A toolbox for studying thermal heterogeneity across spatial scales: from unmanned aerial vehicle imagery to landscape metrics

Re-thinking the environment in landscape genomics

Detecting the extrinsic selective pressures shaping genomic variation is critical for a better understanding of adaptation and for forecasting evolutionary responses of natural populations to changing environmental conditions. With increasing availability of geo-referenced environmental data, landscape genomics provides unprecedented insights into how genomic variation and underlying gene functions affect traits potentially under selection. Yet, the robustness of genotype-environment associations used in landscape genomics remains tempered due to various limitations, including the characteristics of environmental data used, sampling designs employed, and statistical frameworks applied. Here, we argue that using complementary or new environmental data sources and well-informed sampling designs may help improve the detection of selective pressures underlying patterns of local adaptation in various organisms and environments.

Yearly weather variation and surface temperature drives the spatiotemporal dynamics of a threatened butterfly and its host plant

It remains unclear to what extent yearly weather variation and spatial variation in microclimate influences the outcome of interacting plant-animal species and whether responses differ between life stages. We collected data over several years on 46 ha on File Hajdar, Gotland, Sweden, and executed a complete mapping of larva nests (n = 776) and imago (n = 5,952) of the marsh fritillary butterfly Euphydryas aurinia and its host plant Succisa pratensis. The phenology of the butterflies and the major nectar plants visited varied among years. The duration of the adult flight period decreased with increasing ambient air temperatures. The density of butterflies, host plants, and host plant leaf size increased between years with increasing precipitation in the preceding year, and decreased with increasing average ambient air temperature in the preceding year. In 2021–2022 we deployed a unmanned aerial vehicle (UAV) with a high-resolution thermal sensor to measure spatial variation in surface temperatures in the study area. We found that survival from the egg to the larva stage increased with increasing surface temperature and host plant density. Host plants and larva nests generally occupied warmer microhabitats compared to imago butterflies. The results further suggested that the relationships linking surface temperature to the densities of imago, larva, host plants, and leaf size differed qualitatively between years. In 2017, larva nests and host plant density increased with increasing surface temperatures, and butterflies showed a non-linear response with a density peak at intermediate temperatures. As a result of the extreme drought in 2018 there was a reduction in maximum leaf size, and in the densities of plants, larvae, and butterflies. Moreover, the slopes of the relationships linking the density of larvae, butterflies, and plants to temperature shifted from linear positive to negative or curvilinear. Our findings demonstrate how yearly weather variation and heterogeneous surface temperatures can drive the spatiotemporal distribution and dynamics of butterflies and their host plants. The context specificity of the responses indicated by our results makes it challenging to project how climate change will affect the dynamics of ecological communities.

High resolution thermal remote sensing and the limits of species' tolerance

Extinction risks for many insect species, particularly across very broad spatial extents, have been linked to the growing frequency and severity of temperatures that exceed the boundaries of their realized niches. Measurement and mitigation of such impacts is hindered by the availability of high-resolution measurements of species-specific severity of extreme weather, especially temperature. While techniques enabling interpolation of broad-scale remote sensing metrics are vital for such efforts, direct remote sensing measurements of thermal conditions could improve habitat management by providing detailed insights that interpolative approaches cannot. Advances in unmanned aerial vehicle (UAV) technology have created opportunities to better evaluate the role of microclimates in local species extinctions. Here, we develop a method to create high-resolution maps of microclimates using UAV and thermal imaging technology that use species' realized niche boundaries to assess potential effects of severity of extreme temperatures. We generated air temperature maps (5 cm resolution) and canopy height maps (1 cm resolution) for 15 sites in a rare alvar ecosystem in eastern Ontario. We validated these remote sensing observations against independent, in situ temperature observations using iButtons. Temperature observations were accurate and related to physical heterogeneity in alvar habitats. We converted temperature measures into estimates of proximity of thermal niche boundaries for three butterfly species found during field surveys. This is the first time that this method has been applied to high resolution remote sensing observations and offers potential to assess the availability and adequacy of microclimates within habitats at resolutions relevant for conservation management.

