Landscape level analysis of mountain pine beetle in British Columbia, Canada: spatiotemporal development and spatial synchrony within the present outbreak

Eruptive herbivores can exert profound landscape level influences. For example, the ongoing mountain pine beetle outbreak in British Columbia, Canada, has resulted in mortality of mature lodgepole pine over >7 million ha. Analysis of the spatio‐temporal pattern of spread can lend insights into the processes initiating and/or sustaining such phenomena. We present a landscape level analysis of the development of the current outbreak. Aerial survey assessments of tree mortality, projected onto discrete 12×12 km cells, were used as a proxy for insect population density. We examined whether the outbreak potentially originated from an epicenter and spread, or whether multiple localized populations erupted simultaneously at spatially disjunct locations. An aspatial cluster analysis of time series from 1990 to 2003 revealed four distinct time series patterns. Each time series demonstrated a general progression of increasing mountain pine beetle populations. Plotting the geographical locations of each temporal pattern revealed that the outbreak occurred first in an area of west‐central British Columbia, and then in an area to the east. The plot further revealed many localized infestations erupted in geographically disjunct areas, especially in the southern portion of the province. Autologistic regression analyses indicated a significant, positive association between areas where the outbreak first occurred and conservation lands. For example, the delineated area of west‐central British Columbia is comprised of three conservation parks and adjacent working forest. We further examined how population synchrony declines with distance at different population levels. Examination of the spatial dependence of temporal synchrony in population fluctuations during early, incipient years (i.e. 1990–1996) suggested that outbreaking mountain pine beetle populations are largely independent at scales >200 km during non‐epidemic periods. However, during epidemic years (i.e. 1999–2003), populations were clearly synchronous across the entire province, even at distances of up to 900 km. The epicentral pattern of population development can be used to identify and prioritize adjacent landscape units for both reactive and proactive management strategies intended to minimize mountain pine beetle impacts.     

Movement of outbreak populations of mountain pine beetle: influences of spatiotemporal patterns and climate

Insect outbreaks exert landscape-level influences, yet quantifying the relative contributions of various exogenous and endogenous factors that contribute to their pattern and spread remains elusive. We examine an outbreak of mountain pine beetle covering an 800 thousand ha area on the Chilcotin Plateau of British Columbia, Canada, during the 1970s and early 1980s. We present a model that incorporates the spatial and temporal arrangements of outbreaking insect populations, as well as various climatic factors that influence insect development. Onsets of eruptions of mountain pine beetle demonstrated landscape-level synchrony. On average, the presence of outbreaking populations was highly correlated with outbreaking populations within the nearest 18  km the same year and local populations within 6 km in the previous two years. After incorporating these spatial and temporal dependencies, we found that increasing temperatures contributed to explaining outbreak probabilities during this 15  yr outbreak. During collapse years, landscape-level synchrony declined while local synchrony values remained high, suggesting that in some areas host depletion was contributing to population decline. Model forecasts of outbreak propensity one year in advance at a 12 by 12  km scale provided 80% accuracy over the landscape, and never underestimated the occurrence of locally outbreaking populations. This model provides a flexible approach for linking temperature and insect population dynamics to spatial spread, and complements existing decision support tools for resource managers.     

Can animal habitat use patterns influence their vulnerability to extreme climate events? An estuarine sportfish case study

Global climate forecasts predict changes in the frequency and intensity of extreme climate events (ECEs). The capacity for specific habitat patches within a landscape to modulate stressors from extreme climate events, and animal distribution throughout habitat matrices during events, could influence the degree of population level effects following the passage of ECEs. Here, we ask (i) does the intensity of stressors of an ECE vary across a landscape? And (ii) Do habitat use patterns of a mobile species influence their vulnerability to ECEs? Specifically, we measured how extreme cold spells might interact with temporal variability in habitat use to affect populations of a tropical, estuarine‐dependent large‐bodied fish Common Snook, within Everglades National Park estuaries (FL US). We examined temperature variation across the estuary during cold disturbances with different degrees of severity, including an extreme cold spell. Second, we quantified Snook distribution patterns when the passage of ECEs is most likely to occur from 2012 to 2016 using passive acoustic tracking. Our results revealed spatial heterogeneity in the intensity of temperature declines during cold disturbances, with some habitats being consistently 3–5°C colder than others. Surprisingly, Snook distributions during periods of greatest risk to experience an extreme cold event varied among years. During the winters of 2013–2014 and 2014–2015 a greater proportion of Snook occurred in the colder habitats, while the winters of 2012–2013 and 2015–2016 featured more Snook observed in the warmest habitats. This study shows that Snook habitat use patterns could influence vulnerability to extreme cold events, however, whether Snook habitat use increases or decreases their vulnerability to disturbance depends on the year, creating temporally dynamic vulnerability. Faunal global change research should address the spatially explicit nature of extreme climate events and animal habitat use patterns to identify potential mechanisms that may influence population effects following these disturbances.     

