansson \emph{et al.} 2014),
and dengue (Mordecai \emph{et al.} 2017)). The effects of temperature on
ectotherm performance, including mosquito vectors, are typically
non-linear, with performance steadily increasing from zero at a minimum
critical temperature (CT\textsubscript{min}) up to an optimum
temperature (T\textsubscript{opt}), followed by a steep decline towards
the critical thermal maximum (CT\textsubscript{max}) (Fig. 1). The
CT\textsubscript{min} and CT\textsubscript{max} represent the
operational limits for trait performance because temperatures that
exceed their range are not permissive for ectotherm development,
survival, or reproduction (Brown \emph{et al.} 2004; Deutsch \emph{et
al.} 2008; Hoffmann \emph{et al.} 2013; Corkrey \emph{et al.} 2016;
Sinclair \emph{et al.} 2016). These thermal limits in ectotherm
performance are consistent with the metabolic theory of ecology, which
posits that organismal physiological and enzymatic rates will increase
predictably with temperature because of increased efficiency of
biochemical reactions (Huey \& Kingsolver 2019) up to
T\textsubscript{opt}. The steep decline in performance above the
T\textsubscript{opt} is attributed to the declining efficiency of
metabolic processes due to decreases in protein stability as
temperatures increase, eventually resulting in organismal death at the
T\textsubscript{max}. Collectively, this information gives us a Thermal
Performance Curve (TPC), which can be used to infer ecological and
evolutionary outcomes.

Mosquitoes, like other ectotherms, are highly susceptible to changes in
ambient temperature, which demonstrably affects their growth rate
(Tun-Lin \emph{et al.} 2000; Alto \& Juliano 2001; Monteiro \emph{et
al.} 2007; Delatte \emph{et al.} 2009; Paaijmans \emph{et al.} 2013;
Evans \emph{et al.} 2018a; Huxley \emph{et al.} 2022), reproduction
(Carrington \emph{et al.} 2013; Miazgowicz \emph{et al.} 2020),
metabolic rate (Vorhees \emph{et al.} 2013), lifespan (e.g., Alto \&
Juliano 2001; Gunay \emph{et al.} 2010; Christofferson \& Mores 2016;
Miazgowicz \emph{et al.} 2020), biting rate (Afrane \emph{et al.} 2005;
Lardeux \emph{et al.} 2008; Shapiro \emph{et al.} 2017;
Miazgowicz\emph{et al.} 2020), immunity (Suwanchaichinda \& Paskewitz
1998; Murdock \emph{et al.} 2012, 2013, 2014b; Adelman \emph{et al.}
2013; Ferreira \emph{et al.} 2020), and ability to acquire, carry, and
transmit pathogens (Lambrechts \emph{et al.} 2011; Paaijmans \emph{et
al.} 2012; Mordecai \emph{et al.} 2013, 2017; Murdock \emph{et
al.}2014b, 2016; Johnson \emph{et al.} 2015; Shocket \emph{et al.}
2018a, 2020; Tesla \emph{et al.} 2018) in a non-linear, unimodal
fashion. These temperature-trait relationships can vary in overall shape
(e.g., symmetric or asymmetric non-linear relationships) due to
differences in the temperatures that optimize and constrain various
traits, which in combination will determine the predicted thermal
minimum, maximum, and optimum for mosquito fitness, intrinsic growth
rates of mosquito populations, and pathogen transmission (Fig. 1).

Process-based models, which traditionally have relied upon temperature
relationships grounded in metabolic theory, have enhanced our ability to
predict the effects of environmental drivers on spatial and temporal
dynamics of vector-borne disease. Several key biological insights have
resulted from this general approach. First, temperate areas of the world
that currently experience relatively cool temperatures are expected to
increase in thermal suitability for many mosquito-borne diseases with
future climate warming (Siraj \emph{et al.} 2014; Ryan \emph{et
al.}2015; Tesla \emph{et al.} 2018; Ryan \emph{et al.} 2020a), and, in
temperate regions, mosquito-borne pathogens can invade or spread during
the summer in seasonally varying environments (Huber \emph{et al.} 2018;
Ngonghala \emph{et al.} 2021). Secondly, areas that are currently
permissive (near the T\textsubscript{opt}) or warmer than the
T\textsubscript{opt} for transmission are expected to experience a
decline in thermal suitability with future warming (Ryan \emph{et
al.}2015, 2020b; Murdock \emph{et al.} 2016). Third, because mosquito
and pathogen species can have different qualitative and quantitative
relationships with temperature (resulting in different
CT\textsubscript{min}, CT\textsubscript{max}, and T\textsubscript{opt})
(Mordecai \emph{et al.} 2013, 2017, 2019; Johnson \emph{et al.} 2015;
Shapiro \emph{et al.} 2017; Shocket \emph{et al.} 2018a, 2020;
Tesla\emph{et al.} 2018; Miazgowicz \emph{et al.} 2020; Villena \emph{et
al.}2022), shifts in thermal suitability with climate and land use
change could also alter the prevalence and magnitude of mosquito-borne
diseases in a given area (Tesla \emph{et al.} 2018), such as sub-Saharan
Africa (Mordecai \emph{et al.} 2020). Fourth, small variations in
ambient temperature at fine spatial scales can contribute to high
heterogeneity in predicted suitability for pathogen transmission across
various environments (Okech \emph{et al.} 2004; Afrane \emph{et al.}
2005; Paaijmans \& Thomas 2011; Cator \emph{et al.} 2013; Pincebourde
\emph{et al.} 2016; Murdock \emph{et al.} 2017; Thomas \emph{et al.}
2018; Evans\emph{et al.} 2019; Verhulst \emph{et al.} 2020; Wimberly
\emph{et al.}2020), which can have important ramifications for
predicting mosquito-borne pathogen transmission and targeting
interventions (Thomas\emph{et al.} 2018; Wimberly \emph{et al.} 2020).
Finally, disease intervention efforts can also be directly or indirectly
affected by variation in ambient temperature. Various insecticides
(Glunt \emph{et al.} 2014; Akinwande \emph{et al.} 2021),
entomopathogenic fungi (Kikankie \emph{et al.} 2010; Darbro \emph{et
al.} 2011), and\emph{Wolbachia} transinfections (Murdock \emph{et al.}
2014a; Ulrich\emph{et al.} 2016; Ross \emph{et al.} 2017, 2019, 2020;
Foo \emph{et al.} 2019; Gu \emph{et al.} 2022) are thermally sensitive,
indicating that the efficacy and cost of these interventions could vary
seasonally, across geographic regions, and with future climate and land
use change (Parham \& Hughes 2015).

\textbf{3. The effects of humidity on mosquito fitness, population
dynamics, and pathogen transmission}

Spatial and temporal variation in atmospheric moisture has important
implications for an organism's ability to hydroregulate (Box 1).
Hydroregulation is defined as the suite of physiological and behavioral
responses organisms utilize to regulate water balance and tolerate
dehydrating environmental conditions (Chown \& Nicolson 2004; Benoit
2010; Chown \emph{et al.} 2011; Edney 2012; Lucio \emph{et al.} 2013).
The relationship between organismal fitness and optimal hydroregulation
is complex, with significant costs to fitness (e.g., decreased survival
and reproduction) occurring when organisms become dehydrated (Mitchell
\& Bergmann 2016; Anderson \& Andrade 2017) or overhydrated (Chown \&
Nicolson 2004). Insects have a suite of adaptations to conserve water,
like physiological changes in skin or cuticular permeability
(Rajpurohit\emph{et al.} 2008; Wu \& Wright 2015), differential
regulation of urine and feces production (Weihrauch \emph{et al.} 2012;
Durant \& Donini 2019; Durant \emph{et al.} 2021; Lajevardi \emph{et
al.} 2021), and behavioural changes in activity (Kühnholz \& Seeley
1997; Ostwald\emph{et al.} 2016). Insects also can mitigate water loss
by regulating water intake via changes in water utilization, food
sources, and selection of specific habitats (Benoit 2010; Hagan \emph{et
al.} 2018; Bezerra Da Silva \emph{et al.} 2019)). Finally, insects can
also produce water via metabolic processes (Jindra \& Sehnal 1990; Chown
\emph{et al.} 2011). Maintaining water balance is a particular challenge
for blood-feeding (hematophagic) vectors (Kleynhans \& Terblanche 2011;
Chappuis \emph{et al.} 2013), like mosquitoes (Edney 2012), where the
act of taking a blood meal results in overhydration that requires
specialized adaptations for the excretion of water, which in turn
enhances susceptibility to desiccation overall (Benoit \& Denlinger
2010).

Instead of measuring humidity directly (Box 1), many studies use related
variables, like seasonal precipitation or land cover to predict mosquito
population dynamics or pathogen transmission (Johansson \emph{et
al.}2009; Chaves \& Kitron 2011; Soti \emph{et al.} 2012; Chandy
\emph{et al.} 2013; Abdelrazec \& Gumel 2017; Sang \emph{et al.} 2017;
Nosrat\emph{et al.} 2021). Mosquito-borne diseases generally peak
during, or following, periods of highest rainfall (Karim \emph{et al.}
2012; Chowdhury \emph{et al.} 2018; Magombedze \emph{et al.} 2018;
McLaughlin\emph{et al.} 2019). Rainfall can matter as a standalone
variable, since standing water is essential for mosquitoes' ontogenetic
development. However, the effect of precipitation on mosquito population
dynamics and disease transmission can operate through other factors that
covary with precipitation, such as increased humidity and shifts in
temperature that impact mosquito development rates, adult survival and
reproduction, parasite development rates, and mosquito-human contact
rates. The relationship between mosquitoes and precipitation is even
more difficult to discern for mosquito species that develop in
artificial, human watered containers, where complex interactions can
occur between amount of rainfall and access to piped water (Hayden
\emph{et al.} 2010; Padmanabha \emph{et al.} 2010; Schmidt \emph{et al.}
2011; Stewart Ibarra \emph{et al.} 2013; Brown \emph{et al.} 2014; Lippi
\emph{et al.}2018). Similarly, measures of land cover such as the
normalized difference vegetation index (NDVI) have been used to account
for areas too dry for widespread mosquito habitat (Ryan \emph{et al.}
2015). Ultimately, the use of these proxy measures obscures our
understanding of how relative humidity and other environmental variables
affect transmission, which in turn constrains our ability to predict how
mosquito-borne pathogens will respond to future climate and land use
change.

Several studies have demonstrated statistical associations between
humidity and mosquito abundance, as well as vector-borne disease
incidence and prevalence (Mayne 1930; Azil \emph{et al.} 2010;
Chen\emph{et al.} 2010; Buckner \emph{et al.} 2011; Karim \emph{et
al.}2012; Althouse \emph{et al.} 2015; Lega \emph{et al.} 2017; Asigau
\& Parker 2018; Davis \emph{et al.} 2018; Jemal \& Al-Thukair 2018;
Diallo\emph{et al.} 2019; Evans \emph{et al.} 2019; Santos-Vega \emph{et
al.}2022). For example, the sizes of seasonal malaria epidemics in two
cities in India exhibit a clear association with relative humidity (Fig.
2), with a higher correlation than for temperature or rainfall
(Santos-Vega \emph{et al.} 2016). A semi-mechanistic epidemiological
model that incorporates this effect of relative humidity on the
transmission rate parameter accurately predicts the temporal dynamics of
the disease, including the multiyear cycles in the size of seasonal
epidemics (Santos-Vega \emph{et al.} 2016, 2022). Such predictions can
inform mosquito control efforts and targeting prophylaxes. However, the
underlying biology of the relationships that exist between humidity and
these response variables are often assumed and based on a limited number
of empirical studies (summarized in Table 1). Experimental work has thus
far shown generally positive effects of increased relative humidity on
mosquito survival and desiccation tolerance, production and development
of eggs, and mosquito activity (up to 90\% relative humidity). In
contrast, biting rates exhibited increases when conditions are drier and
the effect of humidity on vector competence is less clear (Table 1).

Despite the existing body of research, we still do not have a sufficient
knowledge base for incorporating the effects of humidity into the
current temperature-trait modeling framework. Results from observations
studies cannot necessarily be extrapolated to new locations or into the
future. Further, the effects of humidity on mosquito and pathogen
fitness described by experimental / causation studies are of limited
resolution, typically exploring a limited number of humidity levels and
encompassing only a handful of mosquito species. The need to better
incorporate humidity effects is not unique to vector-borne diseases, but
parallels trends seen in the larger body of ecological work on the
effects of climate variability and climate change on heat health in
ectotherms (van Heerwaarden \& Sgrò 2014; Gunderson \& Stillman 2015).
In the following section, we outline how variation in relative humidity
interacts with temperature to change the thermal performance of
ectothermic vectors and, consequently, pathogen transmission.

\textbf{4. Considering the combined effects of temperature and humidity
on transmission}

The optimal regulation of both body temperature and water balance is
crucial for organismal performance and fitness (Bradshaw 2003). Due to
the fundamental relationship that exists between temperature and the
amount of moisture the air can hold (Fig. 3), variations in both
relative humidity and temperature will alter the degree of moisture
stress ectothermic organisms, like mosquitoes, experience. For a given
amount of atmospheric moisture, warmer temperatures result in higher
saturation vapor pressures that reduce relative humidity and increase
vapor pressure deficit (Fig. 3). Depending on the ambient temperature,
variation in relative humidity can exacerbate or buffer the negative
effects of higher temperature on mosquito fitness and pathogen
transmission. The current manner in which thermal performance of
vector-borne pathogen transmission is conceptualized and empirically
measured does not explicitly account for these effects. Even when
relative humidity is held constant, increases in temperature will
increase the vapor pressure deficit and the evaporative stress an adult
mosquito experiences. Thus, it is currently unclear if the thermal
maximum of a given trait, which is typically an upper lethal limit
(Chown \& Nicolson 2004), is really being driven by temperature effects
on metabolic function or rather is a function of dehydration and water
stress on the organism. Understanding the physiological mechanisms
underpinning mosquito responses to these abiotic constraints will be
critical for predicting how transmission will shift with future
anthropogenic change (Chown \& Gaston 2008; Deutsch \emph{et al.} 2008;
Pörtner \& Farrell 2008; Dillon \emph{et al.} 2010).