Detection of Forest Tree Losses in Côte d’Ivoire Using Drone Aerial Images

The fight against deforestation and forest degradation is now a major challenge for the preservation of global forest ecosystems. The remote sensing forest monitoring methods that are currently deployed are not always adapted to the Ivorian context because of the high cloud cover, diversity of shaded crops, and land clearing techniques. This study proposes a drone-based approach to assess intra-annual tree losses in the Bossématié classified forest. The method used is based on a detection analysis of tree losses in forest areas from a time series of aerial images acquired by drones from November 2018 to April 2019 on five sites in the studied forest. Based on photogrammetric models and photointerpretation, tree heights and tree crown sizes were estimated. Then, tree losses were detected based on the variation of tree heights during the study period. An analysis of the distribution of tree heights in Bossématié classified forest reveals that the maximum tree height was 65.06 m in November 2018 and 64.07 m in April 2019 with an average tree height of 34.29–37.00 m in November 2018 and 34.63–36.88 m in April 2019. The average tree crown area, meanwhile, was estimated to be 152 m². With an estimation accuracy of about 97%, these tree structural data indicate a minimum loss of 107 trees corresponding to a clearing area of 2 ha across all the surveyed sites from November 2018 to April 2019. This forest monitoring approach shows a considerable local loss of biodiversity and should be involved in the implementation of preservation, rehabilitation, and deployment strategies in an operational deforestation monitoring system in Côte d’Ivoire.

Recent advances in the remote sensing of insects

Remote sensing has revolutionised many aspects of ecological research, enabling spatiotemporal data to be collected in an efficient and highly automated manner. The last two decades have seen phenomenal growth in capabilities for high-resolution remote sensing that increasingly offers opportunities to study small, but ecologically important organisms, such as insects. Here we review current applications for using remote sensing within entomological research, highlighting the emerging opportunities that now arise through advances in spatial, temporal and spectral resolution. Remote sensing can be used to map environmental variables, such as habitat, microclimate and light pollution, capturing data on topography, vegetation structure and composition, and luminosity at spatial scales appropriate to insects. Such data can also be used to detect insects indirectly from the influences that they have on the environment, such as feeding damage or nest structures, whilst opportunities for directly detecting insects are also increasingly available. Entomological radar and light detection and ranging (LiDAR), for example, are transforming our understanding of aerial insect abundance and movement ecology, whilst ultra-high spatial resolution drone imagery presents tantalising new opportunities for direct observation. Remote sensing is rapidly developing into a powerful toolkit for entomologists, that we envisage will soon become an integral part of insect science.

Floral infrared emissivity estimates using simple tools

BACKGROUND

Floral temperature has important consequences for plant biology, and accurate temperature measurements are therefore important to plant research. Thermography, also referred to as thermal imaging, is beginning to be used more frequently to measure and visualize floral temperature. Accurate thermographic measurements require information about the object's emissivity (its capacity to emit thermal radiation with temperature), to obtain accurate temperature readings. However, there are currently no published estimates of floral emissivity available. This is most likely to be due to flowers being unsuitable for the most common protocols for emissivity estimation. Instead, researchers have used emissivity estimates collected on vegetative plant tissue when conducting floral thermography, assuming these tissues to have the same emissivity. As floral tissue differs from vegetative tissue, it is unclear how appropriate and accurate these vegetative tissue emissivity estimates are when they are applied to floral tissue.

RESULTS

We collect floral emissivity estimates using two protocols, using a thermocouple and a water bath, providing a guide for making estimates of floral emissivity that can be carried out without needing specialist equipment (apart from the thermal camera). Both protocols involve measuring the thermal infrared radiation from flowers of a known temperature, providing the required information for emissivity estimation. Floral temperature is known within these protocols using either a thermocouple, or by heating the flowers within a water bath. Emissivity estimates indicate floral emissivity is high, near 1, at least across petals. While the two protocols generally indicated the same trends, the water bath protocol gave more realistic and less variable estimates. While some variation with flower species and location on the flower is observed in emissivity estimates, these are generally small or can be explained as resulting from artefacts of these protocols, relating to thermocouple or water surface contact quality.

