Improved methods for measuring forest landscape structure: LiDAR complements field-based habitat assessment

Conservation and monitoring of forest biodiversity requires reliable information about forest structure and composition at multiple spatial scales. However, detailed data about forest habitat characteristics across large areas are often incomplete due to difficulties associated with field sampling methods. To overcome this limitation we employed a nationally available light detection and ranging (LiDAR) remote sensing dataset to develop variables describing forest landscape structure across a large environmental gradient in Switzerland. Using a model species indicative of structurally rich mountain forests (hazel grouse Bonasa bonasia), we tested the potential of such variables to predict species occurrence and evaluated the additional benefit of LiDAR data when used in combination with traditional, sample plot-based field variables. We calibrated boosted regression trees (BRT) models for both variable sets separately and in combination, and compared the models’ accuracies. While both field-based and LiDAR models performed well, combining the two data sources improved the accuracy of the species’ habitat model. The variables retained from the two datasets held different types of information: field variables mostly quantified food resources and cover in the field and shrub layer, LiDAR variables characterized heterogeneity of vegetation structure which correlated with field variables describing the understory and ground vegetation. When combined with data on forest vegetation composition from field surveys, LiDAR provides valuable complementary information for encompassing species niches more comprehensively. Thus, LiDAR bridges the gap between precise, locally restricted field-data and coarse digital land cover information by reliably identifying habitat structure and quality across large areas.     

Quantitatively defining the conservation status of Natura 2000 forest habitats and improving management options for enhancing biodiversity

The main goal of Natura 2000 network is to guarantee the favourable conservation status of habitats and species ensuring European biodiversity. As a result, certain forest areas have been included in this network listed as 9230-Quercus pyrenaica habitat and 9340-Quercus ilex subsp. rotundifolia forest habitat. These areas were previously used for firewood extraction or livestock grazing and browsing. Nowadays these habitats are coppice forests with asexual regeneration, which is far from the desired conservation status. Traditional timber harvesting plans do not take account of the new objectives required for these Natura sites, which attempt to ensure biodiversity and recreational uses instead of simply focusing on timber production. This paper proposes a flexible methodology (applied to the study area “Dehesa Boyal” in ávila, Spain) for managing Natura 2000 forest sites by stands for sustainable forest management and the new requirements. The methodology has two phases. The first, “Division of the forest area into stands”, defines homogeneous patches of vegetation distinct in species composition, physiognomic structure and future management. The second, “Conservation status assessment of stands”, quantifies the conservation status of each previously classified stand considering a series of factors such as: functional health, restoration, floral richness and structure. A total value integrating the conservation status of stands is then calculated for the habitat. Both phases use Geographic Information System tools for managing information and visualizing results. The proposed methodology provides forest managers with a good knowledge of the territory and subsequently enables them to take appropriate conservation measures to maintain biodiversity.     

Habitat type richness associations with environmental variables: a case study in the Greek Natura 2000 aquatic ecosystems

We investigated the potential associations of habitat type richness patterns with a series of environmental variables in 61 protected aquatic ecosystems of the Greek Natura 2000 network. Habitat type classification followed the Natura 2000 classification scheme. Habitat type richness was measured as the number of different habitat types in an area. To overcome a potential area effect in quantifying habitat type richness, we applied the “moving window” technique. The environmental variables were selected to account for some of the major threats to biodiversity, such as fragmentation, habitat loss and climate change. We run GLMs to associate habitat type richness with different combinations of climatic, spatial and topographic variables. Habitat type richness seemed to significantly associate with climatic variables, more than spatial or topographic ones. In particular, for the climatic ones, the importance of precipitation surpassed that of temperature and especially the precipitation of the wettest and driest month had a limiting contribution to richness unlike average climate estimators. Moreover, the landscape’s latitude and longitude and fragmentation were significantly associated to richness. Our findings are in accordance to those observed in recent literature at lower (i.e. species) levels of ecological organization, fact showing that large-scale phenomena (such as climate change) can also be observed at the habitat type level, at least in our case. Thus, following the context of the Habitats Directive (92/43/EEC), that habitat types and not solely species of community interest should be protected and restored, this study serves as a first step towards investigating habitat type richness patterns.     

