Rates of Disturbance vary by data resolution: implications for conservation schedules using the Alberta Boreal Forest as a case study

Investigations of biophysical changes on earth caused by anthropogenic disturbance provide governments with tools to generate sustainable development policy. Canada currently experiences one of the fastest rates of boreal forest disturbance in the world. Plans to conserve the 330 000 km² boreal forest in the province of Alberta exist but conservation targets and schedules must be aligned with rates of forest disturbance. We explore how disturbance rate, and the accuracy with which we detect it, may affect conservation success. We performed a change detection analysis from 1992 to 2008 using Landsat and SPOT satellite image data processing. Canada's recovery strategy for boreal caribou (Rangifer tarandus caribou) states that ≤35% of a caribou range can be either burned or within 500 m of a man‐made feature for caribou to recover. Our analyses show that by 2008 78% of the boreal forest was disturbed and that, if the current rate continues, 100% would be disturbed by 2028. Alberta plans to set aside 22% for conservation in a region encompassing oil sands development to balance economic, environmental, and traditional indigenous land‐use goals. Contrary to the federal caribou recovery strategy, provincial conservation plans do not consider wildfire a disturbance. Based on analyses used in the provincial plan, we apply a 250 m buffer around anthropogenic footprints. Landsat image analysis indicates that the yearly addition of disturbance is 714 km² (0.8%). The higher resolution SPOT images show fine‐scale disturbance indicating that actual disturbance was 1.28 times greater than detected by Landsat. If the SPOT image based disturbance rates continue, the 22% threshold may be exceeded within the next decade, up to 20 years earlier than indicated by Landsat‐based analysis. Our results show that policies for sustainable development will likely fail if governments do not develop time frames that are grounded by accurate calculations of disturbance rates.     

A Practical and Automated Approach to Large Area Forest Disturbance Mapping with Remote Sensing

In this paper, I describe a set of procedures that automate forest disturbance mapping using a pair of Landsat images. The approach is built on the traditional pair-wise change detection method, but is designed to extract training data without user interaction and uses a robust classification algorithm capable of handling incorrectly labeled training data. The steps in this procedure include: i) creating masks for water, non-forested areas, clouds, and cloud shadows; ii) identifying training pixels whose value is above or below a threshold defined by the number of standard deviations from the mean value of the histograms generated from local windows in the short-wave infrared (SWIR) difference image; iii) filtering the original training data through a number of classification algorithms using an n-fold cross validation to eliminate mislabeled training samples; and finally, iv) mapping forest disturbance using a supervised classification algorithm. When applied to 17 Landsat footprints across the U.S. at five-year intervals between 1985 and 2010, the proposed approach produced forest disturbance maps with 80 to 95% overall accuracy, comparable to those obtained from traditional approaches to forest change detection. The primary sources of mis-classification errors included inaccurate identification of forests (errors of commission), issues related to the land/water mask, and clouds and cloud shadows missed during image screening. The approach requires images from the peak growing season, at least for the deciduous forest sites, and cannot readily distinguish forest harvest from natural disturbances or other types of land cover change. The accuracy of detecting forest disturbance diminishes with the number of years between the images that make up the image pair. Nevertheless, the relatively high accuracies, little or no user input needed for processing, speed of map production, and simplicity of the approach make the new method especially practical for forest cover change analysis over very large regions.     

United States Forest Disturbance Trends Observed Using Landsat Time Series

Disturbance events strongly affect the composition, structure, and function of forest ecosystems; however, existing US land management inventories were not designed to monitor disturbance. To begin addressing this gap, the North American Forest Dynamics (NAFD) project has examined a geographic sample of 50 Landsat satellite image time series to assess trends in forest disturbance across the conterminous United States for 1985–2005. The geographic sample design used a probability-based scheme to encompass major forest types and maximize geographic dispersion. For each sample location disturbance was identified in the Landsat series using the Vegetation Change Tracker (VCT) algorithm. The NAFD analysis indicates that, on average, 2.77 Mha y^?1 of forests were disturbed annually, representing 1.09% y^?1 of US forestland. These satellite-based national disturbance rates estimates tend to be lower than those derived from land management inventories, reflecting both methodological and definitional differences. In particular, the VCT approach used with a biennial time step has limited sensitivity to low-intensity disturbances. Unlike prior satellite studies, our biennial forest disturbance rates vary by nearly a factor of two between high and low years. High western US disturbance rates were associated with active fire years and insect activity, whereas variability in the east is more strongly related to harvest rates in managed forests. We note that generating a geographic sample based on representing forest type and variability may be problematic because the spatial pattern of disturbance does not necessarily correlate with forest type. We also find that the prevalence of diffuse, non-stand-clearing disturbance in US forests makes the application of a biennial geographic sample problematic. Future satellite-based studies of disturbance at regional and national scales should focus on wall-to-wall analyses with annual time step for improved accuracy.     

