This article highlights how the loose definition of the term 'refugia' has led to discrepancies in methods used to assess the vulnerability of species to the current trend of rising global ...temperatures. The term 'refugia' is commonly used without distinguishing between macrorefugia and microrefugia, ex situ refugia and in situ refugia, glacial and interglacial refugia or refugia based on habitat stability and refugia based on climatic stability. It is not always clear which definition is being used, and this makes it difficult to assess the appropriateness of the methods employed. For example, it is crucial to develop accurate fine-scale climate grids when identifying microrefugia, but coarse-scale macroclimate might be adequate for determining macrorefugia. Similarly, identifying in situ refugia might be more appropriate for species with poor dispersal ability but this may overestimate the extinction risk for good dispersers. More care needs to be taken to properly define the context when referring to refugia from climate change so that the validity of methods and the conservation significance of refugia can be assessed.
Forest microclimates contrast strongly with the climate outside forests. To fully understand and better predict how forests' biodiversity and functions relate to climate and climate change, ...microclimates need to be integrated into ecological research. Despite the potentially broad impact of microclimates on the response of forest ecosystems to global change, our understanding of how microclimates within and below tree canopies modulate biotic responses to global change at the species, community and ecosystem level is still limited. Here, we review how spatial and temporal variation in forest microclimates result from an interplay of forest features, local water balance, topography and landscape composition. We first stress and exemplify the importance of considering forest microclimates to understand variation in biodiversity and ecosystem functions across forest landscapes. Next, we explain how macroclimate warming (of the free atmosphere) can affect microclimates, and vice versa, via interactions with land‐use changes across different biomes. Finally, we perform a priority ranking of future research avenues at the interface of microclimate ecology and global change biology, with a specific focus on three key themes: (1) disentangling the abiotic and biotic drivers and feedbacks of forest microclimates; (2) global and regional mapping and predictions of forest microclimates; and (3) the impacts of microclimate on forest biodiversity and ecosystem functioning in the face of climate change. The availability of microclimatic data will significantly increase in the coming decades, characterizing climate variability at unprecedented spatial and temporal scales relevant to biological processes in forests. This will revolutionize our understanding of the dynamics, drivers and implications of forest microclimates on biodiversity and ecological functions, and the impacts of global changes. In order to support the sustainable use of forests and to secure their biodiversity and ecosystem services for future generations, microclimates cannot be ignored.
Below‐canopy forest microclimates contrast strongly with the climate outside forests due to the presence of trees and shrubs. Here we review the drivers and the importance of forest microclimates in the face of climate change, and perform a priority ranking of future research avenues.
In the face of the growing challenges brought about by human activities, effective planning and decision-making in biodiversity and ecosystem conservation, restoration, and sustainable development ...are urgently needed. Ecological models can play a key role in supporting this need and helping to safeguard the natural assets that underpin human wellbeing and support life on land and below water (United Nations Sustainable Development Goals; SDG 15 & 14). The urgency and complexity of safeguarding forest (SDG 15.2) and mountain ecosystems (SDG 15.4), for example, and halting decline in biodiversity (SDG 15.5) in the Anthropocene requires a re-envisioning of how ecological models can best support the comprehensive assessments of biodiversity and its change that are required for successful action.
A key opportunity to advance ecological modeling for both predictive and explanatory purposes arises through a collaboration between ecologists and the Earth observation community, and a close integration of remote sensing and species distribution models. Remote sensing products have the capacity to provide continuous spatiotemporal information about key factors driving the distribution of organisms, therefore improving both the use and accuracy of these models for management and planning.
Here we first survey the literature on remote sensing data products available to ecological modelers interested in improving predictions of species range dynamics under global change. We specifically explore the key biophysical processes underlying the distribution of species in the Anthropocene including climate variability, changes in land cover, and disturbances. We then discuss potential synergies between the ecological modeling and remote sensing communities, and highlight opportunities to close the data and conceptual gaps that currently impede a more effective application of remote sensing for the monitoring and modeling of ecological systems. Specific attention is given to how potential collaborations between the two communities could lead to new opportunities to report on progress towards global agendas - such as the Agenda 2030 for sustainable development of the United Nations or the Post-2020 Global Biodiversity Framework of the Convention for Biological Diversity, and help guide conservation and management strategies towards sustainability.