Selection and application of spatial indicators for nature conservation at different institutional levels

As European integration increasingly affects pan-European nature conservation, indicators for the assessment of habitats are urgently needed to support ecosystem integrity monitoring as well as the target of halting biodiversity loss by 2010. The Natura 2000 network of protected sites with a strong focus on the protection of habitat types and strict monitoring obligations is now legally binding for all Member States. From a set of indicators that have been proposed for habitat monitoring by the SPIN project (Spatial Indicators for European Nature Conservation) we describe measures of landscape structure and soil function and their potential for the monitoring and management of protected areas and the surrounding landscape. In a case study from Austria, we show that structure-related indicators hold potential for the documentation of local-scale changes on a degraded raised bog Natura 2000 site. In a regional scale case study in northern Germany, we show how landscape metrics relate agricultural statistics, e.g. farm size and livestock density to landscape structure. In a third case study from Slovenia, we show how coarse-scale soil data can be disaggregated to finer scale by integrating topographic information and additional parameters for modelling, and production of soil-related habitat suitability maps. From these case studies we provide an overview of some of the critical issues affecting the selection and application of spatial indicators for nature conservation monitoring tasks. End users of spatial indicators work at different scales and in different biogeographical regions. The indicator selection and application demonstrated in our three case studies reveals the capability to contribute to a more quantitative evidence base for monitoring and management of biodiversity in Europe.     

Environmental diagnosis: Integrating biodiversity conservation in management of Natura 2000 forest spaces

The conservation of biodiversity in Europe is defined by Directive 92/43/EEC – commonly known as the Habitats Directive – relating to the conservation of natural habitats and of wild flora and fauna. This Directive established the creation of an ecological network of European protected areas – the Natura 2000 network – , and also recognised the need to manage these areas to maintain their “favourable conservation status”.This paper proposes a methodology which enables the conservation of biodiversity to be integrated into the management of Natura 2000 forest spaces. The methodology comprises an “environmental diagnosis” in three phases. The first phase evaluates the current conservation status of habitats using the following criteria: vital functions; floristic richness; forest structure; area occupied by the habitat; and recovery capacity. The second phase assesses the fragility of the space to determine the degree of vulnerability of habitats. This involves evaluating the fire hazard, erosion hazard, and the fragility of the vegetation. The last phase combines the two previous ones to generate management areas (optimum, intermediate or unfavourable) and to prioritise management actions.This methodology was applied in a protected forest area in the Natura 2000 network, located in Avila (Spain). Different management areas were generated for biodiversity conservation, and each habitat was associated to one of them. Finally, actions were prioritised and designed to raise the habitats to a “favourable conservation status”.     

Characterization of diverse plant communities in Aspen Parkland rangeland using LiDAR data

Question: How effective is high-resolution airborne LiDAR technology for quantifying biophysical characteristics of multiple community types within diverse rangeland environments? Location: Native Aspen Parkland vegetation in central Alberta, Canada. Methods: Vegetation within 117 reference plots stratified across eight types, including forest, shrubland, upland grassland and lowland meadow communities, were assessed in 2001 for the height, cover and density of vegetation within various strata (herb, shrub and tree layers). Actual ground data were subsequently compared against modelled values for each community type and strata derived from the analysis of airborne LiDAR data obtained in 2000. Results: LiDAR data were effective for quantifying vegetation height, cover and density of the overstory within closed- and open Populus forest communities. However, LiDAR measurements typically underestimated the height and cover of shrublands, as well as most of the herbaceous communities. Analysis of LiDAR intensity data indicated reflectance generally decreased as LiDAR sampling points moved upwards from the ground to the vegetation canopy. Conclusions: While LiDAR technology is useful for characterizing deciduous forest properties, the quantification of understory vegetation characteristics, as well as those of individual shrublands and grasslands, was more limiting. Further refinements in analysis methods are necessary to increase the reliability of characterizing these communities.     

