Geology topics

Paul D. Henne

Publications and source records attributed to Paul D. Henne.

At least 19 recordsLinked to original sources

USGS2026

Millennial-scale climatic and cultural impacts on vegetation and fire at the southern edge of the Rocky Mountains, USA

Mountain forests and woodlands in semiarid regions of the world are threatened by climatic change and other human impacts. In the southwestern USA, climate and culturally driven changes to the structure and fire regimes of dry coniferous forests over recent centuries are well documented by tree-ring archives. However, the roles of climate and people as drivers of millennial-scale changes are less understood. We present a new record of vegetation dynamics and regional fire activity inferred from pollen, microscopic charcoal, and sediment geochemistry from Santa Fe Lake, NM (3532 m a.s.l.), the southernmost natural lake in the Rocky Mountains. Declining elemental intensities (e.g., Ti, Fe, Si) record local deglaciation after 14,000 cal yr BP followed by upslope expansion of trees indicated by increasing Pinus and Picea pollen percentages as the climate warmed during the Late Glacial. Cool, dry growing seasons probably limited the establishment of dense forests until after 12,200 cal yr BP when we hypothesize that Pinus ponderosa (ponderosa pine) expanded regionally (i.e., within 10–100 km) due to continued warming and a possible increase in monsoonal precipitation. Subalpine forests established near Santa Fe Lake by 10,300 cal yr BP as indicated by abundant conifer stomates and increasing Picea and Pinus aristata pollen percentages, which are highest after 5100 cal yr BP. Increasing Juniperus -type, Quercus , and Pinus edulis -type pollen record changes in vegetation belts at lower elevations after 10,300 cal yr BP. Maize pollen, an unambiguous indicator of Puebloan agriculture, first appears at 800 cal yr BP (1150 cal yr CE) and is present through 1600 cal yr CE when Spanish colonization brought cultural upheaval and population loss to local indigenous communities. Regional fire activity, inferred from microscopic charcoal influx, remained relatively constant for most of our record. However, average microscopic charcoal influx more than doubled relative to the rest of the Holocene during the last 2000 years, with the highest influx after 1550 cal yr BP (400 cal yr CE). The increased influx of microscopic charcoal coincides with archaeological evidence for dramatic regional population growth in the northern Rio Grande region and probably reflects extensive cultural burning associated with the development of an agricultural economy. Although climate was an important driver of vegetation change and fire regimes in the mountains of the southwestern USA during the Holocene, our results suggest that human impacts on regional burning during the last 2000 years far exceeded earlier climate-driven variation.

Rocky Mountains↗

USGS2024

Simulating past and future fire impacts on Mediterranean ecosystems

Worldwide, large wildfires are becoming increasingly common, leading to economic damages and threatening ecosystems and human health. Under future climate change, more frequent fire disturbance may push ecosystems into non-forested alternative stable states. Fire-prone ecosystems such as those in the Mediterranean Basin are expected to be particularly vulnerable, but the position of tipping points is unclear. We compare long-term palaeoecological data from Sardinia with output from a process-based dynamic vegetation model to investigate the mechanisms controlling the complex interactions between fire, climate, and vegetation in the past and the future. Our results show that past vegetation changes from Erica -shrublands to mixed evergreen-broadleaved Quercus ilex -dominated forests were driven by a climate-induced fire regime shift. By simulating vegetation dynamics under varying fire regimes, we could reproduce Holocene vegetation trajectories and mechanistically identify tipping points. Without an immediate reduction of greenhouse gas emissions, we simulate future expansion of fire-prone Mediterranean maquis and increasing fire occurrence. Similarly, high anthropogenic ignition frequencies and plantations of non-native, highly flammable trees could induce a shift to fire-adapted Erica shrublands. However, our simulations indicate that if global warming can be kept below 2°C, Quercus ilex forests will be able to persist and effectively reduce fire occurrences and impacts, making them a valuable restoration target in Mediterranean ecosystems. Synthesis . By combining long-term records of ecosystem change with a dynamic vegetation model, we show that past climate-driven fire regime shifts were the main driver of vegetation change, creating alternative stable states that persisted over centuries. Projected future climate change exceeding Holocene variability leads to pronounced vegetation changes and increased fire risks in our simulations, requiring new fire management strategies to maintain current ecosystem services.