We utilize a trait-based approach that leverages a widely used
relative\emph{R\textsubscript{0}} model (Mordecai \emph{et al.} 2013,
2017, 2019; Murdock \emph{et al.} 2017; Shocket \emph{et al.} 2018a,
2020; Tesla \emph{et al.} 2018; Ryan \emph{et al.} 2020b; Wimberly
\emph{et al.} 2020; Villena \emph{et al.} 2022) to present a framework
that outlines the manner in which variation in relative humidity could
influence the thermal performance of vector-borne pathogen transmission
(Figs. 4 \& 5). Overall, we anticipate that variation in relative
humidity could result in significant shifts in the qualitative shape of
the temperature-trait relationship and cause these effects to vary with
mosquito traits. Drawing from the literature on other ectotherms,
insects, and what little we do know for mosquitoes, we outline several
hypotheses for how variation in relative humidity may affect the thermal
performance of mosquito and pathogen traits (Table 2). We anticipate
variation in relative humidity will be important throughout the mosquito
life cycle, with the largest effects at temperatures that approach the
upper thermal limit (\emph{T\textsubscript{max}} ) for a given trait,
with little to no effect of variation in relative humidity on the
predicted thermal minimum (\emph{T\textsubscript{min}} ) (Table 2). This
hypothesis is based on the observation that for a given change in
relative humidity, the corresponding change in vapor pressure deficit
and evaporative stress will be greater at higher temperatures (Figs. 3
\& 4). How variation in relative humidity affects the predicted thermal
optimum (\emph{T\textsubscript{opt}} ) of a given trait will be somewhat
dependent on the specific trait as well as the magnitude of the effect
at warmer temperatures.

The nature and magnitude of the effects of relative humidity and
temperature variation on mosquito and pathogen traits important for
transmission could differ depending on mosquito life stage. One way in
which relative humidity and temperature interact to affect developing
mosquitoes is through the evaporation rate of larval habitat, which is
also determined by the size and surface area of the larval habitat and
rate of water replenishment (Juliano \& Stoffregen 1994). A second type
of interaction could involve altering some intrinsic factor of the
larval environment such as surface tension, microbial growth, or solute
concentration (Juliano \& Stoffregen 1994; Pérez-Díaz \emph{et
al.}2012). Causal evidence from semi-field experiments shows negative
effects of high relative humidity at temperatures near or above the
predicted thermal optimum for \emph{Aedes albopictus} (Mordecai \emph{et
al.} 2017; Murdock \emph{et al.} 2017) on larval survival and the
probability of adult emergence (Murdock \emph{et al.} 2017). One
possibility is that both temperature and water vapor in the atmosphere
will affect the surface tension of aquatic larval habitats. Warm
temperatures and high humidity may cause larval habitats to have too
little surface tension, while cool and dry larval environments may have
too high surface tension (Singh \& Micks 1957; Pérez-Díaz \emph{et
al.}2012), negatively affecting the ability of larval mosquitoes to
breath, access nutrients, and emerge from the pupal stage. In all
likelihood, both types of effect could be important in the field. Thus,
the effects of relative humidity on the rate of evaporation relative to
larval development or shifts in intrinsic conditions of larval habitats
could have substantial effects on the thermal performance curves for
both mosquito development rate (\emph{MDR} ), the probability of egg to
adult survival (\emph{pEA} ), and consequently the intrinsic growth rate
of mosquito populations.

Once adults emerge from the larval environment, variation in relative
humidity could potentially increase or decrease the predicted upper
thermal limit for adult traits that are critical for mosquito population
dynamics and transmission (Fig. 4, Table 2). For example, decreases in
relative humidity at warm temperatures could decrease mosquito survival
(by increasing the per capita daily mortality rate (\selectlanguage{greek}\emph{μ}\selectlanguage{english})) via
increasing desiccation stress (Mayne 1930; Gaaboub \emph{et al.} 1971;
Lyons \emph{et al.} 2014). This, in turn, will decrease the temperatures
at which mosquitoes can survive to become infected and to transmit
vector-borne pathogens. Evidence from other insect systems (Shelford
(1918); Edney \& Barrass (1962); Chown \& Nicolson (2004); Yu \emph{et
al.} (2010)) would predict that decreases in relative humidity at warm
temperatures could also decrease the per capita daily biting rate
(\emph{a}) and production of eggs (\emph{EFD}) by altering mosquito
activity and blood feeding due to shifts in behavior (e.g., utilization
of specific habitats, times of day, or times of season; Dow \& Gerrish
(1970); Gaaboub \emph{et al.} (1971); Provost (1973); Canyon \emph{et
al.} (1999); Drakou \emph{et al.} (2020)) and physiological responses
(e.g., decreased metabolic rate) to increase desiccation resistance or
tolerance (Chown \& Davis 2003; Marron \emph{et al.} 2003). However, the
evidence that does exist for mosquitoes suggests decreases in relative
humidity can actually increase biting rates on hosts (e.g., \emph{Culex
pipiens}, \emph{Ae. aegypti}, \emph{An. quadramaculatus}; Hagan \emph{et
al.} (2018)). It remains unclear if this pattern would persist in the
field for mosquito species that utilize sugar sources for hydration and
nutrition, because nectar-feeding mosquitoes can increase sugar feeding
behavior when environmental conditions are dry (Fikrig \emph{et
al.}2020). Finally, we also anticipate that the development of
mosquito-borne pathogens and parasites, and potentially mosquito
susceptibility to infection, should be affected by variation in relative
humidity under different ambient temperature conditions based on
physiological acclimation responses (Beitz 2006; Liu \emph{et al.}
2016). Aquaporin water channels allow organisms to rapidly move water
(aquaporins) or water and glycerol (aquaglyceroporins) across cellular
membranes to promote cellular function. Mosquitoes utilize aquaporins
and aquaglyceroporins to minimize water loss in desiccating environments
(Liu \emph{et al.} 2011) and to maintain glycerol concentrations to
stabilize proteins when mosquitoes are exposed to high heat
(Tatzel\emph{et al.} 1996; Diamant \emph{et al.} 2001; Deocaris \emph{et
al.}2006; Liu \emph{et al.} 2016). The physiological responses of
mosquitoes to optimally thermo- and hydro-regulate under sub-optimal
temperature and relative humidity environments could also have
consequences for the energy available to developing pathogen (Liu
\emph{et al.} 2016).

\textbf{5: Implications for understanding pathogen transmission and
control in a changing world}

Understanding the respective effects of variation in temperature and
humidity, as well as any interaction between variables, will be critical
for addressing how the regional and global distributions of mosquito
vectors, and the seasonality and intensity of vector-borne pathogen
transmission, will shift in response to future climate and land use
change. Based on the importance of maintaining optimal temperature and
water balance in other organisms, we also argue that variation in
temperature, humidity, and water availability are important selective
determinants driving local adaptation of mosquitoes to various
environments as well as their capacity to respond to future
environmental change. Finally, variation in temperature and humidity
will also likely affect the efficacy, coverage, and cost of disease
control programs.

5.1 Human-mediated environmental change

Human-mediated climate change is resulting in widespread and uneven
changes in global temperature, humidity, and precipitation patterns and
more frequent extreme weather events (IPCC 2021). In addition to climate
warming, regional changes in humidity and precipitation will result in
increased drought in some areas, while others become wetter
(Konapala\emph{et al.} 2020). If mosquitoes and their transmission
cycles are more sensitive to humidity at higher temperatures, then
future increases in wet vs. dry heat may have very different
implications for mosquito populations and pathogen risk. Regional
variation in temperature and relative humidity could have important
implications for both the seasonal timing and peak of vector-borne
disease (Santos-Vega \emph{et al.} 2016, 2022) as well as pathogen
persistence or emergence. For example, it has been suggested that future
temperatures in tropical Africa will exceed the thermal optimum for
malaria and result in reduced transmission (Mordecai \emph{et al.}
2020). However, these tropical regions are characterized by humid heat,
and malaria may persist if the maximum temperature for transmission
increases at high humidity. Similarly, the potential for arboviruses to
expand into warming temperate climates may be greater in regions with
increasing humid heat vs. dry heat, which has not been considered in
current mechanistic model projections of disease risk with various
climate change scenarios {[}e.g., (Ryan \emph{et al.} 2020a, b; Caldwell
\emph{et al.} 2021){]}.

Land-use change is another key human driver affecting mosquito-borne
disease transmission (Baeza \emph{et al.} 2017). For example, urban
landscapes are one of the most rapidly growing land cover types across
the globe (United Nations 2019), with the proportion of people living in
urban environment projected to increase from 55\% to 68\% between now
and 2050. High environmental heterogeneity in urban areas creates
substantial variation in the local microclimates mosquitoes experience,
through differences in temperature, moisture, and wind speed (Stewart \&
Oke 2012). These differences are mediated by the extent of impervious
surfaces, the distribution of vegetation, and the three-dimensional
structure created by buildings and trees. Together, these changes result
in urban heat and dry islands (Heaviside \emph{et al.} 2017) with higher
land surface (Yuan \& Bauer 2007) and near-surface air temperatures
(Coseo \& Larsen 2014) and lower relative humidity (Heaviside \emph{et
al.} 2017; Lokoshchenko 2017; Yang \emph{et al.} 2017; Hao \emph{et
al.}2018) compared to more vegetated landscapes. This fine-scale
variation in mosquito microclimate can have significant implications for
multiple mosquito species (e.g., \emph{Aedes aegypti, Ae. albopictus,
Anopheles stephensi} ) that drive urban outbreaks of diseases (e.g.,
dengue, chikungunya, Zika, and malaria) (Beebe \emph{et al.} 2009;
Stoddard\emph{et al.} 2009; Li \emph{et al.} 2014; Thomas \emph{et al.}
2016, 2017; Murdock \emph{et al.} 2017; Heinisch \emph{et al.} 2019;
Takken \& Lindsay 2019).

Small-scale variation in temperature and relative humidity could also
have important implications for the spatial distribution of risk in
urban environments (Fig 5). Recent studies that combine field
experimentation with direct monitoring of urban microclimates and
mosquito abundance demonstrate that fine-scale variation (e.g.,
individual neighborhoods or city blocks) in both temperature and
relative humidity can have important implications for mosquito life
history, population dynamics, and disease transmission within urban
environments (Murdock \emph{et al.} 2017; Evans \emph{et al.} 2018b,
2019; Wimberly \emph{et al.} 2020). Thus, neighborhoods with a high
proportion of impervious surfaces that experience mean temperatures near
or exceeding the thermal optimum for transmission could experience even
higher decreases in vectorial capacity than what models would predict
from temperature alone, if drier conditions increase desiccation stress
and reduce mosquito survival.

To generalize the effects of changing temperature and humidity across
diverse locations and into the future, it will be necessary to develop a
conceptual framework that incorporates the psychometrics of temperature
and atmospheric moisture with mosquito biology and the natural and built
environments in which transmission occurs. Incorporating the effects of
humidity into hierarchical models and assessment of mosquito population
dynamics and disease transmission will increase the precision of mapping
environmental suitability, both globally and regionally with
human-mediated environmental change, as well as across heterogeneous
human-modified landscapes.

5.2 Local adaptation and capacity to adapt in the future

There is growing interest in the factors driving adaptation of
mosquitoes to local environmental conditions for providing insights into
the long-term responses of mosquito species to future warming. Mosquito
species are composed of an array of locally adapted populations across
their respective ranges. Substantial genetic variation exists in
mosquito species (Holt \emph{et al.} 2002; Fouet \emph{et al.} 2017;
Maffey \emph{et al.} 2020; Pless \emph{et al.} 2020; Yurchenko \emph{et
al.} 2020; Kang \emph{et al.} 2021) and at fine-spatial scales
(Guti\selectlanguage{ngerman}érrez \emph{et al.} 2010; Jasper \emph{et al.} 2019; Matowo\emph{et
al.} 2019; Ayala \emph{et al.} 2020; Carvajal \emph{et al.}2020), with
significant consequences for transmission potential (Azar\emph{et al.}
2017; Palmer \emph{et al.} 2018; Vega-Rúa \emph{et al.}2020). This
genetic variation can interact with local environmental conditions to
impact the capacity of mosquito vectors to transmit human pathogens
(e.g., dengue; Gloria-Soria \emph{et al.} (2017) and chikungunya;
Zouache \emph{et al.} (2014)). Yet, we still do not have a clear
understanding of what environmental factors are driving this
differentiation.

The work that has been done in this area to date has largely focused on
the effects of temperature variation in driving local adaptation of
current mosquito populations (Sternberg \& Thomas 2014; Couper \emph{et
al.} 2021). However, research from the broader field of ectotherms
{[}e.g., reviewed in Rozen-Rechels \emph{et al.} (2019), vertebrates;
Chown \emph{et al.} (2011), insects{]} suggests that selection on
thermal response curves are constrained by other metabolic stressors,
like desiccation stress, as temperatures warm. For example, a study on
94 \emph{Drosophila} species from diverse climates found substantial
variation in the upper thermal limits among species. Further, the
species specific \emph{CT\textsubscript{max}} correlated positively with
increasing temperature in dry environments, with species from hot and
dry environments exhibited higher heat tolerance. However, this
relationship completely disappeared for species inhabiting wet
environments suggesting temperature as a selective force is less
important when humidity is high (Kellermann \emph{et al.} 2012). A
similar study in ectothermic vertebrates (400 lizards), found the
thermal optimum to be more strongly related to ambient precipitation
than to average temperature (Clusella-Trullas \emph{et al.} 2011).
Environmental mean temperature was only found to be predictive of the
lower thermal limit (\emph{CT\textsubscript{min}} )
(Clusella-Trullas\emph{et al.} 2011).

Both common garden and experimental evolution studies, two standard
approaches to measure local adaptation and evolutionary potential of a
particular species, could be incorrectly attributing observed phenotypic
responses to temperature selection when they could be responding to a
combination of energetic effects and moisture stress. This impacts our
ability to accurately characterize thermal response curves of
mosquitoes, as well as their capacity to adapt to future environmental
change. From our conceptual framework outlined above (Fig. 5), we would
predict that the current approach to studying local adaptation, steeped
in metabolic theory of ecology, will be most predictive of mosquito
population responses to future warming in regions of the world that
currently exist below the species specific thermal optima
(\emph{T\textsubscript{opt}} ). However, for mosquito populations that
inhabit environments above their thermal optima, humidity will be an
important determinant of their capacity to respond to future
environmental change. For example, mosquito populations in warm and wet,
humid environments may have less capacity to adapt to future climate
change in a warming and drying environment than what would be predicted
from evolutionary models that consider the effects of temperature alone.
Conversely, mosquito populations that currently live in warm and dry
environments may have a greater capacity to adapt to warming conditions
if they exhibit higher heat tolerance than their counterparts inhabiting
wetter areas of the geographic distribution.