CONCLUSIONS

Floral emissivity appears to be high, and seems quite consistent across most flowers and between species, at least across petals. A value near 1, for example 0.98, is recommended for accurate thermographic measurements of floral temperature. This suggests that the similarly high values based on vegetation emissivity estimates used by previous researchers were appropriate.

Predicting the effects of climate change on incubation in reptiles: methodological advances and new directions

The unprecedented advancement of global climate change is affecting thermal conditions across spatial and temporal scales. Reptiles with temperature-dependent sex determination (TSD) are uniquely vulnerable to even fine-scale variation in incubation conditions and are a model system for investigating the impacts of shifting temperatures on key physiological and life-history traits. The ways in which current and predicted future climatic conditions translate from macro- to ultra-fine scale temperature traces in subterranean nests is insufficiently understood. Reliably predicting the ways in which fine-scale, daily and seasonally fluctuating nest temperatures influence embryonic development and offspring phenotypes is a goal that remains constrained by many of the same logistical challenges that have persisted throughout more than four decades of research on TSD. However, recent advances in microclimate and developmental modeling should allow us to move farther away from relatively coarse metrics with limited predictive capacity and towards a fully mechanistic model of TSD that can predict incubation conditions and phenotypic outcomes for a variety of reptile species across space and time and for any climate scenario.

Hot and bothered: The role of behaviour and microclimates in buffering species from rising temperatures

In Focus: Bladon, A. J., Lewis, M., Bladon, E. K., Buckton, S. J., Corbett, S., Ewing, S. R., … Turner, E. C. (2020). How butterflies keep their cool: Physical and ecological traits influence thermoregulatory ability and population trends. Journal of Animal Ecology. https://doi.org/10.1111/1365-2656.13319 Threatened with rising average temperatures and the new normal of climate extremes, species that cannot keep pace with climate change must adapt where they are, or face extinction. The ranges of many British butterflies have indeed extended northwards as the climate has warmed, but this option is increasingly restricted by the expansion and intensification of urban and agricultural lands. On a day-to-day basis, butterflies can thermoregulate using behaviours such as adjusting their wing positioning or moving into suitable microclimates. The extent to which these two options buffer individuals from free-air temperature, however, is not well known. Nor is the extent to which the different mechanisms are exploited by different species, and whether that has had any bearing on species' population trends over the time-scale of recent climate change. Using a simple and easily replicated approach, Bladon et al. (2020) were able to quantify intra- and interspecific variation in buffering ability, and species' relative reliance on the two thermoregulatory mechanisms of wing adjustment versus microclimate selection. The authors report marked variation in buffering capacity, correlated with wing size, wing colouration and taxonomic family. Species also differed in their thermoregulatory behaviours, with some - such as the Ringlet Aphantopus hyperantus and Large Skipper Ochlodes sylvanus-achieving impressive buffering through wing positioning. Others, like the Brown Argus Aricia agestis and Small Heath Coenonympha pamphilus, were more reliant on microclimate selection, and these were the species most likely to have shown declining population trends over the past 40 years. The study underscores the importance of individual thermoregulatory behaviours for understanding species' vulnerability to climate change. In combination with much improved methods for measuring and modelling climate at biologically relevant scales, the approach of Bladon et al. (2020) can and should be extended to identify the places and species most at risk, and the steps that conservation practitioners can take to maximise resilience to climate change. Much attention has been given to improving habitat connectivity to facilitate range shifts, but we should also consider how microclimate availability can be enhanced to allow species to manage when they cannot move.

Ecologically relevant thermal fluctuations enhance offspring fitness: biological and methodological implications for studies of thermal developmental plasticity