Modelling species responses to extreme weather provides new insights into constraints on range and likely climate change impacts for Australian mammals

Conservation of species under climate change relies on accurate predictions of species ranges under current and future climate conditions. To date, modelling studies have focused primarily on how changes in long‐term averaged climate conditions are likely to influence species distributions with much less attention paid to the potential effect of extreme events such as droughts and heatwaves which are expected to increase in frequency over coming decades. In this study we explore the benefits of tailoring predictor variables to the specific physiological constraints of species, or groups of species. We show how utilizing spatial predictors of extreme temperature and water availability (heat‐waves and droughts), derived from high‐temporal resolution, long‐term weather records, provides categorically different predictions about the future (2070) distribution of suitable environments for 188 mammal species across different biomes (from arid zones to tropical environments) covering the whole of continental Australia. Models based on long‐term averages‐only and extreme conditions‐only showed similarly high predictive performance tested by hold‐out cross‐validation on current data, and yet some predicted dramatically different future geographic ranges for the same species under 2070 climate scenarios. Our results highlight the importance of accounting for extreme conditions/events by identifying areas in the landscape where species may cope with average conditions, but cannot persist under extreme conditions known or predicted to occur there. Our approach provides an important step toward identifying the location of climate change refuges and danger zones that goes beyond the current standard of extrapolating long‐term climate averages.     

Influences of extreme weather,climate and pesticide use on invertebrates in cereal fields over 42 years

Cereal fields are central to balancing food production and environmental health in the face of climate change. Within them, invertebrates provide key ecosystem services. Using 42 years of monitoring data collected in southern England, we investigated the sensitivity and resilience of invertebrates in cereal fields to extreme weather events and examined the effect of long‐term changes in temperature, rainfall and pesticide use on invertebrate abundance. Of the 26 invertebrate groups examined, eleven proved sensitive to extreme weather events. Average abundance increased in hot/dry years and decreased in cold/wet years for Araneae, Cicadellidae, adult Heteroptera, Thysanoptera, Braconidae, Enicmus and Lathridiidae. The average abundance of Delphacidae, Cryptophagidae and Mycetophilidae increased in both hot/dry and cold/wet years relative to other years. The abundance of all 10 groups usually returned to their long‐term trend within a year after the extreme event. For five of them, sensitivity to cold/wet events was lowest (translating into higher abundances) at locations with a westerly aspect. Some long‐term trends in invertebrate abundance correlated with temperature and rainfall, indicating that climate change may affect them. However, pesticide use was more important in explaining the trends, suggesting that reduced pesticide use would mitigate the effects of climate change.     

Spatial co‐localisation of extreme weather events: a clear and present danger

Extreme weather events have become a dominant feature of the narrative surrounding changes in global climate with large impacts on ecosystem stability, functioning and resilience; however, understanding of their risk of co‐occurrence at the regional scale is lacking. Based on the UK Met Office’s long‐term temperature and rainfall records, we present the first evidence demonstrating significant increases in the magnitude, direction of change and spatial co‐localisation of extreme weather events since 1961. Combining this new understanding with land‐use data sets allowed us to assess the likely consequences on future agricultural production and conservation priority areas. All land‐uses are impacted by the increasing risk of at least one extreme event and conservation areas were identified as the hotspots of risk for the co‐occurrence of multiple event types. Our findings provide a basis to regionally guide land‐use optimisation, land management practices and regulatory actions preserving ecosystem services against multiple climate threats.     

