The influences of forests on the large-scale macroclimate are now established. Through albedo, evapotranspiration, surface roughness, and aerosols, forests influence the climate at large spatial scales. Forest influences on the local microclimate are also being recognized, and forests provide microclimatic refugia to buffer organisms against planetary warming. However, the scientific tools used to study forest influences on climate fail to account for forest microclimates. Earth system models are an important tool to inform land-use policy to mitigate planetary warming. With their big-leaf parameterization of plant canopies, however, the models are not vertically-resolved and do not simulate forest understories. Remotely sensed land surface temperature, another primary research tool to distinguish forest influences from other land cover, differs from the air temperature above and within forests. Multilayer canopy models have received renewed interest over the past several years and are a means to both improve the surface flux parameterizations and simulate vertical profiles within and above plant canopies. We present results of a comparison between the Community Land Model (CLM) multilayer canopy model and observations of air temperature, specific humidity, wind speed, and fluxes (net radiation, sensible heat, latent heat, momentum) taken at multiple heights in a walnut orchard during the Canopy Horizontal Array Turbulence Study (CHATS) from mid-March to mid-June 2007. The dataset provides a benchmark standard with which to test multilayer canopy models. Our model-data comparison highlights the potential of multilayer models to simulate the complex micrometeorology of forest canopies and also points to further research needs.

How to cite: Bonan, G., Burns, S., and Patton, E.: Modeling forest microclimates in the Earth system: a test case using the Canopy Horizontal Array Turbulence Study (CHATS) walnut orchard, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13191, https://doi.org/10.5194/egusphere-egu24-13191, 2024.

Intra-canopy microclimate and regional climate are two highly related components of the Earth system. On one side, intra-canopy microclimate influences strongly the ecosystem itself by regulating the vegetation/atmosphere exchanges which further influence plant dynamics, carbon sequestration and soil water dynamics. It also influences the biodiversity below the canopy by offering microhabitats or temperature buffering, and the regional climate directly by regulating the water and energy exchanges with the lowest levels of the atmosphere. On the other side, regional climate has a strong impact on intra-canopy microclimate, especially in the context of climate change, by reducing temperature gradients or by controlling the vegetation phenology. Despite this apparent strong imbrication, intra-canopy microclimates are very poorly represented in Land Surface Models (LSMs) and climate models in general, making it complicated to study their impact on climate change mitigation or the impact of climate change on the forests and their microclimates. Because of their time computing requirements, LSMs usually prefer simple models such as the “Big-Leaf” representation. However, in front of the urgent need to represent complex ecosystems and microclimates in Earth system models, first steps in this direction can be made, especially to improve the energy and water fluxes in the soil-vegetation-atmosphere continuum. This study presents recent developments made in the ORCHIDEE LSM. Two models have been implemented in ORCHIDEE in order to move from the current big leaf approach at the grid-cell scale to a representation of vertical gradients associated to the microclimate. To do so, firstly, a representation of the water flow in the soil-plant-atmosphere continuum through a hydraulic architecture model has been introduced. Secondly, a previous multi-layer energy budget representation, including turbulent vertical exchanges within the canopy, has been updated to make it operational with the current trunk of ORCHIDEE. Those two models enable a better representation of the intra-canopy leaf-atmosphere exchanges at the Plant Functional Type (PFT) level. Lastly, a representation of the sub-grid heterogeneity is also being implemented enabling a global representation of each PFT intra-canopy microclimates. This presentation will mainly focus on the multi-layer energy budget representation and its applications for different ecosystems at larger scale. Firstly, a comparison between ORCHIDEE and the forest model MuSICA (Ogée et al. (2003)) was performed over several forest sites highlighting the potential benefits as well as the difficulties of modelling the vertical gradients of temperature, wind and humidity within the canopy. Secondly, a first large scale representation of intra-canopy microclimate and its impact on ORCHIDEE energy and water budgets will be presented. Finally, opening perspectives induced by those developments in the ORCHIDEE LSM will be drawn. 

How to cite: Alléon, J., Ottlé, C., Vuichard, N., Luyssaert, S., Bouwen, K., Ogée, J., and Peylin, P.: First steps towards modelling the intra-canopy microclimate in the ORCHIDEE Land Surface Model, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17152, https://doi.org/10.5194/egusphere-egu24-17152, 2024.

Forest canopies can buffer or amplify macroclimate temperature extremes in their understory depending on structural and ecological parameters such as canopy height, canopy openness, and species composition. Forest management practices that alter these parameters have a strong impact on understory temperature extremes, with potential repercussions on forest resilience to climate change.