5.3 Controlling mosquito populations and disease transmission

There have been several mechanistic modelling efforts to understand how
regional and seasonal environmental variation will impact the relative
reproductive number of a pathogen, the intensity of human transmission,
and the efficacy of key disease interventions (e.g., Zika;
Ngonghala\emph{et al.} (2021), schistosomiasis; Nguyen \emph{et al.}
(2021)). These studies have, again, focused largely on the effects of
ambient temperature. However, seasonal and regional variation in
humidity and precipitation could extend or shorten the transmission
season and magnify or depress the intensity of epidemics as predicted
from models incorporating the effects of temperature alone (Huber
\emph{et al.}2018; Ngonghala \emph{et al.} 2021). For example, this is
likely to be the case in seasonally dry environments where
mosquito-borne disease transmission tends to be highest during or just
after the rainy season and lowest during the hottest / driest parts of
the season due to seasonal shifts in mosquito habitat, as well as the
effects of temperature and humidity on mosquito and pathogen traits
relevant for transmission.

How variation in humidity affects the efficacy of current and novel
mosquito control interventions also needs to be considered. Many novel
mosquito control technologies involve the mass release of males that
have been sterilized or genetically engineered to pass on traits that
confer either severe fitness costs (i.e., population suppression
approaches; Alphey \emph{et al.} 2010; Wilke \& Marrelli 2012;
Wang\emph{et al.} 2021) or enhanced resistance to human pathogens (i.e.,
population replacement approaches (Wilke \& Marrelli 2015;
Carballar-Lejarazú \& James 2017; Hegde \& Hughes 2017)). For example,
the \emph{w} Mel strain of the symbiont \emph{Wolbachia} can prevent
dengue, chikungunya, and Zika transmission in \emph{Ae. aegypti}(Moreira
\emph{et al.} 2009; Ye \emph{et al.} 2015; Aliota \emph{et al.}2016a,
b). Experimental work has determined that \emph{w} Mel infections are
temperature sensitive, with high temperatures causing reductions
in\emph{Wolbachia} density (Ulrich \emph{et al.} 2016; Ross \emph{et
al.}2017, 2019, 2020; Foo \emph{et al.} 2019; Gu \emph{et al.} 2022) and
temperature variation affects the host-pathogen interaction and the
outcome of infection in \emph{Wolbachia} -infected mosquitoes
(Murdock\emph{et al.} 2014a). Based on the relationship between
temperature and water balance laid out in this paper, further
experiments should examine whether \emph{Wolbachia} infections are
limited by temperature alone or by cellular water availability, and
examine what role mosquito desiccation stress plays in limiting
\emph{Wolbachia} abundance within mosquitoes at varying temperature.

Furthermore, thermal performance differs between insecticide resistant
vectors and their susceptible counterparts, with important implications
for assessing fitness costs associated with insecticide resistance
(Akinwande \emph{et al.} 2021). Thus, insecticide resistant mosquitoes
may have to optimize temperature and water needs across environmental
constraints differently, and therefore be affected by changes in
humidity, with potentially important consequences for population
dynamics, mosquito-pathogen interactions, and transmission. Identifying
these environmental constraints on efficacy and coverage will be
critical for the successful implementation of current and future control
programs (Parham \& Hughes 2015).

\textbf{6: Conclusions and future directions}

Sufficiently understanding the performance of insect vectors within the
natural environmental mosaics where they occur will require
substantially more data on the spatial and temporal complexities in
microclimate, behavioral responses to temperature and humidity change,
plasticity in thermal tolerance traits, and the eco-physiological
mechanisms of vector water balance, coupled with broader understanding
of the general relationships between water and temperature described in
this paper. We have collated these goals into a general framework
incorporating humidity into research questions and temperature-dependent
mechanistic models (Fig. 5 \& Box 2). We intend for the evidence and
theory presented here to be signposts for future research, leading to a
collective broadening in our understanding of insect vectors and how
their responses to climate variables will affect parasite transmission.

\textbf{References}

Abdelrazec, A. \& Gumel, A.B. (2017). Mathematical assessment of the
role of temperature and rainfall on mosquito population
dynamics.\emph{J. Math. Biol.} , 74, 1351--1395.

Adelman, Z.N., Anderson, M.A.E., Wiley, M.R., Murreddu, M.G., Samuel,
G.H., Morazzani, E.M., \emph{et al.} (2013). Cooler Temperatures
Destabilize RNA Interference and Increase Susceptibility of Disease
Vector Mosquitoes to Viral Infection. \emph{PLoS Negl. Trop. Dis.} , 7,
e2239.

Afrane, Y.A., Lawson, B.W., Githeko, A.K. \& Yan, G. (2005). Effects of
Microclimatic Changes Caused by Land Use and Land Cover on Duration of
Gonotrophic Cycles of \emph{Anopheles gambiae} (Diptera: Culicidae) in
Western Kenya Highlands. \emph{J. Med. Entomol.} , 42, 974--980.

Aguirre, A.A. (2017). Changing Patterns of Emerging Zoonotic Diseases in
Wildlife, Domestic Animals, and Humans Linked to Biodiversity Loss and
Globalization. \emph{ILAR J.} , 58, 315--318.

Akinwande, K.L., Arotiowa, A.R. \& Ete, A.J. (2021). Impacts of changes
in temperature and exposure time on the median lethal concentrations
(LC50) of a combination of organophosphate and pyrethroid in the control
of \emph{Culex quinquefasciatus} , say (Diptera: Culicidae). \emph{Sci.
Afr.} , 12, e00743.

Albernaz, D. a. S., Tai, M.H.H. \& Luz, C. (2009). Enhanced ovicidal
activity of an oil formulation of the fungus \emph{Metarhizium
anisopliae} on the mosquito \emph{Aedes aegypti} . \emph{Med. Vet.
Entomol.} , 23, 141--147.

Aliota, M.T., Peinado, S.A., Velez, I.D. \& Osorio, J.E. (2016a). The
wMel strain of \emph{Wolbachia} Reduces Transmission of Zika virus
by\emph{Aedes aegypti} . \emph{Sci. Rep.} , 6, 28792.

Aliota, M.T., Walker, E.C., Yepes, A.U., Velez, I.D., Christensen, B.M.
\& Osorio, J.E. (2016b). The wMel strain of \emph{Wolbachia} reduces
transmission of Chikungunya virus in \emph{Aedes aegypti} . \emph{PLoS
Negl. Trop. Dis.} , 10, e0004677.

Alphey, L., Benedict, M., Bellini, R., Clark, G.G., Dame, D.A., Service,
M.W., \emph{et al.} (2010). Sterile-Insect Methods for Control of
Mosquito-Borne Diseases: An Analysis. \emph{Vector-Borne Zoonotic Dis.}
, 10, 295--311.

Althouse, B.M., Hanley, K.A., Diallo, M., Sall, A.A., Ba, Y., Faye,
O.,\emph{et al.} (2015). Impact of Climate and Mosquito Vector Abundance
on Sylvatic Arbovirus Circulation Dynamics in Senegal. \emph{Am. J.
Trop. Med. Hyg.} , 92, 88--97.

Alto, B.W., Bettinardi, D.J. \& Ortiz, S. (2015). Interspecific Larval
Competition Differentially Impacts Adult Survival in Dengue
Vectors.\emph{J. Med. Entomol.} , 52, 163--170.

Alto, B.W. \& Juliano, S.A. (2001). Temperature Effects on the Dynamics
of \emph{Aedes albopictus} (Diptera: Culicidae) Populations in the
Laboratory. \emph{J. Med. Entomol.} , 38, 548--556.

Anderson, R.C.O. \& Andrade, D.V. (2017). Trading heat and hops for
water: Dehydration effects on locomotor performance, thermal limits, and
thermoregulatory behavior of a terrestrial toad. \emph{Ecol. Evol.} , 7,
9066--9075.

Angilletta, M.J. (2009). \emph{Thermal adaptation: a theoretical and
empirical synthesis} . OUP Oxford.

Ashepet, M.G., Jacobs, L., Van Oudheusden, M. \& Huyse, T. (2021).
Wicked Solution for Wicked Problems: Citizen Science for Vector-Borne
Disease Control in Africa. \emph{Trends Parasitol.} , 37, 93--96.

Asigau, S. \& Parker, P.G. (2018). The influence of ecological factors
on mosquito abundance and occurrence in Galápagos. \emph{J. Vector
Ecol.} , 43, 125--137.

Ayala, A.M., Vera, N.S., Chiappero, M.B., Almirón, W.R. \& Gardenal,
C.N. (2020). Urban Populations of \emph{Aedes aegypti} (Diptera:
Culicidae) From Central Argentina: Dispersal Patterns Assessed by
Bayesian and Multivariate Methods. \emph{J. Med. Entomol.} , 57,
1069--1076.

Azar, S.R., Roundy, C.M., Rossi, S.L., Huang, J.H., Leal, G., Yun,
R.,\emph{et al.} (2017). Differential Vector Competency of \emph{Aedes
albopictus} Populations from the Americas for Zika Virus. \emph{Am. J.
Trop. Med. Hyg.} , 97, 330--339.

Azil, A.H., Long, S.A., Ritchie, S.A. \& Williams, C.R. (2010). The
development of predictive tools for pre-emptive dengue vector control: a
study of \emph{Aedes aegypti} abundance and meteorological variables in
North Queensland, Australia. \emph{Trop. Med. Int. Health} , 15,
1190--1197.

Baeza, A., Santos-Vega, M., Dobson, A.P. \& Pascual, M. (2017). The rise
and fall of malaria under land-use change in frontier regions.\emph{Nat.
Ecol. Evol.} , 1, 1--7.

Bar-Zeev, M. (1957). The Effect of extreme Temperatures on different
Stages of \emph{Aëdes aegypti} (L.). \emph{Bull. Entomol. Res.} , 48,
593--599.

Bayoh, M.N. (2001). Studies on the development and survival
of\emph{Anopheles gambiae} sensu stricto at various temperatures and
relative humidities. Doctoral. Durham University.

Beck, J., McCain, C.M., Axmacher, J.C., Ashton, L.A., Bärtschi, F.,
Brehm, G., \emph{et al.} (2017). Elevational species richness gradients
in a hyperdiverse insect taxon: a global meta-study on geometrid
moths.\emph{Glob. Ecol. Biogeogr.} , 26, 412--424.

Beebe, N.W., Cooper, R.D., Mottram, P. \& Sweeney, A.W. (2009).
Australia's Dengue Risk Driven by Human Adaptation to Climate
Change.\emph{PLoS Negl. Trop. Dis.} , 3, e429.

Beitz, E. (2006). Aquaporin Water and Solute Channels from Malaria
Parasites and Other Pathogenic Protozoa. \emph{ChemMedChem} , 1,
587--592.

Benoit, J.B. (2010). Water Management by Dormant Insects: Comparisons
Between Dehydration Resistance During Summer Aestivation and Winter
Diapause. In: \emph{Aestivation: Molecular and Physiological Aspects} ,
Progress in Molecular and Subcellular Biology (eds. Arturo Navas, C. \&
Carvalho, J.E.). Springer, Berlin, Heidelberg, pp. 209--229.

Benoit, J.B. \& Denlinger, D.L. (2010). Meeting the challenges of
on-host and off-host water balance in blood-feeding arthropods. \emph{J.
Insect Physiol.} , 56, 1366--1376.

Bezerra Da Silva, C.S., Price, B.E. \& Walton, V.M. (2019).
Water-Deprived Parasitic Wasps (\emph{Pachycrepoideus vindemmiae} ) Kill
More Pupae of a Pest (\emph{Drosophila suzukii} ) as a Water-Intake
Strategy. \emph{Sci. Rep.} , 9, 3592.

Bhatt, S., Weiss, D.J., Cameron, E., Bisanzio, D., Mappin, B.,
Dalrymple, U., \emph{et al.} (2015). The effect of malaria control
on\emph{Plasmodium falciparum} in Africa between 2000 and
2015.\emph{Nature} , 526, 207--211.

Bidlingmayer, W.L. (1974). The Influence of Environmental Factors and
Physiological Stage on Flight Patterns of Mosquitoes Taken in the
Vehicle Aspirator and Truck, Suction, Bait and New Jersey Light
Traps.\emph{J. Med. Entomol.} , 11, 119--146.

Bidlingmayer, W.L. (1985). The measurement of adult mosquito population
changes - some considerations. \emph{J. Am. Mosq. Control Assoc.} , 1,
328--248.

Bradshaw, D. (2003). \emph{Vertebrate Ecophysiology: An Introduction to
its Principles and Applications} . Cambridge University Press,
Cambridge.

Brown, J.H., Gillooly, J.F., Allen, A.P., Savage, V.M. \& West, G.B.
(2004). Toward a Metabolic Theory of Ecology. \emph{Ecology} , 85,
1771--1789.

Brown, L., Medlock, J. \& Murray, V. (2014). Impact of drought on
vector-borne diseases -- how does one manage the risk? \emph{Public
Health} , 128, 29--37.

Buckner, E.A., Blackmore, M.S., Golladay, S.W. \& Covich, A.P. (2011).
Weather and landscape factors associated with adult mosquito abundance
in southwestern Georgia, U.S.A. \emph{J. Vector Ecol.} , 36, 269--278.

Buzan, J.R. \& Huber, M. (2020). Moist Heat Stress on a Hotter
Earth.\emph{Annu. Rev. Earth Planet. Sci.} , 48, 623--655.

Calatayud, J., Hortal, J., Medina, N.G., Turin, H., Bernard, R., Casale,
A., \emph{et al.} (2016). Glaciations, deciduous forests, water
availability and current geographical patterns in the diversity of
European \emph{Carabus} species. \emph{J. Biogeogr.} , 43, 2343--2353.

Caldwell, J.M., LaBeaud, A.D., Lambin, E.F., Stewart-Ibarra, A.M.,
Ndenga, B.A., Mutuku, F.M., \emph{et al.} (2021). Climate predicts
geographic and temporal variation in mosquito-borne disease dynamics on
two continents. \emph{Nat. Commun.} , 12, 1233.

Canyon, D.V., Hii, J.L.K. \& Müller, R. (1999). Adaptation of\emph{Aedes
aegypti} (Diptera: Culicidae) oviposition behavior in response to
humidity and diet. \emph{J. Insect Physiol.} , 45, 959--964.

