Abstract. Microclimate represents climatic conditions at spatial scales of meters to tens of meters and often deviates substantially from regional macroclimate due to effects of local topography and land cover. These deviations shape species distributions, ecosystem processes, and organism responses to climate change, yet spatially explicit microclimatic data have long been unavailable at national scales. Here we present a high-resolution (10 m) dataset of monthly microclimatic temperature offsets for the Czech Republic. Microclimate is expressed as offsets between in situ air temperature measurements at 2 m height and downscaled, elevation-corrected macroclimatic temperatures from the ERA5-Land climate reanalysis. Temperature offsets were modelled separately for mean, minimum, and maximum monthly air temperature using generalized additive models trained on a large network of forest microclimate loggers and standard meteorological stations, covering the period 2018–2024. To capture spatially explicit microclimatic effects, the models integrated variables representing topographic parameters, vegetation characteristics, urban heat island effects and their seasonal dynamics. The resulting CzechGrids Micro dataset consists of 39 GeoTIFF rasters providing monthly and annual local air temperature offsets that can be combined with downscaled ERA5-Land data to derive absolute microclimatic temperatures for any user-defined periods. The maps are primarily intended for applications in ecological research, climate impact assessments, and adaptation planning at fine spatial scales. The CzechGrids Micro monthly temperature offset grids are freely available at: https://doi.org/10.5281/zenodo.18472086 (Macek et al., 2026).

High-resolution microclimatic temperature grids are needed for ecosystem modelling, biodiversity conservation, and forest management. However, existing climatic grids are coarse and do not capture microclimatic temperatures beneath tree canopies or near the ground. To address this, we established a dense network of microclimatic loggers continuously measuring air, near-ground, and soil temperatures. We combined one year of these in situ temperature measurements with high-resolution LiDAR-derived land surface topography and forest structure using boosted spatial generalized additive models to develop 5-m resolution microclimatic grids for the largest forest wilderness area in Central Europe, the Bohemian Forest Ecosystem (BFE). The resulting grids provide reasonable estimates of local annual maximum, mean, and minimum temperatures and growing degree days at different heights with spatially cross-validated RMSE values ranging from 0.41 °C for annual mean soil temperature to 2.34 °C for maximum near-ground temperature. Compared to SoilTemp (soil temperature), ForestTemp (near-ground temperature), and downscaled ERA5-Land (air temperature), the BFE microclimatic grids provide the most accurate local temperature estimates and capture substantially more spatial microclimatic variability.

Due to anthropogenic pressure some species have declined whereas others have increased within their native ranges. Simultaneously, many species introduced by humans have established self-sustaining populations elsewhere (i.e. have become naturalized aliens). Previous studies have shown that particularly plant species that are common within their native range have become naturalized elsewhere. However, how changes in native distributions correlate with naturalization elsewhere is unknown. We compare data on grid-cell occupancy of native vascular plant species over time for 10 European regions (countries or parts thereof). For nine regions, both early occupancy and occupancy change correlate positively with global naturalization success (quantified as naturalization in any administrative region and as the number of such regions). In other words, many plant species spreading globally as naturalized aliens are also expanding within their native regions. This implies that integrating data on native occupancy dynamics in invasion risk assessments might help prevent new invasions.

Atmospheric vapor pressure deficit (VPD) controls local plant physiology and global vegetation productivity. However, at ecologically crucial intermediate spatial scales, the role of VPD variability in forest bryophyte community assembly and the processes controlling this variability are little known. To explore VPD effects on bryophyte community composition and richness and to disentangle processes controlling landscape-scale VPD variability, we recorded bryophyte communities and simultaneously measured forest microclimate air temperature and relative humidity across a topographically diverse landscape representing a bryophyte diversity hotspot in temperate Europe. Based on VPD importance for plant physiology, we hypothesize that VPD can be important also for bryophyte community assembly and that VPD variability will be jointly driven by saturated and actual vapor pressure across the topographically diverse landscape with contrasting forest types and steep microclimatic gradients. Contrary to our expectation, VPD variability was dictated by temperature-driven differences in saturated vapor pressure, while actual vapor pressure was surprisingly constant across the landscape. Gradients in species composition, species richness and community structure of bryophyte assemblages followed closely the VPD variability. The average daily mean VPD was a much better predictor of species composition than average daily maximum VPD. The mean VPD also explained significantly more variation in species composition and richness than maximum temperature, indicating that time-averaged evaporative stress is more relevant for bryophyte communities than microclimatic extremes. While mesic forest bryophytes occurred along the whole VPD gradient, species occurring near their distributional limits and locally rare species preferred sites with low VPD. Consequently, low VPD sites represent species-rich microclimatic refugia within the landscape, where regionally abundant mesic forest bryophytes coexist with rare species occurring near their distributional range limits. Our results showed that VPD variability at ecologically crucial landscape scales is controlled by temperature-driven saturated vapor pressure. Future climate warming will thus increase evaporative stress and reshuffle VPD-sensitive forest bryophyte communities even in topographically diverse landscapes, which are traditionally considered as microclimatic refugia buffered against climate change. Bryophyte species occurring near their distributional range limits in microclimatic refugia with low VPD will be especially vulnerable to the future changes in atmospheric VPD.

