Changes in climate characteristics for a cold period on the territory of the Irkutsk-Cheremkhovo plain

We report the data on changes in snow cover characteristics obtained at meteorological stations Tulun and Bokhan and in their neighborhoods for the period 1961–1990. We examine the changes in snow cover, air temperature and soil temperature at depths of 20, 40 and 80 cm.     

Numerical simulations of the influence of the seasonal snow cover on the occurrence of permafrost at high latitudes

It has repeatedly been reported that snow cover is a dominating factor in determining the presence or absence of permafrost in the discontinuous and sporadic permafrost regions. The temperature at the snow-soil interface by the end of winter, known as the bottom temperature of winter snow (BTS) method, has been used to detect the existence of permafrost in European alpine regions when the maximum snow depth is about 1.0 m or greater. A critical snow thickness of about 50 cm or greater can prevent the development of permafrost in eastern Hudson Bay, Canada. The objective of this study is to investigate the impact of snow cover on the presence or absence of permafrost in cold regions through numerical simulations. A one-dimensional heat transfer model with phase change and a snow cover regime is used to simulate energy exchange between deep soils and the atmosphere. The model has been validated against the in situ data in the Arctic. The simulation results indicate that both snow depth and the onset date of snow cover establishment are important parameters in relation to the presence or absence of permafrost. Early establishment of snow cover can make permafrost disappear, even with a relatively thin snow cover. Permafrost may survive when snow cover starts after the middle of December even with a snow thickness >1.0 m. This effect of snow cover on the ground thermal regime can be explained with reference to the pattern of seasonal temperature variation. Early establishment of snow cover enhances the insulating impact over the entire cold season, thus warming and eventually thawing the permafrost. The insulating effect is substantially reduced when snow cover starts relatively late and snowmelt in the spring creates a huge heat sink, resulting in a favorable combination for permafrost existence.     

Pedotransfer functions to estimate soil bulk density for Northern Africa: Tunisia case

Countries should provide regularly national inventories of greenhouse gas emissions and sinks and, and for the agriculture and forestry sectors this comprise national estimates of soil organic carbon (C) stocks. Estimation of soil C stock requires soil bulk density (D_b) values. However, direct measurement of D_b is often lacking mainly for soils in arid and semi-arid conditions. Much effort has been made in finding alternative solution to predict D_b, either improving in situ determinations, either improving estimation procedures based on other soil properties. Regression models or pedotransfer functions (PTFs) based on easily measured soil properties constitute an adequate tool to assess D_b, since it needs a minimum data set of indicators. A forward stepwise multiple linear regression routine was used to predict D_b from physico-chemical soil properties. In this study, a soil database was organised from published and unpublished data from Tunisia. The database consisted of 238 soil profiles corresponding to 707 soil horizons from Tunisia. A general regression model fitted with all the data showed that OC, Clay, coarse-Sand and pH were the principal contributors to D_b prediction (R² = 0.55, standard error of prediction = 0.14). Additional models based on different set of variables are also provided providing alternative solutions for different levels of soil information. Predictions of the models were often improved when the data were partitioned into groups by soil depth (0–40 and 40–100 cm) and soil orders. This study also showed that CaCO₃ might be an important predictor for deeper soil horizon. The proposed PTFs for Tunisia might be useful for a larger range of soil from arid and sub arid regions.     

Nest site characteristics and nesting success of the Western Burrowing Owl in the eastern Mojave Desert

We evaluated nest site selection at two spatial scales (microsite, territory) and reproductive success of Western Burrowing Owls (Athene cunicularia hypugaea) at three spatial scales (microsite, territory, landscape) in the eastern Mojave Desert. We used binary logistic regression within an information-theoretic approach to assess factors influencing nest site choice and nesting success. Microsite-scale variables favored by owls included burrows excavated by desert tortoise (Gopherus agassizii), burrows with a large mound of excavated soil at the entrance, and a greater number of satellite burrows within 5 m of the nest burrow. At the territory scale, owls preferred patches with greater cover of creosote bush (Larrea tridentata) within 50 m of the nest burrow. An interaction between the presence or absence of a calcic soil horizon layer over the top of the burrow (microsite) and the number of burrows within 50 m (territory) influenced nest site choice. Nesting success was influenced by a greater number of burrows within 5 m of the nest burrow. Total cool season precipitation was a predictor of nesting success at the landscape scale. Conservation strategies can rely on management of habitat for favored and productive nesting sites for this declining species.     