Canyon, D.V., Muller, R. \& Hii J, L.K. (2013). \emph{Aedes
aegypti}disregard humidity-related conditions with adequate
nutrition.\emph{Trop. Biomed.} , 30, 1--8.

Carballar-Lejarazú, R. \& James, A.A. (2017). Population modification of
Anopheline species to control malaria transmission. \emph{Pathog. Glob.
Health} , 111, 424--435.

Cardoso, P., Barton, P.S., Birkhofer, K., Chichorro, F., Deacon, C.,
Fartmann, T., \emph{et al.} (2020). Scientists' warning to humanity on
insect extinctions. \emph{Biol. Conserv.} , 242, 108426.

Carrington, L.B., Armijos, M.V., Lambrechts, L., Barker, C.M. \& Scott,
T.W. (2013). Effects of Fluctuating Daily Temperatures at Critical
Thermal Extremes on \emph{Aedes aegypti} Life-History Traits. \emph{PLOS
ONE} , 8, e58824.

Carvajal, T.M., Ogishi, K., Yaegeshi, S., Hernandez, L.F.T., Viacrusis,
K.M., Ho, H.T., \emph{et al.} (2020). Fine-scale population genetic
structure of dengue mosquito vector, \emph{Aedes aegypti} , in
Metropolitan Manila, Philippines. \emph{PLoS Negl. Trop. Dis.} , 14,
e0008279.

Cator, L.J., Thomas, S., Paaijmans, K.P., Ravishankaran, S., Justin,
J.A., Mathai, M.T., \emph{et al.} (2013). Characterizing microclimate in
urban malaria transmission settings: a case study from Chennai,
India.\emph{Malar. J.} , 12, 84.

Chandy, S., Ramanathan, K., Manoharan, A., Mathai, D. \& Baruah, K.
(2013). Assessing effect of climate on the incidence of dengue in Tamil
Nadu. \emph{Indian J. Med. Microbiol.} , 31, 283--286.

Chaplin, M. (2006). Do we underestimate the importance of water in cell
biology? \emph{Nat. Rev. Mol. Cell Biol.} , 7, 861--866.

Chappuis, C.J., Béguin, S., Vlimant, M. \& Guerin, P.M. (2013). Water
vapour and heat combine to elicit biting and biting persistence in
tsetse. \emph{Parasit. Vectors} , 6, 240.

Chaves, L.F. \& Kitron, U.D. (2011). Weather variability impacts on
oviposition dynamics of the southern house mosquito at intermediate time
scales. \emph{Bull. Entomol. Res.} , 101, 633--641.

Chen, S.-C., Liao, C.-M., Chio, C.-P., Chou, H.-H., You, S.-H. \& Cheng,
Y.-H. (2010). Lagged temperature effect with mosquito transmission
potential explains dengue variability in southern Taiwan: Insights from
a statistical analysis. \emph{Sci. Total Environ.} , 408, 4069--4075.

Chowdhury, F.R., Ibrahim, Q.S.U., Bari, M.S., Alam, M.M.J., Dunachie,
S.J., Rodriguez-Morales, A.J., \emph{et al.} (2018). The association
between temperature, rainfall and humidity with common climate-sensitive
infectious diseases in Bangladesh. \emph{PLOS ONE} , 13, e0199579.

Chown, S.L. \& Davis, A.L.V. (2003). Discontinuous gas exchange and the
significance of respiratory water loss in scarabaeine beetles. \emph{J.
Exp. Biol.} , 206, 3547--3556.

Chown, S.L. \& Gaston, K.J. (2008). Macrophysiology for a changing
world. \emph{Proc. R. Soc. B Biol. Sci.} , 275, 1469--1478.

Chown, S.L. \& Nicolson, S. (2004). \emph{Insect Physiological Ecology:
Mechanisms and Patterns} . OUP Oxford.

Chown, S.L., Sørensen, J.G. \& Terblanche, J.S. (2011). Water loss in
insects: An environmental change perspective. \emph{J. Insect Physiol.}
, 57, 1070--1084.

Christofferson, R.C. \& Mores, C.N. (2016). Potential for Extrinsic
Incubation Temperature to Alter Interplay between Transmission Potential
and Mortality of Dengue-Infected \emph{Aedes aegypti} . \emph{Environ.
Health Insights} , 10, EHI.S38345.

Clusella-Trullas, S., Blackburn, T.M. \& Chown, S.L. (2011). Climatic
Predictors of Temperature Performance Curve Parameters in Ectotherms
Imply Complex Responses to Climate Change. \emph{Am. Nat.} , 177,
738--751.

Cohen, J.M., Civitello, D.J., Brace, A.J., Feichtinger, E.M., Ortega,
C.N., Richardson, J.C., \emph{et al.} (2016). Spatial scale modulates
the strength of ecological processes driving disease
distributions.\emph{Proc. Natl. Acad. Sci.} , 113, E3359--E3364.

Corkrey, R., McMeekin, T.A., Bowman, J.P., Ratkowsky, D.A., Olley, J. \&
Ross, T. (2016). The biokinetic spectrum for temperature. \emph{PLOS
ONE} , 11, e0153343.

Coseo, P. \& Larsen, L. (2014). How factors of land use/land cover,
building configuration, and adjacent heat sources and sinks explain
Urban Heat Islands in Chicago. \emph{Landsc. Urban Plan.} , 125,
117--129.

Costa, E.A.P. de A., Santos, E.M. de M., Correia, J.C. \& Albuquerque,
C.M.R. de. (2010). Impact of small variations in temperature and
humidity on the reproductive activity and survival of \emph{Aedes
aegypti} (Diptera, Culicidae). \emph{Rev. Bras. Entomol.} , 54,
488--493.

Couper, L.I., Farner, J.E., Caldwell, J.M., Childs, M.L., Harris, M.J.,
Kirk, D.G., \emph{et al.} (2021). How will mosquitoes adapt to climate
warming? \emph{eLife} , 10, e69630.

Darbro, J.M., Graham, R.I., Kay, B.H., Ryan, P.A. \& Thomas, M.B.
(2011). Evaluation of entomopathogenic fungi as potential biological
control agents of the dengue mosquito, \emph{Aedes aegypti} (Diptera:
Culicidae). \emph{Biocontrol Sci. Technol.} , 21, 1027--1047.

Davis, J.K., Vincent, G.P., Hildreth, M.B., Kightlinger, L., Carlson, C.
\& Wimberly, M.C. (2018). Improving the prediction of arbovirus
outbreaks: A comparison of climate-driven models for West Nile virus in
an endemic region of the United States. \emph{Acta Trop.} , 185,
242--250.

Delatte, H., Gimonneau, G., Triboire, A. \& Fontenille, D. (2009).
Influence of Temperature on Immature Development, Survival, Longevity,
Fecundity, and Gonotrophic Cycles of \emph{Aedes albopictus} , Vector of
Chikungunya and Dengue in the Indian Ocean. \emph{J. Med. Entomol.} ,
46, 33--41.

Dell, A.I., Pawar, S. \& Savage, V.M. (2011). Systematic variation in
the temperature dependence of physiological and ecological
traits.\emph{Proc. Natl. Acad. Sci.} , 108, 10591--10596.

Deocaris, C.C., Shrestha, B.G., Kraft, D.C., Yamasaki, K., Kaul, S.C.,
Rattan, S.I.S., \emph{et al.} (2006). Geroprotection by
Glycerol.\emph{Ann. N. Y. Acad. Sci.} , 1067, 488--492.

Deutsch, C.A., Tewksbury, J.J., Huey, R.B., Sheldon, K.S., Ghalambor,
C.K., Haak, D.C., \emph{et al.} (2008). Impacts of climate warming on
terrestrial ectotherms across latitude. \emph{Proc. Natl. Acad. Sci.} ,
105, 6668--6672.

Diallo, D., Diagne, C.T., Buenemann, M., Ba, Y., Dia, I., Faye,
O.,\emph{et al.} (2019). Biodiversity Pattern of Mosquitoes in
Southeastern Senegal, Epidemiological Implication in Arbovirus and
Malaria Transmission. \emph{J. Med. Entomol.} , 56, 453--463.

Diamant, S., Eliahu, N., Rosenthal, D. \& Goloubinoff, P. (2001).
Chemical Chaperones Regulate Molecular Chaperones in Vitro and in Cells
under Combined Salt and Heat Stresses*. \emph{J. Biol. Chem.} , 276,
39586--39591.

Dillon, M.E., Wang, G. \& Huey, R.B. (2010). Global metabolic impacts of
recent climate warming. \emph{Nature} , 467, 704--706.

Döring, T.F. (2017). Vector-Borne Diseases. In: \emph{Plant Diseases and
Their Management in Organic Agriculture} , IPM. The American
Phytopathological Society, pp. 107--116.

Dow, R.P. \& Gerrish, G.M. (1970). Day-to-Day Change in Relative
Humidity and the Activity of \emph{Culex nigripalpus} (Diptera:
Culicidae)1. \emph{Ann. Entomol. Soc. Am.} , 63, 995--999.

Drakou, K., Nikolaou, T., Vasquez, M., Petric, D., Michaelakis, A.,
Kapranas, A., \emph{et al.} (2020). The Effect of Weather Variables on
Mosquito Activity: A Snapshot of the Main Point of Entry of
Cyprus.\emph{Int. J. Environ. Res. Public. Health} , 17, 1403.

Durant, A.C. \& Donini, A. (2019). Development of \emph{Aedes
aegypti}(Diptera: Culicidae) mosquito larvae in high ammonia sewage in
septic tanks causes alterations in ammonia excretion, ammonia
transporter expression, and osmoregulation. \emph{Sci. Rep.} , 9, 19028.

Durant, A.C., Grieco Guardian, E., Kolosov, D. \& Donini, A. (2021). The
transcriptome of anal papillae of \emph{Aedes aegypti} reveals their
importance in xenobiotic detoxification and adds significant knowledge
on ion, water and ammonia transport mechanisms. \emph{J. Insect
Physiol.} , 132, 104269.

Edney, E.B. (2012). \emph{Water Balance in Land Arthropods} . Springer
Science \& Business Media.

Edney, E.B. \& Barrass, R. (1962). The body temperature of the tsetse
fly, \emph{Glossina morsitans} Westwood (Diptera, Muscidae). \emph{J.
Insect Physiol.} , 8, 469--481.

Evans, M.V., Hintz, C.W., Jones, L., Shiau, J., Solano, N., Drake,
J.M.,\emph{et al.} (2019). Microclimate and larval habitat density
predict adult \emph{Aedes albopictus} abundance in urban areas.
\emph{Am. J. Trop. Med. Hyg.} , 101, 362--370.

Evans, M.V., Newberry, P.M. \& Murdock, C.C. (2018a). \emph{Carry-over
effects of the larval environment in mosquito-borne disease systems}
.\emph{Popul. Biol. Vector-Borne Dis.} Oxford University Press.

Evans, M.V., Shiau, J.C., Solano, N., Brindley, M.A., Drake, J.M. \&
Murdock, C.C. (2018b). Carry-over effects of urban larval environments
on the transmission potential of dengue-2 virus. \emph{Parasit. Vectors}
, 11, 426.

Ferreira, P.G., Tesla, B., Horácio, E.C.A., Nahum, L.A., Brindley, M.A.,
de Oliveira Mendes, T.A., \emph{et al.} (2020). Temperature dramatically
shapes mosquito gene expression with consequences for mosquito--Zika
virus interactions. \emph{Front. Microbiol.} , 11.

Fikrig, K., Peck, S., Deckerman, P., Dang, S., Fleur, K.S., Goldsmith,
H., \emph{et al.} (2020). Sugar feeding patterns of New York \emph{Aedes
albopictus} mosquitoes are affected by saturation deficit, flowers, and
host seeking. \emph{PLoS Negl. Trop. Dis.} , 14, e0008244.

Foo, I.J.-H., Hoffmann, A.A. \& Ross, P.A. (2019). Cross-Generational
Effects of Heat Stress on Fitness and \emph{Wolbachia} Density
in\emph{Aedes aegypti} Mosquitoes. \emph{Trop. Med. Infect. Dis.} , 4,
13.

Fouet, C., Kamdem, C., Gamez, S. \& White, B.J. (2017). Extensive
genetic diversity among populations of the malaria
mosquito\emph{Anopheles moucheti} revealed by population genomics.
\emph{Infect. Genet. Evol.} , 48, 27--33.

Gaaboub, I.A., El-Sawaf, S.K. \& El-Latif, M.A. (1971). Effect of
Different Relative Humidities and Temperatures on Egg-Production and
Longevity of Adults of \emph{Anopheles (Myzomyia) pharoensis}
Theob.1.\emph{Z. Für Angew. Entomol.} , 67, 88--94.

Garros, C., Bouyer, J., Takken, W. \& Smallegange, R.C. (2017). Control
of vector-borne diseases in the livestock industry: new opportunities
and challenges. In: \emph{Pests and vector-borne diseases in the
livestock industry} , Ecology and Control of Vector-borne Diseases.
Wageningen Academic Publishers, pp. 575--580.

George, T.L., Harrigan, R.J., LaManna, J.A., DeSante, D.F., Saracco,
J.F. \& Smith, T.B. (2015). Persistent impacts of West Nile virus on
North American bird populations. \emph{Proc. Natl. Acad. Sci.} , 112,
14290--14294.

Gething, P.W., Smith, D.L., Patil, A.P., Tatem, A.J., Snow, R.W. \& Hay,
S.I. (2010). Climate change and the global malaria
recession.\emph{Nature} , 465, 342--345.

Gloria-Soria, A., Armstrong, P.M., Powell, J.R. \& Turner, P.E. (2017).
Infection rate of \emph{Aedes aegypti} mosquitoes with dengue virus
depends on the interaction between temperature and mosquito
genotype.\emph{Proc. R. Soc. B Biol. Sci.} , 284, 20171506.

Glunt, K.D., Paaijmans, K.P., Read, A.F. \& Thomas, M.B. (2014).
Environmental temperatures significantly change the impact of
insecticides measured using WHOPES protocols. \emph{Malar. J.} , 13,
350.

González-Tokman, D., Córdoba-Aguilar, A., Dáttilo, W., Lira-Noriega, A.,
Sánchez-Guillén, R.A. \& Villalobos, F. (2020). Insect responses to
heat: physiological mechanisms, evolution and ecological implications in
a warming world. \emph{Biol. Rev.} , 95, 802--821.