Forest recovery following disturbances is essential for maintaining ecosystem services, especially after large-scale events where regeneration is limited by seed availability. Understanding how environmental and biotic factors influence regeneration across spatial scales is fundamental for landscape-scale management, yet the importance and spatial extent of landscape-scale effects on local recovery remains uncertain. We aimed to assess the relative influence of recovery drivers at plot, patch, and landscape scales on post-disturbance forest regeneration. Specifically, we investigated how local topography, disturbance characteristics, and the spatial arrangement of undisturbed forests affect tree regeneration after severe disturbances, namely windthrows, fires, and bark beetle outbreaks. Our study combines a comprehensive ground-based dataset of post-disturbance regeneration from temperate European forests with Landsat-derived maps of forest cover. We applied a distance-weighted regression approach to evaluate the effect of landscape (i.e., undisturbed forest in proximity of disturbance patches) on recovery, improving upon traditional buffer-based approaches. We found that ¾ of the landscape influence on forest regeneration occurred within 112 m from plot centers, with undisturbed forests nearby positively enhancing regeneration, likely due to increased seed availability. In contrast, plot-level factors, namely disturbance severity and elevation, negatively impacted regeneration, suggesting that regeneration success can be hindered by severe disturbances reducing living biological legacies, as well as harsher local climatic conditions, associated with higher elevations. Our findings underline the importance of integrating landscape-scale management with targeted local interventions to promote post-disturbance forest recovery. Management strategies should consider spatially explicit planning to enhance seed source availability and mitigate severe disturbance impacts.

The fourteenth part of the series on the distributions of vascular plants in the Czech Republic includes grid maps of 103 taxa in the genera Achnatherum, Adonis, Consolida, Corallorhiza, Cypripedium, Dianthus, Glaux, Inula, Juncus, Laser, Linum, Mahonia, Malaxis, Mercurialis, Nassella, Ononis, Pseudorchis, Pyracantha, Rosa, Rubus, Sagina, Samolus, Smyrnium, Spiranthes, Stipa and Traunsteinera. These maps were produced by taxonomic experts based on examined herbarium specimens, literature and field records. The spectrum of taxa includes various ecological groups. Rare habitat specialists are represented by the halophytes Glaux maritima, Juncus gerardii and Samolus valerandi, psammophytes Dianthus arenarius subsp. bohemicus and Stipa borysthenica, petrophytes Dianthus gratianopolitanus, D. lumnitzeri and D. moravicus and the serpentinophyte Dianthus carthusianorum subsp. capillifrons. Additional rare and declining species are among orchids, weeds of arable land, and plants of dry grasslands, thermophilous oak forests and subalpine habitats. Three of the included taxa are Czech endemics (Dianthus arenarius subsp. bohemicus, D. carthusianorum subsp. sudeticus and D. moravicus) and two subendemics, with ranges extending into bordering countries (Dianthus carthusianorum subsp. capillifrons and Rubus brdensis). Altogether, half of the mapped taxa are on the national Red List. Alien species are also represented in this paper. The previously introduced neophytes Mahonia aquifolium, Pyracantha coccinea, Sagina apetala and Smyrnium perfoliatum have started to spread in recent decades. Nassella tenuissima has begun to escape from cultivation. In contrast, some formerly more common weeds of arable land have been declining in recent decades. Spatial distributions and often also temporal dynamics of individual taxa are shown in maps and documented by records included in the Pladias database and available in the Supplementary materials. The maps are accompanied by comments that include additional information on the distribution, habitats, taxonomy and biology of the taxa.

