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Abstract

Ecological research heavily relies on coarse-­gridded climate data based on standardized temperature measurements recorded at 2 m height in open landscapes. However, many organisms experience environmental conditions that differ substantially from those captured by these macroclimatic (i.e. free air) temperature grids. In forests, the tree canopy functions as a thermal insulator and buffers sub-­canopy microclimatic conditions, thereby affecting biological and ecological processes. To improve the as- sessment of climatic conditions and climate-­change-­related impacts on forest-­floor biodiversity and functioning, high-­resolution temperature grids reflecting forest microclimates are thus urgently needed. Combining more than 1200 time series of in situ near-­surface forest temperature with topographical, biological and macrocli- matic variables in a machine learning model, we predicted the mean monthly offset between sub-­canopy temperature at 15 cm above the surface and free-­air tempera- ture over the period 2000–­2020 at a spatial resolution of 25 m across Europe. This offset was used to evaluate the difference between microclimate and macroclimate across space and seasons and finally enabled us to calculate mean annual and monthly temperatures for European forest understories. We found that sub-­canopy air temperatures differ substantially from free-­air temperatures, being on average 2.1°C (standard deviation ± 1.6°C) lower in summer and 2.0°C higher (±0.7°C) in winter across Europe. Additionally, our high-­resolution maps expose considerable microcli- matic variation within landscapes, not captured by the gridded macroclimatic prod- ucts. The provided forest sub-­canopy temperature maps will enable future research to model below-­canopy biological processes and patterns, as well as species distribu- tions more accurately.

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... However, nearly zero, zero or even negative thermophilization rates are observed below shady and dense tree canopies, such that many forest communities are lagging behind predictions based on macroclimatic temperature increases (Bertrand et al., 2011;De Frenne et al., 2013b;Dietz et al., 2020;Zellweger et al., 2020). These 'climatic lags' are attributed to trees functioning as ecosystem engineers that regulate the understorey climatic conditions and light availability (i.e. the forest microclimate), long life-cycles and slow colonization rates that are typical to many understorey plant species Haesen et al., 2021;Sanczuk et al., 2022a;Svenning et al., 2008). Climatic lags in understorey plant communities thus arise from individualistic species range dynamics modulated by fine-grained biotic and abiotic environmental variation and species-specific demography, determinant features of a species' current realized range that are rarely considered when projecting future range dynamics under climate change. ...
... Such data will become increasingly available (e.g. Haesen et al., 2021) and will enhance our understanding on the importance of microclimates on species responses to macroclimate warming. ...
... Next to slow species' demography and dispersal rates (Bertrand et al., 2016;Sanczuk et al., 2022a), these 'climatic lags' are attributed to processes operating at fine spatial grains. Due to their highly complex structure, trees are ecosystem engineers that attenuate variation in below-canopy climatic conditions (i.e. the forest microclimate) and buffer forest species from macroclimatic temperature extremes Haesen et al., 2021;. Microclimates determine major forest ecological processes such as nutrient cycling , evapotranspiration (Kassuelke et al., 2022), tree regeneration , soil seed bank composition (Gasperini et al., 2021) and understorey species range dynamics (Hylander et al., 2015;Lenoir et al., 2017;Potter et al., 2013). ...
... In a dry year with scattered and low intensity rainfall, the canopy could intercept light rainfall that evaporated or ran off to the base of the trunks before reaching the seedlings at ground level in the understory (Crockford & Richardson 2000, Chappell et al. 2001, Barbier et al, 2009). This result is contrary to expected patterns of canopy facilitation (Vilà-Cabrera et al. 2019, Zellweger et al. 2020 showing the buffering effect of the canopy on regional climate by improving the microclimate with lower temperatures and reduced droughts at the local scale (Wassie et al. 2009;Pugnaire et al. 2011, Haesen et al. 2021). The switch from facilitation to competition is determined by environmental conditions (Michalet et al. 2014). ...
... SE (-25.4 to -6.0mm in other areas in march-may; S2). This positive effect of forest canopy on germination in ReSCan more continental areas may be explained by a buffering effect of tree canopy on low temperatures(Haesen et al. 2021) and drought level(Wassie et al. 2009;Pugnaire et al. 2011), a moderate increase in temperature improving beech germination(Walbott et al. 2018).Across the 32 sites of ReSCan network, a bioclimatic gradient arose based on water balance and minimal temperatures in spring (S2), determining a gradient of climatic constraint (Tab. 2). ...
Thesis
En milieu tempéré, les hypothèses de distribution et de déplacement des espèces végétales suggèrent une rétraction des aires de distribution des espèces mésophiles en réponse aux changements climatiques. A l’échelle biogéographique, Le déclin de ces populations est attendu de manière plus importante dans la marge chaude de l’aire de distribution des espèces, en limite de tolérance physiologique et écologique. Cependant, les effets de facteurs locaux comme la canopée forestière et les caractéristiques édaphiques sur les conditions environnementales locales sont insuffisamment pris en compte. Si dans le cœur de l’aire de répartition des espèces où l’environnement est favorable, les facteurs locaux sont supposés n’avoir que peu d’impact sur la persistance des espèces, ceux-ci pourraient améliorer les conditions pour les espèces en marge chaude, comme le suggère le modèle « centre-périphérie ».L’effet de la canopée forestière et du type de sol sur la dynamique de régénération du hêtre commun (Fagus sylvatica L.) a été testé dans le cadre d’un dispositif expérimental déployé le long d’un gradient biogéographique en plaine dans le cœur de son aire de distribution en Normandie et en Lorraine ainsi que dans sa marge chaude en Gironde et dans la Drôme. Un total de 32 sites homogènes au niveau des conditions environnementales (exposition, roche-mère, type de communautés sous feuillus à hêtre) a ainsi été équipé et suivi expérimentalement. L’effet sol a été manipulé en installant des mésocosmes de sols reconstitués et en les comparant à des conditions de sols en place sous forêt, et l’effet canopée a été évalué en comparant les sites à mésocosmes édaphiques sous forêts en milieu ouvert adjacent, aboutissant à trois modalités dans chacun des 32 sites : milieu ouvert dans un mésocosmes, sous canopée forestière dans un mésocosme, sous canopée forestière en pleine terre. La germination de faînes leur croissance et la croissance de plants de provenances différentes (cœur et marge d’aire de distribution) ont été suivis pendant deux années en 2019 et 2020 pour évaluer la dynamique de régénération du hêtre.La germination et la survie des plantules de hêtre ont été mesurées en 2019, année extrêmement sèche. Dans ce contexte, les facteurs locaux n’ont pas facilité la régénération du hêtre dans sa marge chaude comme attendu. Les phases précoces de la régénération ne suivent pas un gradient biogéographique latitudinal de la marge chaude vers le cœur de l’aire, mais un gradient de sécheresse longitudinal qui suit le gradient de continentalité. Cela s’explique probablement par le couplage de trois facteurs : climat plus sec dans les sites continentaux, canopée forestière faisant barrière aux très faibles pluies et enfin sols compacts avec de faibles infiltration.En parallèle, la persistance de plants de 3 ans a été mesurée sur deux ans. La résilience des jeunes plants a ainsi pu être testée de 2019 à 2020, deux années les plus sèches de ces 40 dernières années. En plus de la croissance et de la persistance, des traits foliaires supplémentaires ont été mesurés afin de mieux discriminer la réponse des plants aux facteurs locaux testés en fonction de leur provenance.Enfin, des analyses de groupement ont été réalisées sur les relevés des communautés végétales de chaque site forestier. Le déterminisme des types de communautés végétales, un autre facteur local, dans la dynamique de régénération du hêtre a pu être testé par rapport aux réponses de persistance et de croissance des stades précoces du hêtre.Ce travail a conduit à tester différentes hypothèses couramment admises dans la littérature concernant la réponse des populations aux changements globaux, et a mis en avant le rôle complexe joué par les facteurs locaux dans la réponse végétale aux tout premiers stades de régénération.
... The effect of plants on soil properties is very distinct, especially in forest ecosystems because of the long-term influence of forest stand on soil. Trees can affect soil properties directly through the input of organic material (dead organic matter, root exudates), living tissues (roots) and/or indirectly via modification of microclimate, e.g., radiation reaching the ground, evaporation from the soil surface, relative air humidity, air circulation, water input to the soil, etc., [1][2][3][4][5]. The effects differ depending on tree species, because of the different qualities and quantities of organic residues left on the soil surface or going directly into the soil, as well as different crown and root architecture, canopy openness, stemflow rate, etc., [5][6][7]. ...
... Trees can affect soil properties directly through the input of organic material (dead organic matter, root exudates), living tissues (roots) and/or indirectly via modification of microclimate, e.g., radiation reaching the ground, evaporation from the soil surface, relative air humidity, air circulation, water input to the soil, etc., [1][2][3][4][5]. The effects differ depending on tree species, because of the different qualities and quantities of organic residues left on the soil surface or going directly into the soil, as well as different crown and root architecture, canopy openness, stemflow rate, etc., [5][6][7]. Numerous studies have shown that differences in tree cover are reflected especially in the thickness of the surface organic layer, in the soil acidity, in the base saturation, and in the carbon and nitrogen concentrations, and consequently in the responses of the soil microbial biomass, the activity and structure, and the diversity of the microbial communities [8][9][10]. ...