Extreme rainfall events and cooling of sea turtle clutches: Implications in the face of climate warming

Understanding how climate change impacts species and ecosystems is integral to conservation. When studying impacts of climate change, warming temperatures are a research focus, with much less attention given to extreme weather events and their impacts. Here, we show how localized, extreme rainfall events can have a major impact on a species that is endangered in many parts of its range. We report incubation temperatures from the world's largest green sea turtle rookery, during a breeding season when two extreme rainfall events occurred. Rainfall caused nest temperatures to drop suddenly and the maximum drop in temperature for each rain‐induced cooling averaged 3.6°C (n = 79 nests, min = 1.0°C, max = 7.4°C). Since green sea turtles have temperature‐dependent sex determination, with low incubation temperatures producing males, such major rainfall events may have a masculinization effect on primary sex ratios. Therefore, in some cases, extreme rainfall events may provide a “get‐out‐of‐jail‐free card” to avoid complete feminization of turtle populations as climate warming continues.     

Simulating climate change: temperature extremes but not means diminish performance in a widespread butterfly

Climate-change induced shifts in species’ temporal and geographic niches have been well documented, while plastic and genetic responses to climatic change have received much less attention. Plastic responses to changes in temperature are generally well understood, though most experimental studies to date have used constant temperature regimes, the reliability of which is under debate. We here investigate plastic responses in the widespread butterfly Pieris napi to simulated climate change, using ecologically realistic diurnal temperature cycles and current and predicted temperature regimes including effects of a heat wave. Increasing the temperature mean by 3 °C predominantly affected developmental times, cold resistance and adult life span, while an increase in the diurnal temperature amplitude had very little effects. Immune function responded only weakly to different thermal regimes. The simulation of a prolonged heat wave severely impaired juvenile survival, body size and longevity, supporting the wide-held notion that extreme weather events will be much more important for species’ performance and local survival than moderate increases in temperature means. Given that the frequency of extreme weather events is predicted to increase with climate change, even widespread species may be negatively affected.     

Spatial synchrony of the two-year cycle budworm outbreaks in central British Columbia, Canada

Outbreaks of forest defoliating insects are usually synchronized over a large spatial scale. Observed records of past outbreaks are usually short and incomplete, therefore long proxy data are useful for better understanding of the spatial synchrony. In this study, we developed tree-ring proxy records of two-year cycle spruce budworm ( Choristoneura biennis Freeman) outbreaks in central British Columbia, Canada, and examined the spatial patterns of past outbreaks. This budworm is a major defoliating insect of the interior spruce ( Picea engelmannii Parry× P. glauca Moench) and subalpine fir ( Abies lasiocarpa [Hook.] Nutt.) forests in the Prince George Region of British Columbia. Four outbreaks occurred in relatively close synchrony over the entire region in the period 1880–1999, however, the initiation year, the intensity and extent of outbreaks varied spatially and from one outbreak to another. In some instances, the occurrence of outbreaks was restricted to only one area. The general synchrony of outbreaks suggested that a large-scale extrinsic factor, such as weather, was at play. However, the imperfect synchrony of outbreaks suggested that local stand characteristics, such as canopy structure, composition of tree species and host plant quality, probably played a major role in preconditioning outbreaks. Dispersal might play a role in synchronizing outbreaks, but the extent to which it contributed to the synchrony was limited in this mountainous region.     

The thermal mismatch hypothesis explains host susceptibility to an emerging infectious disease

Parasites typically have broader thermal limits than hosts, so large performance gaps between pathogens and their cold‐ and warm‐adapted hosts should occur at relatively warm and cold temperatures, respectively. We tested this thermal mismatch hypothesis by quantifying the temperature‐dependent susceptibility of cold‐ and warm‐adapted amphibian species to the fungal pathogen Batrachochytrium dendrobatidis (Bd) using laboratory experiments and field prevalence estimates from 15 410 individuals in 598 populations. In both the laboratory and field, we found that the greatest susceptibility of cold‐ and warm‐adapted hosts occurred at relatively warm and cool temperatures, respectively, providing support for the thermal mismatch hypothesis. Our results suggest that as climate change shifts hosts away from their optimal temperatures, the probability of increased host susceptibility to infectious disease might increase, but the effect will depend on the host species and the direction of the climate shift. Our findings help explain the tremendous variation in species responses to Bd across climates and spatial, temporal and species‐level variation in disease outbreaks associated with extreme weather events that are becoming more common with climate change.     