Physics-based microclimate models offer a means to explore the effects of forest canopy structure on understory temperatures. Compared to empirical models, they allow to extrapolate results outside the range of canopy structure and climatic conditions that have been observed so far. Although physics-based models may differ in their representation of soil-vegetation-atmosphere interactions, they all rely on a priori knowledge of meteorological data above the forest (also called climate forcing), including air temperature, relative humidity and wind speed timeseries. This raises challenges when conducting sensitivity analyses on structural parameters because canopy structure influences the microclimate not only inside and below the forest canopy but also above it. Employing the same climate forcing for all scenarios of canopy structure is thus deemed inappropriate and adjustments of climate forcing must be accounted for.

In this study, we propose a new physics-based modelling approach to perform sensitivity analyses of canopy structure on understorey microclimate that incorporates the feedback of a change in canopy structure on the climatic conditions above it. This approach relies on existing theories on the similarity of turbulent flux-gradient relationships within the atmospheric surface boundary layer between different scalars (e.g. air temperature and humidity) and wind speed, adapted to rough surfaces such as forest canopies. This approach is tested against datasets collected in various forest ecosystems across Europe and applied to explore the impact of canopy structure, in particular canopy density and clumping, on understory microclimate. Our approach will advance our understanding of the intricate relationships between canopy structure, boundary layer dynamics and microclimate, offering insights for more effective forest management strategies.

How to cite: Bouwen, K., Domec, J.-C., Charru, M., and Ogée, J.: The impact of forest canopy structure on the understory microclimate: a physics-based approach and sensitivity analysis, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10808, https://doi.org/10.5194/egusphere-egu24-10808, 2024.

Temperature and vapor pressure deficit (VPD) are fundamental drivers of plant ecophysiological function, and developing conceptual and predictive frameworks describing how photosynthesis, stomatal conductance, and transpiration respond to (and modify) these drivers is an long-standing research challenge. At the plant- and ecosystem-scale, much of our understanding of these processes has been derived by linking whole plant responses (e.g. from flux towers, sap flow, etc) to the temperature and VPD of the air measured some horizontal or lateral distance away from the plants themselves. However, thermodynamic processes frequently promote large gradients between canopy leaf and air temperatures, with tremendous variations across vertical and horizontal gradients. Here, we will synthesize observations from >100 flux towers to show that this difference can amount to 10 degrees C (or more), especially on hot summer days when heat impacts are most deleterious. The gradient between canopy and air temperature is not well explained by plant functional type, albedo, or climate, but are clearly related to canopy height and the dynamics of evapotranspiration. These profound differences in canopy versus air temperature translate into large (e.g. >5 kPa) differences between the VPD of the air and the vapor pressure differences experienced by leaves. Empirically derived sensitivities of stomatal conductance and photosynthesis to VPD are likely overestimated when the VPD of the air is used as a proxy for the vapor pressure difference experienced by plants. These biases can obscure our species-level understanding of how gas exchange responds to VPD and become especially problematic when observed sensitivities are compared with theoretical expectations or implemented in models that do not account for VPD gradients. We will conclude by discussing some strategies to limit these biases in field settings. 

How to cite: Novick, K., Barnes, M., and Gentine, P.: Large and problematic gradients in temperature and VPD in field research settings, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10235, https://doi.org/10.5194/egusphere-egu24-10235, 2024.

Environmental heterogeneity occurring at small-spatial scale strongly influences the structure, composition, and functioning of tropical rainforests. Environmental filters particularly influence the establishment and survival of young individuals. The relative importance of different micro-environmental variables in shaping tree species distributions through their habitat preference and their regeneration niche however remains poorly known, due in particular to methodological limitations in the characterisation of the small-scale abiotic environment. In this study, we propose to address this knowledge gap and methodological limitation by using the latest LiDAR technology. LiDAR has already proven its ability to describe the 3D forest structure and topography on a fine scale. Forest structure and topography already allowed the prediction of important micro-climatic components for trees and notably light and associated air temperature and moisture as well as local drainage regime. LiDAR technology may also contribute to the prediction of other conditions essential to plant life: soil temperature, water and nutrient access. The LiDAR acquisition methods currently used to map forest structure have some limitations. Standard airborne laser scanning fails to describe the lower canopy in sufficient detail due to occlusion by the upper canopy. Here we explore the potential of low altitude high power laser with enhanced penetration to describe the structure of the forest understorey. We use the recorded laser pulse extinction to build a 3D model of light transmission through the canopy. We evaluate the capacity of the light transmission model to predict microclimatic variables which were monitored in the understorey for 10mo. We also derive a fine resolution digital terrain model from the airborne laser data and explore how soil characteristics covary with topographic features extracted from the DTM.

How to cite: Badouard, V., Verley, P., and Vincent, G.: Using high penetration airborne LiDAR scanning to characterise the micro-environment of dense tropical forest., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10542, https://doi.org/10.5194/egusphere-egu24-10542, 2024.