Article
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Several decades ago, many former pastures in Central Europe were afforested or colonized by trees after being abandoned. Knowledge of the effects of tree species on soil properties is important for planning of the composition of future forests. In this regard, a research location in Vrchdobroč (Central Slovakia), which is former agricultural land used as pasture, enables the exploration of ecosystem processes and properties in stands of different tree species after afforestation. The goal of our study was to find out whether changes in soil properties, including soil microbial activity and diversity among different stands, were already observable 45 years after the afforestation, and how the effects differed among stands of different tree species. The study was conducted in the pure stands of Norway spruce (Picea abies L. Karst.), Douglas fir (Pseudotsuga menziesi (Mirb.) Franco), European beech (Fagus sylvatica L.) and sycamore maple (Acer pseudoplatanus L.). Multivariate analyses of physico-chemical soil properties indicated an overlap between the soils under the Douglas fir and the spruce, but a clear separation of beech from sycamore. In general, both microbial activity and diversity were, surprisingly, highest under the Douglas fir, followed by the sycamore, with the beech and the spruce showing mostly lower values.
... Scientist, therefore, attempts to derive fine-scale (~1-100 m) microclimatic grids through interpolation of in-situ measurements, e.g. (Ashcroft and Gollan, 2012;Fridley, 2009;Greiser et al., 2018;Haesen et al., 2021;Macek et al., 2019) or through mechanistic modelling based on physical principles (Davis et al., 2017;Kearney et al., 2020;Maclean, 2020). However, fine-scale microclimatic grids are still relatively scarce, often local, and not standardized. ...
... topographic wetness index) are successfully used as a proxy for cool air pooling (Ashcroft and Gollan, 2012;Fridley, 2009;Meineri and Hylander, 2017). Indices describing relative topographic position, various landforms or topographic heterogeneity can be used as a proxy for wind exposition or other differences to mezo-and macroclimate (Frey et al., 2016;Haesen et al., 2021;Zellweger et al., 2019a). ...
Article
Increasingly available high-resolution digital elevation models (DEMs) facilitate the use of fine-scale topographic variables as proxies for microclimatic effects not captured by the coarse-grained macroclimate datasets. Species distributions and community assembly rules are, however directly shaped by microclimate and not by topography. DEM-derived topography, sometimes combined with vegetation structure, is thus widely used as a proxy for microclimatic effects in ecological research and conservation applications. However, the suitability of such a strategy has not been evaluated against in situ measured microclimate and species composition. Because bryophytes are highly sensitive to microclimate, they are ideal model organisms for such evaluation. To provide this much needed evaluation, we simultaneously recorded bryophyte species composition, microclimate, and forest vegetation structure at 218 sampling sites distributed across topographically complex sandstone landscape. Using a LiDAR-based DEM with a 1 m resolution, we calculated eleven topographic variables serving as a topographic proxy for microclimate. To characterize vegetation structure, we used hemispherical photographs and LiDAR canopy height models. Finally, we calculated eleven microclimatic variables from a continuous two-year time- series of air and soil temperature and soil moisture. To evaluate topography and vegetation structure as substitutes for the ecological effect of measured microclimate, we partitioned the variation in bryophyte species composition and richness explained by microclimate, topography, and vegetation structure. In situ measured microclimate was clearly the most important driver of bryophyte assemblages in temperate coniferous forests. The most bryophyte-relevant variables were growing degree days, maximum air temperature, and mean soil moisture. Our results thus showed that topographic variables, even when derived from high-resolution LiDAR data and combined with in situ sampled vegetation structure, cannot fully substitute effects of in situ measured microclimate on forest bryophytes.
... are concordant with those of Bátori et al. (2019), which posit enclosed depressions as key habitat with colder and moister conditions for diverse taxa, including strong contrasts with surrounding south facing slopes and plateau in northern Hungary. Our results also suggest that canopy cover is a key explanatory factor for the presence of microrefugia, which is consistent with previous studies that showed the buffering effect of forest on mean and extreme temperatures (Haesen et al., 2021;Keppel et al., 2017;Zellweger et al., 2020). We could not separate clearly whether putative microrefugia were unique due to their particular physiographical parameters, or because of the composition and density of canopy cover. ...
Article
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In the context of global warming, a clear understanding of microrefugia ‐ microsites enabling the survival of species populations outside their main range limits ‐ is crucial. Several studies have identified forcing factors that are thought to favor the existence of microrefugia. However, there is a lack of evidence to conclude whether, and to what extent, the climate encountered within existing microrefugia differs from the surrounding climate. To investigate this, we adopt a “bottom‐up” approach, linking marginal disconnected populations to microclimate. We used the southernmost disconnected and abyssal populations of the circumboreal herbaceous plant Oxalis acetosella in Southern France to study whether populations in sites matching the definition of “microrefugia” occur in particularly favorable climatic conditions compared to neighboring control plots located at distances of between 50 m to 100 m. Temperatures were recorded in putative microrefugia and in neighboring plots for approximately 2 years to quantify their thermal offsets. Vascular plant inventories were carried out to test whether plant communities also reflect microclimatic offsets. We found that current microclimatic dynamics are genuinely at stake in microrefugia. Microrefugia climates are systematically colder compared to those found in neighboring control plots. This pattern was more noticeable during the summer months. Abyssal populations showed stronger offsets compared to neighboring plots than the putative microrefugia occurring at higher altitudes. Plant communities demonstrate this strong spatial climatic variability, even at such a microscale approach, as species compositions systematically differed between the two plots, with species more adapted to colder and moister conditions in microrefugia compared to the surrounding area.
... Banzragch et al. (2022), BWI3 (2012),Haesen et al. (2021),Hobbie et al. (2006), Hornung (1985,Mantau (2012),Möller et al. (2007), TI (Thünen-Institut) (2015).CRediT authorship contribution statementChristoph Leuschner: Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Project administration, Supervision. Agnes Förster: Data curation, Formal analysis, Investigation. ...
Article
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Increasing temperatures and rising atmospheric vapor pressure deficits are exposing forests around the globe to increasing drought and heat stress, demanding a shift to climate-smart forestry for increasing the stress resistance and resilience of production forests and to enhance their climate change mitigation potential. Based on measurements in paired pine and beech forests and the review of literature data, we analyse the biophysical consequences and the carbon cycle impact of large-scale Scots pine (Pinus sylvestris L.) plantations in northern Ger-many in the face of a warming and aridizising climate. We quantified canopy surface albedo and surface temperature , evapotranspiration and deep seepage, carbon (C) storage in biomass and soil and annual C sequestration, and soil acidification of pine plantations in comparison to beech forests (Fagus sylvatica L.), the natural forest vegetation. We find that near-infrared (NIR, 700-3000 mn) canopy surface albedo is higher by 5.2 percentage points during summer over beech as compared to pine forest, resulting in a 9 % higher net radiation and a 0.6 K higher surface temperature of the pine canopy. Deep seepage is on average by 68 mm yr −1 smaller under pine than beech forest (66 mm yr −1 vs. 134 mm yr −1) due to the higher evapotranspiration of pine. C storage in bio-mass and soil is by ∼ 48 Mg C ha −1 higher in beech than pine forests, reflecting the higher productivity of beech, demonstrating an unfavorably low C sequestration potential of Scots pine plantations. We conclude that the large-scale Scots pine plantations in northern Germany (>1.7 million ha) are neither environmental-friendly nor climate smart, given their enhancement of climate-warming, low climate change mitigation potential, and negative effect on groundwater recharge. Replacing pine plantations by beech (or other hardwood) forests in northern Germany and adjacent regions is urgently needed for achieving the goals of climate-smart forestry.
... This is a standard Environment Canada weather station that records air temperature in the open, c. 1.5 m above a level, grassy surface. As such, these data do not account for forest canopy effects on temperature microclimate (Haesen et al., 2021). Climate data were extracted using the WEATHERCAN package in R (LaZerte & Albers, 2018). ...
Article
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● The plume of hot gases rising above a wildfire can heat and kill the buds in tree crowns. This can reduce leaf area and rates of photosynthesis, growth, and reproduction, and may ultimately lead to mortality. These effects vary seasonally, but the mechanisms governing this seasonality are not well understood. ● A trait‐based physical model combining buoyant plume and energy budget theories shows the seasonality of bud necrosis height may originate from temporal variation in climate, fire behaviour, and/or bud functional traits. To assess the relative importance of these drivers, we parameterized the model with time series data for air temperature, fireline intensity, and bud traits from Pinus contorta, Picea glauca, and Populus tremuloides. ● Air temperature, fireline intensity, and bud traits all varied significantly through time, causing significant seasonal variation in predicted necrosis height. Bud traits and fireline intensity explained almost all the variation in necrosis height, with air temperature explaining relatively minor amounts of variation. ● The seasonality of fire effects on tree crowns appears to originate from seasonal variation in functional traits and fire behaviour. Our approach and results provide needed insight into the physical mechanisms linking environmental variation to plant performance via functional traits.
... However, most of these models inform on climate change projections at landscape scales which describe the macroclimatic conditions likely occurring over large areas (Rubio-Salcedo et al., 2015). If, on one hand, it is evident that there is a strict connection between macroclimate and the microclimate occurring at a more detailed scale, on the other hand, it is likely that these relationships are not constant either along spatial gradients or on a temporal scale (Haesen et al., 2021). ...