南京城市森林干扰及恢复自动制图

使用1987—2011年Landsat TM/ETM⁺稠密时间序列数据,以南京市老山林场和紫金山森林为研究对象,通过Ledaps预处理系统生成地表反射率数据集,采用植被变化追踪模型(VCT)得到南京城市森林的干扰及恢复历史数据库产品,并对产品进行验证.结果表明： 空间一致性为65.4%～95.0%,VCT产品监测森林干扰具有较高的空间一致性.2个研究区的森林干扰和恢复随着时间变化波动明显,干扰变化规律相似,但森林恢复规律明显不同.紫金山的森林覆盖率小于老山林场,但总体上,老山林场的森林干扰率和恢复率大于紫金山.     

Tree‐mycorrhizal associations detected remotely from canopy spectral properties

A central challenge in global ecology is the identification of key functional processes in ecosystems that scale, but do not require, data for individual species across landscapes. Given that nearly all tree species form symbiotic relationships with one of two types of mycorrhizal fungi – arbuscular mycorrhizal (AM) and ectomycorrhizal (ECM) fungi – and that AM‐ and ECM‐dominated forests often have distinct nutrient economies, the detection and mapping of mycorrhizae over large areas could provide valuable insights about fundamental ecosystem processes such as nutrient cycling, species interactions, and overall forest productivity. We explored remotely sensed tree canopy spectral properties to detect underlying mycorrhizal association across a gradient of AM‐ and ECM‐dominated forest plots. Statistical mining of reflectance and reflectance derivatives across moderate/high‐resolution Landsat data revealed distinctly unique phenological signals that differentiated AM and ECM associations. This approach was trained and validated against measurements of tree species and mycorrhizal association across ~130 000 trees throughout the temperate United States. We were able to predict 77% of the variation in mycorrhizal association distribution within the forest plots (P < 0.001). The implications for this work move us toward mapping mycorrhizal association globally and advancing our understanding of biogeochemical cycling and other ecosystem processes.     

Pervasive canopy dynamics produce short-term stability in a tropical rain forest landscape

A fundamental property of all forest landscapes is the size frequency distribution of canopy gap disturbances. But characterizing forest structure and changes at large spatial scales has been challenging and most of our understanding is from permanent inventory plots. Here we report the first application of light detection and ranging remote sensing to measurements of canopy disturbance and regeneration in an old-growth tropical rain forest landscape. Pervasive local height changes figure prominently in the dynamics of this forest. Although most canopy gaps recruited to higher positions during 8.5 years, size frequency distributions were similar at two points in time and well-predicted by power-laws. At larger spatial scales (hundreds of ha), height increases and decreases occurred with similar frequency and changes to canopy height that were analysed using a height transition matrix suggest that the distribution of canopy height at the beginning of the study was close to the projected steady-state equilibrium under the recent disturbance regime. Taken together, these findings show how widespread local height changes can produce short-term stability in a tropical rain forest landscape.     

Conservation of Forest Birds: Evidence of a Shifting Baseline in Community Structure

Background

Quantifying changes in forest bird diversity is an essential task for developing effective conservation actions. When subtle changes in diversity accumulate over time, annual comparisons may offer an incomplete perspective of changes in diversity. In this case, progressive change, the comparison of changes in diversity from a baseline condition, may offer greater insight because changes in diversity are assessed over longer periods of times. Our objectives were to determine how forest bird diversity has changed over time and whether those changes were associated with forest disturbance.

Methodology/Principal Findings

We used North American Breeding Bird Survey data, a time series of Landsat images classified with respect to land cover change, and mixed-effects models to associate changes in forest bird community structure with forest disturbance, latitude, and longitude in the conterminous United States for the years 1985 to 2006. We document a significant divergence from the baseline structure for all birds of similar migratory habit and nest location, and all forest birds as a group from 1985 to 2006. Unexpectedly, decreases in progressive similarity resulted from small changes in richness (<1 species per route for the 22-year study period) and modest losses in abundance (−28.7–−10.2 individuals per route) that varied by migratory habit and nest location. Forest disturbance increased progressive similarity for Neotropical migrants, permanent residents, ground nesting, and cavity nesting species. We also documented highest progressive similarity in the eastern United States.