Mountain ecosystems are experiencing significant changes due to climate change. Globally, a prevailing greening trend has been observed over the past decades using remote-sensing normalized difference vegetation index (NDVI), suggesting increasing vegetation cover and primary productivity. However, NDVI responses to warming differ across regions. Cold, energy-limited alpine and tundra ecosystems tend to respond positively to warming, while arid, water-limited ecosystems may experience reduced NDVI due to higher transpiration rates limiting plant growth. Additionally, CO _2 fertilization effect enhances vegetation productivity by improving plant water use efficiency. This study investigates the drivers of temporal trends in annual maximum NDVI (NDVImax) along an elevational gradient in the arid Western Himalaya (Ladakh, India). We hypothesize that NDVImax will be more sensitive to precipitation anomalies at lower elevations, whereas at higher elevations it will be more sensitive to temperature anomalies. Using Landsat satellite data from 2001 to 2022, we related NDVImax temporal anomalies to temperature and precipitation obtained from the ERA5-Land reanalysis dataset, and local snow cover from MODIS. Our results show complex interactions between climate and elevation that influence NDVImax. Contrary to our expectations, precipitation exhibited a strong positive effect on NDVImax across all elevations and seasons, except for autumn at higher elevations. Temperature effects were weaker and varied across seasons and elevations. Higher summer temperatures increased NDVImax at higher elevations but decreased it at lower elevations. We observed a multidecadal greening trend independent of temperature and precipitation, with this greening being more pronounced at lower elevations. This study highlights the importance of context dependency in understanding vegetation dynamics in fragile, low-productivity mountain ecosystems.

Understanding the spatial patterns and drivers of species richness is crucial for biodiversity conservation. Using data from Pladias, a comprehensive botanical database of the Czech Republic, we mapped the richness of various plant species groups across grid cells in the country and examined the effects of current environmental conditions, current landscape structure, and historical landscape development. We also applied five methods to account for uneven sampling intensity and found that only rarefaction provided estimates of species richness independent of sampling intensity. Using spatial error models and a variation partitioning approach, we showed that plant richness at the country scale is predominantly driven by current environmental conditions. For overall species richness, as well as for native and threatened species richness, the most important factors were the proportion of carbonate bedrock and the level of climate moisture, while the heat sum in the growing season was crucial for naturalized alien species richness. Historical landscape development, especially the long-term continuity of forests and grasslands, significantly influenced the richness of all, native, and particularly threatened species. Human population density was positively related to all species groups, emerging as the most important variable for the richness of naturalized alien species. However, our study shows that uneven sampling intensity in the Pladias database may distort the effect of certain environmental factors, such as the heat sum in the growing season. These findings emphasize the importance of carefully considering the uneven intensity of sampling before analysing species richness and highlight the role of current environmental variables, current landscape structure, and historical landscape development in shaping plant species richness at the regional scale.

Accurately assessing the impacts of climate change on forest ecosystems requires understanding how macroclimate and microclimate interact over time. Forest microclimates, strongly influenced by canopy cover and terrain, often deviate significantly from regional macroclimate. Recent research has highlighted the role of forest microclimate buffering for understory plant communities, which seem to be less impacted by global climate change. However, the increasing magnitude and frequency of macroclimatic extremes and associated forest disturbances could still threaten these communities, potentially overwhelming the forest buffering capacity and significantly altering plant community composition. Addressing these uncertainties requires long-term microclimate time-series. Yet, long-term datasets on forest microclimatic dynamics remain scarce. Here, we aim to fill this gap by leveraging detailed historical microclimate measurements from the 1950s in central European forests. These unique data serve as a foundation for developing and validating mechanistic microclimate models, enabling the reconstruction of long-term microclimate dynamics. Using biophysical principles, mechanistic modeling provides a robust approach to simulating near-ground temperature and humidity conditions based on macroclimatic inputs and local landscape and vegetation characteristics. By integrating macroclimate data with our in situ microclimate measurements, this research paves the way for exploring how forest microclimates influence plant community composition over time and disentangling the relative contributions of micro- and macroclimatic drivers to long-term vegetation change.