Article
Climate change is already causing considerable reductions in biodiversity in all terrestrial ecosystems. These consequences are expected to be exacerbated in biomes that are particularly exposed to change, such as those in the Mediterranean, and in certain groups of more sensitive organisms, such as epiphytic lichens. These poikylohydric organisms find suitable light and water conditions on trunks under the tree canopy. Despite their small size, epiphytic communities contribute significantly to the functionality of forest ecosystems. In this work, we surveyed epiphytic lichen communities in a Mediterranean area (Sardinia, Italy) and hypothesized that 1) the effect of microclimate on lichens at tree scale is mediated by the functional traits of these organisms and that 2) micro-refuge trees with certain morphological characteristics can mitigate the negative effects of future climate change. Results confirm the first hypothesis, while the second is only partially supported, suggesting that the capability of specific trees to host specific conditions may not be sufficient to maintain the diversity and ecosystem functionality of lichen communities in the Mediterranean.
... Including these microclimate measurements and novel spatial map data (e.g. Haesen et al., 2021; in future models and mapping efforts will increase accuracy of future predictions (Lembrechts et al., 2021a). Our study illustrates that forest microclimates themselves are subject to climate change, which will have important consequences for forestdwelling species and must hence not be neglected. ...
Article
Forest canopies buffer macroclimatic temperature fluctuations. However, we do not know if and how the capacity of canopies to buffer understorey temperature will change with accelerating climate change. Here we map the difference (offset) between temperatures inside and outside forests in the recent past and project these into the future in boreal, temperate and tropical forests. Using linear mixed-effect models, we combined a global database of 714 paired time series of temperatures (mean, minimum and maximum) measured inside forests vs. in nearby open habitats with maps of macroclimate, topography and forest cover to hindcast past (1970–2000) and to project future (2060–2080) temperature differences between free-air temperatures and sub-canopy microclimates. For all tested future climate scenarios, we project that the difference between maximum temperatures inside and outside forests across the globe will increase (i.e. result in stronger cooling in forests), on average during 2060–2080, by 0.27 ± 0.16 °C (RCP2.6) and 0.60 ± 0.14 °C (RCP8.5) due to macroclimate changes. This suggests that extremely hot temperatures under forest canopies will, on average, warm less than outside forests as macroclimate warms. This knowledge is of utmost importance as it suggests that forest microclimates will warm at a slower rate than non-forested areas, assuming that forest cover is maintained. Species adapted to colder growing conditions may thus find shelter and survive longer than anticipated at a given forest site. This highlights the potential role of forests as a whole as microrefugia for biodiversity under future climate change.
... The role of temperature in animal territory settlement decisions is little explored, with settlement studies including temperature focussing at the scale of species ranges (Frey et al. 2016), on the role of environmental factors such as habitat (Jones 2001), on the temperature of nest sites themselves (Hart et al. 2016, Carroll et al. 2020), or differences in temperature between breeding habitat types (Walsberg 1993, Pollock et al. 2015. We expect this paucity of studies is because measuring territory-scale temperature has only recently become achievable with new methods (Haesen et al. 2021). Furthermore, while effects of temperature on breeding Figure 1. ...
Article
Temperature plays an important role in determining the breeding phenology of birds in temperate climates, with higher spring temperatures associated with earlier breeding. However, the effect of localised territory‐scale temperature variations is poorly understood, with relationships between temperature and breeding phenology mostly studied using coarse‐grained climatic indices. Here, we interpolate spring temperatures recorded at 150‐m2 grid intersections encompassing 417 ha of forest to examine the influence of territory‐scale temperature, and its interaction with mean annual temperature, on territory selection, breeding phenology, clutch size and fledging success for three co‐occurring single‐brooded passerine birds using data from 672 nests over four years. All species exhibited significant trends in reproductive traits associated with territory‐scale temperature. Pied flycatchers Ficedula hypoleuca settled in cooler territories first, where they raised more fledglings. Blue tits Cyanistes caeruleus laid larger clutches in warmer territories in warm years and always laid earlier at warmer territories irrespective of annual temperature variation. Contrastingly, pied flycatcher and wood warbler Phylloscopus sibilatrix breeding phenology was earlier at warmer territories in cool years and cooler territories in warm years, with wood warbler clutch size responding similarly to this interaction. Greater previous breeding experience and higher rates of historical territory occupancy (territory quality) also predicted earlier breeding phenology and higher fledging success for pied flycatchers. We suggest that the migratory pied flycatcher and wood warbler are best synchronised with their prey availability in cooler years at a local population level. However resident blue tits match local phenology across all years, which is potentially advantageous under warmer predicted climate change scenarios. We conclude that temperature at the territory scale can be an important driver of settlement and breeding phenology and influence reproductive traits.
... It is crucial to have this knowledge, especially with increasing availability of fine-scale environmental data (e.g. Haesen et al., 2021;Li et al., 2021) and their use in predictive models developed for conservation and climate change studies (see for example Stark & Fridley, 2022;Zellweger et al., 2019). Therefore, we here address the following questions: (a) What are the trade-offs between analysis grain and positional error when modelling species distributions? ...
Article
The performance of species distribution models (SDMs) is known to be affected by analysis grain and positional error of species occurrences. Coarsening of the analysis grain has been suggested to compensate for positional errors. Nevertheless, this way of dealing with positional errors has never been thoroughly tested. With increasing use of fine‐scale environmental data in SDMs, it is important to test this assumption. Models using fine‐scale environmental data are more likely to be negatively affected by positional error as the inaccurate occurrences might easier end up in unsuitable environment. This can result in inappropriate conservation actions. Here, we examined the trade‐offs between positional error and analysis grain and provide recommendations for best practice. We generated narrow niche virtual species using environmental variables derived from LiDAR point clouds at 5 × 5 m fine‐scale. We simulated the positional error in the range of 5 m to 99 m and evaluated the effects of several spatial grains in the range of 5 m to 500 m. In total, we assessed 49 combinations of positional accuracy and analysis grain. We used three modelling techniques (MaxEnt, BRT and GLM) and evaluated their discrimination ability, niche overlap with virtual species and change in realized niche. We found that model performance decreased with increasing positional error in species occurrences and coarsening of the analysis grain. Most importantly, we showed that coarsening the analysis grain to compensate for positional error did not improve model performance. Our results reject coarsening of the analysis grain as a solution to address the negative effects of positional error on model performance. We recommend fitting models with the finest possible analysis grain and as close to the response grain as possible even when available species occurrences suffer from positional errors. If there are significant positional errors in species occurrences, users are unlikely to benefit from making additional efforts to obtain higher resolution environmental data unless they also minimize the positional errors of species occurrences. Our findings are also applicable to coarse analysis grain, especially for fragmented habitats, and for species with narrow niche breadth.
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The Vitality of Forests: Illustrating the evidence connecting forests and human health, is intended to better justify why the public, policymakers, and private sector should be interested in forests’ role beyond their recreational, carbon sequestration, or biodiversity conservation potential. The evidence demonstrates that public health and forests are entwined—at the local, regional, and global scale—and that across each of nature’s contributions to human health, forest conservation, protection, and management can improve human lives.
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The climate is changing rapidly, with potentially strong effects on biodiversity and ecosystem services. However, compared to the macroclimate, the microclimate in forests is very different, with less fluctuations and mainly lower maximum temperatures. This microclimate buffering is variable through space and time and largely depends on forest structure and tree species identity. On average maximum summer temperatures are about 4-6 °C lower in Flemish forests than outside, while minimum temperatures in winter are about 2-3 °C higher. This microclimate buffering is important for many forest species and ecosystem services, definitely in times of climate change. Forests in Flanders are highly fragmented, with a median forest area of 1.1 ha, which results in a high amount of forest edge compared to forest cores: about 15% of the Flemish forest area is located at less than 10 m from a forest border. These forest edge zones are very different from forest cores. For vascular plant biodiversity for instance, higher species numbers are found at the forest edge, but the share of forest specialists and the phylogenetic diversity are higher in forest cores. Also ecosystem services exhibit important edge effects, with a higher carbon storage and a reduced microclimatic buffering in forest edges compared to cores. Climate adaptive forest management combines cold and warm forest microclimates on a landscape scale to simultaneously conserve cold-adapted species and promote establishment of warm-adapted species.
Article
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Background Cork oak agroforestry systems (AFS) have been managed for centuries by humans to produce cork and other goods and services and have recently been recognised as an important reservoir for biodiversity improvement and conservation. However, despite having recently been included as a natural habitat of community-wide interest within the EU Habitats Directive, these systems are in a critical situation of decline. Among other factors, they are strongly threatened by climate change, the effects of which are also expected to be particularly severe in the Mediterranean region. In this study, we aimed to evaluate the influence of climate variability by examining primary production indicators and also to analyse whether the geographical location may have a role in the incidence of the adverse effects of climate. Methods Cork oak AFS were identified in the Forest Map of Spain and the Land use map of Portugal and categorized on the basis of canopy cover. Seasonal climate data from 2001 to 2020 were used to model relationships with climate predictors and proximity to the coast. Hotspot analysis was conducted to identify significant spatial clusters of high- and low-efficiency areas. Results The responses to the influence of climatic conditions differed among the various cork oak AFS categories, particularly in the forest category, which was less dependent on climate variations. Relative humidity and water availability were the main drivers of net primary production (NPP). Carbon use efficiency (CUE) was limited by relative humidity and spring temperature in open ecosystems. Proximity to the coast proved beneficial, especially in years with adverse weather conditions, but was not a limiting factor for survival of the ecosystem. Finally, the results of the hotspot analysis supported the other findings, highlighting high-efficiency areas close to the coast and cold spots grouped in specific areas or dispersed inland. Conclusions Canopy plays a key role in the influence of climatic conditions, particularly in forest categories in which a high density seems to generate microclimate conditions. Water availability, both via the soil and air moisture, is the main driver of primary production, reflecting different adaptive strategies. The oceanic atmosphere may act as a buffer in years of extreme drought.