Gray, E.M. \& Bradley, T.J. (2005). Physiology of desiccation resistance
in \emph{Anopheles gambiae} and \emph{Anopheles arabienses} . \emph{Am.
J. Trop. Med. Hyg.} , 73, 553--559.

Grimstad, P.R. \& DeFoliart, G.R. (1975). Mosquito Nectar Feeding in
Wisconsin in Relation to Twilight and Microclimate. \emph{J. Med.
Entomol.} , 11, 691--698.

Gu, X., Ross, P.A., Rodriguez-Andres, J., Robinson, K.L., Yang, Q., Lau,
M.-J., \emph{et al.} (2022). A \emph{w} Mel \emph{Wolbachia} variant
in\emph{Aedes aegypti} from field-collected \emph{Drosophila
melanogaster}with increased phenotypic stability under heat stress.
\emph{Environ. Microbiol.} , 24, 2119--2135.

Gunay, F., Alten, B. \& Ozsoy, E.D. (2010). Estimating reaction norms
for predictive population parameters, age specific mortality, and mean
longevity in temperature-dependent cohorts of \emph{Culex
quinquefasciatus} Say (Diptera: Culicidae). \emph{J. Vector Ecol.} , 35,
354--362.

Gunderson, A.R. \& Stillman, J.H. (2015). Plasticity in thermal
tolerance has limited potential to buffer ectotherms from global
warming. \emph{Proc. R. Soc. B Biol. Sci.} , 282, 20150401.

Gutiérrez, L.A., Gómez, G.F., González, J.J., Castro, M.I., Luckhart,
S., Conn, J.E., \emph{et al.} (2010). Microgeographic Genetic Variation
of the Malaria Vector \emph{Anopheles darlingi} Root (Diptera:
Culicidae) from Córdoba and Antioquia, Colombia. \emph{Am. J. Trop. Med.
Hyg.} , 83, 38--47.

Hagan, R.W., Didion, E.M., Rosselot, A.E., Holmes, C.J., Siler, S.C.,
Rosendale, A.J., \emph{et al.} (2018). Dehydration prompts increased
activity and blood feeding by mosquitoes. \emph{Sci. Rep.} , 8, 6804.

Hamann, E., Blevins, C., Franks, S.J., Jameel, M.I. \& Anderson, J.T.
(2021). Climate change alters plant--herbivore interactions. \emph{New
Phytol.} , 229, 1894--1910.

Hao, L., Huang, X., Qin, M., Liu, Y., Li, W. \& Sun, G. (2018).
Ecohydrological Processes Explain Urban Dry Island Effects in a Wet
Region, Southern China. \emph{Water Resour. Res.} , 54, 6757--6771.

Hayden, M.H., Uejio, C.K., Walker, K., Ramberg, F., Moreno, R., Rosales,
C., \emph{et al.} (2010). Microclimate and Human Factors in the
Divergent Ecology of \emph{Aedes aegypti} along the Arizona,
U.S./Sonora, MX Border. \emph{EcoHealth} , 7, 64--77.

Heaviside, C., Macintyre, H. \& Vardoulakis, S. (2017). The Urban Heat
Island: Implications for Health in a Changing Environment. \emph{Curr.
Environ. Health Rep.} , 4, 296--305.

van Heerwaarden, B. \& Sgrò, C.M. (2014). Is adaptation to climate
change really constrained in niche specialists? \emph{Proc. R. Soc. B
Biol. Sci.} , 281, 20140396.

Hegde, S. \& Hughes, G.L. (2017). Population modification
of\emph{Anopheles} mosquitoes for malaria control: pathways to
implementation. \emph{Pathog. Glob. Health} , 111, 401--402.

Heinisch, M.R.S., Diaz-Quijano, F.A., Chiaravalloti-Neto, F., Menezes
Pancetti, F.G., Rocha Coelho, R., dos Santos Andrade, P., \emph{et
al.}(2019). Seasonal and spatial distribution of \emph{Aedes aegypti}
and\emph{Aedes albopictus} in a municipal urban park in São Paulo, SP,
Brazil. \emph{Acta Trop.} , 189, 104--113.

Hoffmann, A.A., Chown, S.L. \& Clusella-Trullas, S. (2013). Upper
thermal limits in terrestrial ectotherms: how constrained are
they?\emph{Funct. Ecol.} , 27, 934--949.

Holt, R.A., Subramanian, G.M., Halpern, A., Sutton, G.G., Charlab, R.,
Nusskern, D.R., \emph{et al.} (2002). The Genome Sequence of the Malaria
Mosquito \emph{Anopheles gambiae} . \emph{Science} , 298, 129--149.

Howe, D.A., Hathaway, J.M., Ellis, K.N. \& Mason, L.R. (2017). Spatial
and temporal variability of air temperature across urban neighborhoods
with varying amounts of tree canopy. \emph{Urban For. Urban Green.} ,
27, 109--116.

Huber, J.H., Childs, M.L., Caldwell, J.M. \& Mordecai, E.A. (2018).
Seasonal temperature variation influences climate suitability for
dengue, chikungunya, and Zika transmission. \emph{PLoS Negl. Trop. Dis.}
, 12, e0006451.

Huey, R.B. \& Kingsolver, J.G. (2019). Climate warming, resource
availability, and the metabolic meltdown of ectotherms. \emph{Am. Nat.}
, 194, E140--E150.

Huxley, P.J., Murray, K.A., Pawar, S. \& Cator, L.J. (2021). The effect
of resource limitation on the temperature dependence of mosquito
population fitness. \emph{Proc. R. Soc. B Biol. Sci.} , 288, 20203217.

Huxley, P.J., Murray, K.A., Pawar, S. \& Cator, L.J. (2022). Competition
and resource depletion shape the thermal response of population fitness
in \emph{Aedes aegypti} . \emph{Commun. Biol.} , 5, 1--11.

Hylton, A.R. (1969). Studies on Longevity of Adult \emph{Eretmapodites
chrysogaster, Aedes togoi} and \emph{Aedes (Stegomyia)
albopictus}Females (Diptera: Culicidae). \emph{J. Med. Entomol.} , 6,
147--149.

IPCC. (2021). \emph{Climate Change 2021: The Physical Science Basis.
Contribution of Working Group I to the Sixth Assessment Report of the
Intergovernmental Panel on Climate Change} . Cambridge University Press,
Geneva, Switzerland.

Jamieson, M.A., Trowbridge, A.M., Raffa, K.F. \& Lindroth, R.L. (2012).
Consequences of Climate Warming and Altered Precipitation Patterns for
Plant-Insect and Multitrophic Interactions. \emph{Plant Physiol.} , 160,
1719--1727.

Jasper, M., Schmidt, T.L., Ahmad, N.W., Sinkins, S.P. \& Hoffmann, A.A.
(2019). A genomic approach to inferring kinship reveals limited
intergenerational dispersal in the yellow fever mosquito. \emph{Mol.
Ecol. Resour.} , 19, 1254--1264.

Jemal, Y. \& Al-Thukair, A.A. (2018). Combining GIS application and
climatic factors for mosquito control in Eastern Province, Saudi
Arabia.\emph{Saudi J. Biol. Sci.} , 25, 1593--1602.

Jindra, M. \& Sehnal, F. (1990). Linkage between diet humidity,
metabolic water production and heat dissipation in the larvae
of\emph{Galleria mellonella} . \emph{Insect Biochem.} , 20, 389--395.

Johansson, M.A., Dominici, F. \& Glass, G.E. (2009). Local and Global
Effects of Climate on Dengue Transmission in Puerto Rico. \emph{PLoS
Negl. Trop. Dis.} , 3, e382.

Johansson, M.A., Powers, A.M., Pesik, N., Cohen, N.J. \& Staples, J.E.
(2014). Nowcasting the Spread of Chikungunya Virus in the
Americas.\emph{PLOS ONE} , 9, e104915.

Johnson, B.J., Manby, R. \& Devine, G.J. (2020). What Happens on
Islands, doesn't Stay on Islands: Patterns of Synchronicity in Mosquito
Nuisance and Host-Seeking Activity between a Mangrove Island and
Adjacent Coastal Development. \emph{Urban Ecosyst.} , 23, 1321--1333.

Johnson, L.R., Ben-Horin, T., Lafferty, K.D., McNally, A., Mordecai, E.,
Paaijmans, K.P., \emph{et al.} (2015). Understanding uncertainty in
temperature effects on vector-borne disease: a Bayesian
approach.\emph{Ecology} , 96, 203--213.

Juliano, S.A. \& Stoffregen, T.L. (1994). Effects of habitat drying on
size at and time to metamorphosis in the tree hole mosquito \emph{Aedes
triseriatus} . \emph{Oecologia} , 97, 369--376.

Kang, D.S., Kim, S., Cotten, M.A. \& Sim, C. (2021). Transcript Assembly
and Quantification by RNA-Seq Reveals Significant Differences in Gene
Expression and Genetic Variants in Mosquitoes of the \emph{Culex
pipiens} (Diptera: Culicidae) Complex. \emph{J. Med. Entomol.} , 58,
139--145.

Karim, Md.N., Munshi, S.U., Anwar, N. \& Alam, Md.S. (2012). Climatic
factors influencing dengue cases in Dhaka city: A model for dengue
prediction. \emph{Indian J. Med. Res.} , 136, 32--39.

Kearney, M. \& Porter, W. (2009). Mechanistic niche modelling: combining
physiological and spatial data to predict species' ranges. \emph{Ecol.
Lett.} , 12, 334--350.

Kellermann, V., Overgaard, J., Hoffmann, A.A., Fløjgaard, C., Svenning,
J.-C. \& Loeschcke, V. (2012). Upper thermal limits of
\emph{Drosophila}are linked to species distributions and strongly
constrained phylogenetically. \emph{Proc. Natl. Acad. Sci.} , 109,
16228--16233.

Kessler, S. \& Guerin, P.M. (2008). Responses of \emph{Anopheles
gambiae} , \emph{Anopheles stephensi} , \emph{Aedes aegypti} ,
and\emph{Culex pipiens} mosquitoes (Diptera: Culicidae) to cool and
humid refugium conditions. \emph{J. Vector Ecol.} , 33, 145--149.

Kikankie, C.K., Brooke, B.D., Knols, B.G., Koekemoer, L.L., Farenhorst,
M., Hunt, R.H., \emph{et al.} (2010). The infectivity of the
entomopathogenic fungus \emph{Beauveria bassiana} to
insecticide-resistant and susceptible \emph{Anopheles
arabiensis}mosquitoes at two different temperatures. \emph{Malar. J.} ,
9, 71.

Kleynhans, E. \& Terblanche, J. (2011). Complex Interactions between
Temperature and Relative Humidity on Water Balance of Adult Tsetse
(Glossinidae, Diptera): Implications for Climate Change. \emph{Front.
Physiol.} , 2, 74.

Klink, R. van, Bowler, D.E., Gongalsky, K.B., Swengel, A.B., Gentile, A.
\& Chase, J.M. (2020). Meta-analysis reveals declines in terrestrial but
increases in freshwater insect abundances. \emph{Science} , 368,
417--420.

Knowles, R. \& Basu, B.C. (1943). Laboratory Studies on the Infectivity
of \emph{Anopheles stephensi} . \emph{J. Malar. Inst. India} , 5.

Konapala, G., Mishra, A.K., Wada, Y. \& Mann, M.E. (2020). Climate
change will affect global water availability through compounding changes
in seasonal precipitation and evaporation. \emph{Nat. Commun.} , 11,
3044.

Kühnholz, S. \& Seeley, T.D. (1997). The control of water collection in
honey bee colonies. \emph{Behav. Ecol. Sociobiol.} , 41, 407--422.

Lajevardi, A., Sajadi, F., Donini, A. \& Paluzzi, J.-P.V. (2021).
Studying the Activity of Neuropeptides and Other Regulators of the
Excretory System in the Adult Mosquito. \emph{JoVE J. Vis. Exp.} ,
e61849.

Lambrechts, L., Paaijmans, K.P., Fansiri, T., Carrington, L.B., Kramer,
L.D., Thomas, M.B., \emph{et al.} (2011). Impact of daily temperature
fluctuations on dengue virus transmission by \emph{Aedes aegypti}
.\emph{Proc. Natl. Acad. Sci.} , 108, 7460--7465.

Lardeux, F.J., Tejerina, R.H., Quispe, V. \& Chavez, T.K. (2008). A
physiological time analysis of the duration of the gonotrophic cycle
of\emph{Anopheles pseudopunctipennis} and its implications for malaria
transmission in Bolivia. \emph{Malar. J.} , 7, 141.

Lawrence, M.G. (2005). The Relationship between Relative Humidity and
the Dewpoint Temperature in Moist Air: A Simple Conversion and
Applications. \emph{Bull. Am. Meteorol. Soc.} , 86, 225--234.

Lega, J., Brown, H.E. \& Barrera, R. (2017). \emph{Aedes
aegypti}(Diptera: Culicidae) Abundance Model Improved With Relative
Humidity and Precipitation-Driven Egg Hatching. \emph{J. Med. Entomol.}
, 54, 1375--1384.

Lenhart, P.A., Eubanks, M.D. \& Behmer, S.T. (2015). Water stress in
grasslands: dynamic responses of plants and insect
herbivores.\emph{Oikos} , 124, 381--390.

Lewis, D.J. (1933). Observations on \emph{Aëdes aegypti} , L. (Dipt.
Culic.) under controlled Atmospheric Conditions. \emph{Bull. Entomol.
Res.} , 24, 363--372.

Li, Y., Kamara, F., Zhou, G., Puthiyakunnon, S., Li, C., Liu,
Y.,\emph{et al.} (2014). Urbanization increases \emph{Aedes
albopictus}larval habitats and accelerates mosquito development and
survivorship.\emph{PLoS Negl. Trop. Dis.} , 8, e3301.

Lippi, C.A., Stewart-Ibarra, A.M., Muñoz, Á.G., Borbor-Cordova, M.J.,
Mejía, R., Rivero, K., \emph{et al.} (2018). The Social and Spatial
Ecology of Dengue Presence and Burden during an Outbreak in Guayaquil,
Ecuador, 2012. \emph{Int. J. Environ. Res. Public. Health} , 15, 827.

Liu, K., Tsujimoto, H., Cha, S.-J., Agre, P. \& Rasgon, J.L. (2011).
Aquaporin water channel AgAQP1 in the malaria vector
mosquito\emph{Anopheles gambiae} during blood feeding and humidity
adaptation.\emph{Proc. Natl. Acad. Sci.} , 108, 6062--6066.