Natural thermal environments are notably complex and challenging to mimic in controlled studies. Consequently, our understanding of the ecological relevance and underlying mechanisms of organismal responses to thermal environments is often limited. For example, studies of thermal developmental plasticity have provided key insights into the ecological consequences of temperature variation, but most laboratory studies use treatments that do not reflect natural thermal regimes. While controlling other important factors, we compared the effects of naturally fluctuating temperatures with those of commonly used laboratory regimes on development of lizard embryos and offspring phenotypes and survival. We incubated eggs in four treatments: three that followed procedures commonly used in the literature, and one that precisely mimicked naturally fluctuating nest temperatures. To explore context-dependent effects, we replicated these treatments across two seasonal regimes: relatively cool temperatures from nests constructed early in the season and warm temperatures from late-season nests. We show that natural thermal fluctuations have a relatively small effect on developmental variables but enhance hatchling performance and survival at cooler temperatures. Thus, natural thermal fluctuations are important for successful development and simpler approximations (e.g. repeated sine waves, constant temperatures) may poorly reflect natural systems under some conditions. Thus, the benefits of precisely replicating real-world temperatures in controlled studies may outweigh logistical costs. Although patterns might vary according to study system and research goals, our methodological approach demonstrates the importance of incorporating natural variation into controlled studies and provides biologists interested in thermal ecology with a framework for validating the effectiveness of commonly used methods.

Unmanned aerial vehicles for biodiversity-friendly agricultural landscapes - A systematic review

The development of biodiversity-friendly agricultural landscapes is of major importance to meet the sustainable development challenges of our time. The emergence of unmanned aerial vehicles (UAVs), i.e. drones, has opened a new set of research and management opportunities to achieve this goal. On the one hand, this review summarizes UAV applications in agricultural landscapes, focusing on biodiversity conservation and agricultural land monitoring, based on a systematic review of the literature that resulted in 550 studies. Additionally, the review proposes how to integrate UAV research in these fields and point to new potential applications that may contribute to biodiversity-friendly agricultural landscapes. UAV-based imagery can be used to identify and monitor plants, floral resources and animals, facilitating the detection of quality habitats with high prediction power. Through vegetation indices derived from their sensors, UAVs can estimate biomass, monitor crop plant health and stress, detect pest or pathogen infestations, monitor soil fertility and target patches of high weed or invasive plant pressure, allowing precise management practices and reduced agrochemical input. Thereby, UAVs are helping to design biodiversity-friendly agricultural landscapes and to mitigate yield-biodiversity trade-offs. In conclusion, UAV applications have become a major means of biodiversity conservation and biodiversity-friendly management in agriculture, while latest developments, such as the miniaturization and decreasing costs of hyperspectral sensors, promise many new applications for the future.

Using UAV Visible Images to Estimate the Soil Moisture of Steppe

Although unmanned aerial vehicles (UAVs) have been utilized in many aspects of steppe management, they have not been commonly used to monitor the soil moisture of steppes. To explore the technology of detecting soil moisture by UAV in a typical steppe, we conducted a watered test in the Loess Plateau of China, quantitatively revealing the relationship between the surface soil moisture and the visible images captured using an UAV. The results showed that the surface soil moisture was significantly correlated with the brightness of UAV visible images, and the surface soil moisture could be estimated based on the brightness of the visible images of the UAV combined with vegetation coverage. This study addresses the problem of soil moisture measurement in flat regions of arid and semi-arid steppes at the mesoscale, and contributes to the popularization of the use of UAVs in steppe ecological research.

Adaptation to the abiotic environment in insects: the influence of variability on ecophysiology and evolutionary genomics

Advances in tools to gather environmental, phenotypic, and molecular data have accelerated our ability to detect abiotic drivers of variation across the genome-to-phenome spectrum in model and non-model insects. However, differences in the spatial and temporal resolution of these data sets may create gaps in our understanding of linkages between environment, genotype, and phenotype that yield missed or misleading results about adaptive variation. In this review we highlight sources of variability that might impact studies of phenotypic and 'omic environmental adaptation, challenges to collecting data at relevant scales, and possible solutions that link intensive fine-scale reductionist studies of mechanisms to large-scale biogeographic patterns.