Preprint
Identifying climate-change refugia is a key adaptation strategy for reducing global warming impacts. Knowledge of the effects of underlying geology on thermal regime along climate gradients and the ecological responses to the geology-controlled thermal regime is essential to plan appropriate climate adaptation strategies. The dominance of volcanic rocks in the watershed is used as a landscape-scale surrogate for cold groundwater inputs to clarify the importance of underlying geology. Using statistical models, we explored the relationship between watershed geology and the mean summer water temperature of mountain streams along climate gradients in the Japanese archipelago. Summer water temperature was explained by the interaction between the watershed geology and climate in addition to independent effects. The cooling effect associated with volcanic rocks was more pronounced in streams with less summer precipitation or lower air temperatures. We also examined the function of volcanic streams as cold refugia under contemporary and future climatic conditions. Community composition analyses revealed that volcanic streams hosted distinct stream communities composed of more cold-water species compared with non-volcanic streams. Scenario analyses revealed a geology-related pattern of thermal habitat loss for cold-water species. Non-volcanic streams rapidly declined in thermally suitable habitats for lotic sculpins even under the lowest emission scenario (RCP 2.6). In contrast, most volcanic streams will be sustained below the thermal threshold, especially for low and mid-level emission scenarios (RCP 2.6, 4.5). However, the distinct stream community in volcanic streams and geology-dependent habitat loss for lotic sculpins was not uniform and was more pronounced in areas with less summer precipitation or lower air temperatures. Although further studies are needed to understand underlying mechanisms of the interplay of watershed geology and climate, findings highlight that watershed geology, climate variability, and their interaction should be considered simultaneously for effective management of climate-change refugia in mountain streams.
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Microclimate varies greatly over short horizontal and vertical distances, and timescales. This multi-level heterogeneity influences terrestrial biodiversity and ecosystem functions by determining the ambient environment where organisms live in. Fine-scale heterogeneity in microclimate temperatures is driven by local topography, land and water cover, snow, and soil characteristics. However, their relative influence over boreal and tundra biomes and in different seasons, has not been comprehensively quantified. Here, we aim to (1) quantify temperature variations measured at three heights: soil (-6 cm), near-surface (15 cm) and air (150 cm), and (2) determine the relative influence of the environmental variables in driving thermal variability. We measured temperature at 446 sites within seven focus areas covering large macroclimatic, topographic, and ecosystem gradients (tundra, mires, forests) of northern Europe. Our data, consisting of over 60 million temperature readings during the study period of 2019/11–2020/10, reveal substantial thermal variability within and across the focus areas. Near-surface temperatures in the tundra showed the greatest instantaneous differences within a given focus area (32.3 °C) while the corresponding differences for soil temperatures ranged from 10.0 °C (middle boreal forest) to 27.1 °C (tundra). Instantaneous differences in wintertime air temperatures were the largest in the tundra (up to 25.6°C, median 4.2 °C), while in summer the differences were largest in the southern boreal forest (13.1°C, median 4.8°C). Statistical analyses indicate that monthly-aggregated temperature variations in boreal forests are closely linked to water bodies, wetlands, and canopy cover, whereas in the tundra, variation was linked to elevation, topographic solar radiation, and snow cover. The results provide new understanding on the magnitude of microclimate temperature variability and its seasonal drivers and will help to project local impacts of climate change on boreal forest and tundra ecosystems.
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Aim: The increasing availability of regional and global climate data presents an opportunity to build better ecological models; however, it is not always clear which climate dataset is most appropriate. The aim of this study was to better understand the impacts that alternative climate datasets have on the modelled distribution of plant species, and to develop systematic approaches to enhancing their use in species distribution models (SDMs). Location: Victoria, southeast Australia and the Himalayan Kingdom of Bhutan. Methods: We compared the statistical performance of SDMs for 38 plant species in Victoria and 12 plant species in Bhutan with multiple algorithms using globally and regionally calibrated climate datasets. Individual models were compared against one another and as SDM ensembles to explore the potential for alternative predictions to improve statistical performance. We develop two new spatially continuous metrics that support the interpretation of ensemble predictions by characterizing the per-pixel congruence and variability of contributing models. Results: There was no clear consensus on which climate dataset performed best across all species in either study region. On average, multi-model ensembles (across the same species with different climate data) increased AUC/TSS/Kappa/OA by up to 0.02/0.03/0.03/0.02 in Victoria and 0.06/0.11/0.11/0.05 in Bhutan. Ensembles performed better than most single models in both Victoria (AUC = 85%; TSS = 68%) and Bhutan (AUC = 86%; TSS = 69%). SDM ensembles using models fitted with alternative algorithms and/or climate datasets each provided a significant improvement over single model runs. Main conclusions: Our results demonstrate that SDM ensembles, built using alternative models of the same climate variables, can quantify model congruence and identify regions of the highest uncertainty while mitigating the risk of erroneous predictions. Algorithm selection is known to be a large source of error for SDMs, and our results demonstrate that climate dataset selection can be a comparably significant source of uncertainty.
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Geospatial modelling can give fundamental insights in the biogeography of life, providing key information about the living world in current and future climate scenarios. Emerging statistical and machine learning approaches can help us to generate new levels of predictive accuracy in exploring the spatial patterns in ecological and biophysical processes. Although these statistical models cannot necessarily represent the essential mechanistic insights that are needed to understand global biogeochemical processes under ever-changing environmental conditions, they can provide unparalleled predictive insights that can be useful for exploring the variation in biophysical processes across space. As such, these emerging tools can be a valuable approach to complement existing mechanistic approaches as we aim to understand the biogeography of Earth's ecosystems. Here, we present a comprehensive methodology that efficiently handles large datasets to produce global predictions. This mapping pipeline can be used to generate quantitative, spatially explicit predictions, with a particular emphasis on spatially-explicit insights into the evaluation of model uncertainties and inaccuracies.
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Many organisms live in environments in which temperatures differ substantially from those measured by standard weather stations. The last decade has witnessed a paradigm shift in efforts to quantify these differences and to understand their ecological, functional and evolutionary implications. This renewed interest in microclimate ecology has been accompanied by the development of various compact temperature sensors and radiation shields. However, it is clear that there are many pitfalls when measuring temperature using these devices. Here we address the problem of measuring temperatures in these microenvironments accurately. We first discuss the theory of measuring surface, ground and air temperatures with reference to energy fluxes and how these are modified by material, reflective properties, and size of the device. We highlight the particular difficulties associated with measuring air temperature. We then report on the results of a series of experiments in which air temperatures recorded by various commonly used microclimate temperature loggers are compared to those obtained using research‐grade instruments and synoptic weather stations. While accurate measurements of surface and ground temperatures and air temperatures at night and in shaded environments can be relatively easily obtained, we show substantial errors are to be expected when measuring air temperatures in environments exposed to sunlight. Most standard sensors yield large errors, which can reach 25°C due to radiative fluxes operating on the thermometer. This problem cannot be wholly overcome by shielding the thermometer from sunlight, as the shield itself will influence both the temperatures being measured and the accuracy of measurement. We demonstrate that reasonably accurate estimates of air temperature can be obtained with low‐cost and unshielded ultrafine‐wire thermocouples that possess low thermal emissivity and a highly reflective surface. As the processes that create microclimatic temperature variation are the same as those that cause errors, other logger types should be used with care, and generally avoided in environments exposed to sunlight and close to the ground where wind speeds are lower. We urge researchers interested in microclimates and their effects to pay greater heed to the physics of heat exchange when attempting to measure microclimate temperatures and to understand the trade‐offs that exist in so doing.
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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.
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Framed within the Copernicus Climate Change Service of the European Commission, the European Centre for Medium-Range Weather Forecasts (ECMWF) is producing an enhanced global dataset for the land component of the 5th generation of European ReAnalysis (ERA5), hereafter named as ERA5-Land. Once completed, the period covered will span from 1950 to present, with continuous updates to support land monitoring applications. ERA5-Land describes the evolution of the water and energy cycles over land in a consistent manner over the production period, enabling the characterisation of trends and anomalies. This is achieved through global high resolution numerical integrations of the ECMWF land surface model driven by the downscaled meteorological forcing from the ERA5 climate reanalysis, including an elevation correction for the thermodynamic near-surface state. ERA5-Land shares with ERA5 most of the parametrizations that guarantees the use of the state-of-the-art land surface modeling applied to Numerical Weather Prediction (NWP) models. A main advantage of ERA5-Land compared to ERA5 and the older ERA-Interim is the horizontal resolution, which is enhanced globally to 9 km compared to 31 km (ERA5) or 80 km (ERA-Interim), whereas the temporal resolution is hourly as in ERA5. Evaluation against independent in situ observations and global model or satellite-based reference datasets shows the added value of ERA5-Land in the description of the hydrological cycle, in particular with enhanced soil moisture and lake description, and an overall better agreement of river discharge estimations with available observations. However, ERA5-Land snow depth fields present a mixed behaviour when compared to those of ERA5, depending on geographical location and altitude. The description of the energy cycle shows comparable results with ERA5. Nevertheless, ERA5-Land reduces the global averaged root mean square error of the skin temperature, taking as reference MODIS data, mainly due to the contribution of coastal points where spatial resolution is important. Since January 2020, the ERA5-Land period available extends from January 1981 to near present, with 2 to 3 months delay with respect to real-time. The segment prior to 1981 is in production, aiming to a release of the whole dataset in summer 2021. The high spatial and temporal resolution of ERA5-Land, its extended period, and the consistency of the fields produced makes it a valuable dataset to support hydrological studies, to initialise NWP and climate models, and to support diverse applications dealing with water resource, land and environmental management. The full ERA5-Land hourly and monthly averaged dataset presented in this paper are available through the Climate Data Store, https://doi.org/10.24381/cds.e2161bac and https://doi.org/10.24381/cds.68d2bb30, respectively.