Effectiveness of a large reserve network in protecting freshwater biodiversity: a test for the Iberian Peninsula

相似文献   

Climate change threatens European conservation areas

Europe has the world's most extensive network of conservation areas. Conservation areas are selected without taking into account the effects of climate change. How effectively would such areas conserve biodiversity under climate change? We assess the effectiveness of protected areas and the Natura 2000 network in conserving a large proportion of European plant and terrestrial vertebrate species under climate change. We found that by 2080, 58?±?2.6% of the species would lose suitable climate in protected areas, whereas losses affected 63?±?2.1% of the species of European concern occurring in Natura 2000 areas. Protected areas are expected to retain climatic suitability for species better than unprotected areas (P?相似文献   

Modelling relationships between birds and vegetation structure using airborne LiDAR data: a review with case studies from agricultural and woodland environments

Airborne LiDAR (Light Detection and Ranging) is a remote sensing technology that offers the ability to collect high horizontal sampling densities of high vertical resolution vegetation height data, over larger spatial extents than could be obtained by field survey. The influence of vegetation structure on the bird is a key mechanism underlying bird–habitat models. However, manual survey of vegetation structure becomes prohibitive in terms of time and cost if sampling needs to be of sufficient density to incorporate fine-grained heterogeneity at a landscape extent. We show that LiDAR data can help bridge the gap between grain and extent in organism–habitat models. Two examples are provided of bird–habitat models that use structural habitat information derived from airborne LiDAR data. First, it is shown that data on crop and field boundary height can be derived from LiDAR data, and so have the potential to predict the distribution of breeding Sky Larks in a farmed landscape. Secondly, LiDAR-retrieved canopy height and structural data are used to predict the breeding success of Great Tits and Blue Tits in broad-leaved woodland. LiDAR thus offers great potential for parameterizing predictive bird–habitat association models. This could be enhanced by the combination of LiDAR data with multispectral remote sensing data, which enables a wider range of habitat information to be derived, including both structural and compositional characteristics.     

Range reshuffling: Climate change,invasive species,and the case of Nothofagus forests in Aotearoa New Zealand

Aim

The impact of climate change on forest biodiversity and ecosystem services will be partly determined by the relative fortunes of invasive and native forest trees under future conditions. Aotearoa New Zealand has high conservation value native forests and one of the world's worst invasive tree problems. We assess the relative effects of habitat redistribution on native Nothofagus and invasive conifer (Pinaceae) species in New Zealand as a case study on the compounding impacts of climate change and tree invasions.

Location

Aotearoa New Zealand.

Methods

We use species distribution models (SDMs) to predict the current and future distribution of habitat for five native Nothofagus species and 13 invasive conifer species under two 2070 climate scenarios. We calculate habitat loss/gain for all species and examine overlap between the invasive and native species now and in future.

Results

Most species will lose habitat overall. The native species saw large changes in the distribution of habitat with extensive losses in North Island and gains mostly in South Island. Concerningly, we found that most new habitat for Nothofagus was also suitable for at least one invasive species. However, there were refugia for the native species in the wetter parts of the climate space.

Main Conclusion

If the predicted changes in habitat distribution translate to shifts in forest distribution, it would cause widespread ecological disruption. We discuss how acclimation, adaptation and biotic interactions may prevent/delay some changes. But we also highlight that the poor establishment capacity of Nothofagus, and the contrasting ability of the conifers to invade, will present persistent conservation challenges in areas of both new habitat and forest retreat. Pinaceae are problematic invaders globally, and our results highlight that control of invasions and active native forest restoration will likely be key to managing forest biodiversity under future climates.     