Journal of Ecology↗

USGS2024

Pollen in polar ice implies eastern Canadian forest dynamics diverged from climate after European settlement

Rapid warming and human exploitation threaten boreal forests. Understanding links among vegetation, climate, and people in this vast biome requires highly resolved long-term records that integrate regional inputs. We developed an 850-year pollen-based record of supraregional vegetation change using a southern Greenland ice core and atmospheric modeling that identified the boreal and mixed-conifer forests of eastern Canada as the dominant pollen source regions. Conifer pollen increased ∼1400 CE at the onset of the cooler and drier Little Ice Age. A subsequent decline began ∼1650 CE and a statistically significant pollen change after 1760 CE suggests ecological consequences of the Little Ice Age cooling and initial human exploitation that persisted until recent decades. These supraregional changes are broadly consistent with local records and demonstrate intensification of human impacts on northern forests, suggesting a shift from a climate-modulated to an increasingly human-controlled system during recent centuries.

Geophysical Research Letters↗

USGS2023

Changes in wildfire occurrence and risk to homes from 1990 through 2019 in the Southern Rocky Mountains, USA

Wildfires and housing development have increased since the 1990s, presenting unique challenges for wildfire management. However, it is unclear how the relative influences of housing growth and changing wildfire occurrence have altered risk to homes, or the potential for wildfire to threaten homes. We used a random forests model to predict burn probability in relation to weather variables at 1-km resolution and monthly intervals from 1990 through 2019 in the Southern Rocky Mountains ecoregion. We quantified risk by combining the predicted burn probabilities with decadal housing density. We then compared the predicted burn probabilities and risk across the study area with observed values and quantified trends. Finally, we evaluated how housing growth and changes in burn probability influenced risk individually and combined. Fires burned 9055 km 2 and exposed more than 8500 homes from 1990 to 2019. Observed burned area increased 632% from the 1990s to the 2000s, which combined with housing growth, resulted in a 1342% increase in homes exposed. Increases continued in the 2010s but at lower rates; burned area by 65% and exposure by 32%. The random forests model had excellent fit and high correlation with observations (AUC = 0.88 and r = 0.9). Observed values were within the 95% uncertainty interval for all years except 2016 (burned area) and 2000 (exposure). However, our model overpredicted in years with low observed burned area and underpredicted in years with high observed burned area. Overpredictions in risk resulted in lower rates of change in predicted risk compared with change in observed exposure. Increases in risk between the 1990s and 2000s were primarily due to warmer and drier weather conditions and secondarily because of housing growth. However, increases between the 2000s and 2010s were primarily due to housing growth. Our modeling approach identifies spatial and temporal patterns of wildfire potential and risk, which is critical information to guide decision-making. Because the drivers behind risk shift over time, strategies to mitigate risk may need to account for multiple drivers simultaneously.

Colorado, New Mexico, Wyoming↗

USGS2023

An aridity threshold model of fire sizes and annual area burned in extensively forested ecoregions of the western USA

Wildfire occurrence varies among regions and through time due to the long-term impacts of climate on fuel structure and short-term impacts on fuel flammability. Identifying the climatic conditions that trigger extensive fire years at regional scales can enable development of area burned models that are both spatially and temporally robust, which is crucial for understanding the impacts of past and future climate change. We identified region-specific thresholds in fire-season aridity that distinguish years with limited, moderate, and extensive area burned for 11 extensively forested ecoregions in the western United States. We developed a new area burned model using these relationships and demonstrate its application in the Southern Rocky Mountains using climate projections from five global climate models (GCMs) that bracket the range of projected changes in aridity. We used the aridity thresholds to classify each simulation year as having limited, moderate, or extensive area burned and defined fire-size distributions from historical fire records for these categories. We simulated individual fires from a regression relating fire season aridity to the annual number of fires and drew fire sizes from the corresponding fire-size distributions. We project dramatic increases in area burned after 2020 under most GCMs and after 2060 with all GCMs as the frequency of extensive fire years increases. Our adaptable model can readily incorporate new observations (e.g., extreme fire years) to directly address the non-stationarity of fire-climate relationships as climatic conditions diverge from past observations. Our aridity threshold fire model provides a simple yet spatially robust approach to project regional changes in area burned with broad applicability to ecosystem and vegetation simulation models.