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Soil moisture controls environmental processes and species distributions, but it is difficult to measure and interpolate across space. Topographic Wetness Index (TWI) derived from digital elevation model is therefore often used as a proxy for soil moisture. However, different algorithms can be used to calculate TWI and this potentially affects TWI relationship with soil moisture and species assemblages. To disentangle insufficiently-known effects of different algorithms on TWI relation with soil moisture and plant species composition, we measured the root-zone soil moisture throughout a growing season and recorded vascular plants and bryophytes in 45 temperate forest plots. For each plot, we calculated 26 TWI variants from a LiDAR-based digital terrain model and related these TWI variants to the measured soil moisture and moisture-controlled species assemblages of vascular plants and bryophytes. A flow accumulation algorithm determined the ability of the TWI to predict soil moisture, while the flow width and slope algorithms had only a small effects. The TWI calculated with the most often used single-flow D8 algorithm explained less than half of the variation in soil moisture and species composition explained by the TWI calculated with the multiple-flow FD8 algorithm. Flow dispersion used in the FD8 algorithm strongly affected the TWI performance, and a flow dispersion close to 1.0 resulted in the TWI best related to the soil moisture and species assemblages. Using downslope gradient instead of the local slope gradient can strongly decrease TWI performance. Our results clearly showed that the method used to calculate TWI affects study conclusion. However, TWI calculation is often not specified and thus impossible to reproduce and compare among studies. We therefore provide guidelines for TWI calculation and recommend the FD8 flow algorithm with a flow dispersion close to 1.0, flow width equal to the raster cell size and local slope gradient for TWI calculation.
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Changes in forest disturbances can have strong impacts on forests, yet we lack consistent data on Europe’s forest disturbance regimes and their changes over time. Here we used satellite data to map three decades of forest disturbances across continental Europe, and analysed the patterns and trends in disturbance size, frequency and severity. Between 1986 and 2016, 17% of Europe’s forest area was disturbed by anthropogenic and/or natural causes. We identified 36 million individual disturbance patches with a mean patch size of 1.09 ha, which equals an annual average of 0.52 disturbance patches per km2 of forest area. The majority of disturbances were stand replacing. While trends in disturbance size were highly variable, disturbance frequency consistently increased and disturbance severity decreased. Here we present a continental-scale characterization of Europe’s forest disturbance regimes and their changes over time, providing spatial information that is critical for understanding the ongoing changes in Europe’s forests. Changes in forest disturbance affect their sustainability. This study finds that between 1986 and 2016, 36 million disturbances by humans or other causes affected 17% of Europe’s forest area.
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Many analyses of biological responses to climate rely on gridded climate data derived from weather stations, which differ from the conditions experienced by organisms in at least two respects. First, the microclimate recorded by a weather station is often quite different to that near the ground surface, where many organisms live. Second, the temporal and spatial resolutions of gridded climate datasets derived from weather stations are often too coarse to capture the conditions experienced by organisms. Temporally and spatially coarse data have clear benefits in terms of reduced model size and complexity, but here we argue that coarse-grained data introduce errors that, in biological studies, are too often ignored. However, in contrast to common perception, these errors are not necessarily caused directly by a spatial mismatch between the size of organisms and the scale at which climate data are collected. Rather, errors and biases are primarily due to (i) systematic discrepancies between the climate used in analysis and that experienced by organisms under study and (ii) the non-linearity of most biological responses in combination with differences in climate variance between locations and time periods for which models are fitted and those for which projections are made. We discuss when exactly problems of scale can be expected to arise and highlight the potential to circumvent these by spatially and temporally down-scaling climate. We also suggest ways in which adjustments to deal with issues of scale could be made without the need to run high-resolution models over wide extents.
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Biogeographical units are widely adopted in ecological research and nature conservation management, even though biogeographical regionalisation is still under scientific debate. The European Environment Agency provided an official map of the European Biogeographical Regions (EBRs), which contains the official boundaries used in the Habitats and Birds Directives. However, these boundaries bisect cells in the official EU 10 km × 10 km grid used for many purposes, including reporting species and habitat data, meaning that 6881 cells overlap two or more regions. Therefore, superimposing the EBRs vector map over the grid creates ambiguities in associating some cells with European Biogeographical Regions. To provide an operational tool to unambiguously define the boundaries of the eleven European Biogeographical Regions, we provide a specifically developed raster map of Grid-Based European Biogeographical Regions (GB-EBRs). In this new map, the borders of the EBRs are reshaped to coherently match the standard European 10 km × 10 km grid imposed for reporting tasks by Article 17 of the Habitats Directive and used for many other datasets. We assign each cell to the EBR with the largest area within the cell.
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There is mounting evidence of species redistribution as climate warms. Yet, our knowledge of the coupling between species range shifts and isotherm shifts remains limited. Here, we introduce BioShifts—a global geo-database of 30,534 range shifts. Despite a spatial imbalance towards the most developed regions of the Northern Hemisphere and a taxonomic bias towards the most charismatic animals and plants of the planet, data show that marine species are better at tracking isotherm shifts, and move towards the pole six times faster than terrestrial species. More specifically, we find that marine species closely track shifting isotherms in warm and relatively undisturbed waters (for example, the Central Pacific Basin) or in cold waters subject to high human pressures (for example, the North Sea). On land, human activities impede the capacity of terrestrial species to track isotherm shifts in latitude, with some species shifting in the opposite direction to isotherms. Along elevational gradients, species follow the direction of isotherm shifts but at a pace that is much slower than expected, especially in areas with warm climates. Our results suggest that terrestrial species are lagging behind shifting isotherms more than marine species, which is probably related to the interplay between the wider thermal safety margin of terrestrial versus marine species and the more constrained physical environment for dispersal in terrestrial versus marine habitats. Compiling a global geo-database of >30,000 range shifts, the authors show that marine species closely track shifting isotherms, whereas terrestrial species lag behind, probably due to wider thermal safety margins and movement constraints imposed by human activities.
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Current analyses and predictions of spatially‐explicit patterns and processes in ecology most often rely on climate data interpolated from standardized weather stations. This interpolated climate data represents long‐term average thermal conditions at coarse spatial resolutions only. Hence, many climate‐forcing factors that operate at fine spatiotemporal resolutions are overlooked. This is particularly important in relation to effects of observation height (e.g. vegetation, snow and soil characteristics) and in habitats varying in their exposure to radiation, moisture and wind (e.g. topography, radiative forcing, or cold‐air pooling). Since organisms living close to the ground relate more strongly to these microclimatic conditions than to free‐air temperatures, microclimatic ground and near‐surface data are needed to provide realistic forecasts of the fate of such organisms under anthropogenic climate change, as well as of the functioning of the ecosystems they live in. To fill this critical gap, we highlight a call for temperature time series submissions to SoilTemp, a geospatial database initiative compiling soil and near‐surface temperature data from all over the world. Currently this database contains time series from 7538 temperature sensors from 51 countries across all key biomes. The database will pave the way towards an improved global understanding of microclimate and bridge the gap between the available climate data and the climate at fine spatiotemporal resolutions relevant to most organisms and ecosystem processes.
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Many questions in global change ecology deal with large-scale patterns, with global databases of species distributions, species traits and ecosystem processes becoming increasingly available (e.g. Bruelheide et al., 2018). Current analyses of these large-scale patterns - and their predictions under anthropogenic climate change - often rely on spatially coarse-resolution global climatic data interpolated from weather station measurements. These weather stations are systematically located in open landscapes, where the wind continuously mixes the air, and are shielded from direct solar radiation, thus ignoring many climate-forcing processes that operate near the ground, at very fine spatial resolutions, and in microhabitats that vary in their terrain, exposure to winds and vegetation cover (De Frenne & Verheyen, 2016).
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Most studies of the biological effects of future climatic changes rely on seasonally aggregated, coarse‐resolution data. Such data mask spatial and temporal variability in microclimate driven by terrain, wind and vegetation and ultimately bear little resemblance to the conditions that organisms experience in the wild. Here, I present methods for providing fine‐grained, hourly and daily estimates of current and future temperature and soil moisture over decadal timescales. Observed climate data and spatially‐coherent probabilistic projections of daily future weather were disaggregated to hourly and used to drive empirically‐calibrated physical models of thermal and hydrological microclimates. Mesoclimatic effects (cold‐air drainage, coastal exposure and elevation) were determined from coarse resolution climate surfaces using thin‐plate spline models with coastal exposure and elevation as predictors. Differences between micro‐ and mesoclimate temperatures were determined from terrain, vegetation and ground properties using energy balance equations. Soil moisture was computed in a thin upper layer and an underlying deeper layer, and the exchange of water between these layers was calculated using the Van Genuchten equation. Code for processing the data and running the models is provided as a series of R packages. The methods were applied to the Lizard Peninsula, United Kingdom, to provide hourly estimates of temperature (100 m grid resolution over entire area, one m for a selected area) for the periods 1983–2017 and 2041–2049. Results indicated that there is fine‐resolution variability in climatic changes, driven primarily by interactions between landscape features and decadal trends in weather conditions. High‐temporal resolution extremes in conditions under future climate change were predicted to be considerably less novel than the extremes estimated using seasonally aggregated variables. The study highlights the need to more accurately estimate the future climatic conditions experienced by organisms and equips biologists with the means to do so.