Over the past 60 years, natural habitats have been affected by various anthropogenic pressures. However, little is known about how these pressures have influenced the species composition of whole floras across large areas. We used a large database of the Czech flora to assess broad-scale temporal trends in temperate European flora over the last 60 years. We extracted over 4.6 million occurrence records of 1912 species collected over the past six decades and analysed the changes in species occurrence frequency over time using dynamic occupancy models within a Bayesian framework that accounted for various biases in the data. Five main patterns of temporal change were revealed. The increasing species were supported by different environmental changes that peaked at different periods. Competitively strong, nutrient-demanding generalist species that successfully colonize new and highly disturbed habitats supported by eutrophication and anthropogenic disturbances strongly increased in 1961-1980. Shade-tolerant species of less disturbed habitats increased between 1981 and 2000, indicating an effect of habitat abandonment, and thermophilous species began to spread in the last 20 years, reflecting rising temperatures. Competitively strong species of less frequently disturbed habitats with higher moisture and nutrient requirements and low light requirements increased gradually over the last six decades. In contrast, specialized species of nutrient-poor habitats with low colonization and competitive ability, associated with more frequent but less severe disturbances, steadily decreased due to the ongoing decline of habitat quality after the cessation of traditional management, and many of them have been included in the national Red List.

AimThe scale of environmental data is often defined by their extent (spatial area, temporal duration) and resolution (grain size, temporal interval). Although describing climate data scale via these terms is appropriate for most meteorological applications, for ecology and biogeography, climate data of the same spatiotemporal resolution and extent may differ in their relevance to an organism. Here, we propose that climate proximity, or how well climate data represent the actual conditions that an organism is exposed to, is more important for ecological realism than the spatiotemporal resolution of the climate data.LocationTemperature comparison in nine countries across four continents; ecological case studies in Alberta (Canada), Sabah (Malaysia) and North Carolina/Tennessee (USA).Time Period1960-2018.Major Taxa StudiedCase studies with flies, mosquitoes and salamanders, but concepts relevant to all life on earth.MethodsWe compare the accuracy of two macroclimate data sources (ERA5 and WorldClim) and a novel microclimate model (microclimf) in predicting soil temperatures. We then use ERA5, WorldClim and microclimf to drive ecological models in three case studies: temporal (fly phenology), spatial (mosquito thermal suitability) and spatiotemporal (salamander range shifts) ecological responses.ResultsFor predicting soil temperatures, microclimf had 24.9% and 16.4% lower absolute bias than ERA5 and WorldClim respectively. Across the case studies, we find that increasing proximity (from macroclimate to microclimate) yields a 247% improvement in performance of ecological models on average, compared to 18% and 9% improvements from increasing spatial resolution 20-fold, and temporal resolution 30-fold respectively.Main ConclusionsWe propose that increasing climate proximity, even if at the sacrifice of finer climate spatiotemporal resolution, may improve ecological predictions. We emphasize biophysically informed approaches, rather than generic formulations, when quantifying ecoclimatic relationships. Redefining the scale of climate through the lens of the organism itself helps reveal mechanisms underlying how climate shapes ecological systems.

Abstract Changes in species' native range size and occupancy have been dramatically accelerated by anthropogenic pressures in the last centuries. At the same time humans have introduced thousands of species beyond their historic range limits, and some of these have established self-sustaining populations (i.e. become naturalized). It is known that particularly common plant species have become naturalized, but how dynamics in native distributions relate to global naturalization is unknown. We retrieved data on grid-cell occupancy of native vascular plant species for 10 European regions, for at least two periods, to calculate for each species an occupancy-change index. For nine of the ten regions, we found a significant increase in global naturalization with both the early period occupancy and occupancy-change index. This finding shows that many of the plant species expanding globally as naturalized aliens are also expanding within their native ranges and suggests that the same drivers underlie both processes.

Species distribution models (SDMs) have proven valuable in filling gaps in our knowledge of species occurrences. However, despite their broad applicability, SDMs exhibit critical shortcomings due to limitations in species occurrence data. These limitations include, in particular, issues related to sample size, positional uncertainty, and sampling bias. In addition, it is widely recognised that the quality of SDMs as well as the approaches used to mitigate the impact of the aforementioned data limitations depend on species ecology. While numerous studies have evaluated the effects of these data limitations on SDM performance, a synthesis of their results is lacking. However, without a comprehensive understanding of their individual and combined effects, our ability to predict the influence of these issues on the quality of modelled species–environment associations remains largely uncertain, limiting the value of model outputs. In this paper, we review studies that have evaluated the effects of sample size, positional uncertainty, sampling bias, and species ecology on SDMs outputs. We build upon their findings to provide recommendations for the critical assessment of species data intended for use in SDMs.