•SDMs inform environmental interventions and policies towards achieving the SDGs.•RS helps fill data gaps and improve spatio-temporal transferability of projections.•Biodiversity monitoring in the Anthropocene needs close integration of RS in SDMs.•Joint ventures between the ecological modeling and RS communities are needed.
Ecologists are increasingly recognizing the conservation significance of microrefugia, but it is inherently difficult to locate these small patches with unusual climates, and hence they are also ...referred to as cryptic refugia. Here we introduce a new methodology to quantify and locate potential microrefugia using fine‐scale topoclimatic grids that capture extreme conditions, stable climates, and distinct differences from the surrounding matrix. We collected hourly temperature data from 150 sites in a large (200 km by 300 km) and diverse region of New South Wales, Australia, for a total of 671 days over 2 years. Sites spanned a range of habitats including coastal dune shrublands, eucalypt forests, exposed woodland ridges, sheltered rainforest gullies, upland swamps, and lowland pastures. Climate grids were interpolated using a regional regression approach based on elevation, distance to coast, canopy cover, latitude, cold‐air drainage, and topographical exposure to winds and radiation. We identified extreme temperatures on two separate climatic gradients: the 5th percentile of minimum temperatures and the 95th percentile of maximum temperatures. For each gradient, climatic stability was assessed on three different time scales (intra‐seasonal, intra‐annual and inter‐annual). Differences from the matrix were assessed using a moving window with a 5 km radius. We averaged the Z‐scores for these extreme, stable and isolated climates to identify potential locations of microrefugia. We found that our method successfully predicted the location of communities that were considered to occupy refugia, such as rainforests that have progressively contracted in distribution over the last 2.5 million years, and alpine grasslands that have contracted over the last 15 thousand years. However, the method was inherently sensitive to the gradient selected and other aspects of the modelling process. These uncertainties could be dealt with in a conservation planning context by repeating the methodology with various parameterizations and identifying areas that were consistently identified as microrefugia.
•Moisture reduces exposure to temperature extremes, facilitating climate refugia.•Variability of air temperatures related to humidity, but soil temperatures to VPD.•Moisture differentially affects ...spatial distribution of soil and air temperatures.•Microrefugia will be more apparent under dry conditions.
Climate change poses significant threats to biodiversity, but some species may be able to escape its effects in small locations with unusual and stable climates (microrefugia). However, there are still great uncertainties about where microrefugia are located, and the exact role that moisture plays in buffering extreme temperatures. In this study we quantified the effects of moisture on the distribution and variability of near-surface soil and air temperatures. We collected hourly 1cm soil and 5cm air temperatures and humidities at 111 sites from May 2011 to March 2012. Sites were diverse in terms of elevation (2–1428m), distance from coast (180m–403km), canopy cover (0–100%), topographic exposure, and susceptibility to cold air drainage. We found that variability (diurnal range) of both soil and air temperatures decreased under moister conditions. While air temperatures were related more strongly to humidity, soil temperatures were related more to vapour pressure deficit (VPD). That is, both high temperature and low humidity were required before the VPD was sufficient to dry out the soil and allow soil temperatures to vary. We then used a regional regression approach to model the spatial distribution of minimum and maximum air and soil temperatures for each day over the 10 months in terms of latitude, elevation, canopy cover, distance to coast, cold air drainage potential, and topographic exposure to the south and northwest. We found that elevation was the dominant factor explaining the distribution of soil and air temperatures under moist conditions. Other factors, such as canopy cover and topographic exposure, had a stronger influence on air temperatures whenever humidity was low. However, these factors only affected soil temperatures at times when higher temperatures combined with low humidity to produce higher VPD. Our results provide new insights into how moisture influences the spatial distribution of near-surface soil and air temperatures. Microrefugia will be more apparent under drier conditions, but climate change may affect refugia for soil and air temperatures differently. Higher temperatures will cause VPD to increase more than would be expected by any change in humidity, and refugia in terms of soil temperatures may therefore become increasingly apparent.