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Context Forest microclimates differ from regional macroclimates because forest canopies affect energy fluxes near the ground. However, little is known about the environmental drivers of understorey temperature heterogeneity and its effects on species assemblages, especially at landscape scales. Objectives We aimed to identify which temperature variables best explain the landscape-scale distribution of forest vegetation and to disentangle the effects of elevation, terrain attributes and canopy cover on understorey temperatures. Methods We measured growing season air temperature, canopy cover and plant community composition within 46 plots established across a 400-km² area in Czech Republic. We linked growing season maximum, mean and minimum temperatures with elevation, canopy cover and topographic proxies for heat load, topographic position, soil moisture and cold air drainage, and created fine-scale topoclimatic maps of the region. We compared the biological relevance of in situ measured temperatures and temperatures derived from fine-scaled topoclimatic maps and global WorldClim 2 maps. Results Maximum temperature was the best predictor of understorey plant species composition. Landscape-scale variation in maximum temperature was jointly driven by elevation and terrain topography (adjRsquared = 0.79) but not by canopy cover. Modelled maximum temperature derived from our topoclimatic maps explained significantly more variation in plant community composition than WorldClim 2 grids. Conclusions Terrain topography creates landscape-scale variation in maximum temperature, which in turn controls plant species assembly within the forest understorey. Maximum temperature is therefore an important but neglected microclimatic driver of species distribution across landscapes.
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Aim: Forest understorey microclimates are often buffered against extreme heat or cold, with important implications for the organisms living in these environments. We quantified seasonal effects of understorey microclimate predictors describing canopy structure, canopy composition and topography (i.e., local factors) and the forest patch size and distance to the coast (i.e., landscape factors). Location: Temperate forests in Europe. Time period: 2017-2018. Major taxa studied: Woody plants. Methods: We combined data from a microclimate sensor network with weather-station records to calculate the difference, or offset, between temperatures measured inside and outside forests. We used regression analysis to study the effects of local and landscape factors on the seasonal offset of minimum, mean and maximum temperatures. Results: The maximum temperature during the summer was on average cooler by 2.1 °C inside than outside forests, and the minimum temperatures during the winter and spring were 0.4 and 0.9 °C warmer. The local canopy cover was a strong nonlinear driver of the maximum temperature offset during summer, and we found increased cooling beneath tree species that cast the deepest shade. Seasonal offsets of minimum temperature were mainly regulated by landscape and topographic features, such as the distance to the coast and topographic position. Main conclusions: Forest organisms experience less severe temperature extremes than suggested by currently available macroclimate data; therefore, climate–species relationships and the responses of species to anthropogenic global warming cannot be modelled accurately in forests using macroclimate data alone. Changes in canopy cover and composition will strongly modulate the warming of maximum temperatures in forest understories, with important implications for understanding the responses of forest biodiversity and functioning to the combined threats of land‐use change and climate change. Our predictive models are generally applicable across lowland temperate deciduous forests, providing ecologically important microclimate data for forest understories.
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Soil organisms are a crucial part of the terrestrial biosphere. Despite their importance for ecosystem functioning, few quantitative, spatially explicit models of the active belowground community currently exist. In particular, nematodes are the most abundant animals on Earth, filling all trophic levels in the soil food web. Here we use 6,759 georeferenced samples to generate a mechanistic understanding of the patterns of the global abundance of nematodes in the soil and the composition of their functional groups. The resulting maps show that 4.4 ± 0.64 × 10²⁰ nematodes (with a total biomass of approximately 0.3 gigatonnes) inhabit surface soils across the world, with higher abundances in sub-Arctic regions (38% of total) than in temperate (24%) or tropical (21%) regions. Regional variations in these global trends also provide insights into local patterns of soil fertility and functioning. These high-resolution models provide the first steps towards representing soil ecological processes in global biogeochemical models and will enable the prediction of elemental cycling under current and future climate scenarios.
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Aim: While species distribution models (SDMs) traditionally link species occurrences to free-air temperature data at coarse spatiotemporal resolution, the distribution of organisms might rather be driven by temperatures more proximal to their habitats. Several solutions are currently available, such as downscaled or interpolated coarse-grained free-air temperatures, satellite-measured land surface temperatures (LST) or in-situ measured soil temperatures. A comprehensive comparison of temperature data sources and their performance in SDMs is however currently lacking. Location: Northern Scandinavia Time period: 1970 - 2017 Major taxa studied: Higher plants Methods: We evaluated different sources of temperature data (WorldClim, CHELSA, MODIS, E-OBS, topoclimate and soil temperature from miniature data loggers), differing in spatial resolution (1’’ to 0.1°), measurement focus (free-air, ground-surface or soil temperature) and temporal extent (year-long vs. long-term averages), and use them to fit SDMs for 50 plant species with different growth forms in a high-latitudinal mountain region. Results: Differences between these temperature data sources originating from measurement focus and temporal extent overshadow the effects of temporal climatic differences and spatiotemporal resolution, with elevational lapse rates ranging from -0.6 °C per 100 m for long-term free-air temperature data to -0.2 °C per 100 m for in-situ soil temperatures. Most importantly, we found that the performance of the temperature data in SDMs depended on species’ growth forms. The use of in-situ soil temperatures improved the explanatory power of our SDMS (R² on average +16%), especially for forbs and graminoids (R²: +24% and +21% on average, respectively) compared to the other data sources. Main conclusions: We suggest future studies using SDMs to use the temperature dataset that best reflects the species’ ecology, rather than automatically using coarse-grained data from WorldClim or CHELSA.
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Macroclimate warming is often assumed to occur within forests despite the potential for tree cover to modify microclimates. Here, using paired measurements, we compared the temperatures under the canopy versus in the open at 98 sites across 5 continents. We show that forests function as a thermal insulator, cooling the understory when ambient temperatures are hot and warming the understory when ambient temperatures are cold. The understory versus open temperature offset is magnified as temperatures become more extreme and is of greater magnitude than the warming of land temperatures over the past century. Tree canopies may thus reduce the severity of warming impacts on forest biodiversity and functioning.
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Species distribution models (SDMs) are widely used to make predictions and assess questions regarding the spatial distribution and redistribution of species under environmental changes. Current SDMs are, however, often based on free‐air or synoptic temperature conditions with a coarse resolution, and thus may fail to capture apparent temperature (cf. microclimate) experienced by living organisms within their habitats. Microclimate is nevertheless crucial in habitats characterized by a vertical component (e.g. forests, mountains, or cities) or by horizontal variation in surface cover. The mismatch between how we usually express climate (cf. coarse‐grained free‐air conditions) and the apparent microclimatic conditions that living organisms experience has only recently been acknowledged in SDMs, yet several studies have already made considerable progress in tackling this problem from different angles. In this review, we summarize the currently available methods to obtain meaningful microclimatic data for use in distribution modelling. We discuss the issue of extent and resolution, and propose an integrated framework using a selection of appropriately‐placed sensors in combination with both detailed measurements of the habitat 3D structure, for example derived from digital elevation models or airborne laser scanning, and long‐term records of free‐air conditions from weather stations. As such, we can obtain microclimatic data with finer spatiotemporal resolution and of sufficient extent to model current and future species distributions. This article is protected by copyright. All rights reserved.
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1.Climate is of fundamental importance to the ecology and evolution of all organisms. However, studies of climate–organism interactions usually rely on climate variables interpolated from widely‐spaced measurements or modelled at coarse resolution, whereas the conditions experienced by many organisms vary over scales from millimetres to metres. 2.To help bridge this mismatch in scale, we present models of the mechanistic processes that govern fine‐scale variation in near‐ground air temperature. The models are flexible (enabling application to a wide variety of locations and contexts), can be run using freely available data and are provided as an R package. 3.We apply a mesoclimate to the Lizard Peninsula in Cornwall to provide hourly estimates of air temperature at resolution of 100m for the period Jan‐Dec 2010. A microclimate model is then applied to a one km2 region of the Lizard Peninsula, Caerthillean Valley (49.969 ºN, 5.215 ºW), to provide hourly estimates of near‐ground air temperature at resolution of one m2 during May 2010. 4.Our models reveal substantial spatial variation in near‐ground temperatures, driven principally by variation in topography and, at the microscale, by vegetation structure. At the meso‐scale, hours of exposure to air temperatures at one m height in excess of 25 °C ranged from 23 to 158 hours, despite this temperature never being recorded by the weather station within the study area during the study period. At the micro‐scale, steep south‐facing slopes with minimal vegetation cover experienced temperatures in excess of 40 °C. 5.The microclima package is flexible and efficient and provides an accurate means of modelling fine‐scale variation in temperature. We also provide functions that facilitate users to obtain and process a variety of freely available datasets needed to drive the model. This article is protected by copyright. All rights reserved.