Mapping physiology: biophysical mechanisms define scales of climate change impacts

The rocky intertidal zone is a highly dynamic and thermally variable ecosystem, where the combined influences of solar radiation, air temperature and topography can lead to differences greater than 15°C over the scale of centimetres during aerial exposure at low tide. For most intertidal organisms this small-scale heterogeneity in microclimates can have enormous influences on survival and physiological performance. However, the potential ecological importance of environmental heterogeneity in determining ecological responses to climate change remains poorly understood. We present a novel framework for generating spatially explicit models of microclimate heterogeneity and patterns of thermal physiology among interacting organisms. We used drone photogrammetry to create a topographic map (digital elevation model) at a resolution of 2 × 2 cm from an intertidal site in Massachusetts, which was then fed into to a model of incident solar radiation based on sky view factor and solar position. These data were in turn used to drive a heat budget model that estimated hourly surface temperatures over the course of a year (2017). Body temperature layers were then converted to thermal performance layers for organisms, using thermal performance curves, creating 'physiological landscapes' that display spatially and temporally explicit patterns of 'microrefugia'. Our framework shows how non-linear interactions between these layers lead to predictions about organismal performance and survivorship that are distinct from those made using any individual layer (e.g. topography, temperature) alone. We propose a new metric for quantifying the 'thermal roughness' of a site (RqT, the root mean square of spatial deviations in temperature), which can be used to quantify spatial and temporal variability in temperature and performance at the site level. These methods facilitate an exploration of the role of micro-topographic variability in driving organismal vulnerability to environmental change using both spatially explicit and frequency-based approaches.

Using Unmanned Aerial Systems (UAS) and Object-Based Image Analysis (OBIA) for Measuring Plant-Soil Feedback Effects on Crop Productivity

Unmanned aerial system (UAS) acquired high-resolution optical imagery and object-based image analysis (OBIA) techniques have the potential to provide spatial crop productivity information. In general, plant-soil feedback (PSF) field studies are time-consuming and laborious which constrain the scale at which these studies can be performed. Development of non-destructive methodologies is needed to enable research under actual field conditions and at realistic spatial and temporal scales. In this study, the influence of six winter cover crop (WCC) treatments (monocultures Raphanus sativus, Lolium perenne, Trifolium repens, Vicia sativa and two species mixtures) on the productivity of succeeding endive (Cichorium endivia) summer crop was investigated by estimating crop volume. A three-dimensional surface and terrain model were photogrammetrically reconstructed from UAS imagery, acquired on 1 July 2015 in Wageningen, the Netherlands. Multi-resolution image segmentation (MIRS) and template matching algorithms were used in an integrated workflow to detect individual crops (accuracy = 99.8%) and delineate C. endivia crop covered area (accuracy = 85.4%). Mean crop area (R = 0.61) and crop volume (R = 0.71) estimates had strong positive correlations with in situ measured dry biomass. Productivity differences resulting from the WCC treatments were greater for estimated crop volume in comparison to in situ biomass, the legacy of Raphanus was most beneficial for estimated crop volume. The perennial ryegrass L. perenne treatment resulted in a significantly lower production of C. endivia. The developed workflow has potential for PSF studies as well as precision farming due to its flexibility and scalability. Our findings provide insight into the potential of UAS for determining crop productivity on a large scale.

Thermal landscape change as a driver of ectotherm responses to plant invasions

A growing body of research demonstrates the impacts of invasive alien plants on native animals, but few studies consider thermal effects as a driver of the responses of native organisms. As invasive alien plants establish and alter the composition and arrangement of plant communities, the thermal landscapes available to ectotherms also change. Our study reviews the research undertaken to date on the thermal effects of alien plant invasions on native reptiles, amphibians, insects and arachnids. The 37 studies published between 1970 and early 2019 portray an overall detrimental effect of invasive plants on thermal landscapes, ectothermic individuals' performance and species abundance, diversity and composition. With a case study of a lizard species, we illustrate the use of thermal ecology tools in plant invasion research and test the generality of alien plant effects: changes in thermoregulation behaviour in invaded landscapes varied depending on the level of invasion and lizard traits. Together, the literature review and case study show that thermal effects of alien plants on ectotherms can be substantial albeit context-dependent. Further research should cover multiple combinations of native/invasive plant growth forms, invasion stages and ectotherm traits. More attention is also needed to test causality along the chain of effects from thermal landscapes to individuals, populations and communities.