Fine‐scale climate change: modelling spatial variation in biologically meaningful rates of warming

The existence of fine‐grain climate heterogeneity has prompted suggestions that species may be able to survive future climate change in pockets of suitable microclimate, termed ‘microrefugia’. However, evidence for microrefugia is hindered by lack of understanding of how rates of warming vary across a landscape. Here, we present a model that is applied to provide fine‐grained, multidecadal estimates of temperature change based on the underlying physical processes that influence microclimate. Weather station and remotely derived environmental data were used to construct physical variables that capture the effects of terrain, sea surface temperatures, altitude and surface albedo on local temperatures, which were then calibrated statistically to derive gridded estimates of temperature. We apply the model to the Lizard Peninsula, United Kingdom, to provide accurate (mean error = 1.21 °C; RMS error = 1.63 °C) hourly estimates of temperature at a resolution of 100 m for the period 1977–2014. We show that rates of warming vary across a landscape primarily due to long‐term trends in weather conditions. Total warming varied from 0.87 to 1.16 °C, with the slowest rates of warming evident on north‐east‐facing slopes. This variation contributed to substantial spatial heterogeneity in trends in bioclimatic variables: for example, the change in the length of the frost‐free season varied from +11 to ?54 days and the increase in annual growing degree‐days from 51 to 267 °C days. Spatial variation in warming was caused primarily by a decrease in daytime cloud cover with a resulting increase in received solar radiation, and secondarily by a decrease in the strength of westerly winds, which has amplified the effects on temperature of solar radiation on west‐facing slopes. We emphasize the importance of multidecadal trends in weather conditions in determining spatial variation in rates of warming, suggesting that locations experiencing least warming may not remain consistent under future climate change.     

A spatiotemporal pattern analysis of historical mountain pine beetle outbreaks in British Columbia,Canada

This study documents the spatiotemporal patterns of mountain pine beetle infestations by applying a novel approach based on a landscape infestation dynamics conceptual model in combination with morphological spatial pattern analysis using the mountain pine beetle infested pine mortality data (1960–2010) collected by the annual British Columbia aerial overview survey. The pattern analysis at the provincial level reveals that the 1980s outbreak did not crash as originally thought. The current outbreak is most likely a result of the progressive buildup of the epidemic infestations during the transition period (1985–1995) under favourable weather conditions and substantially improved host resources. This is also true for the Northeast and Cariboo areas of the province specifically, even though the infestations in the Cariboo area remained at incipient‐epidemic levels during the transition period after the 1980s outbreak crashed in 1985. In the Southeast area, the current outbreak apparently continued from the outbreak that initiated in the late 1970s and early 1980s. The 1980s outbreak originated from multiple spatially separate locations whereas the current outbreak initiated from a single location in Tweedsmuir Provincial Park. The centralized and self‐amplifying buildup of the current outbreak implicates at least three substantial expansions that occurred in 2002, 2006, and 2008. This study suggests that at the provincial level, as well as for the Northeast and Southeast areas of the province, the current outbreak is declining but most likely will continue for many years given the ongoing and future warming climate and a large proportion of pines that remain in the habitats of mountain pine beetles. This study also suggests that dispersals, particularly long‐distance dispersal, may play a key role in driving the spread and expansion of the current outbreak although uncertainty remains due to the local dynamics of the beetle populations.     

Historical and projected interactions between climate change and insect voltinism in a multivoltine species

Climate change can cause major changes to the dynamics of individual species and to those communities in which they interact. One effect of increasing temperatures is on insect voltinism, with the logical assumption that increases in surface temperatures would permit multivoltine species to increase the number of generations per year. Though insect development is primarily driven by temperature, most multivoltine insect species rely on photoperiodic cues, which do not change from year‐to‐year or in response to climate warming, to initiate diapause. Thus, the relationship between climate change and voltinism could be complex. We use a phenology model for grape berry moth, Paralobesia viteana (Clemens), which incorporates temperature‐dependent development and diapause termination, and photoperiod‐dependent diapause induction, to explore historical patterns in year‐to‐year voltinism fluctuations. We then extend this model to predict voltinism under varying scenarios of climate change to show the importance of both the quality and quantity of accumulated heat units. We also illustrate that increases in mean surface temperatures > 2 °C can have dramatic effects on insect voltinism by causing a shift in the ovipositional period that currently is subject to diapause‐inducing photoperiods.     