Ecological Modelling↗

USGS2022

Large fires or small fires, will they differ in affecting shifts in species composition and distributions under climate change?

Climate change is expected to increase fire activity, which has the potential to accelerate climate-induced shifts in species composition and distribution in the boreal-temperate ecotone. Wildfire can kill resident trees, and thus provide establishment opportunities for migrating tree species. However, the role of fire size and its interactions with tree species with varied life-history attributes in driving climate-induced shifts is not understood. Future fire regimes could be characterized by many small fires or a few large fires. Large and small fires create and regulate distinct burn patterns, which may influence tree-species responses and post-fire successional trajectories. Here we investigated the effects of future fire-regime variability on the boreal-temperate ecotone of northeastern China under climate change using a coupled forest dynamic model (LANDIS PRO) and ecosystem process model (LINKAGES). We simulated fire regimes using the LANDIS PRO fire module. We designed two fire scenarios (frequent, small fires and infrequent, large fires) to represent different fire regimes in terms of fire size. Results showed fire-catalyzed, climate-induced transitions from boreal to pioneer and temperate forest communities. Frequent, small fires resulted in 13% and 23% higher increases in pioneer and temperate species respectively, relative to infrequent, large fires. Therefore, species composition shifts were faster following frequent, small fires than infrequent, large fires. The results can help policymakers and forest managers determine tradeoffs among strategies to mitigate or adapt to climate change under altered fire regimes.

Great Xing'an Mountains↗

USGS2022

A new indicator approach to reconstruct agricultural land use in Europe from sedimentary pollen assemblages

The reconstruction of human impact is pivotal in palaeoecological studies, as humans are among the most important drivers of Holocene vegetation and ecosystem change. Nevertheless, separating the anthropogenic footprint on vegetation dynamics from the impact of climate and other environmental factors (disturbances such as fire, erosion, floods, landslides, avalanches, volcanic eruptions) is a challenging and still largely open issue. For this purpose, palynologists mostly rely on cultural indicator pollen types and related indices that consist of sums or ratios of these pollen types. However, the high environmental and biogeographical specificity of cultural indicator plants hinders the application of the currently available indices to wide geographical settings. Furthermore, the achievable taxonomic resolution of cultural indicator pollen types may hamper their indicative capacity. In this study, we propose the agricultural land use probability (LUP) index, a novel approach to quantify human impact intensity on European ecosystems based on cultural indicator pollen types. From the ‘classic’ cultural indicators, we construct the LUP index by selecting those with the best indicator capacity based on bioindication criteria. We first train the LUP index using twenty palynological sequences along a broad environmental gradient, spanning from treeless alpine to subtropical mediterranean evergreen plant communities. We then validate the LUP index using independent pollen datasets and archaeological proxies. Finally, we discuss the suitability of the selected pollen types and the potential of the LUP index for quantifying Holocene human impact in Europe, concluding that careful application of the LUP index may significantly contribute to refining pollen-based land-use reconstructions.

Palaeogeography, Palaeoclimatology, Palaeoecology↗

USGS2021

Alpine glacier reveals ecosystem impacts of Europe's prosperity and peril over the last millennium

Information about past ecosystem dynamics and human activities is stored in the ice of Colle Gnifetti glacier in the Swiss Alps. Adverse climatic intervals incurred crop failures and famines and triggered reestablishment of forest vegetation but also societal resilience through innovation. Historical documents and lake sediments record these changes at local—regional scales but often struggle to comprehensively document continental-scale impacts on ecosystems. Here, we provide unique multiproxy evidence of broad-scale ecosystem, land use, and climate dynamics over the past millennium from a Colle Gnifetti microfossil and oxygen isotope record. Microfossil data indicate that before 1750 CE forests and fallow land rapidly replaced crop cultivation during historically documented societal crises caused by climate shifts and epidemics. Subsequently, with technology and the introduction of more resilient crops, European societies adapted to the Little Ice Age cold period, but resource overexploitation and industrialization led to new regional to global-scale environmental challenges.