西辽河流域植被NPP时空分布特征及其影响因素研究

为研究西辽河流域植被生长特征及受气候变化的影响,该文以2000年—2015年MOD17A3的年均植被净初级生产力(NPP)数据、植被类型数据、土壤类型数据以及气温、降水资料为基础,利用GIS和RS技术,分析了西辽河流域植被净初级生产力时空格局、演变特征及驱动因子。结果表明:(1)西辽河流域近16年来植被NPP总量呈波动增加的趋势,变化范围为156.89～260.90 g C·m^-2·a^-1,平均值为219.76 g C·m^-2·a^-1,空间分布呈“边缘高、中间低”的特征; 植被NPP变化斜率为-16.53～16.65,95.74%的区域NPP呈增加趋势。(2)不同植被类型的NPP总量大小排序为草原>栽培植被>阔叶林>灌丛>草甸>针叶林; 西辽河流域固碳的植被类型主要是草原、栽培植被以及阔叶林,固碳能力较强的为针叶林。(3)生长在棕壤、褐土和潮土的植被年均NPP较高,生长在栗钙土和风沙土的植被年均NPP较低。(4)16年间植被NPP增长主要受降雨影响。气候暖-湿化及生态建设工程的实施,促进了西辽河流域植被的生长。以上研究结果为后期流域生态环境治理提供了科学依据及数据支持。     

基于植被和环境因子的亚高山森林土壤水源涵养功能空间尺度上推模型构建——以岷江上游杂谷脑流域为例

土壤层水源涵养功能是森林水源涵养功能的主体。目前关于森林土壤水源涵养功能的研究主要集中在林地或坡面尺度上。由于流域尺度,尤其是环境空间异质性强的西南亚高山区流域,如何将林地尺度实测结果上推至流域或更大空间尺度仍是生态水文领域面临的巨大挑战之一。以川西岷江上游杂谷脑流域为研究对象,融合多种森林类型样地实测与流域尺度多源遥感数据,构建了基于植被和环境因子的林地-流域森林土壤水源涵养功能尺度转换模型,实现了流域尺度土壤水源涵养功能快速评价及其空间分布预测。样地尺度研究结果表明各类型森林的土壤水文特性各异,总体表现为天然林优于人工林,混交林优于单纯林。林地土壤持水能力受到区域气候、植被、土壤及地形等因子的共同影响,其中风速、NDVI及林龄与土壤最大持水量、毛管持水量及非毛管持水量均呈极显著正相关（P<0.01）。基于关键植被和环境因子构建的林地-流域土壤水源涵养功能尺度上推模型精度较高,土壤最大持水量、土壤毛管持水量和土壤非毛管持水量模型拟合优度R²分别为0.700、0.720和0.908;土壤最大持水量、土壤毛管持水量和土壤非毛管持水量的模型预测值与野外实测值的相关系数介于0.69-0.79之间,平均误差均低于20%,表明模型预测结果可靠。利用构建的土壤水源涵养功能尺度上推模型,估算得出流域尺度森林土壤持水量的空间分布,其结果表明杂谷脑流域森林土壤持水量空间分异明显,海拔较高区域森林土壤持水量最高,其次为距道路和河流有一定距离的缓坡地带,下游干旱河谷地区土壤持水量最低。本研究为亚高山森林生态功能的恢复和提升提供了科学依据和评价工具。     

Assessing long-term spatial changes of natural habitats using old maps and archival sources: a case study from Central Europe

Landscapes intensively farmed over a long time period represent a threat for natural habitats and high levels of biodiversity. Information on the historical land use and spatial changes of natural habitats can help to explain the causes of a number of contemporary phenomena, which are important for the development of effective conservation and ecosystem management. This case study from the Czech Republic shows that archival written sources describing landscape quality, including vegetation cover, allow the reclassification of old maps to the level of natural habitat categories (sensu Natura 2000), with the aim of analyzing historic changes in land cover. Significant natural habitat decreases began by the middle of the 19th century. Over the course of 250 years, this area of formerly widespread natural wet meadows has declined by 99 %. An area of water vegetation was reduced by 95 %, willow carrs by 98 %, and a mosaic of willow carrs, wet Cirsium meadow, and alder carrs has decreased by 100 %. These decreases were caused by the conversion of meadows, pastures, and ponds into arable lands. Areas of oak-hornbeam forest, acidophilous oak forest, and thermophilous oak forest were primarily converted into monocultures of coniferous trees. Similarly, the areas with alluvial forests decreased. We conclude that old maps and other archive materials, despite their coarse accuracy, can serve as useful tools for disclosing natural habitat changes and their causes, providing a foundation for formulating biodiversity conservation strategies.     