Liu, K., Tsujimoto, H., Huang, Y., Rasgon, J.L. \& Agre, P. (2016).
Aquaglyceroporin function in the malaria mosquito \emph{Anopheles
gambiae} . \emph{Biol. Cell} , 108, 294--305.

Liu, O.R. \& Gaines, S.D. (2022). Environmental context dependency in
species interactions. \emph{Proc. Natl. Acad. Sci.} , 119, e2118539119.

Lokoshchenko, M.A. (2017). Urban Heat Island and Urban Dry Island in
Moscow and Their Centennial Changes. \emph{J. Appl. Meteorol. Climatol.}
, 56, 2729--2745.

Lomax, J.L. (1968). Proceedings. Fifty-fifth annual meeting. New Jersey
Mosquito Extermination Association. A study of mosquito mortality
relative to temperature and relative humidity in an overwintering
site.\emph{Proc. Fifty-Fifth Annu. Meet. N. J. Mosq. Exterm. Assoc.
Study Mosq. Mortal. Relat. Temp. Relat. Humidity Overwintering Site} .

Lucio, P.S., Degallier, N., Servain, J., Hannart, A., Durand, B., de
Souza, R.N., \emph{et al.} (2013). A case study of the influence of
local weather on \emph{Aedes aegypti} (L.) aging and mortality. \emph{J.
Vector Ecol.} , 38, 20--37.

Lyons, C.L., Coetzee, M., Terblanche, J.S. \& Chown, S.L. (2014).
Desiccation tolerance as a function of age, sex, humidity and
temperature in adults of the African malaria vectors \emph{Anopheles
arabiensis} and \emph{Anopheles funestus} . \emph{J. Exp. Biol.} , 217,
3823--3833.

Maffey, L., Garzón, M.J., Confalonieri, V., Chanampa, M.M., Hasson, E.
\& Schweigmann, N. (2020). Genome-Wide Screening of \emph{Aedes
aegypti}(Culicidae: Diptera) Populations From Northwestern Argentina:
Active and Passive Dispersal Shape Genetic Structure. \emph{J. Med.
Entomol.} , 57, 1930--1941.

Magombedze, G., Ferguson, N.M. \& Ghani, A.C. (2018). A trade-off
between dry season survival longevity and wet season high net
reproduction can explain the persistence of \emph{Anopheles}
mosquitoes.\emph{Parasit. Vectors} , 11, 576.

Marron, M.T., Markow, T.A., Kain, K.J. \& Gibbs, A.G. (2003). Effects of
starvation and desiccation on energy metabolism in desert and
mesic\emph{Drosophila} . \emph{J. Insect Physiol.} , 49, 261--270.

Matowo, N.S., Abbasi, S., Munhenga, G., Tanner, M., Mapua, S.A., Oullo,
D., \emph{et al.} (2019). Fine-scale spatial and temporal variations in
insecticide resistance in \emph{Culex pipiens} complex mosquitoes in
rural south-eastern Tanzania. \emph{Parasit. Vectors} , 12, 413.

Mayne, B. (1930). A Study of the Influence of Relative Humidity on the
Life and Infectibility of the Mosquito. \emph{Indian J. Med. Res.} , 17.

Mcgaughey, W.H. \& Knight, K.L. (1967). Preoviposition Activity of the
Black Salt-Marsh Mosquito, \emph{Aedes taeniorhynchus} (Diptera:
Culicidae)1. \emph{Ann. Entomol. Soc. Am.} , 60, 107--115.

McLaughlin, K., Russell, T.L., Apairamo, A., Bugoro, H., Oscar, J.,
Cooper, R.D., \emph{et al.} (2019). Smallest \emph{Anopheles
farauti}occur during the peak transmission season in the Solomon
Islands.\emph{Malar. J.} , 18, 1--8.

Miazgowicz, K.L., Shocket, M.S., Ryan, S.J., Villena, O.C., Hall, R.J.,
Owen, J., \emph{et al.} (2020). Age influences the thermal suitability
of \emph{Plasmodium falciparum} transmission in the Asian malaria
vector\emph{Anopheles stephensi} . \emph{Proc. R. Soc. B Biol. Sci.} ,
287, 20201093.

Mitchell, A. \& Bergmann, P.J. (2016). Thermal and moisture habitat
preferences do not maximize jumping performance in frogs. \emph{Funct.
Ecol.} , 30, 733--742.

Mogi, M., Miyagi, I., Abadi, K., \& syafruddin. (1996). Inter- and
Intraspecific Variation in Resistance to Desiccation by Adult\emph{Aedes
(Stegomyia) spp.} (Diptera: Culicidae) from Indonesia.\emph{J. Med.
Entomol.} , 33, 53--57.

Monteiro, L.C.C., Souza, J.R.B. de \& Albuquerque, C.M.R. de. (2007).
Eclosion rate, development and survivorship of \emph{Aedes
albopictus}(Skuse) (Diptera: Culicidae) under different water
temperatures.\emph{Neotrop. Entomol.} , 36, 966--971.

Mordecai, E.A., Caldwell, J.M., Grossman, M.K., Lippi, C.A., Johnson,
L.R., Neira, M., \emph{et al.} (2019). Thermal biology of mosquito-borne
disease. \emph{Ecol. Lett.} , 22, 1690--1708.

Mordecai, E.A., Cohen, J.M., Evans, M.V., Gudapati, P., Johnson, L.R.,
Lippi, C.A., \emph{et al.} (2017). Detecting the impact of temperature
on transmission of Zika, dengue, and chikungunya using mechanistic
models. \emph{PLoS Negl. Trop. Dis.} , 11, e0005568.

Mordecai, E.A., Paaijmans, K.P., Johnson, L.R., Balzer, C., Ben\selectlanguage{english}-Horin,
T., Moor, E. de, \emph{et al.} (2013). Optimal temperature for malaria
transmission is dramatically lower than previously predicted.\emph{Ecol.
Lett.} , 16, 22--30.

Mordecai, E.A., Ryan, S.J., Caldwell, J.M., Shah, M.M. \& LaBeaud, A.D.
(2020). Climate change could shift disease burden from malaria to
arboviruses in Africa. \emph{Lancet Planet. Health} , 4, e416--e423.

Moreira, L.A., Iturbe-Ormaetxe, I., Jeffery, J.A., Lu, G., Pyke, A.T.,
Hedges, L.M., \emph{et al.} (2009). A \emph{Wolbachia} symbiont
in\emph{Aedes aegypti} limits infection with dengue, chikungunya,
and\emph{Plasmodium} . \emph{Cell} , 139, 1268--1278.

Murdock, C.C., Blanford, S., Hughes, G.L., Rasgon, J.L. \& Thomas, M.B.
(2014a). Temperature alters \emph{Plasmodium} blocking
by\emph{Wolbachia} . \emph{Sci. Rep.} , 4, 3932.

Murdock, C.C., Blanford, S., Luckhart, S. \& Thomas, M.B. (2014b).
Ambient temperature and dietary supplementation interact to shape
mosquito vector competence for malaria. \emph{J. Insect Physiol.} , 67,
37--44.

Murdock, C.C., Evans, M.V., McClanahan, T.D., Miazgowicz, K.L. \& Tesla,
B. (2017). Fine-scale variation in microclimate across an urban
landscape shapes variation in mosquito population dynamics and the
potential of \emph{Aedes albopictus} to transmit arboviral
disease.\emph{PLoS Negl. Trop. Dis.} , 11, e0005640.

Murdock, C.C., Moller-Jacobs, L.L. \& Thomas, M.B. (2013). Complex
environmental drivers of immunity and resistance in malaria
mosquitoes.\emph{Proc. R. Soc. B Biol. Sci.} , 280, 20132030.

Murdock, C.C., Paaijmans, K.P., Bell, A.S., King, J.G., Hillyer, J.F.,
Read, A.F., \emph{et al.} (2012). Complex effects of temperature on
mosquito immune function. \emph{Proc. R. Soc. B Biol. Sci.} , 279,
3357--3366.

Murdock, C.C., Sternberg, E.D. \& Thomas, M.B. (2016). Malaria
transmission potential could be reduced with current and future climate
change. \emph{Sci. Rep.} , 6, 27771.

Ngonghala, C.N., Ryan, S.J., Tesla, B., Demakovsky, L.R., Mordecai,
E.A., Murdock, C.C., \emph{et al.} (2021). Effects of changes in
temperature on Zika dynamics and control. \emph{J. R. Soc. Interface} ,
18, 20210165.

Nguyen, K.H., Boersch-Supan, P.H., Hartman, R.B., Mendiola, S.Y.,
Harwood, V.J., Civitello, D.J., \emph{et al.} (2021). Interventions can
shift the thermal optimum for parasitic disease transmission.\emph{Proc.
Natl. Acad. Sci.} , 118, e2017537118.

Nosrat, C., Altamirano, J., Anyamba, A., Caldwell, J.M., Damoah, R.,
Mutuku, F., \emph{et al.} (2021). Impact of recent climate extremes on
mosquito-borne disease transmission in Kenya. \emph{PLoS Negl. Trop.
Dis.} , 15, e0009182.

Okech, B.A., Gouagna, L.C., Knols, B.G.J., Kabiru, E.W., Killeen, G.F.,
Beier, J.C., \emph{et al.} (2004). Influence of indoor microclimate and
diet on survival of \emph{Anopheles gambiae s.s.} (Diptera: Culicidae)
in village house conditions in western Kenya. \emph{Int. J. Trop. Insect
Sci.} , 24, 207--212.

Ostwald, M.M., Smith, M.L. \& Seeley, T.D. (2016). The behavioral
regulation of thirst, water collection and water storage in honey bee
colonies. \emph{J. Exp. Biol.} , 219, 2156--2165.

Paaijmans, K.P., Blanford, S., Chan, B.H.K. \& Thomas, M.B. (2012).
Warmer temperatures reduce the vectorial capacity of malaria
mosquitoes.\emph{Biol. Lett.} , 8, 465--468.

Paaijmans, K.P., Heinig, R.L., Seliga, R.A., Blanford, J.I., Blanford,
S., Murdock, C.C., \emph{et al.} (2013). Temperature variation makes
ectotherms more sensitive to climate change. \emph{Glob. Change Biol.} ,
19, 2373--2380.

Paaijmans, K.P. \& Thomas, M.B. (2011). The influence of mosquito
resting behaviour and associated microclimate for malaria
risk.\emph{Malar. J.} , 10, 183.

Padmanabha, H., Soto, E., Mosquera, M., Lord, C.C. \& Lounibos, L.P.
(2010). Ecological Links Between Water Storage Behaviors and \emph{Aedes
aegypti} Production: Implications for Dengue Vector Control in Variable
Climates. \emph{EcoHealth} , 7, 78--90.

Palmer, W.H., Varghese, F.S. \& Van Rij, R.P. (2018). Natural Variation
in Resistance to Virus Infection in Dipteran Insects. \emph{Viruses} ,
10, 118.

Parham, P.E. \& Hughes, D.A. (2015). Climate influences on the
cost-effectiveness of vector-based interventions against malaria in
elimination scenarios. \emph{Philos. Trans. R. Soc. B Biol. Sci.} , 370,
20130557.

Perez-Diaz, J.L., Alvarez-Valenzuela, M.A. \& Garcia-Prada, J.C. (2012).
The effect of the partial pressure of water vapor on the surface tension
of the liquid water--air interface. \emph{J. Colloid Interface Sci.} ,
381, 180--182.

Pilotto, F., Kuhn, I., Adrian, R., Alber, R., Alignier, A., Andrews,
C.,\emph{et al.} (2020). Meta-analysis of multidecadal biodiversity
trends in Europe. \emph{Nat. Commun.} , 11, 3486.

Pincebourde, S., Murdock, C.C., Vickers, M. \& Sears, M.W. (2016).
Fine-scale microclimatic variation can shape the responses of organisms
to global change in both natural and urban environments. \emph{Integr.
Comp. Biol.} , 56, 45--61.

Platt, R.B., Collins, C.L. \& Witherspoon, J.P. (1957). Reactions
of\emph{Anopheles quadrimaculatus} Say to Moisture, Temperature, and
Light. \emph{Ecol. Monogr.} , 27, 303--324.

Platt, R.B., Love, G.J. \& Williams, E.L. (1958). A Positive Correlation
Between Relative Humidity and the Distribution and Abundance
of\emph{Aedes vexans} . \emph{Ecology} , 39, 167--169.

Pless, E., Hopperstad, K.A., Ledesma, N., Dixon, D., Henke, J.A. \&
Powell, J.R. (2020). Sunshine versus gold: The effect of population age
on genetic structure of an invasive mosquito. \emph{Ecol. Evol.} , 10,
9588--9599.

Portner, H.O. \& Farrell, A.P. (2008). Physiology and Climate
Change.\emph{Science} , 322, 690--692.

Provost, M.W. (1973). Mosquito flight and night relative humidity in
Florida. \emph{Fla. Sci.} , 36, 217--225.

Rajpurohit, S., Parkash, R. \& Ramniwas, S. (2008). Body melanization
and its adaptive role in thermoregulation and tolerance against
desiccating conditions in drosophilids. \emph{Entomol. Res.} , 38,
49--60.

Reiskind, M.H. \& Lounibos, L.P. (2009). Effects of intraspecific larval
competition on adult longevity in the mosquitoes \emph{Aedes aegypti}and
\emph{Aedes albopictus} . \emph{Med. Vet. Entomol.} , 23, 62--68.

Romps, D.M. (2021). The Rankine--Kirchhoff approximations for moist
thermodynamics. \emph{Q. J. R. Meteorol. Soc.} , 147, 3493--3497.

Ross, P.A., Axford, J.K., Yang, Q., Staunton, K.M., Ritchie, S.A.,
Richardson, K.M., \emph{et al.} (2020). Heatwaves cause fluctuations in
wMel \emph{Wolbachia} densities and frequencies in \emph{Aedes aegypti}
.\emph{PLoS Negl. Trop. Dis.} , 14, e0007958.

Ross, P.A., Ritchie, S.A., Axford, J.K. \& Hoffmann, A.A. (2019). Loss
of cytoplasmic incompatibility in \emph{Wolbachia} -infected \emph{Aedes
aegypti} under field conditions. \emph{PLoS Negl. Trop. Dis.} , 13,
e0007357.