Geophysical Research Letters↗

USGS2021

The changes in species composition mediate direct effects of climate change on future fire regimes of boreal forests in northeastern China

Direct effects of climate change (i.e. temperature rise, changes in seasonal precipitation, wind patterns and atmospheric stability) affect fire regimes of boreal forests by altering fire behaviour, fire seasons and fuel moisture. Climate change also alters species composition and fuel characteristics, which subsequently alter fire regimes. However, indirect effects of climate change are often simplified or neglected in the direct climate–fire relationship models and dynamic global vegetation models. This may result in high uncertainties associated with existing projections of fire regimes for climate change scenarios. Moreover, few studies have examined fire regime predictions beyond the 21st century, and consequently, how the fire regimes of boreal forests would respond to climate change at the long term (>100 years) are not clear. We develop a coupled modelling framework integrating direct and indirect effects of climate change to predict fire occurrence probability and burned area for boreal forests in northeastern China. We applied repeated measures ANOVA to quantify direct and indirect effects of climate change on fire regimes in the short (0–50 years), medium (60–100 years) and long term (150–200 years). Results showed that for the 21st century, direct effects of climate change are likely to exert a stronger influence on fire regimes than indirect effects. However, increases in fire occurrence probability and burned area will accelerate the transition of boreal forests to temperate forests in the period 2100–2200, and thereby reduce fire occurrence probability and burned area. This suggests that vegetation change will mediate direct effects of climate change on fire regimes of boreal forests at the long term. Synthesis and applications . Vegetation change will mediate direct effects of climate change on fire regimes of boreal forests at the long term. This finding suggested that policymakers may consider adaptive management by planting deciduous species to reduce fire occurrence probability and resistant management by reducing competition to promote boreal species under changing climate conditions.

Journal of Applied Ecology↗

USGS2021

8,000 years of climate, vegetation, fire and land-use dynamics in the thermo-mediterranean vegetation belt of northern Sardinia (Italy)

Knowledge about the vegetation history of Sardinia, the second largest island of the Mediterranean, is scanty. Here, we present a new sedimentary record covering the past ~ 8,000 years from Lago di Baratz, north-west Sardinia. Vegetation and fire history are reconstructed by pollen, spores, macrofossils and charcoal analyses and environmental dynamics by high-resolution element geochemistry together with pigment analyses. During the period 8,100–7,500 cal BP , when seasonality was high and fire and erosion were frequent, Erica arborea and E. scoparia woodlands dominated the coastal landscape. Subsequently, between 7,500 and 5,500 cal BP , seasonality gradually declined and thermo-mediterranean woodlands with Pistacia and Quercus ilex partially replaced Erica communities under diminished incidence of fire. After 5,500 cal BP , evergreen oak forests expanded markedly, erosion declined and lake levels increased, likely in response to increasing (summer) moisture availability. Increased anthropogenic fire disturbance triggered shrubland expansions (e.g. Tamarix and Pistacia ) around 5,000–4,500 cal BP . Subsequently around 4,000–3,500 cal BP evergreen oak-olive forests expanded massively when fire activity declined and lake productivity and anoxia reached Holocene maxima. Land-use activities during the past 4,000 years (since the Bronze Age) gradually disrupted coastal forests, but relict stands persisted under rather stable environmental conditions until ca. 200 cal BP , when agricultural activities intensified and Pinus and Eucalyptus were planted to stabilize the sand dunes. Pervasive prehistoric land-use activities since at least the Bronze Age Nuraghi period included the cultivation of Prunus , Olea europaea and Juglans regia after 3,500–3,300 cal BP , and Quercus suber after 2,500 cal BP . We conclude that restoring less flammable native Q. ilex and O. europaea forest communities would markedly reduce fire risk and erodibility compared to recent forest plantations with flammable non-native trees (e.g. Pinus , Eucalyptus ) and xerophytic shrubland (e.g. Cistus , Erica ).

Sardinia↗

USGS2020

Increased burning in a warming climate reduces carbon uptake in the Greater Yellowstone Ecosystem despite productivity gains