Effects of the ephemeral stream on plant species diversity and distribution in an alluvial fan of arid desert region: An application of a low altitude UAV

Biodiversity conservation, plant growth and spatial distribution of plant species are the central issues in contemporary community ecology. Ephemeral stream may influence soil properties, which in turn may determine biodiversity and function of an ecosystem in alluvial fan of arid desert region. Ephemeral stream is one of the most common natural disturbances, yet the effects of the ephemeral stream on plant communities in terms of species diversity and plant species distribution remain poorly studied. In this study, the information of species distribution, ephemeral stream beds (‘washes’), and the characteristics of plant growth, i.e. height, crown area, were interpreted at different heights using the images of low altitude unmanned aerial vehicle (UAV). After that, soil properties such as soil texture (sand, silt and clay), soil water content, pH, soil organic matter, soil electric conductivity, soil bulk density and the percentage of gravel content, and their relationships with UAV data were assessed in order to explore the influences of ephemeral stream on species diversity, plant growth characteristics and species distribution in an alluvial fan of arid desert region. The results showed that deep-rooted plants were only distributed in washes whereas shallow-rooted plants were distributed in both washes and the outside of washes (‘non-washes’). Species richness was significantly higher in washes than that in non-washes whereas the opposite pattern was true for abundance. Soil properties, plant height and crown area were higher in washes than that in non-washes. Plant height, crown area and the total number of individual plants increased with increasing wash width and per unit length of stream flow. This study highlights that the coupling factors of ephemeral stream, such as soil erosion, particle transport and sedimentation, can dramatically cause changes in soil properties and total number of individual plants, and hence, can influence species diversity, plant growth characteristics and spatial distribution of plant species in an alluvial fan of arid desert regions.

Drones for Conservation in Protected Areas: Present and Future

Park managers call for cost-effective and innovative solutions to handle a wide variety of environmental problems that threaten biodiversity in protected areas. Recently, drones have been called upon to revolutionize conservation and hold great potential to evolve and raise better-informed decisions to assist management. Despite great expectations, the benefits that drones could bring to foster effectiveness remain fundamentally unexplored. To address this gap, we performed a literature review about the use of drones in conservation. We selected a total of 256 studies, of which 99 were carried out in protected areas. We classified the studies in five distinct areas of applications: “wildlife monitoring and management”; “ecosystem monitoring”; “law enforcement”; “ecotourism”; and “environmental management and disaster response”. We also identified specific gaps and challenges that would allow for the expansion of critical research or monitoring. Our results support the evidence that drones hold merits to serve conservation actions and reinforce effective management, but multidisciplinary research must resolve the operational and analytical shortcomings that undermine the prospects for drones integration in protected areas.

Mango Yield Mapping at the Orchard Scale Based on Tree Structure and Land Cover Assessed by UAV

In the value chain, yields are key information for both growers and other stakeholders in market supply and exports. However, orchard yields are often still based on an extrapolation of tree production which is visually assessed on a limited number of trees; a tedious and inaccurate task that gives no yield information at a finer scale than the orchard plot. In this work, we propose a method to accurately map individual tree production at the orchard scale by developing a trade-off methodology between mechanistic yield modelling and extensive fruit counting using machine vision systems. A methodological toolbox was developed and tested to estimate and map tree species, structure, and yields in mango orchards of various cropping systems (from monocultivar to plurispecific orchards) in the Niayes region, West Senegal. Tree structure parameters (height, crown area and volume), species, and mango cultivars were measured using unmanned aerial vehicle (UAV) photogrammetry and geographic, object-based image analysis. This procedure reached an average overall accuracy of 0.89 for classifying tree species and mango cultivars. Tree structure parameters combined with a fruit load index, which takes into account year and management effects, were implemented in predictive production models of three mango cultivars. Models reached satisfying accuracies with R2 greater than 0.77 and RMSE% ranging from 20% to 29% when evaluated with the measured production of 60 validation trees. In 2017, this methodology was applied to 15 orchards overflown by UAV, and estimated yields were compared to those measured by the growers for six of them, showing the proper efficiency of our technology. The proposed method achieved the breakthrough of rapidly and precisely mapping mango yields without detecting fruits from ground imagery, but rather, by linking yields with tree structural parameters. Such a tool will provide growers with accurate yield estimations at the orchard scale, and will permit them to study the parameters that drive yield heterogeneity within and between orchards.