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Forest canopies buffer climate extremes and promote microclimates that may function as refugia for understory species under changing climate. However, the biophysical conditions that promote and maintain microclimatic buffering and its stability through time are largely unresolved. We posited that forest microclimatic buffering is sensitive to local water balance and canopy cover, and we measured this effect during the growing season across a climate gradient in forests of the northwestern United States (US). We found that forest canopies buffer extremes of maximum temperature and vapor pressure deficit (VPD), with biologically meaningful effect sizes. For example, during the growing season, maximum temperature and VPD under at least 50% forest canopy were 5.3°C and 1.1 kPa lower on average, respectively, compared to areas without canopy cover. Canopy buffering of temperature and vapor pressure deficit was greater at higher levels of canopy cover, and varied with water balance, implying that buffering effects are subject to changes in local hydrology. We project changes in the water balance for the mid‐21st century and predict how such changes may impact the ability of western US forests to buffer climate extremes. Our results suggest that some forests will lose their capacity to buffer climate extremes as sites become increasingly water limited. Changes in water balance combined with accelerating canopy losses due to increases in the frequency and severity of disturbance will create potentially non‐linear changes in the microclimate conditions of western US forests. This article is protected by copyright. All rights reserved.
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Soil temperature (ST) has a key role in Arctic ecosystem functioning and global environmental change. However, soil thermal conditions do not necessarily follow synoptic temperature variations. This is because local biogeophysical processes can lead to a pronounced soil-atmosphere thermal offset (∆T) while altering the coupling (βT) between ST and ambient air temperature (AAT). Here, we aim to uncover the spatiotemporal variation in these parameters and identify their main environmental drivers. By deploying a unique network of 322 temperature loggers and surveying biogeophysical processes across an Arctic landscape, we found that the spatial variation in ∆T during the AAT≤0 period (mean ∆T=6.0°C, standard deviation ± 1.2°C) was directly and indirectly constrained by local topography controlling snow depth. By contrast, during the AAT>0 period, ∆T was controlled by soil characteristics, vegetation and solar radiation (∆T=-0.6°C ± 1.0°C). Importantly, ∆T was not constant throughout the seasons reflecting the influence of βT on the rate of local soil warming being stronger after (mean βT = 0.8 ± 0.1) than before (βT = 0.2 ± 0.2) snowmelt. Our results highlight the need for continuous microclimatic and local environmental monitoring, and suggest a potential for large buffering and non-uniform warming of snow-dominated Arctic ecosystems under projected temperature increase.
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We created a new dataset of spatially interpolated monthly climate data for global land areas at a very high spatial resolution (approximately 1 km 2). We included monthly temperature (minimum, maximum and average), precipitation, solar radiation, vapour pressure and wind speed, aggregated across a target temporal range of 1970–2000, using data from between 9000 and 60 000 weather stations. Weather station data were interpolated using thin-plate splines with covariates including elevation, distance to the coast and three satellite-derived covariates: maximum and minimum land surface temperature as well as cloud cover, obtained with the MODIS satellite platform. Interpolation was done for 23 regions of varying size depending on station density. Satellite data improved prediction accuracy for temperature variables 5–15% (0.07–0.17 ∘ C), particularly for areas with a low station density, although prediction error remained high in such regions for all climate variables. Contributions of satellite covariates were mostly negligible for the other variables, although their importance varied by region. In contrast to the common approach to use a single model formulation for the entire world, we constructed the final product by selecting the best performing model for each region and variable. Global cross-validation correlations were ≥ 0.99 for temperature and humidity, 0.86 for precipitation and 0.76 for wind speed. The fact that most of our climate surface estimates were only marginally improved by use of satellite covariates highlights the importance having a dense, high-quality network of climate station data.
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Climate change is predicted to cause widespread declines in biodiversity, but these predictions are derived from coarse-resolution climate models applied at global scales. Such models lack the capacity to incorporate microclimate variability, which is critical to biodiversity microrefugia. In forested montane regions, microclimate is thought to be influenced by combined effects of elevation, microtopography, and vegetation, but their relative effects at fine spatial scales are poorly known. We used boosted regression trees to model the spatial distribution of fine-scale, under-canopy air temperatures in mountainous terrain. Spatial models predicted observed independent test data well (r = 0.87). As expected, elevation strongly predicted temperatures, but vegetation and microtopography also exerted critical effects. Old-growth vegetation characteristics, measured using LiDAR (light detection and ranging), appeared to have an insulating effect; maximum spring monthly temperatures decreased by 2.5°C across the observed gradient in old-growth structure. These cooling effects across a gradient in forest structure are of similar magnitude to 50-year forecasts of the Intergovernmental Panel on Climate Change and therefore have the potential to mitigate climate warming at local scales. Management strategies to conserve old-growth characteristics and to curb current rates of primary forest loss could maintain microrefugia, enhancing biodiversity persistence in mountainous systems under climate warming.
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Author Cloud cover affects many important ecological processes, including reproduction, growth, survival, and behavior. When quantified globally at high spatial resolution, cloud cover dynamics can provide key information for delineating a variety of habitat types and predicting species distributions. In this study, we develop a new near-global, fine-grain (≈1 km) dataset of monthly cloud frequencies from 15 y of twice-daily satellite images. The new data reveal cloud cover dynamics at unprecedented spatial resolution. We show that the direct, observation-based nature of cloud-derived metrics can improve predictions of habitats, ecosystem, and species distributions with reduced spatial autocorrelation compared to commonly used interpolated climate data. These findings support the fundamental role of remote sensing as an effective lens through which to understand and globally monitor the fine-grain spatial variability of key biodiversity and ecosystem properties. Applications of these new data extend beyond ecology to validation of global climate models, economic applications in solar energy, tourism, and resource planning. With climate and land-use changes expected to perturb the geography of these conditions and ecological connections, standardized satellite-based observation of cloud cover may represent a key avenue for monitoring the health of biodiversity and ecosystems into the future.
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Forests play a key role in global carbon cycling and sequestration. However, the potential for carbon drawdown is affected by forest fragmentation and resulting changes in microclimate, nutrient inputs, disturbance and productivity near edges. Up to 20% of the global forested area lies within 100 m of an edge and, even in temperate forests, knowledge on how edge conditions affect carbon stocks and how far this influence penetrates into forest interiors is scarce. Here we studied carbon stocks in the aboveground biomass, forest floor and the mineral topsoil in 225 plots in deciduous forest edges across Europe and tested the impact of macroclimate, nitrogen deposition and smaller-grained drivers (e.g. microclimate) on these stocks. Total carbon and carbon in the aboveground biomass stock were on average 39% and 95% higher at the forest edge than 100 m into the interior. The increase in the aboveground biomass stock close to the edge was mainly related to enhanced nitrogen deposition. No edge influence was found for stocks in the mineral topsoil. Edge-to-interior gradients in forest floor carbon changed across latitude: carbon stocks in the forest floor were higher near the edge in southern Europe. Forest floor carbon decreased with increasing litter quality (i.e. high decomposition rate) and decreasing plant area index, whereas higher soil temperatures negatively affected the mineral topsoil carbon. Based on high-resolution forest fragmentation maps, we estimate that the additional carbon stored in deciduous forest edges across Europe amounts to not less than 183 Tg carbon, which is equivalent to the storage capacity of 1 million ha of additional forest. This study underpins the importance of including edge influences when quantifying the carbon stocks in temperate forests and stresses the importance of preserving natural forest edges and small forest patches with a high edge-to-interior surface area.
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1.Climate change will increase the level of drought stress experienced by plant communities, but the spatial distribution of projected changes in dryness remains highly uncertain. Species can, to some extent, deal with climate uncertainty through natural variation in adaptive responses to environmental heterogeneity and predictability. Biodiversity conservation could thus target populations pre‐adapted to climatic heterogeneity to anticipate climate uncertainty. Disentangling adaptive evolution of trait means vs. trait plasticity, however, requires a sampling design with genetic replicates grown under distinct environmental conditions. 2.Here, we applied three soil moisture treatments to genetic replicates of Fragaria vesca plants raised from seeds that were sampled in distinct topographical settings, to study adaptive trait and plasticity divergence in response to drought. 3.We demonstrate that various plant traits evolved along distinct topographical gradients. Populations on south‐exposed slopes, for example, retained high levels of both flowering and runner formation under drought stress, while north‐faced populations hardly flowered under reduced soil moisture levels. Aspect but not elevation was found to coincide with variation in plant traits, suggesting that micro‐environmental variation rather than general clines in elevation drive evolution in mountainous landscapes. Our results also indicate that traits and their plasticity can evolve independently in response to distinct topographical stressors. 4.Synthesis. We conclude that heterogeneous landscapes (i) harbor micro‐refugia of adaptive genetic diversity that protect natural populations against environmental change, and (ii) represent invaluable sources of quantitative genetic variation that could support conservation where climate projections are inconclusive.
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Questions Does the influence of forest edges on plant species richness and composition depend on forest management? Do forest specialists and generalists show contrasting patterns? Location Mesic, deciduous forests across Europe. Methods Vegetation surveys were performed in forests with three management types (unthinned, thinned 5‐10 years ago and recently thinned) along a macroclimatic gradient from Italy to Norway. In each of 45 forests, we established five vegetation plots along a south‐facing edge‐to‐interior gradient (n = 225). Forest specialist, generalist and total species richness, as well as evenness and proportion of specialists, were tested as a function of the management type and distance to the edge while accounting for several environmental variables (e.g. landscape composition and soil characteristics). Magnitude and distance of edge influence were estimated for species richness per management type. Results Highest total species richness was found in thinned forests. Edge influence on generalist plant species richness was contingent on the management type, with the smallest decrease in species richness from the edge‐to‐interior in unthinned forests. In addition, generalist richness increased with the proportion of forests in the surrounding landscape and decreased in forests dominated by tree species that cast more shade. Forest specialist species richness however, was not affected by management type or distance to the edge, but only increased with pH and increasing proportion of forests in the landscape. Conclusions Forest thinning affects the plant community composition along edge‐to‐interior transects of European forests with richness of forest specialists and generalists responding differently. Therefore, future studies should take the forest management into account when interpreting edge‐to‐interior because both modify the microclimate, soil processes and deposition of polluting aerosols. This interaction is key to predict the effects of global change on forest plants in landscapes characterized by a mosaic of forest patches and agricultural land, typical for Europe.