Current predictions of how species will respond to climate change are based on coarse-grained climate surfaces or idealized scenarios of uniform warming. These predictions may erroneously estimate ...the risk of extinction because they neglect to consider spatially heterogenous warming at the landscape scale or identify refugia where species can persist despite unfavourable regional climate. To address this issue, we investigated the heterogeneity in warming that has occurred in a 10 km x 10 km area from 1972 to 2007. We developed estimates by combining long-term daily observations from a limited number of weather stations with a more spatially comprehensive dataset (40 sites) obtained during 2005-2006. We found that the spatial distribution of warming was greater inland, at lower elevations, away from streams, and at sites exposed to the northwest (NW). These differences corresponded with changes in weather patterns, such as an increasing frequency of hot, dry NW winds. As plant species were biased in the topographic and geographic locations they occupied, these differences meant that some species experienced more warming than others, and are at greater risk from climate change. This species bias could not be detected at coarser scales. The uneven seasonal nature of warming (e.g. more warming in winter, minimums increased more than maximums) means that climate change predictions will vary according to which predictors are selected in species distribution models. Models based on a limited set of predictors will produce erroneous predictions when the correct limiting factor is not selected, and this is difficult to avoid when temperature predictors are correlated because they are produced using elevation-sensitive interpolations. The results reinforce the importance of downscaling coarse-grained (~50 km) temperature surfaces, and suggest that the accuracy of this process could be improved by considering regional weather patterns (wind speed, direction, humidity) and topographic exposure to key wind directions.
Most statistical models of microclimate focus on the difference or ‘offset’ between standardized air temperatures (macroclimate) and those of a specific habitat such as forest understorey, grassland ...or under a log. However, these offsets can fluctuate from positive to negative over a single day such that common practice consists in aggregating data into daily mean, minimum and maximum before modelling monthly offsets for each summary statistic. Here, we propose a more parsimonious and flexible approach relying on just two parameters: the slope and equilibrium. The slope captures the linear relationship between microclimate and macroclimate, while the equilibrium is the point at which microclimate equals macroclimate. Although applicable to other habitats, we demonstrate the relevance of our method by focusing on forest understoreys.
We installed temperature sensors at 1‐m height inside forest stands and in nearby open grasslands equipped with standardized weather stations, across 13 sites in France spanning a wide climatic gradient. From a year of hourly temperatures and for each sensor, we established relationships between microclimate and macroclimate temperatures using two linear mixed‐effects models, during the leaf‐on (May–November) and leaf‐off period (December–April). We extracted the monthly equilibrium and slope for each sensor, and used another set of linear mixed‐effects models to investigate their main determinants.
The slope was chiefly determined by stand structure variables interacting with the leaf‐on/leaf‐off period: stand type (conifer vs broadleaf); shade‐casting ability; stand age; dominant height; stem density; and cover of the upper and lower shrub layer. In contrast, forest structure had no explanatory power on the equilibrium. We found the equilibrium to be positively related to mean macroclimate temperature, interacting with the open/forest habitat.
The method introduced here overcomes several shortcomings of modelling microclimate offsets. By demonstrating that the slope and equilibrium vary in predictable ways, we have established a general linkage between microclimate and macroclimate temperatures that can be applied to any location or time if we know the mean macroclimate temperature (equilibrium) and buffering or amplifying capacity of the habitat (slope). We also warn about methodological biases due to the reference used for macroclimate.
The terrestrial flora of Antarctica's frozen continent is restricted to sparse ice-free areas and dominated by lichens and bryophytes. These plants frequently battle sub-zero temperatures, extreme ...winds and reduced water availability; all influencing their ability to survive and grow. Antarctic mosses, however, can have canopy temperatures well above air temperature. At midday, canopy temperatures can exceed 15°C, depending on moss turf water content. In this study, the optimum temperature of photosynthesis was determined for six Antarctic moss species:
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collected from King George Island (maritime Antarctica) and/or the Windmill Islands, East Antarctica. Both chlorophyll fluorescence and gas exchange showed maximum values of electron transport rate occurred at canopy temperatures higher than 20°C. The optimum temperature for both net assimilation of CO
and photoprotective heat dissipation of three East Antarctic species was 20-30°C and at temperatures below 10°C, mesophyll conductance did not significantly differ from 0. Maximum mitochondrial respiration rates occurred at temperatures higher than 35°C and were lower by around 80% at 5°C. Despite the extreme cold conditions that Antarctic mosses face over winter, the photosynthetic apparatus appears optimised to warm temperatures. Our estimation of the total carbon balance suggests that survival in this cold environment may rely on a capacity to maximize photosynthesis for brief periods during summer and minimize respiratory carbon losses in cold conditions.
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