Extreme climatic events drive mammal irruptions: regression analysis of 100‐year trends in desert rainfall and temperature

Extreme climatic events, such as flooding rains, extended decadal droughts and heat waves have been identified increasingly as important regulators of natural populations. Climate models predict that global warming will drive changes in rainfall and increase the frequency and severity of extreme events. Consequently, to anticipate how organisms will respond we need to document how changes in extremes of temperature and rainfall compare to trends in the mean values of these variables and over what spatial scales the patterns are consistent. Using the longest historical weather records available for central Australia – 100 years – and quantile regression methods, we investigate if extreme climate events have changed at similar rates to median events, if annual rainfall has increased in variability, and if the frequency of large rainfall events has increased over this period. Specifically, we compared local (individual weather stations) and regional (Simpson Desert) spatial scales, and quantified trends in median (50th quantile) and extreme weather values (5th, 10th, 90th, and 95th quantiles). We found that median and extreme annual minimum and maximum temperatures have increased at both spatial scales over the past century. Rainfall changes have been inconsistent across the Simpson Desert; individual weather stations showed increases in annual rainfall, increased frequency of large rainfall events or more prolonged droughts, depending on the location. In contrast to our prediction, we found no evidence that intra‐annual rainfall had become more variable over time. Using long‐term live‐trapping records (22 years) of desert small mammals as a case study, we demonstrate that irruptive events are driven by extreme rainfalls (>95th quantile) and that increases in the magnitude and frequency of extreme rainfall events are likely to drive changes in the populations of these species through direct and indirect changes in predation pressure and wildfires.     

Simulating direct and indirect effects of climatic changes on rare perennial plant species in fragmented landscapes

Question: How does climate change influence plant species population dynamics, their time to extinction, and proportion of occupied habitats in a fragmented landscape? Location: Germany and Central European lowland. Methods: We apply a mechanistic general simulation model to test the response of plant functional types to direct and indirect effects of climate change. Three functional types were chosen to represent a set of well‐studied perennial plant species: Juncus atratus, Gentiana pneumonanthe and Primula veris. We link local population dynamics within a heterogeneous, fragmented landscape context. “Species spheres”, i.e. multi‐dimensional parameter ranges rather than single parameter realizations, based on field and literature data served as proxy for life stage transition parameters. Four climatic scenarios summarizing different cumulative weather effects on demographic rates and different local disturbance frequencies were run. The model predicts “time to extinction” (TE) and “proportion of occupied habitat” (POH) as regional indicators for species extinction risk. Results: TE decreased for all species when weather conditions worsened, and even more so when the frequency of local destructive events additionally increased. However, management towards fewer disturbance events could buffer the negative effect of climate to some extent. The magnitude of these responses varied with species type. POH declined with an increase in bad weather as well as with increasing disturbance frequency. The better the climatic conditions, the less severe were disturbances on population performance. Conclusions: The “species spheres” proved to be a valuable approach for predictive trends. As climate change usually also implies destructive events such as land‐use change, flooding or fire, our model on local and regional extinction risks can support conservation issues and management actions.     

Extreme weather‐year sequences have nonadditive effects on environmental nitrogen losses

The frequency and intensity of extreme weather years, characterized by abnormal precipitation and temperature, are increasing. In isolation, these years have disproportionately large effects on environmental N losses. However, the sequence of extreme weather years (e.g., wet–dry vs. dry–wet) may affect cumulative N losses. We calibrated and validated the DAYCENT ecosystem process model with a comprehensive set of biogeophysical measurements from a corn–soybean rotation managed at three N fertilizer inputs with and without a winter cover crop in Iowa, USA. Our objectives were to determine: (i) how 2‐year sequences of extreme weather affect 2‐year cumulative N losses across the crop rotation, and (ii) if N fertilizer management and the inclusion of a winter cover crop between corn and soybean mitigate the effect of extreme weather on N losses. Using historical weather (1951–2013), we created nine 2‐year scenarios with all possible combinations of the driest (“dry”), wettest (“wet”), and average (“normal”) weather years. We analyzed the effects of these scenarios following several consecutive years of relatively normal weather. Compared with the normal–normal 2‐year weather scenario, 2‐year extreme weather scenarios affected 2‐year cumulative NO₃^? leaching (range: ?93 to +290%) more than N₂O emissions (range: ?49 to +18%). The 2‐year weather scenarios had nonadditive effects on N losses: compared with the normal–normal scenario, the dry–wet sequence decreased 2‐year cumulative N₂O emissions while the wet–dry sequence increased 2‐year cumulative N₂O emissions. Although dry weather decreased NO₃^? leaching and N₂O emissions in isolation, 2‐year cumulative N losses from the wet–dry scenario were greater than the dry–wet scenario. Cover crops reduced the effects of extreme weather on NO₃^? leaching but had a lesser effect on N₂O emissions. As the frequency of extreme weather is expected to increase, these data suggest that the sequence of interannual weather patterns can be used to develop short‐term mitigation strategies that manipulate N fertilizer and crop rotation to maximize crop N uptake while reducing environmental N losses.     