Conclusions/Significance

Contemporary forest bird community structure is changing rapidly over a relatively short period of time (e.g., ∼22 years). Forest disturbance and forest regeneration are primary factors associated with contemporary forest bird community structure, longitude and latitude are secondary factors, and forest loss is a tertiary factor. Importantly, these findings suggest some regions of the United States may already fall below the habitat amount threshold where fragmentation effects become important predictors of forest bird community structure.     

Global vegetation models: incorporating transient changes to structure and composition

Abstract. We describe an approach for developing a Dynamic Global Vegetation Model (DGVM) that accounts for transient changes in vegetation distribution over a decadal time scale. The DGVM structure is based on a linkage between an equilibrium global vegetation model and smaller scale ecosystem dynamics modules that simulate the rate of vegetation change. Vegetation change is classified into four basic types, based largely on the projected change in above-ground biomass of the vegetation. These four types of change are: (1) dieback of forest, shrubland or grassland; (2) successional replacement within forest, shrubland or grassland; (3) invasion of forest, shrubland or grassland; (4) change in tree/grass ratio. We then propose an approach in which the appropriate ecosystem dynamics module for each type of change is applied and the grid cells of the global model updated accordingly. An approach for accounting for fire, as an example of a disturbance which may strongly influence the rate and spatial pattern of forest dieback, is incorporated. We also discuss data needs for the development, calibration and validation of the model.     

Applying climatically associated species pools to the modelling of compositional change in tropical montane forests

Aim Predictive species distribution modelling is a useful tool for extracting the maximum amount of information from biological collections and floristic inventories. However, in many tropical regions records are only available from a small number of sites. This can limit the application of predictive modelling, particularly in the case of rare and endangered species. We aim to address this problem by developing a methodology for defining and mapping species pools associated with climatic variables in order to investigate potential species turnover and regional species loss under climate change scenarios combined with anthropogenic disturbance. Location The study covered an area of 6800 km² in the highlands of Chiapas, southern Mexico. Methods We derived climatically associated species pools from floristic inventory data using multivariate analysis combined with spatially explicit discriminant analysis. We then produced predictive maps of the distribution of tree species pools using data derived from 451 inventory plots. After validating the predictive power of potential distributions against an independent historical data set consisting of 3105 botanical collections, we investigated potential changes in the distribution of tree species resulting from forest disturbance and climate change. Results Two species pools, associated with moist and cool climatic conditions, were identified as being particularly threatened by both climate change and ongoing anthropogenic disturbance. A change in climate consistent with low‐emission scenarios of general circulation models was shown to be sufficient to cause major changes in equilibrium forest composition within 50 years. The same species pools were also found to be suffering the fastest current rates of deforestation and internal forest disturbance. Disturbance and deforestation, in combination with climate change, threaten the regional distributions of five tree species listed as endangered by the IUCN. These include the endemic species Magnolia sharpii Miranda and Wimmeria montana Lundell. Eleven vulnerable species and 34 species requiring late successional conditions for their regeneration could also be threatened. Main conclusions Climatically associated species pools can be derived from floristic inventory data available for tropical regions using methods based on multivariate analysis even when data limitations prevent effective application of individual species modelling. Potential consequences of climate change and anthropogenic disturbance on the species diversity of montane tropical forests in our study region are clearly demonstrated by the method.     

Functional traits and climate drive interspecific differences in disturbance-induced tree mortality

With climate change, natural disturbances such as storm or fire are reshuffled, inducing pervasive shifts in forest dynamics. To predict how it will impact forest structure and composition, it is crucial to understand how tree species differ in their sensitivity to disturbances. In this study, we investigated how functional traits and species mean climate affect their sensitivity to disturbances while controlling for tree size and stand structure. With data on 130,594 trees located on 7617 plots that were disturbed by storm, fire, snow, biotic or other disturbances from the French, Spanish, and Finnish National Forest Inventory, we modeled annual mortality probability for 40 European tree species as a function of tree size, dominance status, disturbance type, and intensity. We tested the correlation of our estimated species probability of disturbance mortality with their traits and their mean climate niches. We found that different trait combinations controlled species sensitivity to disturbances. Storm-sensitive species had a high height-dbh ratio, low wood density and high maximum growth, while fire-sensitive species had low bark thickness and high P50. Species from warmer and drier climates, where fires are more frequent, were more resistant to fire. The ranking in disturbance sensitivity between species was overall consistent across disturbance types. Productive conifer species were the most disturbance sensitive, while Mediterranean oaks were the least disturbance sensitive. Our study identified key relations between species functional traits and disturbance sensitivity, that allows more reliable predictions of how changing climate and disturbance regimes will impact future forest structure and species composition at large spatial scales.     