The origin of shallow landslides in Moravia (Czech Republic) in the spring of 2006

At the end of March 2006, the Czech Republic (CZ) witnessed a fast thawing of an unusually thick snow cover in conjunction with massive rainfall. Most watercourses suffered floods, and more than 90 shallow landslides occurred in the Moravian region of Eastern CZ, primarily in non-forested areas. This region, geologically part of the Outer Western Carpathians, is prone to landslides because the bedrock is highly erodible Mesozoic and Tertiary flysch.The available meteorological data (depth of snow, water equivalent of the snow, cumulative rainfall, air and soil temperatures) from five local weather stations were used to construct indices quantitatively describing the snow thaw. Among these, the Total Cumulative Precipitation (TCP) combines the amount of water from both thawing snow and rainfall. This concurrence of rain and runoff from snow melt was the decisive factor in triggering the landslides in the spring.The TCP index was applied to data of snow thaw periods for the last 20 years, when no landslides were recorded. This was to establish the safe threshold of TCP without landslides. The calculated safe threshold value for the region is ca. 100 mm of water delivered to the soil during the spring thaw (corresponding to ca. 11 mm day^− 1). In 2006, 10% of the landslides occurred under or at 100 mm of TCP. The upper value of 155 mm covered all of the landslides.     

Using hyperspectral imagery to predict post-wildfire soil water repellency

A principal task of evaluating large wildfires is to assess fire's effect on the soil in order to predict the potential watershed response. Two types of soil water repellency tests, the water drop penetration time (WDPT) test and the mini-disk infiltrometer (MDI) test, were performed after the Hayman Fire in Colorado, in the summer of 2002 to assess the infiltration potential of the soil. Remotely sensed hyperspectral imagery was also collected to map post-wildfire ground cover and soil condition. Detailed ground cover measurements were collected to validate the remotely sensed imagery and to examine the relationship between ground cover and soil water repellency. Percent ash cover measured on the ground was significantly correlated to WDPT (r = 0.42; p-value < 0.0001), and the MDI test (r = − 0.37; p-value < 0.0001). A Mixture Tuned Matched Filter (MTMF) spectral unmixing algorithm was applied to the hyperspectral imagery, which produced fractional cover maps of ash, soil, and scorched and green vegetation. The remotely sensed ash image had significant correlations to the water repellency tests, WDPT (r = 0.24; p-value = 0.001), and the MDI test (r = − 0.21; p-value = 0.005). An iterative threshold analysis was also applied to the ash and water repellency data to evaluate the relationship at increasingly higher levels of ash cover. Regression analysis between the means of grouped data: MDI time vs. ash cover data (R² =0.75) and vs. Ash MTMF scores (R² = 0.63) yielded significantly stronger relationships. From these results we found on-the-ground ash cover greater than 49% and remotely sensed ash cover greater than 33% to be indicative of strongly water repellent soils. Combining these results with geostatistical analyses indicated a spatial autocorrelation range of 15 to 40 m. Image pixels with high ash cover (> 33%), including pixels within 15 m of these pixel patches, were used to create a likelihood map of soil water repellency. This map is a good indicator of areas where soil experienced severe fire effects—areas that likely have strong water repellent soil conditions and higher potential for post-fire erosion.     

Factors contributing to dust storms in source regions producing the yellow-sand phenomena observed in Japan from 1993 to 2002

Asian-dust (yellow-sand) phenomena observed in Japan have been increasing in recent years, especially from 2000 to 2002. The main cause is severe dust events in arid and semi-arid regions of northeast Asia. The dust source area in northeast Asia (target area: 35°–45°N and 100°–115°E) was identified with reference to past results, and the relationship between the yellow-sand phenomena observed in Japan and dust outbreaks in the target area was examined during the springtime (March to May) from 1993 to 2002. The annual change in the number of dust phenomena observed in Japan agreed well with the Dust Storm Frequency (DSF) in the target area (R² = 0.8796). Even though strong wind (≧7.0 m s⁻¹) has a profound effect on dust storms (R² = 0.515), coverage of the Normalized Differential Vegetation Index (NDVI), ranging from 0 to 0.1 (bare land with snow cover) and 0.1 to 0.2 (bare land) in April, also affected dust storms in the target area (R² = 0.486 and 0.418).     