The unifying element of all biodiversity data is the issue of taxon hierarchy modeling. We compared 25 existing databases in terms of handling taxa hierarchy and presentation of this data. We used documentation or demo installations of databases as a source of information and next in line was the analysis of structures using R packages provided by inspected platforms. If neither of these was available, we used the public interface of individual databases. For almost half (12) of the databases analyzed, we did not find any formalized taxa hierarchy data structure, providing only biological information about taxon membership in higher ranks, which is not fully formalizable and thus not generally usable. The least effective Adjacency List model (storing parentId of a taxon) dominates among the remaining providers. This study demonstrates the lack of attention paid by current biodiversity databases to modeling taxon hierarchy, particularly to making it available to researchers in the form of a hierarchical data structure within the data provided. For biodiversity relational databases, the Closure Table type is the most suitable of the known data models, which also corresponds to the ontology concept. However, its use is rather sporadic within the biodiversity databases ecosystem.

Riparian ecosystems are among the most valuable natural ecosystems in terms oftheir diversity and ecosystem functions, but their intensive use by humans has led to their degra-dation and reduction in extent. One of the last free-flowing rivers in central Europe is the Elbe,with more than 600 km of water course without weirs. Thanks to the relatively natural fluvialregime, exposed gravel bars hosting specific vegetation including several endangered specieshave been preserved. In this study, we examined how factors that are related to fluvial dynamicsinfluence plant communities, above and belowground, on gravel bars that are periodicallyexposed along the Elbe in the Czech Republic. This study was carried out along a 40 km longstretch of the river between & Uacute;st & iacute; nad Labem and the Czech-German border. There, 10 localitieswere selected where 60 plots 1 x 1 m in size were established that were arranged in transectsperpendicular to the river. Plant communities were recorded in terms of their composition andrichness of both the standing vegetation and the soil seed bank, which provides information onthe regeneration potential of these communities. All vascular plant species were identified atthe peak of vegetation development and the soil seed bank cultivated from sediment samplednext to the plots. Of the environmental factors, the texture and chemical properties of the sedi-ment were analysed, and hydrological modelling was used to determine the duration of plotexposure. The composition of the vegetation was most influenced by the duration of plot expo-sure, which separated the species of long- and short-flooded sites. In contrast, the compositionof the seed bank was not significantly influenced by the environmental factors studied, but byfunctional species traits, with stress-tolerant species capable of clonal spread clearly differentfrom light- and moisture-demanding species witha ruderal life-strategy. It is concluded thatfluctuations in water level are essential for maintaining species richness on gravel bars becausethey create a strong gradient, which promotes the coexistence of species with different require-ments in small areas

Recent observations of tree regeneration failures following large and severe disturbances, particularly under warm and dry conditions, have raised concerns about the resilience of forest ecosystems and their recovery dynamics in the face of climate change. We investigated the recovery of temperate forests in Europe after large and severe disturbance events (i.e., resulting in more than 70% canopy loss in patches larger than 1 ha), with a range of one to five decades since the disturbance occurred. The study included 143 sites of different forest types and management practices that had experienced 28 disturbance events, including windthrow (132 sites), fire (six sites), and bark beetle outbreaks (five sites). We focused on assessing post-disturbance tree density, structure, and composition as key indicators of forest resilience. We compared post-disturbance height-weighted densities with site-specific pre-disturbance densities to qualitatively assess the potential for structural and compositional recovery, overall and for dominant tree species, respectively. Additionally, we analyzed the ecological drivers of post-windthrow tree density, such as forest management, topography, and post-disturbance aridity, using a series of generalized additive models. The descriptive results show that European temperate forests have been resilient to past large and severe disturbances and concurrent climate conditions, albeit with lower resilience to high-severity fire compared with other disturbance agents. Across sites and disturbance agents, the potential for structural recovery was greater than that of compositional recovery, with a large proportion of plots becoming dominated by early-successional species after disturbance. The models showed that increasing elevation and salvage logging negatively affect post-windthrow regeneration, particularly for late-successional species, while pioneer species are negatively affected by increasing summer aridity. These findings provide a key baseline for assessing future recovery and resilience following the recent occurrence of widespread disturbance in the region and in anticipation of future conditions characterized by increasing heat and drought stress. As a result of global change, forest disturbances are becoming larger and more severe, which may put forest recovery at risk, especially under a warm and dry climate. Our study shows that European temperate forests have been able to recover after large and severe disturbances and concurrent climate conditions, although with more difficulty after fires compared with other disturbance agents. The main factors negatively influencing tree regeneration after wind disturbances were increasing elevation and the removal of damaged trees from the disturbed forests.image