Can hyperparasitoids cause large‐scale outbreaks of insect herbivores?

Synchronous population fluctuations occur in many species and have large economic impacts, but remain poorly understood. Dispersal, climate and natural enemies have been hypothesized to cause synchronous population fluctuations across large areas. For example, insect herbivores cause extensive forest defoliation and have many natural enemies, such as parasitoids, that may cause landscape‐scale changes in density. Between outbreaks, parasitoid‐caused mortality of hosts/herbivores is high, but it drops substantially during outbreak episodes. Because of their essential role in regulating herbivore populations, we need to include parasitoids in spatial modelling approaches to more effectively manage insect defoliation. However, classic host‐parasitoid population models predict parasitoid density, and parasitoid density is difficult to relate to host‐level observations of parasitoid‐caused mortality. We constructed a novel model to study how parasitoids affect insect outbreaks at the landscape scale. The model represents metacommunity dynamics, in which herbivore regulation, colonisation and extinction are driven by interactions with the forest, primary parasitoids and hyperparasitoids. The model suggests that parasitoid spatial dynamics can produce landscape‐scale outbreaks. Our results propose the testable prediction that hyperparasitoid prevalence should increase just before the onset of an outbreak because of hyperparasitoid overexploitation. If verified empirically, hyperparasitoid distribution could provide a biotic indicator that an outbreak will occur.     

Forest insects and climate change: long‐term trends in herbivore damage

Long‐term data sets, covering several decades, could help to reveal the effects of observed climate change on herbivore damage to plants. However, sufficiently long time series in ecology are scarce. The research presented here analyzes a long‐term data set collected by the Hungarian Forest Research Institute over the period 1961–2009. The number of hectares with visible defoliation was estimated and documented for several forest insect pest species. This resulted in a unique time series that provides us with the opportunity to compare insect damage trends with trends in weather patterns. Data were analyzed for six lepidopteran species: Thaumetopoea processionea, Tortrix viridana, Rhyacionia buoliana, Malacosoma neustria, Euproctis chrysorrhoea, and Lymantria dispar. All these species exhibit outbreak dynamics in Hungary. Five of these species prefer deciduous tree species as their host plants, whereas R. buoliana is a specialist on Pinus spp. The data were analyzed using general linear models and generalized least squares regression in relation to mean monthly temperature and precipitation. Temperature increased considerably, especially over the last 25 years (+1.6°C), whereas precipitation exhibited no trend over the period. No change in weather variability over time was observed. There was increased damage caused by two species on deciduous trees. The area of damage attributed to R. buoliana decreased over the study period. There was no evidence of increased variability in damage. We conclude that species exhibiting a trend toward outbreak‐level damage over a greater geographical area may be positively affected by changes in weather conditions coinciding with important life stages. Strong associations between the geographical extent of severe damage and monthly temperature and precipitation are difficult to confirm, studying the life‐history traits of species could help to increase understanding of responses to climate change.     

Nest box design for a changing climate: The value of improved insulation

Mean air temperatures and the frequency, intensity and duration of extreme weather events such as heatwaves are increasing due to climate change. Nest boxes experience more variable and extreme temperatures than natural cavities, which may reduce survival and reproductive success of the species which utilize them, but little is known about the factors which drive nest box temperature profiles. We quantified the potential for retrofitted insulation on nest boxes to modify internal temperatures and to mimic the thermal characteristics of natural cavities more closely. We tested three types of materials with insulative or reflective properties which were easy to retrofit to nest boxes: 3‐cm‐thick polystyrene, pleated foil batts and reflective paint. We found that polystyrene and foil batts reduced mean nest box temperatures during the day by 0.31 ± 0.01°C and 0.17 ± 0.01°C, respectively (but up to 5.84°C and 4.02°C). The effects of all insulation types were dependent on the time of day, and only polystyrene had a significant effect at night, with a greater capacity to retain heat (mean 0.21 ± 0.01°C warmer). Contrary to expectations, reflective paint caused a small increase in temperature during the late afternoon. In our study, the temperature modulation provided by insulation was able to match or exceed that due to variation in nest location and surrounding vegetation canopy cover. Our findings show that polystyrene and foil batts may offer effective and tractable means to mitigate the effects of extreme temperatures in nest boxes and thereby help achieve temperature profiles more similar to natural cavities.