Vertical distribution of snow cover and its relation to temperature over the Manasi River Basin of Tianshan Mountains,Northwest China

How snow cover changes in response to climate change at different elevations within a mountainous basin is a less investigated question. In this study we focused on the vertical distribution of snow cover and its relation to elevation and temperature within different elevation zones of distinct climatology, taking the mountainous Manasi River Basin of Xinjiang, Northwest China as a case study. Data sources include MODIS 8-day snow product, MODIS land surface temperature (LST) data from 2001 to 2014, and in situ temperature data observed at three hydrological stations from 2001 to 2012. The results show that: (1) the vertical distribution of snow areal extent (SAE) is sensitive to elevation in low (<2100 m) and high altitude (>3200 m) regions and shows four different seasonal patterns, each pattern is well correspondent to the variation of temperature. (2) The correlation between vertical changes of the SAE and temperature is significant in all seasons except for winter. (3) The correlation between annual changes of the SAE and temperature decreases with increasing elevation, the negative correlation is significant in area below 4000 m. (4) The snow cover days (SCDs) and its long-term change show visible differences in different altitude range. (5) The long-term increasing trend of SCDs and decreasing trend of winter temperature have a strong vertical relation with elevation below 3600 m. The decreasing trend of SCDs is attributed to the increasing trend of summer temperature in the area above 3600 m.     

Scanning reflectance spectroscopy (380–730 nm): a novel method for quantitative high-resolution climate reconstructions from minerogenic lake sediments

High-resolution (annual to sub-decadal) quantitative reconstructions of climate variables are needed from a variety of paleoclimate archives across the world to place current climate change in the context of long-term natural climate variability. Rapid, high-resolution, non-destructive scanning techniques are required to produce such high-resolution records from lake sediments. In this study we explored the potential of scanning reflectance spectroscopy (VIS-RS; 380–730 nm) to produce quantitative summer temperature reconstructions from minerogenic sediments of proglacial, annually laminated Lake Silvaplana, in the eastern Swiss Alps. The scanning resolution was 2 mm, which corresponded to sediment deposition over 1–2 years. We found correlations up to r = 0.84 (p < 0.05) for the calibration period 1864–1950, between six reflectance-dependent variables and summer (JJAS) temperature. These reflectance-dependent variables (e.g. slope of the reflectance 570/630 nm, indicative of illite, biotite and chlorite; minimum reflectance at 690 nm indicative of chlorite) indicate the mineralogical composition of the clastic sediments, which is, in turn, related to climate in the catchment of this particular proglacial lake. We used multiple linear regression (MLR) to establish a calibration model that explains 84% of the variance of summer (JJAS) temperature during the calibration period 1864–1950. We then applied the calibration model downcore to develop a quantitative summer temperature reconstruction extending back to AD 1177. This temperature reconstruction is in good agreement with two independent temperature reconstructions based on documentary data that extend back to AD 1500 and tree ring data that extend back to AD 1177. This study confirms the great potential of in situ scanning reflectance spectroscopy as a novel non-destructive technique to rapidly acquire high-resolution quantitative paleoclimate information from minerogenic lake sediments.     

An integrated methodology for assessing soil salinization,a pre-condition for land desertification

Soil salinization is mainly an arid-zone problem leading to land desertification. It reduces soil quality and limits the growing of crops. The control of this problem involves inventorying, mapping, and monitoring soil salinity, which requires cost-effective, rapid, and reliable methods for determining soil salinity in the field, and rapid, specific data-processing methods. This paper shows the usefulness of an integrated methodology involving a hand-held electromagnetic sensor (Geonics-EM38) and the ESAP (Electrical conductivity or salinity, Sampling, Assessment and Prediction) software for assessing, predicting, and mapping soil salinity. The salinity of a 0.45-ha surface-irrigated plot was analysed by reading the EM38 at 161 locations, and by employing the ESAP software for calibrating the sensor, and predicting and mapping soil salinity at multiple depths. To calibrate the EM38 sensor, the electrical conductivity of the saturation extract (ECe) of 57 soil samples taken at 19 points was measured. The multiple linear regression (MLR) calibration model predicted ECe from EM38 readings with R² ranging from 0.71 to 0.95 for the multiple-depth profile. Furthermore, the MLR calibration model provided field range average estimates of soil salinity. Fifty-seven percent of the field had ECe values above 4 dS m⁻¹. The salinity levels and distribution in the root zone identified areas with inverted profiles, which revealed drainage problems. The integrated method presented is a breakthrough in the ability to accurately and rapidly assess soil salinity in agricultural lands.     