Pileated Gibbon Density in Relation to Habitat Characteristics and Post‐logging Forest Recovery

ABSTRACT Although it is known that forest loss and degradation negatively impact most forest‐dwelling primates, such relationships are difficult to quantify because many primates are difficult to survey over large areas. Furthermore, recovery times are also difficult to assess due to a lack of long‐term data. Here, we determined how forest characteristics and habitat disturbance correlate with the abundance of pileated gibbons, Hylobates pileatus. We studied a population in Khao Ang Rue Nai Wildlife Sanctuary in southeastern Thailand, assessed its density using an auditory method combined with distance sampling at 24 randomly placed sample sites. In addition, we determined how simple forest structural characteristics and habitat disturbance correlate with the gibbon abundance. Average gibbon density per site was 1.02 ± 0.16 (SE) groups/km² (range 0–2.74). Bivariate analyses indicated that densities depended on food tree biomass, level of disturbance, evergreen forest cover, time since protection, and distance to the sanctuary boundary. Multiple regression analysis suggested evergreen forest cover and distance to boundary were the most influential factors. Because evergreen forest cover, time since protection, and habitat disturbance are correlated, these results suggest a direct dependence of gibbon densities on mature, undisturbed evergreen forest. While gibbons can persist in disturbed areas if the forest is protected, it appears that recovery to previous densities may take decades. We suggest that this is due to the slow pace of forest regeneration and/or poor recovery potential of gibbons.     

Spatial scale and sampling resolution affect measures of gap disturbance in a lowland tropical forest: implications for understanding forest regeneration and carbon storage

Treefall gaps play an important role in tropical forest dynamics and in determining above-ground biomass (AGB). However, our understanding of gap disturbance regimes is largely based either on surveys of forest plots that are small relative to spatial variation in gap disturbance, or on satellite imagery, which cannot accurately detect small gaps. We used high-resolution light detection and ranging data from a 1500 ha forest in Panama to: (i) determine how gap disturbance parameters are influenced by study area size, and the criteria used to define gaps; and (ii) to evaluate how accurately previous ground-based canopy height sampling can determine the size and location of gaps. We found that plot-scale disturbance parameters frequently differed significantly from those measured at the landscape-level, and that canopy height thresholds used to define gaps strongly influenced the gap-size distribution, an important metric influencing AGB. Furthermore, simulated ground surveys of canopy height frequently misrepresented the true location of gaps, which may affect conclusions about how relatively small canopy gaps affect successional processes and contribute to the maintenance of diversity. Across site comparisons need to consider how gap definition, scale and spatial resolution affect characterizations of gap disturbance, and its inferred importance for carbon storage and community composition.     

Observed forest sensitivity to climate implies large changes in 21st century North American forest growth

Predicting long‐term trends in forest growth requires accurate characterisation of how the relationship between forest productivity and climatic stress varies across climatic regimes. Using a network of over two million tree‐ring observations spanning North America and a space‐for‐time substitution methodology, we forecast climate impacts on future forest growth. We explored differing scenarios of increased water‐use efficiency (WUE) due to CO₂‐fertilisation, which we simulated as increased effective precipitation. In our forecasts: (1) climate change negatively impacted forest growth rates in the interior west and positively impacted forest growth along the western, southeastern and northeastern coasts; (2) shifting climate sensitivities offset positive effects of warming on high‐latitude forests, leaving no evidence for continued ‘boreal greening’; and (3) it took a 72% WUE enhancement to compensate for continentally averaged growth declines under RCP 8.5. Our results highlight the importance of locally adapted forest management strategies to handle regional differences in growth responses to climate change.     