Chapter
Most ecological studies of the effects of climate on species are based on average conditions above ground level (measured by meteorological stations) averaged across 100 km2 or larger areas. However, most terrestrial organisms experience conditions in a much smaller area at the ground surface or within vegetation canopies, the climate of which can be very different to large-scale averages. Therefore, to accurately characterise the climatic conditions suitable for species, it is essential to include microclimate information. Microclimates are affected by the shape of the landscape, including the steepness and aspect of slopes, height above sea level, proximity to the sea or inland water, and whether a site is in a valley or at the top of a hill. Plants also modify the conditions found within or below their canopies, with the structure of vegetation playing an important role. The recent increase in the availability of microsensors and remotely sensed data at appropriate resolutions has led some ecologists to begin to include microclimate information within a variety of contexts; however the field can be confusing and intimidating and mistakes are often made along the way. In this chapter, we provide an overview of microclimatic processes and summarise the available methods of measuring and modelling microclimate data for incorporation in ecological research. We highlight pitfalls to avoid emerging novel methods and the limitations of some techniques. We also consider future research directions and opportunities within this emerging field.
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The understorey harbours a substantial part of vascular plant diversity in temperate forests and plays an important functional role, affecting ecosystem processes such as nutrient cycling and overstorey regeneration. Global change, however, is putting these understorey communities on trajectories of change, potentially altering and reducing their functioning in the future. Developing mitigation strategies to safeguard the diversity and functioning of temperate forests in the future is challenging and requires improved predictive capacity. Process-based models that predict understorey community composition over time, based on first principles of ecology, have the potential to guide mitigation endeavours but such approaches are rare. Here, we review fourteen understorey modelling approaches that have been proposed during the last three decades. We evaluate their inclusion of mechanisms that are required to predict the impact of global change on understorey communities. We conclude that none of the currently existing models fully accounts for all processes that we deem important based on empirical and experimental evidence. Based on this review, we contend new models are needed to project the complex impacts of global change on forest understoreys. Plant functional traits should be central to such future model developments, as they drive community assembly processes and provide valuable information on the functioning of the understorey. Given the important role of the overstorey, a coupling of understorey models to overstorey models will be essential to predict the impact of global change on understorey composition and structure, and how it will affect the functioning of temperate forests in the future.
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In the face of climate change, populations have two survival options - they can remain in situ and tolerate the new climatic conditions ("stay"), or they can move to track their climatic niches ("go"). For sessile and small-stature organisms like alpine plants, staying requires broad climatic tolerances, realized niche shifts due to changing biotic interactions, acclimation through plasticity, or rapid genetic adaptation. Going, in contrast, requires good dispersal and colonization capacities. Neither the magnitude of climate change experienced locally nor the capacities required for staying/going in response to climate change are constant across landscapes, and both aspects may be strongly affected by local microclimatic variation associated with topographic complexity. We combine ideas from population and community ecology to discuss the effects of topographic complexity in the landscape on the immediate "stay" or "go" opportunities of local populations and communities, and on the selective pressures that may have shaped the stay or go capacities of the species occupying contrasting landscapes. We demonstrate, using example landscapes of different topographical complexity, how speciesö thermal niches could be distributed across these landscapes, and how these, in turn, may affect many population and community ecological processes that are related to adaptation or dispersal. Focusing on treeless alpine or Arctic landscapes, where temperature is expected to be a strong determinant, our theorethical framework leads to the hypothesis that populations and communities of topographically complex (rough and patchy) landscapes should be both more resistant and more resilient to climate change than those of topographically simple (flat and homogeneous) landscapes. Our theorethical framework further points to how meta-community dynamics such as mass effects in topographically complex landscapes and extinction lags in simple landscapes, may mask and delay the long-term outcomes of these landscape differences under rapidly changing climates.
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What seems like a trivial task is one of the most difficult ones in functional plant ecology and biogeography: selecting the appropriate measures of temperature for an ecologically meaningful description of habitat conditions and for a mechanistic understanding of responses of plants. The difficulty becomes even more severe at elevations above the climatic tree limit, where plant stature, topography and seasonal snow cover interact in producing temperature conditions that largely deviate from weather station records. Temporal resolution and the distinction between extremes and means for biogeographic applications are emphasized. We summarize the key issues in handling temperature as a driver of plant life in general and in high elevation ecosystems in particular. Future directions in plant-temperature research at high elevation need to resolve the thermal species range limit issues (identify the fundamental temperature niche) and the complex controls of plant development (phenology) in a topography context.
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Climate, physical landscapes, and biota interact to generate heterogeneous hydrologic conditions in space and over time, which are reflected in spatial patterns of species distributions. As these species distributions respond to rapid climate change, microrefugia may support local species persistence in the face of deteriorating climatic suitability. Recent focus on temperature as a determinant of microrefugia insufficiently accounts for the importance of hydrologic processes and changing water availability with changing climate. Where water scarcity is a major limitation now or under future climates, hydrologic microrefugia are likely to prove essential for species persistence, particularly for sessile species and plants. Zones of high relative water availability – mesic microenvironments – are generated by a wide array of hydrologic processes, and may be loosely coupled to climatic processes and therefore buffered from climate change. Here, we review the mechanisms that generate mesic microenvironments and their likely robustness in the face of climate change. We argue that mesic microenvironments will act as species-specific refugia only if the nature and space/time variability in water availability are compatible with the ecological requirements of a target species. We illustrate this argument with case studies drawn from California oak woodland ecosystems. We posit that identification of hydrologic refugia could form a cornerstone of climate-cognizant conservation strategies, but that this would require improved understanding of climate change effects on key hydrologic processes, including frequently cryptic processes such as groundwater flow.
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The role of modern climatic microrefugia is a neglected aspect in the study of biotic responses to anthropogenic climate change. Current projections of species redistribution at continental extent are based on climatic grids of coarse (≥ 1-km) resolutions that fail to capture spatiotemporal dynamics associated with climatic microrefugia. Here we review recent methods to model the climatic component of potential microrefugia and highlight research gaps in accounting for the buffering capacity due to biophysical processes operating at very fine (< 1-m) resolutions (e.g. canopy cover) and the associated microclimatic stability over time (i.e. decoupling). To overcome this challenge, we propose a spatially hierarchical downscaling framework combining a free-air temperature grid at 1-km resolution, a digital elevation model at 25-m resolution and small-footprint light detection-and-ranging (LiDAR) data at 50-cm resolution with knowledge from the literature to mechanistically model sub-canopy temperatures and account for microclimatic decoupling. We applied this framework on a virtual sub-canopy species and simulated the impact of a warming scenario on its potential distribution. Modelling sub-canopy temperatures at 50-cm resolution and accounting for microclimatic stability over time enlarges the range of temperature conditions towards the cold end of the gradient, mitigates regional temperature changes and decreases extirpation risks. Incorporating these spatiotemporal dynamics into species redistribution models, being correlative, mechanistic or hybrid, will increase the probability of local persistence, which has important consequences in the understanding of the capacity of species to adapt. We finally provide a synthesis on additional ways that the field could move towards effectively considering potential climatic microrefugia for species redistribution. This article is protected by copyright. All rights reserved.
Article
Microclimatic variables are necessary for a wide range of pure and applied problems in environmental science. In ecology, microclimatic conditions are prerequisites for modelling the heat and water budgets of organisms, from which climatic constraints on behaviour, life histories, distribution and abundance can be inferred. Despite the critical importance of microclimates, there is no general-purpose, accessible microclimate model available for use in ecological studies. Here we introduce and document the microclimate model of the biophysical modelling package NicheMapR, an R package that includes a suite of programs for mechanistic modelling of heat and mass exchange between organisms and their environments. The NicheMapR microclimate model is based on a Fortran program originally developed by Porter, Mitchell, Beckman and McCullough for predicting hourly above- and below-ground conditions from meteorological, terrain, vegetation and soil data. The model includes routines for computing solar radiation, including effects of shading, slope, aspect and horizon angles (hillshade), and can include variable substrate properties with depth. Here we configure the program to be called from R as part of the NicheMapR package, and describe the model in detail including new functionality for modelling soil water balance and snow, optional input of hourly or daily weather input data, and an R implementation of the Global Aerosol Data Set for obtaining local estimates of aerosol profiles as input to the model. We include scripts for core operation of the model, for building a global, monthly long-term average dataset with all necessary environmental inputs, for computing physical properties of air, and for running the model with the global climate database. Example applications are provided in the paper and in the associated vignettes, including customisation the model to run with user-supplied weather inputs. This article is protected by copyright. All rights reserved.
Article
A spatial mismatch exists between regional climate models and conditions experienced by individual organisms. We demonstrate an approach to downscaling air temperatures for site-level studies using airborne LiDAR data and remote microclimate loggers. In 2012-2013, we established a temperature logger network in the forested region of central Missouri, USA, and obtained sub-hourly meteorological measurements from a centrally located weather station. We then used linear mixed models within an information theoretic approach to evaluate hourly and seasonal effects of insolation, vegetation structure, elevation, and meteorological measurements on near-surface air temperatures. The best-supported models predicted fine-scale temperatures with high accuracy during both the winter and growing seasons. We recommend that researchers consider the scales relevant to specific applications when using our approach to develop site-specific spatio-temporal models.