Analysis of satellite and model datasets for variability and trends in Arctic snow extent and depth, 1948–2006

This study aims to investigate the spatiotemporal trends in snow depth (SD) and snow cover extent (SCE) for Arctic lands, excluding Greenland, for the period 1948–2006. The investigation not only delineates how the Arctic regions are manifesting significant annual trends in both SD and SCE, but also provides a comprehensive understanding of their historical context. To achieve these objectives, the combined resources of the hydrological and biogeochemical model (CHANGE), National Oceanic and Atmospheric Administration (NOAA) weekly SCE data, and in situ observations of SD were used. Most regions in the Arctic exhibited a significant negative trend in SD over the 59 years of study. The magnitude of the negative trend was stronger in North America than in Eurasia, where the decrease became more significant, starting from the late 1980s, coinciding well with the temperature rise during that time. During the same period, the warming temperature caused a prominent decrease in deeper SDs (i.e., >35 cm), so that the corresponding SCEs exhibited negative anomalies, with the greatest declines being observed at SDs > 55 cm. In contrast, the SCEs for SD ≤ 35 cm showed increased anomalies during the most recent two decades. The increased anomalies signify a sequential result induced by the decrease in the SCEs with deeper SDs, rather than the expansion of snow to snow-free regions. These changes resulted in a northward shift of the shallow SD line, which took place to a highly significant degree in North America. These results suggest that the Arctic SCE and SD will undergo more intense changes in response to the future climate warming.     

近50年青藏高原东部冬季积雪的时空变化特征

选取青藏高原东部地区1961-2010 年64 个测站的积雪数据,分析了冬季积雪日数的空间分布和年代际变化特征,结果表明：高原东部冬季积雪空间分布差异较大,巴颜喀拉山、唐古拉山和念青唐古拉山多雪且变率大,藏南谷地、川西干暖河谷地带及柴达木盆地少雪且变率小,这样的空间分布是由周边大气环流系统及复杂局地地形共同造成的;高原东部冬季积雪表现出“少—多—少”的年代际变化特征,分别在80 年代末和20 世纪末发生由少到多和由多到少的两次突变,尤其是20 世纪末的突变更为显著;降雪和气温的变化是影响积雪日数的重要因素,其中降雪的影响更为显著;80 年代末高原冬季降雪由少到多的突变是造成积雪日数发生相应变化的主要原因;20 世纪末高原冬季气温和降雪分别发生由低到高和由多到少突变,其影响叠加导致积雪日数发生了更为显著的突变。     

Spatial precipitation and evapotranspiration in the typical steppe of Inner Mongolia,China – A model based approach using MODIS data

We present a simple method to derive spatial precipitation (P) and evapotranspiration (ET) for the typical steppe of the Xilin river catchment at 1 km and 8-day resolution during the main vegetation period (23 April to 28 August) of 2006. The hydrological model BROOK90 was parameterised from eddy covariance measurements. The daily model input data, precipitation, minimum (Ta_min) and maximum air temperature (Ta_max), were derived by manipulating MODIS leaf area index (LAI) and surface temperature data. P was estimated based on a linear regression of P measured at several sites against the mean gain of the MODIS LAI of surrounding 3 × 3 pixels areas (R² = 0.76). Ta_min and Ta_max were derived using a relationship between measured Ta_min and Ta_max and MODIS surface temperatures (R² = 0.92 and R² = 0.88, respectively). The mean precipitation was 145 mm; it varied between 52 mm in the north-western region and 239 mm in the eastern region. In spring, the modelled ET was low (<0.8 mm d⁻¹); evaporation dominated over transpiration and spatial differences were small. At the end of June, the mean ET reached its maximum (2 mm d⁻¹) and spatial differences were pronounced. From July on, transpiration dominated over declining evaporation, and spatial differences decreased in August.     