1. The effects of changing climate and disturbance on mountain forest carbon stocks vary with tree species distributions and over elevational gradients. Warming can increase carbon uptake by stimulating productivity at high elevations but also enhance carbon release by increasing respiration and the frequency, intensity, and size of wildfires. 2. To understand the consequences of climate change for temperate mountain forests, we simulated interactions among climate, wildfire, tree species, and their combined effects on regional carbon stocks in forests of the Greater Yellowstone Ecosystem, USA with the LANDIS‐II landscape change model. Simulations used historical climate and future potential climate represented by downscaled projections from five general circulation models (GCMs) that bracket the range of variability under the representative concentration pathway (RCP) 8.5 emissions scenario. 3. Total ecosystem carbon increased by 67% through 2100 in simulations with historical climate, and by 38 – 69% with GCM climate. Differences in carbon uptake among GCMs resulted primarily from variation in area burned, not productivity. Warming increased productivity by extending the growing season, especially near upper treeline, but did not offset biomass losses to fire. By 2100, simulated area burned increased by 27 – 215% under GCM climate, with the largest increases after 2050. With warming >3 °C in mean annual temperature, the increased frequency of large fires reduced live carbon stocks by 4 – 36% relative to the control, historical climate scenario. However, relative losses in total carbon were delayed under GCMs with large increases in summer precipitation and buffered by carbon retained in soils and the wood of fire‐killed trees. Increasing fire size limited seed dispersal, and reductions in soil moisture limited seedling establishment; both effects will likely constrain long‐term forest regeneration and carbon uptake. 4. Synthesis. Forests in the GYE can maintain a carbon sink through the mid‐century in a warming climate but continued warming may cause the loss of forest area, live aboveground biomass, and ultimately, ecosystem carbon. Future changes in carbon stocks in similar forests throughout western North America will depend on regional thresholds for extensive wildfire and forest regeneration and therefore, changes may occur earlier in drier regions.

Idaho, Montana, Wyoming↗

USGS2020

Spatially explicit reconstruction of post-megafire forest recovery through landscape modeling

Megafires are large wildfires that occur under extreme weather conditions and produce mixed burn severities across diverse environmental gradients. Assessing megafire effects requires data covering large spatiotemporal extents, which are difficult to collect from field inventories. Remote sensing provides an alternative but is limited in revealing post-fire recovery trajectories and the underlying processes that drive the recovery. We developed a novel framework to spatially reconstruct the post-fire time-series of forest conditions after the 1987 Black Dragon fire of China by integrating a forest landscape model (LANDIS) with remote sensing and inventory data. We derived pre-fire (1985) forest composition and the megafire perimeter and severity using remote sensing and inventory data. We simulated the megafire and the post-megafire forest recovery from 1985 to 2015 using the LANDIS model. We demonstrated that the framework was effective in reconstructing the post-fire stand dynamics and that it is applicable to other types of disturbances.

Environmental Modelling and Software↗

USGS2020

A critical assessment of human-impact indices based on anthropogenic pollen indicators

Anthropogenic pollen indicators in pollen records are an established tool for reconstructing the history of human impacts on vegetation and landscapes. They are also used to disentangle the influence of human activities and climatic variability on ecosystems. The comprehensive anthropogenic pollen-indicator approach developed by Behre (1981) has been widely used, including beyond its original geographical scope of Central and Western Europe. Uncritical adoption of this approach for other areas is risky because adventives (plants introduced with agriculture) in Central Europe can be apophytes (native plants favoured by human disturbances) in other regions. This problem can be addressed by identifying region-specific, anthropogenic-indicator pollen types and/or developing region-specific, human-impact indices from pollen assemblages. However, understanding of regional variation in the timing and intensity of human impacts is limited by the lack of standardization, validation and intercomparison of such regional approaches. Here we review the most common European anthropogenic pollen-indicator approaches to assess their performance at six sites spanning a continental gradient over the boreal, temperate and Mediterranean biomes. Specifically, we evaluate the human-indicator approaches by using independent archaeological evidence and models. We present new insights into how these methodologies can assist in the interpretation of pollen records as well as into how a careful selection of pollen types and/or indices according to the specific geographical scope of each study is key to obtain meaningful reconstructions of anthropogenic activity through time. The evaluated approaches generally perform better in the regions for which they were developed. However, we find marked differences in their capacity to identify human impact, while some approaches do not perform well even in the regions for which they were developed, others might be used, with due caution, outside their original areas or biomes. We conclude that alongside the increasing wealth of pollen datasets a need to develop novel tools may assist numeric human impact reconstructions.