太行山南麓山区不同植被恢复类型土壤理化和细根结构特征

在干旱半干旱地区,由于水分匮乏、土壤贫瘠等因素,将形成一定的裸地斑块,而这些斑块极易造成水土流失、滑坡等灾害,而具有不同植被覆盖的林地则能有效的保持水土。为完善干旱半干旱地区不同植被恢复类型下土壤理化和细根特征,选择太行山南麓山区具有代表性的裸露地、草地、荆条地、侧柏地、栓皮地和刺槐地等植被恢复类型,比较了各植被恢复类型下的土壤养分、粒径及细根状况等差异。研究表明:1)相对于裸露地,有植被覆盖的植被恢复类型拥有良好的土壤及细根状况。2)在不同植被类型中,刺槐林的有效氮转化速率较高;侧柏林有较高的细根参数;草地能够提高土壤中可吸收的磷组分。3)林地类型和土层均对土壤中含水率、黏粒、细根生物量和比根长产生极显著影响(P0.001)。4)各植被类型的对于土壤斑块的利用能力不同;不同植被类型中土壤及细根状况变化量具有一定的相似性,研究为生态恢复中植被类型的合理布局提供了新思路。     

Secondary forest buffers the effects of fragmentation on aerial insectivorous bat species following 30 years of passive forest restoration

Passive forest restoration can buffer the effects of habitat loss on biodiversity. We acoustically surveyed aerial insectivorous bats in a whole-ecosystem fragmentation experiment in the Brazilian Amazon over a 2-year period, across 33 sites, comprising continuous old-growth forest, remnant fragments, and regenerating secondary forest matrix. We analyzed the activity of 10 species/sonotypes to investigate occupancy across habitat types and responses to fragment size and interior-edge-matrix (IEM) disturbance gradients. Employing a multiscale approach, we investigated guild (edge foragers, forest specialists, flexible forest foragers, and open space specialists) and species-level responses to vegetation structure and forest cover, edge, and patch density across six spatial scales (0.5–3 km). We found species-specific habitat occupancy patterns and nuanced responses to fragment size and the IEM disturbance gradient. For example, Furipterus horrens had lower activity in secondary forest sites and the interior and edge of the smallest fragments (1 and 10 ha) compared to continuous forest, and only two species (Pteronotus spp.) showed no habitat preference and no significant responses across the IEM and fragment size gradients. Only the Molossus sonotype responded negatively to vegetation structure. We uncovered no negative influence of forest cover or edge density at guild or species-level. Our results indicate that reforestation can buffer the negative effects of fragmentation and although these effects can still be detected in some species, generally aerial insectivorous bats appear to be in recovery after 30 years of passive forest restoration. Our findings reinforce the need to protect regenerating forests while conserving vast expanses of old-growth forest.     

Microclimate species distribution models estimate lower levels of climate-related habitat loss for salamanders