Differential seedling performance and environmental correlates in shrub canopy vs. interspace microsites

Shrubs in semi-arid ecosystems promote micro-environmental variation in a variety of soil properties and site characteristics. However, little is known regarding post-fire seedling performance and its association with environmental variation in former shrub canopy and interspace microsites. We compared post-fire seeding success and various soil properties important for seedling establishment between shrub canopy and interspace microsites in Wyoming big sagebrush (Artemisia tridentata) plant communities in southeast Oregon, U.S.A. We burned 5, 20 × 20 m sites and established paired canopy and interspace micro-transects seeded with bluebunch wheatgrass (Pseudoroegneria spicata, 193 seeds/m) or crested wheatgrass (Agropyron cristatum, 177 seeds/m). At one year post-fire, seedling density was 69% higher (p = 0.012) for crested wheatgrass (compared to bluebunch wheatgrass) and 75% higher (p = 0.019) for interspace microsites (compared to canopy). However, tiller and leaf area production were over twice as high (p < 0.05) in canopy microsites. Soil color and soil temperature, explained 19–32% of variation in seedling performance metrics. Shrub effects on seeding success are complex and interact with abiotic disturbances, but patterns of increased seedling performance in canopy microsites and their relationships to soil variables may suggest tactics for increasing success of restoration practices.     

The influence of snow cover on ground freeze-thaw frequency,intensity, and duration: An experimental study conducted in coastal northern Sweden

The impact of snow cover on seasonal ground frost and freeze-thaw processes is not yet fully understood. The authors therefore examined how snow cover affects seasonal ground frost in a coastal setting in northern Sweden. Air and soil temperatures were recorded in a paired-plot experiment, both with and without snow cover, during the frost season 2012–2013. The frequency, duration, and intensity of the freeze-thaw cycles during the frost season were calculated. The results showed that the freeze-thaw frequency was 57% higher at the soil surface and the intensity 10 °C colder in the spring of 2013, when the ground lacked snow cover. Furthermore, the duration of the seasonal freeze-thaw cycle was 30 days longer on average in cases where there was natural snow accumulation. The correlation between air and ground surface temperatures weakened with increased snow-cover depth. The authors conclude that continued increases in air temperature and decreases in snow in coastal northern Sweden might alter freeze-thaw cycles and thus affect natural and human systems such as geomorphology, ecology, spatial planning, transport, and forestry.     

MODIS-based estimation of air temperature of the Tibetan Plateau

The immense and towering Tibetan Plateau acts as a heating source and, thus, deeply shapes the climate of the Eurasian continent and even the whole world. However, due to the scarcity of meteorological observation stations and very limited climatic data, little is quantitatively known about the heating effect and temperature pattern of the Tibetan Plateau. This paper collected time series of MODIS land surface temperature （LST） data, together with meteorological data of 137 stations and ASTER GDEM data for 2001-2007, to estimate and map the spatial distribution of monthly mean air temperatures in the Tibetan Plateau and its neighboring areas. Time series analysis and both ordinary linear regression （OLS） and geographical weighted regression （GWR） of monthly mean air temperature （Ta） with monthly mean land surface temperature （Ts） were conducted. Regression analysis shows that recorded Ta is rather closely related to Ts, and that the GWR estimation with MODIS Ts and altitude as independent variables, has a much better result with adjusted R 2 〉 0.91 and RMSE = 1.13-1.53℃ than OLS estimation. For more than 80% of the stations, the Ta thus retrieved from Ts has residuals lower than 2℃. Analysis of the spatio-temporal pattern of retrieved Ta data showed that the mean temperature in July （the warmest month） at altitudes of 4500 m can reach 10℃. This may help explain why the highest timberline in the Northern Hemisphere is on the Tibetan Plateau.     

青藏高原腹地多年冻土区地表反照率的季节变化及主要影响因子

准确获取青藏高原地表反照率的季节变化特征对高原地表能水循环研究具有重要意义。本文利用青藏高原多年冻土区西大滩和唐古拉2007年的气象及辐射数据,运用相关分析方法研究了太阳高度角、积雪及活动层冻融过程对地表反照率变化的影响。结果显示:冷暖季降雪过程中地表反照率的变化差异较明显;地表无积雪覆盖期间,地表反照率与气温和表层土壤含水量呈反相关关系。利用多元回归分析法构建了以积雪日数和气温为影响因子的月均地表反照率计算回归方程,经检验与观测值对比平均相对误差为7.1%,可用于青藏高原北部地表反照率的估算。     

Diurnal surface temperature difference index derived from ground-based meteorological measurements for assessment of moisture availability

Droughts have become widespread in the Northern Hemisphere, including in China, where they have affected farmland resources on the Loess Plateau. Given this background, we proposed a new index, the Normalized Day-Night Surface Temperature Index (NTDI), to estimate moisture availability (m_a), defined as the ratio of actual to reference evapotranspiration. The NTDI is defined as the ratio of the difference between the maximum daytime surface temperature and the minimum nighttime surface temperature, to the difference between the maximum and minimum surface temperatures estimated from meteorological data by applying energy balance equations.To calculate the index, we used data of 20 clear-sky meteorological observations made during the 2005 growing season at a natural grassland station in the Liudaogou River basin on the Loess Plateau. The NTDI showed a significant inverse exponential correlation with m_a (R² = 0.97, p < 0.001), whereas the numerator of the index (the maximum daytime surface temperature minus the minimum nighttime surface temperature) was only weakly correlated with m_a (R² = 0.24, p = 0.03). This result indicates that normalization relative to the index denominator (maximum surface temperature − minimum surface temperature) dramatically improved the accuracy of the estimate.     