Ross, P.A., Wiwatanaratanabutr, I., Axford, J.K., White, V.L.,
Endersby-Harshman, N.M. \& Hoffmann, A.A. (2017).
\emph{Wolbachia}infections in \emph{Aedes aegypti} differ markedly in
their response to cyclical heat stress. \emph{PLOS Pathog.} , 13,
e1006006.

Roura-Pascual, N., Hui, C., Ikeda, T., Leday, G., Richardson, D.M.,
Carpintero, S., \emph{et al.} (2011). Relative roles of climatic
suitability and anthropogenic influence in determining the pattern of
spread in a global invader. \emph{Proc. Natl. Acad. Sci.} , 108,
220--225.

Rowley, W.A. \& Graham, C.L. (1968). The effect of temperature and
relative humidity on the flight performance of female \emph{Aedes
aegypti} . \emph{J. Insect Physiol.} , 14, 1251--1257.

Rozen-Rechels, D., Dupoue, A., Lourdais, O., Chamaille-Jammes, S.,
Meylan, S., Clobert, J., \emph{et al.} (2019). When water interacts with
temperature: Ecological and evolutionary implications of
thermo-hydroregulation in terrestrial ectotherms. \emph{Ecol. Evol.} ,
9, 10029--10043.

Rudolfs, W. (1923). \emph{Observations on the Relations Between
Atmospheric Conditions and the Behavior of Mosquitoes} . New Jersey
Agricultural Experiment Stations.

Rudolfs, W. (1925). Relation between Temperature, Humidity and Activity
of House Mosquitoes. \emph{J. N. Y. Entomol. Soc.} , 33, 163--169.

Ryan, S.J., Carlson, C.J., Tesla, B., Bonds, M.H., Ngonghala, C.N.,
Mordecai, E.A., \emph{et al.} (2020a). Warming temperatures could expose
more than 1.3 billion new people to Zika virus risk by 2050. \emph{Glob.
Change Biol.} , 27, 84--93.

Ryan, S.J., Lippi, C.A. \& Zermoglio, F. (2020b). Shifting transmission
risk for malaria in Africa with climate change: a framework for planning
and intervention. \emph{Malar. J.} , 19, 170.

Ryan, S.J., McNally, A., Johnson, L.R., Mordecai, E.A., Ben-Horin, T.,
Paaijmans, K., \emph{et al.} (2015). Mapping physiological suitability
limits for malaria in Africa under climate change. \emph{Vector-Borne
Zoonotic Dis.} , 15, 718--725.

Samuel, M.D., Hobbelen, P.H.F., DeCastro, F., Ahumada, J.A., LaPointe,
D.A., Atkinson, C.T., \emph{et al.} (2011). The dynamics, transmission,
and population impacts of avian malaria in native Hawaiian birds: a
modeling approach. \emph{Ecol. Appl.} , 21, 2960--2973.

Sang, R., Lutomiah, J., Said, M., Makio, A., Koka, H., Koskei,
E.,\emph{et al.} (2017). Effects of Irrigation and Rainfall on the
Population Dynamics of Rift Valley Fever and Other Arbovirus Mosquito
Vectors in the Epidemic-Prone Tana River County, Kenya. \emph{J. Med.
Entomol.} , 54, 460--470.

Santos-Vega, M., Bouma, M.J., Kohli, V. \& Pascual, M. (2016).
Population density, climate variables and poverty synergistically
structure spatial risk in urban malaria in India. \emph{PLoS Negl. Trop.
Dis.} , 10, e0005155.

Santos-Vega, M., Martinez, P.P., Vaishnav, K.G., Kohli, V., Desai, V.,
Bouma, M.J., \emph{et al.} (2022). The neglected role of relative
humidity in the interannual variability of urban malaria in Indian
cities. \emph{Nat. Commun.} , 13, 533.

Schmidt, C.A., Comeau, G., Monaghan, A.J., Williamson, D.J. \& Ernst,
K.C. (2018). Effects of desiccation stress on adult female longevity
in\emph{Aedes aegypti} and \emph{Ae. albopictus} (Diptera: Culicidae):
results of a systematic review and pooled survival
analysis.\emph{Parasit. Vectors} , 11, 267.

Schmidt, W.-P., Suzuki, M., Thiem, V.D., White, R.G., Tsuzuki, A.,
Yoshida, L.-M., \emph{et al.} (2011). Population Density, Water Supply,
and the Risk of Dengue Fever in Vietnam: Cohort Study and Spatial
Analysis. \emph{PLOS Med.} , 8, e1001082.

Shapiro, L.L.M., Whitehead, S.A. \& Thomas, M.B. (2017). Quantifying the
effects of temperature on mosquito and parasite traits that determine
the transmission potential of human malaria. \emph{PLOS Biol.} , 15,
e2003489.

Shelford, V.E. (1918). A Comparison of the Responses of Animals in
Gradients of Environmental Factors with Particular Reference to the
Method of Reaction of Representatives of the Various Groups from
Protozoa to Mammals. \emph{Science} , 48, 225--230.

Shocket, M.S., Ryan, S.J. \& Mordecai, E.A. (2018a). Temperature
explains broad patterns of Ross River virus transmission. \emph{eLife} ,
7, e37762.

Shocket, M.S., Vergara, D., Sickbert, A.J., Walsman, J.M., Strauss,
A.T., Hite, J.L., \emph{et al.} (2018b). Parasite rearing and infection
temperatures jointly influence disease transmission and shape
seasonality of epidemics. \emph{Ecology} , 99, 1975--1987.

Shocket, M.S., Verwillow, A.B., Numazu, M.G., Slamani, H., Cohen, J.M.,
El Moustaid, F., \emph{et al.} (2020). Transmission of West Nile and
five other temperate mosquito-borne viruses peaks at temperatures
between 23degC and 26degC. \emph{eLife} , 9, e58511.

Sinclair, B.J., Marshall, K.E., Sewell, M.A., Levesque, D.L., Willett,
C.S., Slotsbo, S., \emph{et al.} (2016). Can we predict ectotherm
responses to climate change using thermal performance curves and body
temperatures? \emph{Ecol. Lett.} , 19, 1372--1385.

Singh, K.E.P. \& Micks, D.W. (1957). The Effects of Surface Tension on
Mosquito Development. \emph{Mosq. News} , 17.

Siraj, A.S., Rodriguez-Barraquer, I., Barker, C.M., Tejedor-Garavito,
N., Harding, D., Lorton, C., \emph{et al.} (2018). Spatiotemporal
incidence of Zika and associated environmental drivers for the 2015-2016
epidemic in Colombia. \emph{Sci. Data} , 5, 180073.

Siraj, A.S., Santos-Vega, M., Bouma, M.J., Yadeta, D., Carrascal, D.R.
\& Pascual, M. (2014). Altitudinal Changes in Malaria Incidence in
Highlands of Ethiopia and Colombia. \emph{Science} .

Soti, V., Tran, A., Degenne, P., Chevalier, V., Seen, D.L., Thiongane,
Y., \emph{et al.} (2012). Combining Hydrology and Mosquito Population
Models to Identify the Drivers of Rift Valley Fever Emergence in
Semi-Arid Regions of West Africa. \emph{PLoS Negl. Trop. Dis.} , 6,
e1795.

Steiner, F.M., Schlick-Steiner, B.C., VanDerWal, J., Reuther, K.D.,
Christian, E., Stauffer, C., \emph{et al.} (2008). Combined modelling of
distribution and niche in invasion biology: a case study of two
invasive\emph{Tetramorium} ant species. \emph{Divers. Distrib.} , 14,
538--545.

Sternberg, E.D. \& Thomas, M.B. (2014). Local adaptation to temperature
and the implications for vector-borne diseases. \emph{Trends Parasitol.}
, 30, 115--122.

Stewart Ibarra, A.M., Ryan, S.J., Beltran, E., Mejia, R., Silva, M. \&
Munoz, A. (2013). Dengue Vector Dynamics (\emph{Aedes aegypti} )
Influenced by Climate and Social Factors in Ecuador: Implications for
Targeted Control. \emph{PLOS ONE} , 8, e78263.

Stewart, I.D. \& Oke, T.R. (2012). Local Climate Zones for Urban
Temperature Studies. \emph{Bull. Am. Meteorol. Soc.} , 93, 1879--1900.

Stoddard, S.T., Morrison, A.C., Vazquez-Prokopec, G.M., Soldan, V.P.,
Kochel, T.J., Kitron, U., \emph{et al.} (2009). The role of human
movement in the transmission of vector-borne pathogens. \emph{PLoS Negl.
Trop. Dis.} , 3, e481.

Stuchin, M., Machalaba, C.C. \& Karesh, W.B. (2016). \emph{VECTOR-BORNE
DISEASES: ANIMALS AND PATTERNS} . \emph{Glob. Health Impacts
Vector-Borne Dis. Workshop Summ.} National Academies Press (US).

Suwanchaichinda, C. \& Paskewitz, S.M. (1998). Effects of Larval
Nutrition, Adult Body Size, and Adult Temperature on the Ability
of\emph{Anopheles gambiae} (Diptera: Culicidae) to Melanize Sephadex
Beads. \emph{J. Med. Entomol.} , 35, 157--161.

Takken, W. \& Lindsay, S. (2019). Increased threat of urban malaria
from\emph{Anopheles stephensi} mosquitoes, Africa. \emph{Emerg. Infect.
Dis.} , 25, 1431--1433.

Tatzel, J., Prusiner, S.B. \& Welch, W.J. (1996). Chemical chaperones
interfere with the formation of scrapie prion protein. \emph{EMBO J.} ,
15, 6363--6373.

Tesla, B., Demakovsky, L.R., Mordecai, E.A., Ryan, S.J., Bonds, M.H.,
Ngonghala, C.N., \emph{et al.} (2018). Temperature drives Zika virus
transmission: evidence from empirical and mathematical
models.\emph{Proc. R. Soc. B Biol. Sci.} , 285.

Thomas, S., Ravishankaran, S., Justin, J.A., Asokan, A., Mathai, M.T.,
Valecha, N., \emph{et al.} (2016). Overhead tank is the potential
breeding habitat of \emph{Anopheles stephensi} in an urban transmission
setting of Chennai, India. \emph{Malar. J.} , 15, 274.

Thomas, S., Ravishankaran, S., Justin, N.A.J.A., Asokan, A., Kalsingh,
T.M.J., Mathai, M.T., \emph{et al.} (2018). Microclimate variables of
the ambient environment deliver the actual estimates of the extrinsic
incubation period of \emph{Plasmodium vivax} and \emph{Plasmodium
falciparum} : a study from a malaria-endemic urban setting, Chennai in
India. \emph{Malar. J.} , 17, 201.

Thomas, S., Ravishankaran, S., Justin, N.A.J.A., Asokan, A., Mathai,
M.T., Valecha, N., \emph{et al.} (2017). Resting and feeding preferences
of \emph{Anopheles stephensi} in an urban setting, perennial for
malaria. \emph{Malar. J.} , 16, 111.

Thomson, R.C.M. (1938). The Reactions of Mosquitoes to Temperature and
Humidity. \emph{Bull. Entomol. Res.} , 29, 125--140.

Tun-Lin, W., Burkot, T.R. \& Kay, B.H. (2000). Effects of temperature
and larval diet on development rates and survival of the dengue
vector\emph{Aedes aegypti} in north Queensland, Australia. \emph{Med.
Vet. Entomol.} , 14, 31--37.

Ulrich, J.N., Beier, J.C., Devine, G.J. \& Hugo, L.E. (2016). Heat
Sensitivity of wMel \emph{Wolbachia} during \emph{Aedes
aegypti}Development. \emph{PLoS Negl. Trop. Dis.} , 10, e0004873.

United Nations, D. of E. and S.A., Population Division.
(2019).\emph{World Urbanization Prospects: The 2018 Revision
(ST/ESA/SER.A/420)} . United Nations, New York, NY.

Urbanski, J.M., Benoit, J.B., Michaud, M.R., Denlinger, D.L. \&
Armbruster, P. (2010). The molecular physiology of increased egg
desiccation resistance during diapause in the invasive
mosquito,\emph{Aedes albopictus} . \emph{Proc. R. Soc. B Biol. Sci.} ,
277, 2683--2692.

Vega-Rua, A., Marconcini, M., Madec, Y., Manni, M., Carraretto, D.,
Gomulski, L.M., \emph{et al.} (2020). Vector competence of \emph{Aedes
albopictus} populations for chikungunya virus is shaped by their
demographic history. \emph{Commun. Biol.} , 3, 1--13.

Verhulst, N.O., Brendle, A., Blanckenhorn, W.U. \& Mathis, A. (2020).
Thermal preferences of subtropical \emph{Aedes aegypti} and
temperate\emph{Ae. japonicus} mosquitoes. \emph{J. Therm. Biol.} , 91,
102637.

Villena, O.C., Ryan, S.J., Murdock, C.C. \& Johnson, L.R. (2022).
Temperature impacts the transmission of malaria parasites
by\emph{Anopheles gambiae} and \emph{Anopheles stephensi}
mosquitoes.\emph{Ecology} , n/a, e3685.

Vorhees, A.S., Gray, E.M. \& Bradley, T.J. (2013). Thermal Resistance
and Performance Correlate with Climate in Populations of a Widespread
Mosquito. \emph{Physiol. Biochem. Zool.} , 86, 73--81.

Wang, G.-H., Gamez, S., Raban, R.R., Marshall, J.M., Alphey, L., Li,
M.,\emph{et al.} (2021). Combating mosquito-borne diseases using genetic
control technologies. \emph{Nat. Commun.} , 12, 4388.

Warner, R.E. (1968). The Role of Introduced Diseases in the Extinction
of the Endemic Hawaiian Avifauna. \emph{The Condor} , 70, 101--120.

Weaver, S.C., Charlier, C., Vasilakis, N. \& Lecuit, M. (2018). Zika,
Chikungunya, and Other Emerging Vector-Borne Viral Diseases. \emph{Annu.
Rev. Med.} , 69, 395--408.

Weihrauch, D., Donini, A. \& O'Donnell, M.J. (2012). Ammonia transport
by terrestrial and aquatic insects. \emph{J. Insect Physiol.} ,
Molecular Physiology of Epithelial Transport in Insects - a Tribute to
William R. Harvey, 58, 473--487.

W.H.O. (2020). \emph{World malaria report 2020: 20 years of global
progress and challenges.} World Health Organization, Geneva.