基于长时间序列Landsat影像的南方人工林干扰与恢复制图分析

基于1986年到2011年的Landsat影像,以南方人工林分布区域广东省佛冈县为例,运用Landsat生态系统自适应处理系统(LEDAPS)预处理生成标准的地面反射率数据构建Landsat时间序列堆栈(LTSS)用于Land Trendr算法监测人工林森林干扰与恢复的长时间序列变化,分析了连续24a森林干扰的年份变化、干扰量以及干扰持续的时间,验证了算法识别干扰的精度,并探讨了人工林干扰的驱动力。结果表明佛冈县的森林干扰较为剧烈,一般都在1000 hm~2。而1987、2002、2004、2005、2006、2007和2009年的干扰面积均超过2000 hm~2,其中1987、2007年两年的干扰面积达到6000 hm~2以上。相比森林干扰的变化,佛冈县的森林恢复面积随时间的变化相对平稳。通过对佛冈县森林干扰和恢复面积的趋势分析,发现20世纪80年代末到90年代森林干扰和恢复的面积基本少于2000年以后的变化面积,变化趋势比2000年以后的显得平缓;从2000年开始,森林干扰面积逐渐上升,总体面积变化趋势高于森林的恢复,但森林的恢复面积仍有所提升。其中,佛冈县的森林干扰持续1a时间的面积比例约38%,持续2a时间约28%,持续3a时间约25%,持续4a时间约7%,主要为短期急剧的干扰事件。另外,持续时间为4a以上的森林干扰和恢复的面积在佛冈县不超过100hm~2。2000年之前持续干扰和急剧干扰面积相当,变化比较平缓;到2000年之后,急剧干扰的面积远大于持续干扰,最高约达2800 hm~2,但两者都呈现波动上升的变化趋势。在选取的两个4km~2的样方中,基于影像光谱识别以及通过比对干扰资料的可视化验证方法表明算法结果与真实地表的解译信息较吻合,误差约为0.1km~2。利用长时间序列遥感影像进行森林干扰的自动化监测十分必要,导出的定性、定位与定量信息,一方面为可持续的森林经营奠定基础,另一方面为评价森林生产力与森林碳储量提供有效的数据支撑。     

Past Human Disturbance Effects upon Biodiversity are Greatest in the Canopy; A Case Study on Rainforest Butterflies

A key part of tropical forest spatial complexity is the vertical stratification of biodiversity, with widely differing communities found in higher rainforest strata compared to terrestrial levels. Despite this, our understanding of how human disturbance may differentially affect biodiversity across vertical strata of tropical forests has been slow to develop. For the first time, how the patterns of current biodiversity vary between three vertical strata within a single forest, subject to three different types of historic anthropogenic disturbance, was directly assessed. In total, 229 species of butterfly were detected, with a total of 5219 individual records. Butterfly species richness, species diversity, abundance and community evenness differed markedly between vertical strata. We show for the first time, for any group of rainforest biodiversity, that different vertical strata within the same rainforest, responded differently in areas with different historic human disturbance. Differences were most notable within the canopy. Regenerating forest following complete clearance had 47% lower canopy species richness than regenerating forest that was once selectively logged, while the reduction in the mid-storey was 33% and at ground level, 30%. These results also show for the first time that even long term regeneration (over the course of 30 years) may be insufficient to erase differences in biodiversity linked to different types of human disturbance. We argue, along with other studies, that ignoring the potential for more pronounced effects of disturbance on canopy fauna, could lead to the underestimation of the effects of habitat disturbance on biodiversity, and thus the overestimation of the conservation value of regenerating forests more generally.     

Logging leaves a fingerprint on the number,size, spatial configuration and geometry of tropical forest canopy gaps

Recent advances in remote sensing such as airborne laser scanning have revolutionized our ability to accurately map forest canopy gaps, with huge implications for tracking forest dynamics at scale. However, few studies have explored how canopy gaps vary among forests at different successional stages following disturbances, such as those caused by logging. Moreover, most studies have focused exclusively on the size distribution of gaps, ignoring other key features such as their spatial distribution and shape. Here, we test a series of hypotheses about how the number, size, spatial configuration, and geometry of gaps vary across a logging disturbance gradient in Malaysian Borneo. As predicted, we found that recently logged forests had much higher gap fraction compared to old-growth forests, a result of having both a greater total number of gaps and a higher proportion of large gaps. Regrowing forests, on the other hand, fell at the opposite end of the spectrum, being characterized by both fewer and smaller gaps compared to nearby old-growth forests. Across all successional stages gaps were found to be spatially clustered. However, logging significantly diluted the degree of spatial aggregation and led to the formation of gaps with much more complex geometries. Our results showcase how logging and subsequent regrowth substantially alter not just the number and size of gaps in a forest, but also their spatial arrangement and shape. Linking these emergent patterns to their underlying processes is key to better understanding the impacts of human disturbance on the structure and function of tropical forests.     