Palaeolimnological validation of estimated reference values for a lake profundal macroinvertebrate metric (Benthic Quality Index)

Modern assessment and monitoring of aquatic ecosystems is increasingly based on biota and the “reference condition” approach, in which the observed values (O) of biological variables are compared to those expected in the absence of human disturbance (E). To use this approach, correct estimation and validation of reference conditions are critical. Because appropriate modern or historical data are never available for this approach, palaeolimnological data offer an alternative. We used a calibration data set from 73 profundal sites in semi-pristine Finnish lakes to construct a regression model for estimating expected values for the chironomid Benthic Quality Index (BQI)—a macroinvertebrate metric widely used in bioassessment—from environmental variables that are insensitive to human disturbance. For comparison, reference values were estimated using the European legislative rationale based on a priori lake typology. Performance of the alternative approaches was assessed by internal ‘leave-one-out’ cross-validation using the calibration set and by external cross-validation using independent palaeolimnological data on BQI values representing the historical pristine status of 24 lake basins. Additionally, for 19 of these sites, which vary in their degree of human impact, the ratio of present BQI to that in pristine condition, which shows the degree of actual change, if any, was calculated from palaeolimnological data and compared with the O/E ratios based on the present chironomid data and estimated E. A linear regression model with mean depth and mean/maximum depth ratio as independent variables estimated the reference values of BQI much closer to the observed ones (r ² = 0.58, RMSEP = 0.65 and r ² = 0.71 RMSEP = 0.55; for internal and external cross-validation, respectively) than did the typology approach (r ² = 0.28, RMSEP = 0.86; r ² = 0.10, RMSEP = 0.97). The regression approach also yielded O/E ratios more similar to the actual ones (r ² = 0.79, RMSEP = 0.09) than did the typology approach (r ² = 0.62, RMSEP = 0.23). Our results strongly support the use of lake morphometric variables and modelling instead of categorical lake typology for the establishment of reference conditions for profundal macroinvertebrate communities and demonstrate the utility of palaeolimnological data in the validation of reference values and assessment methods.     

Characterizing the potential distribution of the invasive Asian longhorned beetle (Anoplophora glabripennis) in Worcester County,Massachusetts

The Asian longhorned beetle (ALB) (Anoplophora glabripennis) is an invasive insect pest that has established populations in Worcester County, Massachusetts as of 2008. ALB predominantly targets red maple (Acer rubrum), sugar maple (Acer saccharum), which are prominent in New England hardwood forests, and Norway maple (Acer platanoides), which was planted in built environments as street trees in response to severe weather and invasive insect and pathogen disturbances. Mahalanobis Typicality models related presence locations of ALB presence-only locations in Worcester County towns from 2008 to 2012 to biotic, abiotic, and anthropogenic variables to predict the potential distribution of ALB and to determine locations most characteristic of infestation. k-fold cross-validation and a continuous Boyce Index were employed to validate model performance and to identify threshold values at which continuous models of typicality could be reclassified into categorical maps. Distance-to-roads (r² = 0.19) and probability of maple presence (r² = 0.13) were the most important predictor variables in the ALB model. Locations that were most consistently susceptible to ALB infestation had significant high maple presence (p < 0.001) and significant low distance-to-roads (p < 0.001) compared to the whole study area, suggesting that ALB in Worcester County, MA, prefers maple-dominant edge habitats at the current stage of invasion. The localized ALB potential distribution model was consistently accurate (Boyce Continuous Index = 0.84) despite the lack of absence locations and incomplete knowledge of ALB niche breadth in both native and invaded ranges. The results from this study could be used as a baseline for effective adaptive management policies that could help prioritize the need for early detection/eradication measures and address the potential ecological and social ramifications of the current ALB outbreak in Worcester County. It is hoped that the model employed could be further tested for future outbreaks as they are discovered in the USA.