Wilke, A.B.B. \& Marrelli, M.T. (2012). Genetic Control of Mosquitoes:
population suppression strategies. \emph{Rev. Inst. Med. Trop. Sao
Paulo} , 54, 287--292.

Wilke, A.B.B. \& Marrelli, M.T. (2015). Paratransgenesis: a promising
new strategy for mosquito vector control. \emph{Parasit. Vectors} , 8,
342.

Wimberly, M.C., Davis, J.K., Evans, M.V., Hess, A., Newberry, P.M.,
Solano-Asamoah, N., \emph{et al.} (2020). Land cover affects
microclimate and temperature suitability for arbovirus transmission in
an urban landscape. \emph{PLoS Negl. Trop. Dis.} , 14, e0008614.

Witter, L.A., Johnson, C.J., Croft, B., Gunn, A. \& Poirier, L.M.
(2012). Gauging climate change effects at local scales: weather-based
indices to monitor insect harassment in caribou. \emph{Ecol. Appl.} ,
22, 1838--1851.

Wright, R.E. \& Knight, K.L. (1966). Effect of environmental factors on
biting activity of \emph{Aedes vexans} (Meigen) and \emph{Aedes
trivittatus} (Coquillett). \emph{Mosq. News} , 26.

Wu, G.C. \& Wright, J.C. (2015). Exceptional thermal tolerance and water
resistance in the mite \emph{Paratarsotomus macropalpis}(Erythracaridae)
challenge prevailing explanations of physiological limits. \emph{J.
Insect Physiol.} , 82, 1--7.

Yang, P., Ren, G. \& Hou, W. (2017). Temporal--Spatial Patterns of
Relative Humidity and the Urban Dryness Island Effect in Beijing
City.\emph{J. Appl. Meteorol. Climatol.} , 56, 2221--2237.

Ye, Y.H., Carrasco, A.M., Frentiu, F.D., Chenoweth, S.F., Beebe, N.W.,
Hurk, A.F. van den, \emph{et al.} (2015). \emph{Wolbachia} Reduces the
Transmission Potential of Dengue-Infected \emph{Aedes aegypti}
.\emph{PLoS Negl. Trop. Dis.} , 9, e0003894.

Yu, H.-P., Shao, L., Xiao, K., Mu, L.-L. \& Li, G.-Q. (2010).
Hygropreference behaviour and humidity detection in the yellow-spined
bamboo locust, \emph{Ceracris kiangsu} . \emph{Physiol. Entomol.} , 35,
379--384.

Yuan, F. \& Bauer, M.E. (2007). Comparison of impervious surface area
and normalized difference vegetation index as indicators of surface
urban heat island effects in Landsat imagery. \emph{Remote Sens.
Environ.} , 106, 375--386.

Yurchenko, A.A., Masri, R.A., Khrabrova, N.V., Sibataev, A.K., Fritz,
M.L. \& Sharakhova, M.V. (2020). Genomic differentiation and
intercontinental population structure of mosquito vectors \emph{Culex
pipiens pipiens} and \emph{Culex pipiens molestus} . \emph{Sci. Rep.} ,
10, 7504.

Zhang, L.J., Wu, Z.L., Wang, K.F., Liu, Q., Zhuang, H.M. \& Wu, G.
(2015). Trade-off between thermal tolerance and insecticide resistance
in \emph{Plutella xylostella} . \emph{Ecol. Evol.} , 5, 515--530.

Zouache, K., Fontaine, A., Vega-Rua, A., Mousson, L., Thiberge, J.-M.,
Lourenco-De-Oliveira, R., \emph{et al.} (2014). Three-way interactions
between mosquito population, viral strain and temperature underlying
chikungunya virus transmission potential. \emph{Proc. R. Soc. B Biol.
Sci.} , 281, 20141078.

\textbf{Figure Legends:}

\textbf{Figure 1: A} Similar to other ectothermic organisms, the life
history traits of mosquitoes and the pathogens they transmit typically
exhibit non-linear relationships with environmental temperature, where
trait performance is constrained by both cool and warm temperatures and
optimized at some intermediate temperature. Further, the effect of
temperature on these individual traits can vary qualitatively and
quantitatively, resulting in different temperature ranges across which
trait performance can occur, temperatures that maximize trait
performance, and the overall shape of the temperature-trait relationship
(e.g., symmetric vs. asymmetric). As a result, predicting the effects of
temperature on mosquito fitness, population growth rates, or pathogen
transmission is complex. \textbf{B} Mathematical models of vector-borne
pathogen transmission that incorporate these temperature-trait
relationships generally predict transmission to also follow a non-linear
relationship and to peak at some intermediate temperature, as depicted
here with the temperature-dependent relative reproductive
number\emph{R\textsubscript{0}} as a conceptual example. This model
incorporates the effects of temperature on traits that drive mosquito
population dynamics (e.g., per capita mosquito development rate
(\emph{MDR} ), the probability of egg to adult survival (\emph{pEA} ),
and the per capita number of eggs females produce per day (\emph{EFD}
)), host-vector contact rates (the per capita daily biting rate of
female mosquitoes (\emph{a} )), and the number of mosquitoes alive and
infectious (transmission (\emph{b} ) and infection (\emph{c} )
probabilities, the extrinsic incubation period (1/\emph{EIR} ), and the
per capita mosquito mortality rate (\selectlanguage{greek}\emph{μ} \selectlanguage{english})). Where the predicted
thermal minimum (\emph{T\textsubscript{min}} ), maximum
(\emph{T\textsubscript{max}} ), and optimum (\emph{T\textsubscript{opt}}
) for transmission occur will be dependent upon the relative effect of
each trait, the nature of the temperature-trait relationship, and how
these factors combine to shape the transmission process. Adapted from
Mordecai et al. 2017.

\textbf{Figure 2:} Monthly malaria case data for \emph{Plasmodium
falciparum} shown (in purple) with a corresponding time series for
relative humidity (RH, red) for two cities in India, Ahmedabad
(\textbf{A} ) and Surat (\textbf{B} ). Total cases during the
transmission season from August to November are shown as a function of
mean RH in a critical time window preceding this season and including
the monsoons from May to July for Ahmedabad (\textbf{C} ) and March to
July for Surat (\textbf{D} ).~Figure is taken from Santos-Vega et al.
(2022)\emph{Nature Communications} doi: 10.1038/s41467-022-28145-7.
Figure is reproduced under Creative Commons Attribution 4.0
International License.

\textbf{Figure 3:} The total amount of water the air can hold, expressed
here as saturation vapor pressure (\emph{Es} ), increases exponentially
with temperature and is estimated as a function of temperature using the
Tetens equation. The actual amount of water in the air, expressed here
as vapor pressure (\emph{Ea} ), can be derived from relative humidity
(\emph{RH} ) as \emph{Ea} = \emph{RH} /100 * \emph{Es} . The vapor
pressure deficit (\emph{VPD} ) is the absolute difference between
\emph{Es} and\emph{Ea} and is an important metric of atmospheric
moisture because it has a near linear relationship with evaporative
potential. Thus, as temperature warms, for a given decrease in \emph{RH}
, there will be a larger increase in \emph{VPD} and the amount of water
stress mosquitoes experience.

\textbf{Figure 4: A} Thermal performance is often measured by placing
mosquitoes in different life stages and infection stages across a range
of constant temperatures at a set relative humidity (typically between
70-90\% RH). However, despite holding relative humidity constant, as
temperatures warm there will be a corresponding increase in the vapor
pressure deficit (\emph{VPD} ) and the amount of water stress mosquitoes
experience. Overlaying these relationships (from Figure 1) on a given
temperature-trait relationship demonstrates that the sensitivity of
trait performance to variation in relative humidity should be highest on
the descending limb of this relationship. \emph{Es} = saturation vapor
pressure, which increases exponentially with temperature and is
estimated as a function of temperature using the Tetens
equation.\emph{Ea} = vapor pressure, meaning the actual amount of water
in the air, and can be derived from relative humidity (\emph{RH} ) as
\emph{Ea}= \emph{RH} /100 * \emph{Es} . \textbf{B-D} represent the
hypothetical responses of three temperature-trait relationships to
variation in relative humidity. These shifts are predicted to both
decrease the thermal optimum and maximum for some traits (e.g.,
\textbf{B} lifespan and \textbf{D} vector competence) or increase them
for others (e.g.,\textbf{C} per capita biting rate).

\textbf{Figure 5:} Laboratory work with field derived mosquitoes can be
conducted to estimate the effect of multiple environmental variables on
mosquito fitness, population dynamics, and pathogen transmission. For
example, mosquitoes could be housed across a range of constant
temperature (\emph{T} ) and relative humidity (\emph{RH} ) conditions
that are reflective of monthly field conditions. From these experiments,
one can estimate the effects of variation in these environmental
variables on key \emph{larval traits} (\textbf{A} : mosquito development
rate (\emph{MDR} ) and the probability of egg to adult survival
(\emph{pEA} )),\emph{adult traits} (\textbf{B} : per capita mortality
rate (\selectlanguage{greek}\emph{μ} \selectlanguage{english}), per capita eggs laid per day (\emph{EFD} ), and per
capita daily biting rate (\emph{a} )), and \emph{parasite / pathogen
traits} (\textbf{C} : vector competence (\emph{bc} ) and the extrinsic
incubation period (\emph{EIP} )). \textbf{D} Bayesian hierarchical
models can be used to develop \emph{T} and \emph{RH} response surfaces
for each trait, which can either be incorporated in process-based
modeling approaches to infer effects on seasonal and inter-annual
variation in vector-borne pathogen transmission dynamics. \textbf{E}
Bayesian models can also be used to generate a \emph{T} and \emph{RH}
dependent, relative\emph{R\textsubscript{0}} model that can be used to
predict environmental suitability for pathogen transmission at various
spatial scales. A crucial detail for modeling approaches, based on the
evidence presented in Box 2, is that the effects of \emph{T} and
\emph{RH} will be interactive, not additive. (Inset on temporal dynamics
in \textbf{D}is from Santos-Vega et al. (2022) \emph{Nature
Communications;} doi: 10.1038/s41467-022-28145-7. Figure is reproduced
under Creative Commons Attribution 4.0 International License.)

\textbf{Table 1: Summary of the published literature that investigated
the effects of relative humidity on mosquitoes, organised by life
history trait, presented with a summary of the effect of RH.}\selectlanguage{english}
\begin{longtable}[]{@{}lllll@{}}
\toprule
\textbf{Life History Trait} & \textbf{Range Explored (RH\%)} &
\textbf{Effect of RH} & \textbf{Mosquito Species} &
\textbf{References}\tabularnewline
Longevity/Survival/ Desiccation tolerance & 5 - 100 & Increased RH
significantly increased female longevity; tendency to survive longest at
low temp - high humidity combinations and females to survive longer than
males & \emph{Anopheles gambiae, An. stephensi, An. subpictus, An.
culicifacies, An. pharoensis, An. arabiensis, An. funestus, Ae. aegypti,
Ae. albopictus, Ae. togoi, Ae. paullusi, Culex pipiens, Eretmapodites
chrysogaster} & (Mayne 1930; Lewis 1933; Lomax 1968; Hylton 1969;
Gaaboub \emph{et al.} 1971; Mogi \emph{et al.} 1996; Bayoh 2001; Gray \&
Bradley 2005; Reiskind \& Lounibos 2009; Costa \emph{et al.} 2010;
Urbanski \emph{et al.} 2010; Canyon \emph{et al.} 2013; Lyons \emph{et
al.} 2014; Alto \emph{et al.} 2015; Lega \emph{et al.} 2017; Schmidt
\emph{et al.} 2018)\tabularnewline
Egg production & 34 - 95 & Increased RH increased egg production;
significantly lower numbers of eggs and delayed oviposition in dry
conditions & \emph{An. pharoensis, Ae. aegypti, Ae. taeniorhynchus, Ae.
vexans, Ae. trivittatus} & (Mcgaughey \& Knight 1967; Gaaboub \emph{et
al.} 1971; Canyon \emph{et al.} 1999, 2013; Costa \emph{et al.} 2010;
Lega \emph{et al.} 2017)\tabularnewline
Activity/Behaviour & 10-30, up to 100 & Mosquito activity increases with
increasing relative humidity to a point (\textasciitilde{}90\%) and then
precipitously declines, also has a general lower limit at
\textasciitilde{}40\%. & \emph{An. quadrimaculatus, An. earlei, An.
walkeri, An. crucians, Ae. aegypti, Ae. sollicitans, Ae. cantator, Ae.
vexans, Ae. trivittatus, Ae. canadensis, Ae. communis, Ae. sticticus,
Ae. taeniorhynchus, Ae. vigilax, Cx. pipiens, Cx. fatigans, Cx.
restuans, Cx. nigripalpus, Cx. sitiens, Coquillettidia perturbans,
Psorophora confinnis, Uranotaenia sapphirina} & (Rudolfs 1923, 1925;
Thomson 1938; Platt \emph{et al.} 1957, 1958; Wright \& Knight 1966;
Rowley \& Graham 1968; Dow \& Gerrish 1970; Provost 1973; Bidlingmayer
1974, 1985; Grimstad \& DeFoliart 1975; Witter \emph{et al.} 2012; Hagan
\emph{et al.} 2018; Johnson \emph{et al.} 2020)\tabularnewline
\emph{Plasmodium} infection & 39 - 100 & Mixed or unclear effects of
humidity & \emph{An. stephensi, An. subpictus, An. culicifacies, An.
fuliginosus, Cx quinquefasciatus, Cx. fatigans} & (Mayne 1930; Knowles
\& Basu 1943)\tabularnewline
Egg-hatching & Real-world RH data; 0-100 & Adding RH data to a
predictive model focused on egg hatching made the model more accurate.
Egg hatching worse at lower humidities & \emph{Ae. aegypti} & (Bar-Zeev
1957; Albernaz \emph{et al.} 2009; Lega \emph{et al.}
2017)\tabularnewline
Microclimate preference upon emergence & 75, 86 & Newly emerged adults
with no access to water or sugar preferred cooler, more humid refugia. &
\emph{An. gambiae, An. stephensi, Ae. aegypti, and Cx. pipiens} &
(Kessler \& Guerin 2008)\tabularnewline
\bottomrule
\end{longtable}\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/Tab/Tab}

\end{center}
\end{figure}

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\verb`BoxesV4.docx`  available at \url{https://authorea.com/users/602661/articles/633405-humidity-the-overlooked-variable-in-thermal-biology-of-mosquito-borne-disease}

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