Studying the feedback between forest structure and the environment, particularly below canopies, is crucial for sustainable forest management, biodiversity conservation, and climate mitigation. Advanced vegetation models play a key role in unraveling the complex interaction between forest composition and environmental conditions, as these allow to understand the dynamics of ecosystems by simulating the interactions between plant species and their environment. An essential aspect necessitating refinement in these models is understanding how radiation interacts with intricate structures like forest canopies.

In this study, we employ advanced terrestrial laser scanning techniques, distributed fiber-optic, and microclimate sensors to investigate the relationships between light, microclimate, carbon cycling, and forest structure in temperate forests. In a temperate forest in Belgium, we implemented a sensor setup since March 2023. It comprises a Distributed Temperature Sensing (DTS) fiber, Temperature and Moisture Sensor (TMS) microclimate loggers, SurveyTag microclimate loggers, Photosynthetic Active Radiation (PAR) sensors, and pyranometer (direct/diffuse) light sensors along a 135 m long transect from forest edge to core. Monthly 3D terrestrial laser scanning (TLS) of the transect allowed us to quantify forest structure with high spatiotemporal resolution.

Preliminary results reveal distinct microclimate gradients along the transect and seasonal changes in forest structure in 3D space, including budding and changes in canopy volume. These findings will be used to calibrate and improve existing radiative transfer models (RTMs) to be further implemented in vegetation models. Integrating observations and model parameters in a common framework will provide breakthrough insights into the feedbacks between light, forest structure, microclimate, and their impact on the carbon cycle in temperate forests.

How to cite: Van de Walle, E., De Hertog, S., Meunier, F., Calders, K., De Frenne, P., Yang, Z., Stock, M., wyffels, F., Terryn, L., Sanczuk, P., Verhelst, T. E., and Verbeeck, H.: Quantifying and modelling feedbacks between forest structure, light, microclimate and carbon cycling in temperate forests, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1767, https://doi.org/10.5194/egusphere-egu24-1767, 2024.

Despite terrestrial vegetation being one of the largest carbon sinks, it’s representation within weather and climate models is simple due to computational and data constraints. Whilst the representation of many processes has been improved, the absorption of light by vegetation canopies is still described using the assumption of a plane-parallel turbid medium, which is not realistic. This approach assumes randomly distributed leaves, with no horizontal or vertical variability, and a flat canopy base. However, it is widely used as it permits the radiative transfer for vegetation to be described using a two-stream model (Sellers, 1985) that can be solved analytically.

This work examines the importance of including realistic vegetation structure in photosynthesis calculations, testing the sensitivity of modelled Gross Primary Productivity (GPP) to the common turbid-media approximation by using detailed forest canopy information. We derive a methodology for calculating GPP from radiative transfer calculations from a high-resolution, computationally demanding, radiative transfer model, DART (Discrete Anisotropic Radiative Transfer). The GPP calculation  is based upon the photosynthesis scheme from the JULES (Joint UK Land Environment Simulator) land surface model. We explore the impacts of structure on GPP for six real forest canopies, from across the globe using 3D vegetation data collected using Terrestrial Lidar Scanning (TLS). The use of a 3D radiative transfer model allows us to investigate how much difference the two-stream approach introduces compared to detailed forest canopies with different levels of structure. We examine the profiles of both the absorbed radiation (fAPAR) and GPP.

Across the six forest scenes used, there is generally a reduction in GPP as more structure is introduced. However, this is particularly the case in scenes where the horizontal variation of LAI is high. Additionally, in these scenes, we find that this increase in GPP is less pronounced at low sun angles. This work suggests that consideration should be taken in incorporating horizontal variability of the vegetation within weather and climate models, particularly when identifying the effects of forests on the global carbon budget.

How to cite: Stretton, M., Quaife, T., Wilkes, P., and Disney, M.: The impact of forest canopy structure on modelled photosynthesis, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5471, https://doi.org/10.5194/egusphere-egu24-5471, 2024.

Significant mismatches between macro- and microclimates challenge our ability to accurately estimate the climatic conditions experienced by organisms and thus to predict responses to climate change. This study aims to evaluate the relationship between macro- and microclimate for small-scale plants such as bryophytes, which are highly dependent on local environmental conditions.

To achieve this, we established a Europe-wide collaborative network of bryologists (the BryoMicroClim project), to measure the microclimate experienced by a bryophyte species. The moss Hedwigia striata, evaluated as near-threatened in Europe (Hodgetts et al., 2019), was selected as the target species. This species grows mainly in forests or rocky areas. We selected 15 sampling sites across Europe, spanning a wide range of climate conditions (Portugal, Spain, France, Belgium, Wales, Scotland, and Sweden). In each site, mostly continuous forested areas, we measured air temperature and humidity using three dataloggers (Envloggers, Environmental loggers) installed near H. striata populations. In the Iberian Peninsula, we also installed other dataloggers (BtMs, Bryolichen Temperature Moisture), specifically designed to measure ambient temperature, humidity, and water content of nonvascular cryptogams.