Quaternary Science Reviews↗

USGS2019

Evaluating k-nearest neighbor (kNN) imputation models for species-level aboveground forest biomass mapping in northeast China

Quantifying spatially explicit or pixel-level aboveground forest biomass (AFB) across large regions is critical for measuring forest carbon sequestration capacity, assessing forest carbon balance, and revealing changes in the structure and function of forest ecosystems. When AFB is measured at the species level using widely available remote sensing data, regional changes in forest composition can readily be monitored. In this study, wall-to-wall maps of species-level AFB were generated for forests in Northeast China by integrating forest inventory data with Moderate Resolution Imaging Spectroradiometer (MODIS) images and environmental variables through applying the optimal k -nearest neighbor ( k NN) imputation model. By comparing the prediction accuracy of 630 k NN models, we found that the models with random forest (RF) as the distance metric showed the highest accuracy. Compared to the use of single-month MODIS data for September, there was no appreciable improvement for the estimation accuracy of species-level AFB by using multi-month MODIS data. When k > 7, the accuracy improvement of the RF-based k NN models using the single MODIS predictors for September was essentially negligible. Therefore, the k NN model using the RF distance metric, single-month (September) MODIS predictors and k = 7 was the optimal model to impute the species-level AFB for entire Northeast China. Our imputation results showed that average AFB of all species over Northeast China was 101.98 Mg/ha around 2000. Among 17 widespread species, larch was most dominant, with the largest AFB (20.88 Mg/ha), followed by white birch (13.84 Mg/ha). Amur corktree and willow had low AFB (0.91 and 0.96 Mg/ha, respectively). Environmental variables (e.g., climate and topography) had strong relationships with species-level AFB. By integrating forest inventory data and remote sensing data with complete spatial coverage using the optimal k NN model, we successfully mapped the AFB distribution of the 17 tree species over Northeast China. We also evaluated the accuracy of AFB at different spatial scales. The AFB estimation accuracy significantly improved from stand level up to the ecotype level, indicating that the AFB maps generated from this study are more suitable to apply to forest ecosystem models (e.g., LINKAGES) which require species-level attributes at the ecotype scale.

Remote Sensing↗

USGS2019

A landscape model of variable social-ecological fire regimes

Fire regimes are now recognized as the product of social processes whereby fire on any landscape is the product of human-generated drivers: climate change, historical patterns of vegetation manipulation, invasive species, active fire suppression, ongoing fuel management efforts, prescribed burning, and accidental ignitions. We developed a new fire model (Social-Climate Related Pyrogenic Processes and their Landscape Effects: SCRPPLE) that emphasizes the social dimensions of fire and enables simulation of fuel-treatment effects, fire suppression, and prescribed fires. Fire behavior was parameterized with daily fire weather, ignition, and fire-boundary data. SCRPPLE was initially parameterized and developed for the Lake Tahoe Basin (LTB) in California and Nevada, USA although its behavior is general and could be applied worldwide. We demonstrate the behavior and utility of our model via four simple scenarios that emphasize the social dimensions of fire regimes: a) Recent Historical: simulated recent historical patterns of lightning and accidental fires and current patterns of fire suppression, b) Natural-Fire-Regime: simulated wildfire without suppression, accidental fires, or prescribed fires, holding all other factors the same as Recent Historical, c) Enhanced Suppression: simulated a doubling of the effectiveness of suppression, holding all other factors the same as Recent Historical, and d) Reduced Accidental Ignitions: within which the number of accidental fires was reduced by half, holding all other factors the same as Recent Historical. Results indicate that SCRPPLE can recreate past fire regimes, including size, intensity, and locations. Furthermore, our results indicate that the ‘Enhanced Suppression’ and ‘Reduced Accidental Ignitions’ scenarios had similar capacity to reduce fire and related tree mortality over time, suggesting that within the broad outlines of the scenarios, reducing accidental fires can be as effective as substantially increasing resources for suppression.

California, Nevada↗

USGS2018

Estimating soil respiration in a subalpine landscape using point, terrain, climate and greenness data