Species distribution models (SDMs) largely rely on free-air temperatures at coarse spatial resolutions to predict habitat suitability, potentially overlooking important microhabitat. Integrating microclimate data into SDMs may improve predictions of organismal responses to climate change and support targeting of conservation assets at biologically relevant scales, especially for small, dispersal-limited species vulnerable to climate-change-induced range loss. We integrated microclimate data that account for the buffering effects of forest vegetation into SDMs at a very high spatial resolution (3 m²) for three plethodontid salamander species in Great Smoky Mountains National Park (North Carolina and Tennessee). Microclimate SDMs were used to characterize potential changes to future plethodontid habitat, including habitat suitability and habitat spatial patterns. Additionally, we evaluated spatial discrepancies between predictions of habitat suitability developed with microclimate and coarse-resolution, free-air climate data. Microclimate SDMs indicated substantial losses to plethodontid ranges and highly suitable habitat by mid-century, but at much more conservative levels than coarse-resolution models. Coarse-resolution SDMs generally estimated higher mid-century losses to plethodontid habitat compared to microclimate models and consistently undervalued areas containing highly suitable microhabitat. Furthermore, microclimate SDMs revealed potential areas of future gain in highly suitable habitat within current species’ ranges, which may serve as climatic microrefugia. Taken together, this study highlights the need to develop microclimate SDMs that account for vegetation and its biophysical effects on near-surface temperatures. As microclimate datasets become increasingly available across the world, their integration into correlative and mechanistic SDMs will be imperative for accurately estimating organismal responses to climate change and helping environmental managers tasked with spatially prioritizing conservation assets.     

Quantifying Tropical Dry Forest Type and Succession: Substantial Improvement with LiDAR

Improved technologies are needed to advance our knowledge of the biophysical and human factors influencing tropical dry forests, one of the world's most threatened ecosystems. We evaluated the use of light detection and ranging (LiDAR) data to address two major needs in remote sensing of tropical dry forests, i.e., classification of forest types and delineation of forest successional status. We evaluated LiDAR‐derived measures of three‐dimensional canopy structure and subcanopy topography using classification‐tree techniques to separate different dry forest types and successional stages in the Guánica Biosphere Reserve in Puerto Rico. We compared the LiDAR‐based results with classifications made from commonly used remote sensing data, including Landsat satellite imagery and radar‐based topographic data. The accuracy of the LiDAR‐based forest type classification (including native‐ and exotic‐dominated forest classes) was substantially higher than those from previously available data (kappa = 0.90 and 0.63, respectively). The best result was obtained when combining LiDAR‐derived metrics of canopy structure and topography, and adding Landsat spectral data did not improve the classification. For the second objective, we observed that LiDAR‐derived variables of vegetation structure were better predictors of forest successional status (i.e., mid‐secondary, late‐secondary, and primary forests) than was spectral information from Landsat. Importantly, the key LiDAR predictors identified within each classification‐tree model agreed with previous ecological knowledge of these forests. Our study highlights the value of LiDAR remote sensing for assessing tropical dry forests, reinforcing the potential for this novel technology to advance research and management of tropical forests in general.     

激光雷达技术在动物生态学领域的研究进展

激光雷达(light detection and ranging, LiDAR)作为一门新兴的主动遥感技术, 近年来由于在提取和反演森林参数水平上不断提高, 被越来越多地应用于动物生态学研究中。本文通过整理和搜集国内外文献, 对激光雷达的技术特点及其在森林参数提取和动物生境上的研究进展进行综述, 指出当前基于LiDAR的森林参数反演算法主要服务于森林资源调查或林学研究, 缺少对动物生态或生理意义相关的参数量化信息。目前该技术在国内的动物生态学方面的应用较少, 尚未见文章发表。通过总结国外学者的研究, 分别从动物生境选择与三维森林结构的关系、栖息地立体生境制图、生物多样性评估和物种分布模型预测三个方面综述了LiDAR在动物生态学研究中的应用现状。相比传统方法, LiDAR技术提供的高精度三维结构信息, 能够显著提高动物生境质量的评估、生物多样性的监测水平和物种分布模型的评价精度, 有利于从机理上加深对物种生境选择和集群过程的理解。但目前LiDAR技术的应用主要集中在对已知的生态关系研究, 尤其是冠层结构与动物分布的关系, 缺少对林下层生活的动物生境质量和生物多样性的监测和评估, 同时很多有关动物生存和繁衍与立体生境的关系研究有待从LiDAR数据中进一步挖掘分析。未来应加强对森林林下层三维信息的提取, 提高林下层动物生境质量和生物多样性的监测水平, 同时建立适用于动物生态和生理意义相关的参数, 为动物生境质量和生物多样性的评估提供标准的量化指标。     