Review: Using physiologically based models to predict population responses to phytochemicals by wild vertebrate herbivores

To understand how foraging decisions impact individual fitness of herbivores, nutritional ecologists must consider the complex in vivo dynamics of nutrient-nutrient interactions and nutrient-toxin interactions associated with foraging. Mathematical modeling has long been used to make foraging predictions (e.g. optimal foraging theory) but has largely been restricted to a single currency (e.g. energy) or using simple indices of nutrition (e.g. fecal nitrogen) without full consideration of physiologically based interactions among numerous co-ingested phytochemicals. Here, we describe a physiologically based model (PBM) that provides a mechanistic link between foraging decisions and demographic consequences. Including physiological mechanisms of absorption, digestion and metabolism of phytochemicals in PBMs allows us to estimate concentrations of ingested and interacting phytochemicals in the body. Estimated phytochemical concentrations more accurately link intake of phytochemicals to changes in individual fitness than measures of intake alone. Further, we illustrate how estimated physiological parameters can be integrated with the geometric framework of nutrition and into integral projection models and agent-based models to predict fitness and population responses of vertebrate herbivores to ingested phytochemicals. The PBMs will improve our ability to understand the foraging decisions of vertebrate herbivores and consequences of those decisions and may help identify key physiological mechanisms that underlie diet-based ecological adaptations.

Structure is more important than physiology for estimating intracanopy distributions of leaf temperatures

Estimating leaf temperature distributions (LTDs) in canopies is crucial in forest ecology. Leaf temperature affects the exchange of heat, water, and gases, and it alters the performance of leaf-dwelling species such as arthropods, including pests and invaders. LTDs provide spatial variation that may allow arthropods to thermoregulate in the face of long-term changes in mean temperature or incidence of extreme temperatures. Yet, recording LTDs for entire canopies remains challenging. Here, we use an energy-exchange model (RATP) to examine the relative roles of climatic, structural, and physiological factors in influencing three-dimensional LTDs in tree canopies. A Morris sensitivity analysis of 13 parameters showed, not surprisingly, that climatic factors had the greatest overall effect on LTDs. In addition, however, structural parameters had greater effects on LTDs than did leaf physiological parameters. Our results suggest that it is possible to infer forest canopy LTDs from the LTDs measured or simulated just at the surface of the canopy cover over a reasonable range of parameter values. This conclusion suggests that remote sensing data can be used to estimate 3D patterns of temperature variation from 2D images of vegetation surface temperatures. Synthesis and applications. Estimating the effects of LTDs on natural plant-insect communities will require extending canopy models beyond their current focus on individual species or crops. These models, however, contain many parameters, and applying the models to new species or to mixed natural canopies depends on identifying the parameters that matter most. Our results suggest that canopy structural parameters are more important determinants of LTDs than are the physiological parameters that tend to receive the most empirical attention.

Tropical forests are thermally buffered despite intensive selective logging

Tropical rainforests are subject to extensive degradation by commercial selective logging. Despite pervasive changes to forest structure, selectively logged forests represent vital refugia for global biodiversity. The ability of these forests to buffer temperature-sensitive species from climate warming will be an important determinant of their future conservation value, although this topic remains largely unexplored. Thermal buffering potential is broadly determined by: (i) the difference between the "macroclimate" (climate at a local scale, m to ha) and the "microclimate" (climate at a fine-scale, mm to m, that is distinct from the macroclimate); (ii) thermal stability of microclimates (e.g. variation in daily temperatures); and (iii) the availability of microclimates to organisms. We compared these metrics in undisturbed primary forest and intensively logged forest on Borneo, using thermal images to capture cool microclimates on the surface of the forest floor, and information from dataloggers placed inside deadwood, tree holes and leaf litter. Although major differences in forest structure remained 9-12 years after repeated selective logging, we found that logging activity had very little effect on thermal buffering, in terms of macroclimate and microclimate temperatures, and the overall availability of microclimates. For 1°C warming in the macroclimate, temperature inside deadwood, tree holes and leaf litter warmed slightly more in primary forest than in logged forest, but the effect amounted to <0.1°C difference between forest types. We therefore conclude that selectively logged forests are similar to primary forests in their potential for thermal buffering, and subsequent ability to retain temperature-sensitive species under climate change. Selectively logged forests can play a crucial role in the long-term maintenance of global biodiversity.