Discriminating Tsuga canadensis Hemlock Forest Defoliation Using Remotely Sensed Change Detection

The eastern hemlock (Tsuga Canadensis) is declining in health and vigor in eastern North America due to infestation by an introduced insect, the hemlock woolly adelgid (Adelges isugue). Adelgid feeding activity results in the defoliation of hemlock forest canopy over several years. We investigated the application of Landsat satellite imagery and change-detection techniques to monitor the health of hemlock forest stands in northern New Jersey. We described methods used to correct effects due to atmospheric conditions and monitor the health status of hemlock stands over time. As hemlocks defoliate, changes occur in the spectral reflectance of the canopy in near infrared and red wavelengths—changes captured in the Normalized Difference Vegetation Index. By relating the differences in this index over time to hemlock defoliation on the ground, four classes of hemlock forest health were predicted across spatially heterogeneous landscapes with 82% accuracy. Using a time series of images, we are investigating temporal and spatial patterns in hemlock defoliation across the study area over the past decade. Based on the success of this methodology, we are no expanding out study to monitor hemlock health across the entire Mid-Atlantic region.     

Assessing fragmentation and disturbance of west Kenyan rainforests by means of remotely sensed time series data and landscape metrics

Biodiversity in tropical rainforests is heavily influenced by land use/cover change (LUCC), but so far there have been few LUCC studies conducted in Africa. We present several methods that make use of remotely sensed data and landscape metrics and allow for assessment of the development of land cover and thus forest fragmentation and disturbance over a substantial period of time. The study covers Kakamega Forest and its associated forest areas in western Kenya, over the last 30 years. The accuracy of a supervised multispectral classification of Landsat time series data encompassing seven time steps between 1972 and 2001 is numerically assessed using ground truth reference data considering the 2001 time step. Here, buffering the forest areas by 1 km, highest user's accuracies for the forest classes ‘near natural + old secondary forest’ (87.50%), ‘secondary forest’ (80.00%) and ‘bushland/shrubs’ (81.08%) are revealed. Images of a spatially distributed fragmentation index derived from the land cover time series by applying a three by 3 pixel‐sized moving window to determine forest pixels’ adjacency, highlight trends in forest fragmentation, e.g. the splitting into two separate forests along the Yala/Ikuywa corridor. Calculations of mean fragmentation indices for the Biodiversity Monitoring Transect Analysis in Eastern Africa (BIOTA‐East Africa) focus research areas are used to evaluate the fragmentation index and to demonstrate its potential to extrapolate (e.g. biological) field findings in space and time. Here we argue for a correlation of the fragmentation indices results not only with forest management regimes, but with population distribution and accessibility (e.g. by roads). A cluster analysis applying the isodata‐algorithm on the classification results of all seven times steps allows for a rapid visual assessment of the distinct pattern of typical land cover development trends since 1972. This reveals that parts of Kakamega Forest have experienced severe forest loss while others, especially in the north‐east, show signs of succession.     

Montane forest ecotones moved downslope in northeastern USA in spite of warming between 1984 and 2011

Ecotones are transition zones that form, in forests, where distinct forest types meet across a climatic gradient. In mountains, ecotones are compressed and act as potential harbingers of species shifts that accompany climate change. As the climate warms in New England, USA, high‐elevation boreal forests are expected to recede upslope, with northern hardwood species moving up behind. Yet recent empirical studies present conflicting findings on this dynamic, reporting both rapid upward ecotonal shifts and concurrent increases in boreal species within the region. These discrepancies may result from the limited spatial extent of observations. We developed a method to model and map the montane forest ecotone using Landsat imagery to observe change at scales not possible for plot‐based studies, covering mountain peaks over 39 000 km². Our results show that ecotones shifted downward or stayed stable on most mountains between 1991 and 2010, but also shifted upward in some cases (13–15% slopes). On average, upper ecotone boundaries moved down ?1.5 m yr^?1 in the Green Mountains, VT, and ?1.3 m yr^?1 in the White Mountains, NH. These changes agree with remeasured forest inventory data from Hubbard Brook Experimental Forest, NH, and suggest that processes of boreal forest recovery from prior red spruce decline, or human land use and disturbance, may swamp out any signal of climate‐mediated migration in this ecosystem. This approach represents a powerful framework for evaluating similar ecotonal dynamics in other mountainous regions of the globe.