Effects of decadal experimental drought and climate extremes on vegetation growth in Mediterranean forests and shrublands

Increased drought combined with extreme episodes of heatwaves is triggering severe impacts on vegetation growth, particularly for plant communities in arid and semiarid ecosystems. Although there is an abundance of short‐term field drought experiments in natural ecosystems, remaining knowledge gaps limit the understanding and prediction of vegetation growth to ongoing and future climate scenarios. Here, we assessed the impacts of long‐term (1999–2016) experimental drought (ca. ?30% rainfall) on the vegetation growth of a Mediterranean high (H) and low (L)‐canopy forests and an early‐successional shrubland, as indicated by above‐ground biomass increment (ABI) and standing density, respectively. We found habitat context (impact of historical climate change, soil depth and successional status) of the study sites significantly affected the magnitude of climate impacts; there were synergistic effects of experimental drought and meteorological drought (Standardised Precipitation–Evapotranspiration Index, SPEI) as well as extreme dry years on vegetation growth. Long‐term experimental drought decreased the ABI for the two forest canopy types and the standing density for the shrubland. Water availabilities in winter–spring (SPEIs) were positively correlated with the ABI and standing density. Moreover, experimental drought decreased the vegetation growth in extreme dry years for the shrubland. We propose that future work not only study the vegetation dynamics with physiological, phenological and demographical changes in long‐term processes and across climate gradients, but also should explore the changes of multiple functions simultaneously (e.g. multifunctionality) under long‐term processes and extremes. This type of analysis of long‐term data is essential to understand and predict biodiversity loss, composition shifts, declines in ecosystem function and carbon budgets at temporal and spatial scales, to enable policy makers to design and implement strategies for the maintenance of sustainable ecosystem function under future climate change scenarios.     

Climatic water deficit,tree species ranges,and climate change in Yosemite National Park

Aim (1) To calculate annual potential evapotranspiration (PET), actual evapotranspiration (AET) and climatic water deficit (Deficit) with high spatial resolution; (2) to describe distributions for 17 tree species over a 2300‐m elevation gradient in a 3000‐km² landscape relative to AET and Deficit; (3) to examine changes in AET and Deficit between past (c. 1700), present (1971–2000) and future (2020–49) climatological means derived from proxies, observations and projections; and (4) to infer how the magnitude of changing Deficit may contribute to changes in forest structure and composition. Location Yosemite National Park, California, USA. Methods We calculated the water balance within Yosemite National Park using a modified Thornthwaite‐type method and correlated AET and Deficit with tree species distribution. We used input data sets with different spatial resolutions parameterized for variation in latitude, precipitation, temperature, soil water‐holding capacity, slope and aspect. We used climate proxies and climate projections to model AET and Deficit for past and future climate. We compared the modelled future water balance in Yosemite with current species water‐balance ranges in North America. Results We calculated species climatic envelopes over broad ranges of environmental gradients – a range of 310 mm for soil water‐holding capacity, 48.3°C for mean monthly temperature (January minima to July maxima), and 918 mm yr^?1 for annual precipitation. Tree species means were differentiated by AET and Deficit, and at higher levels of Deficit, species means were increasingly differentiated. Modelled Deficit for all species increased by a mean of 5% between past (c. 1700) and present (1971–2000). Projected increases in Deficit between present and future (2020–49) were 23% across all plots. Main conclusions Modelled changes in Deficit between past, present and future climate scenarios suggest that recent past changes in forest structure and composition may accelerate in the future, with species responding individualistically to further declines in water availability. Declining water availability may disproportionately affect Pinus monticola and Tsuga mertensiana. Fine‐scale heterogeneity in soil water‐holding capacity, aspect and slope implies that plant water balance may vary considerably within the grid cells of kilometre‐scale climate models. Sub‐grid‐cell soil and topographical data can partially compensate for the lack of spatial heterogeneity in gridded climate data, potentially improving vegetation‐change projections in mountainous landscapes with heterogeneous topography.