Landscape carbon (C) flux estimates are necessary for assessing the ability of terrestrial ecosystems to buffer further increases in anthropogenic carbon dioxide (CO2) emissions. Advances in remote sensing have allowed for coarse-scale estimates of gross primary productivity (GPP) (e.g., MODIS 17), yet efforts to assess spatial patterns in respiration lag behind those of GPP. Here, we demonstrate a method to predict growing season soil respiration at a regional scale in a forested ecosystem. We related field measurements (n=144) of growing season soil respiration across subalpine forests in the Southern Rocky Mountains ecoregion to a suite of biophysical predictors with a Random Forest model (30 m pixel size). We found that Landsat Enhanced Vegetation Index (EVI), growing season AI, temperature, precipitation, elevation, and slope aspect explained spatiotemporal variability in soil respiration. Our model had a psuedo-r2 of 0.45 and root mean squared error (RMSE) of roughly one-quarter of the mean value of respiration. Predicted growing season soil respiration across the region was remarkably consistent across 2004, 2005 and 2006 (150-d averages of 542.8, 544.3, and 536.5 g C m-2, respectively). Yet, we observed substantial variability in spatial patterns of soil respiration predictions that varied between years, suggesting that our method is sensitive to changes in respiration drivers. We compared our estimates to MODIS GPP and nocturnal net ecosystem exchange (NEE) derived from eddy covariance towers as a proxy for ecosystem respiration. Averaged across the predictive region, mean predicted growing season soil respiration was 73% of MODIS GPP, while predicted soil respiration was generally within 20% of nocturnal NEE from eddy covariance towers. This study demonstrated that geospatial and remotely-sensed datasets can be used in a statistical modeling framework to estimate soil respiration at landscape scales.

Colorado, Wyoming↗

USGS2018

Microclimatic gradients provide evidence for a glacial refugium for temperate trees in a sheltered hilly landscape of Northern Italy

Aim Refugia play a key role in conserving biodiversity during periods of unfavourable and highly variable regional climate. However, refugial populations are often small and fragmented, which makes their identification difficult. In this study, we investigate whether an area of complex topography in the southern foreland of the Alps could have provided a suitable microclimate to serve as a glacial refugium for temperate trees during the last glacial. Location The Euganean Hills in Northern Italy (Veneto). Methods We assessed the current microclimatic variability in the ecologically diverse region on a fine scale by recording half‐hourly near‐surface temperatures over a period of 11 months. After comparing our measurements with today's vegetation distribution, broad‐scale synoptic patterns, and topoclimatic factors, we estimated refugial suitability based on extreme temperatures, climatic stability, and difference from the regional average. Results Present‐day temperature gradients within the Euganean Hills are large enough to explain the presence of the temperate tree species Fagus sylvatica as well as Mediterranean Quercus ilex , two species that are absent elsewhere in the adjacent Po Plain. During winter, anticyclonic weather patterns resulted in strong atmospheric inversions, with temperatures increasing by +1°C/100 m in the hills relative to the surrounding Po Plain. Main conclusions Our high‐resolution climate data support multi‐proxy palaeoecological records identifying the Euganean Hills as a refugium for temperate trees. Temperature anomalies of 2–4°C relative to the surrounding Po Plain are sufficient to allow several temperate tree species to survive the Last Glacial Maximum (LGM) in the Euganean Hills under a harsh continental climate. Specifically, elevations >200 m a.s.l. in the central parts of the hills may have provided suitable conditions for local LGM refugia. Regions of complex topography such as the Euganean Hills conserved past and present biodiversity and provide high‐priority areas for conservation under future climate warming.

Journal of Biogeography↗

USGS2018

Integrating forest inventory data and MODIS data to map species-level biomass in Chinese boreal forests

Timely and accurate knowledge of species-level biomass is essential for forest managers to sustain forest resources and respond to various forest disturbance regimes. In this study, maps of species-level biomass in Chinese boreal forests were generated by integrating Moderate Resolution Imaging Spectroradiometer (MODIS) images with forest inventory data using k nearest neighbor ( k NN) methods and evaluated at different scales. The performance of 630 k NN models based on different distance metrics, k values, and temporal MODIS predictor variables were compared. Random Forest (RF) showed the best performance among the six distance metrics: RF, Euclidean distance, Mahalanobis distance, most similar neighbor in canonical correlation space, most similar neighbor computed using projection pursuit, and gradient nearest neighbor. No appreciable improvement was observed using multi-month MODIS data compared with using single-month MODIS data. At the pixel scale, species-level biomass for larch and white birch had relatively good accuracy (root mean square deviation < 62.1%), while the other species had poorer accuracy. The accuracy of most species except for willow and spruce was improved up to the ecoregion scale. The maps of species-level biomass captured the effects of disturbances including fire and harvest and can provide useful information for broad-scale forest monitoring over time.

Canadian Journal of Forest Research↗