Forest canopies can buffer the understory against temperature extremes, often creating cooler microclimates during warm summer days compared to temperatures outside the forest. The buffering of maximum temperatures in the understory results from a combination of canopy shading and air cooling through soil water evaporation and plant transpiration. Therefore, buffering capacity of forests depends on canopy cover and soil moisture content, which are increasingly affected by more frequent and severe canopy disturbances and soil droughts. The extent to which this buffering will be maintained in future conditions is unclear due to the lack of understanding about the relationship between soil moisture and air temperature buffering in interaction with canopy cover and topographic settings. We explored how soil moisture variability affects temperature offsets between outside and inside the forest on a daily basis, using temperature and soil moisture data from 54 sites in temperate broadleaf forests in Central Europe over four climatically different summer seasons. Daily maximum temperatures in forest understories were on average 2 degrees C cooler than outside temperatures. The buffering of understory temperatures was more effective when soil moisture was higher, and the offsets were more sensitive to soil moisture on sites with drier soils and on sun-exposed slopes with high topographic heat load. Based on these results, the soil-water limitation to forest temperature buffering will become more prevalent under future warmer conditions and will likely lead to changes in understory communities. Thus, our results highlight the urgent need to include soil moisture in models and predictions of forest microclimate, understory biodiversity and tree regeneration, to provide a more precise estimate of the effects of climate change.

Filtering approaches on Global Ecosystem Dynamics Investigation (GEDI) data differ considerably across existing studies and it is yet unclear which method is the most effective. We conducted an in-depth analysis of GEDI's vertical accuracy in mapping terrain and canopy heights across three study sites in temperate forests and grasslands in Spain, California, and New Zealand. We started with unfiltered data (2,081,108 footprints) and describe a workflow for data filtering using Level 2A parameters and for geolocation error mitigation. We found that retaining observations with at least one detected mode eliminates noise more effectively than sensitivity. The accuracy of terrain and canopy height observations depended considerably on the number of modes, beam sensitivity, landcover, and terrain slope. In dense forests, a minimum sensitivity of 0.9 was required, while in areas with sparse vegetation, sensitivity of 0.5 sufficed. Sensitivity greater than 0.9 resulted in an overestimation of canopy height in grasslands, especially on steep slopes, where high sensitivity led to the detection of multiple modes. We suggest excluding observations with more than five modes in grasslands. We found that the most effective strategy for filtering low-quality observations was to combine the quality flag and difference from TanDEM-X, striking an optimal balance between eliminating poor-quality data and preserving a maximum number of high-quality observations. Positional shifts improved the accuracy of GEDI terrain estimates but not of vegetation height estimates. Our findings guide users to an easy way of processing of GEDI footprints, enabling the use of the most accurate data and leading to more reliable applications.

AbstractGlobal mapping of forest height is an extremely important task for estimating habitat quality and modeling biodiversity. Recently, three global canopy height maps have been released, the global forest canopy height map (GFCH), the high‐resolution canopy height model of the Earth (HRCH), and the global map of tree canopy height (GMTCH). Here, we assessed their accuracy and usability for biodiversity modeling. We examined their accuracy by comparing them with the reference canopy height models derived from airborne laser scanning (ALS). Our results show considerable differences between the evaluated maps. The root mean square error ranged between 10 and 18 m for GFCH, 9–11 m for HRCH, and 10–17 m for GMTCH, respectively. GFCH and GMTCH consistently underestimated the height of all canopies regardless of their height, while HRCH tended to overestimate the height of low canopies and underestimate tall canopies. Biodiversity models using predicted global canopy height maps as input data are sufficient for estimating simple relationships between species occurrence and canopy height, but their use leads to a considerable decrease in the discrimination ability of the models and to mischaracterization of species niches where derived indices (e.g., canopy height heterogeneity) are concerned. We showed that canopy height heterogeneity is considerably underestimated in the evaluated global canopy height maps. We urge that for temperate areas rich in ALS data, activities should concentrate on harmonizing ALS canopy height maps rather than relying on modeled global products.