We used the slope and equilibrium approach (Grill et al., 2022) to infer if the microclimate temperature and relative humidity variability (as measured by the in-situ dataloggers) is buffered or amplified in relation to the macroclimate variability (from ERA5-Land and ERA5 data). We observed that microclimate temperatures were buffered or amplified depending on site conditions. As hypothesized, microclimate temperatures had a buffered variability in dense forest sites. Our results suggest that collecting bryophyte-relevant microclimate data at fine spatial resolutions and long time scales will be critical to better understand the potential vulnerability of bryophytes to climate change.

How to cite: Hespanhol, H. and the BryoMicroClim: BryoMicroClim: Collecting bryophyte-relevant microclimate data to assess the gap between macro- and microclimate , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13257, https://doi.org/10.5194/egusphere-egu24-13257, 2024.

In recent decades, species distribution models (SDMs) have become pivotal in forecasting how changing environmental conditions impact species distributions across space and time. Most SDMs rely on correlations, utilizing statistical or machine-learning techniques to infer links between species occurrences and their environment. Typically, these models rely on a traditional set of bioclimatic variables, often available at a coarse spatial resolution of 30 arc seconds or less. These macroclimatic data are derived through interpolating weather station data, essentially reflecting the free-air temperature conditions in open ecosystems. However, a significant portion of terrestrial life on Earth and many critical ecological processes respond to climate conditions at much finer scales beneath the canopies of trees. Neglecting this mismatch might lead to inaccurate predictions, misinterpretations, and potentially flawed conservation decisions. Hence, there's a pressing need to incorporate finer-scale microclimate data in ecological modelling to ensure more accurate assessments and informed conservation strategies.

By developing an innovative spatial machine learning model capable of quantifying the temperature buffering capacity of European forests at very fine resolutions, we crafted the ForestClim database, containing a novel set of bioclimatic variables. These variables unveil the intricate microclimatic temperature variations within forest ecosystems, marking a significant scientific breakthrough that shows promise to enhance ecological models and predictions. Furthermore, by freely sharing this data, we lower the threshold for fellow ecologists to incorporate pertinent microclimatic information into their research.

Leveraging the open-access ForestClim database, we further assessed how large-scale, gridded microclimate temperature data affect the accuracy of SDMs of European forest plant species and how their modelled environmental niches and projected geographic ranges differ from conventional SDMs. The study's findings demonstrate that SDMs based on microclimate significantly outperform their macroclimate-based counterparts. They also reveal the introduction of a systematic bias in thermal response curves when relying on macroclimate-based models, potentially leading to inaccuracies in forecasting range shifts. Furthermore, the inclusion of microclimate data in these models enables the identification of microrefugia within the landscape - areas where species can find a stable and suitable climate amid unfavourable, changing macroclimatic conditions. This newfound information holds particular significance in the realm of conservation science, as microclimate-based SDMs prove to be valuable tools for gaining insights into biodiversity conservation in the face of climate change. This is especially pertinent given the increasing policy and management emphasis on conserving refugia worldwide.

How to cite: Van Meerbeek, K. and Haesen, S.: Fine-scale microclimate data improve species distribution models of forest plant species, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4103, https://doi.org/10.5194/egusphere-egu24-4103, 2024.

Recent research has shown that the impacts of climate change on terrestrial species distributions are more complex than expected. Species distributions are showing significant delays in responses, or have shifted in unexpected directions. Scientists have identified several mechanisms that could explain these mismatches, including slow population dynamics, habitat fragmentation, and biotic interactions that limit the spread of species. Yet, one crucial aspect remains largely overlooked: we first need relevant high-resolution baseline climate change data to accurately answer this question.

Indeed, organisms respond to microclimate change, which can differ significantly from macroclimate change. We know that local temperatures near the ground or below vegetation can be several degrees different from weather station data. However, it remains a mystery how quickly these microclimates are changing, as this depends as much on climate change as on land use changes.

In this talk, we will explore how the SoilTemp-database, a global database of more than 75,000 in-situ measured microclimate time series, can be used to improve global microclimate products and ultimately provide better estimates of microclimate change. By applying these products to improve our estimates of species distributions, we can better understand the impacts of climate change on biodiversity, crucial for adjusting biodiversity management to a rapidly changing world.

How to cite: Lembrechts, J. and network, S.: Microclimate change: the hidden driver of species redistributions, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4745, https://doi.org/10.5194/egusphere-egu24-4745, 2024.