Fine-Scale Microclimatic Variation Can Shape the Responses of Organisms to Global Change in Both Natural and Urban Environments

When predicting the response of organisms to global change, models use measures of climate at a coarse resolution from general circulation models or from downscaled regional models. Organisms, however, do not experience climate at such large scales. The climate heterogeneity over a landscape and how much of that landscape an organism can sample will determine ultimately the microclimates experienced by organisms. This past few decades has seen an important increase in the number of studies reporting microclimatic patterns at small scales. This synthesis intends to unify studies reporting microclimatic heterogeneity (mostly temperature) at various spatial scales, to infer any emerging trends, and to discuss the causes and consequences of such heterogeneity for organismal performance and with respect to changing land use patterns and climate. First, we identify the environmental drivers of heterogeneity across the various spatial scales that are pertinent to ectotherms. The thermal heterogeneity at the local and micro-scales is mostly generated by the architecture or the geometrical features of the microhabitat. Then, the thermal heterogeneity experienced by individuals is modulated by behavior. Second, we survey the literature to quantify thermal heterogeneity from the micro-scale up to the scale of a landscape in natural habitats. Despite difficulties in compiling studies that differ much in their design and aims, we found that there is as much thermal heterogeneity across micro-, local and landscape scales, and that the temperature range is large in general (>9 °C on average, and up to 26 °C). Third, we examine the extent to which urban habitats can be used to infer the microclimatic patterns of the future. Urban areas generate globally drier and warmer microclimatic patterns and recent evidence suggest that thermal traits of ectotherms are adapted to them. Fourth, we explore the interplay between microclimate heterogeneity and the behavioral thermoregulatory abilities of ectotherms in setting their overall performance. We used a random walk framework to show that the thermal heterogeneity allows a more precise behavioral thermoregulation and a narrower temperature distribution of the ectotherm compared to less heterogeneous microhabitats. Finally, we discuss the potential impacts of global change on the fine scale mosaics of microclimates. The amplitude of change may differ between spatial scales. In heterogeneous microhabitats, the amplitude of change at micro-scale, caused by atmospheric warming, can be substantial while it can be limited at the local and landscape scales. We suggest that the warming signal will influence species performance and biotic interactions by modulating the mosaic of microclimates.

Microclimate Data Improve Predictions of Insect Abundance Models Based on Calibrated Spatiotemporal Temperatures

A large body of literature has recently recognized the role of microclimates in controlling the physiology and ecology of species, yet the relevance of fine-scale climatic data for modeling species performance and distribution remains a matter of debate. Using a 6-year monitoring of three potato moth species, major crop pests in the tropical Andes, we asked whether the spatiotemporal resolution of temperature data affect the predictions of models of moth performance and distribution. For this, we used three different climatic data sets: (i) the WorldClim dataset (global dataset), (ii) air temperature recorded using data loggers (weather station dataset), and (iii) air crop canopy temperature (microclimate dataset). We developed a statistical procedure to calibrate all datasets to monthly and yearly variation in temperatures, while keeping both spatial and temporal variances (air monthly temperature at 1 km² for the WorldClim dataset, air hourly temperature for the weather station, and air minute temperature over 250 m radius disks for the microclimate dataset). Then, we computed pest performances based on these three datasets. Results for temperature ranging from 9 to 11°C revealed discrepancies in the simulation outputs in both survival and development rates depending on the spatiotemporal resolution of the temperature dataset. Temperature and simulated pest performances were then combined into multiple linear regression models to compare predicted vs. field data. We used an additional set of study sites to test the ability of the results of our model to be extrapolated over larger scales. Results showed that the model implemented with microclimatic data best predicted observed pest abundances for our study sites, but was less accurate than the global dataset model when performed at larger scales. Our simulations therefore stress the importance to consider different temperature datasets depending on the issue to be solved in order to accurately predict species abundances. In conclusion, keeping in mind that the mismatch between the size of organisms and the scale at which climate data are collected and modeled remains a key issue, temperature dataset selection should be balanced by the desired output spatiotemporal scale for better predicting pest dynamics and developing efficient pest management strategies.