Rocky Mountain Research Station
governmentFort Collins, United States
Research output, citation impact, and the most-cited recent papers from Rocky Mountain Research Station (United States). Aggregated across the NobleBlocks index of 300M+ scholarly works.
Top-cited papers from Rocky Mountain Research Station
We present TerraClimate, a dataset of high-spatial resolution (1/24°, ~4-km) monthly climate and climatic water balance for global terrestrial surfaces from 1958-2015. TerraClimate uses climatically aided interpolation, combining high-spatial resolution climatological normals from the WorldClim dataset, with coarser resolution time varying (i.e., monthly) data from other sources to produce a monthly dataset of precipitation, maximum and minimum temperature, wind speed, vapor pressure, and solar radiation. TerraClimate additionally produces monthly surface water balance datasets using a water balance model that incorporates reference evapotranspiration, precipitation, temperature, and interpolated plant extractable soil water capacity. These data provide important inputs for ecological and hydrological studies at global scales that require high spatial resolution and time varying climate and climatic water balance data. We validated spatiotemporal aspects of TerraClimate using annual temperature, precipitation, and calculated reference evapotranspiration from station data, as well as annual runoff from streamflow gauges. TerraClimate datasets showed noted improvement in overall mean absolute error and increased spatial realism relative to coarser resolution gridded datasets.
Climate strongly influences global wildfire activity, and recent wildfire surges may signal fire weather-induced pyrogeographic shifts. Here we use three daily global climate data sets and three fire danger indices to develop a simple annual metric of fire weather season length, and map spatio-temporal trends from 1979 to 2013. We show that fire weather seasons have lengthened across 29.6 million km(2) (25.3%) of the Earth's vegetated surface, resulting in an 18.7% increase in global mean fire weather season length. We also show a doubling (108.1% increase) of global burnable area affected by long fire weather seasons (>1.0 σ above the historical mean) and an increased global frequency of long fire weather seasons across 62.4 million km(2) (53.4%) during the second half of the study period. If these fire weather changes are coupled with ignition sources and available fuel, they could markedly impact global ecosystems, societies, economies and climate.
Persistent changes in tree mortality rates can alter forest structure, composition, and ecosystem services such as carbon sequestration. Our analyses of longitudinal data from unmanaged old forests in the western United States showed that background (noncatastrophic) mortality rates have increased rapidly in recent decades, with doubling periods ranging from 17 to 29 years among regions. Increases were also pervasive across elevations, tree sizes, dominant genera, and past fire histories. Forest density and basal area declined slightly, which suggests that increasing mortality was not caused by endogenous increases in competition. Because mortality increased in small trees, the overall increase in mortality rates cannot be attributed solely to aging of large trees. Regional warming and consequent increases in water deficits are likely contributors to the increases in tree mortality rates.
, water, and energy exchange between the biosphere and the atmosphere, and other meteorological and biological measurements, from 212 sites around the globe (over 1500 site-years, up to and including year 2014). These sites, independently managed and operated, voluntarily contributed their data to create global datasets. Data were quality controlled and processed using uniform methods, to improve consistency and intercomparability across sites. The dataset is already being used in a number of applications, including ecophysiology studies, remote sensing studies, and development of ecosystem and Earth system models. FLUXNET2015 includes derived-data products, such as gap-filled time series, ecosystem respiration and photosynthetic uptake estimates, estimation of uncertainties, and metadata about the measurements, presented for the first time in this paper. In addition, 206 of these sites are for the first time distributed under a Creative Commons (CC-BY 4.0) license. This paper details this enhanced dataset and the processing methods, now made available as open-source codes, making the dataset more accessible, transparent, and reproducible.
The response of soil organic matter (OM) decomposition to increasing temperature is a critical aspect of ecosystem responses to global change. The impacts of climate warming on decomposition dynamics have not been resolved due to apparently contradictory results from field and lab experiments, most of which has focused on labile carbon with short turnover times. But the majority of total soil carbon stocks are comprised of organic carbon with turnover times of decades to centuries. Understanding the response of these carbon pools to climate change is essential for forecasting longer-term changes in soil carbon storage. Herein, we briefly synthesize information from recent studies that have been conducted using a wide variety of approaches. In our effort to understand research to-date, we derive a new conceptual model that explicitly identifies the processes controlling soil OM availability for decomposition and allows a more explicit description of the factors regulating OM decomposition under different circumstances. It explicitly defines resistance of soil OM to decomposition as being due either to its chemical conformation (quality) or its physico-chemical protection from decomposition. The former is embodied in the depolymerization process, the latter by adsorption/desorption and aggregate turnover. We hypothesize a strong role for variation in temperature sensitivity as a function of reaction rates for both. We conclude that important advances in understanding the temperature response of the processes that control substrate availability, depolymerization, microbial efficiency, and enzyme production will be needed to predict the fate of soil carbon stocks in a warmer world.
The theory of planned behavior (Ajzen, 1985, 1987) is used to predict leisure intentions and behavior. College students completed a questionnaire that measured involvement, moods, attitudes, subjective norms, perceived behavioral control, and intentions concerning five leisure activities: spending time at the beach, jogging or running, mountain climbing, boating, and biking. One year later the participants reported how often they had performed these behaviors during the preceding year. Between- and within-subjects analyses showed that attitudes toward leisure activities consist of affective and instrumental components, and that reported mood correlates with the former but not the latter. Consistent with the theory, attitudes, subjective norms, and perceived behavioral control predicted leisure intentions (R =.50 to.86), and intentions and perceived control predicted leisure behavior (R =.48 to.78). Contrary to expectations, involvement did not affect accuracy of prediction. It is concluded that the theory of planned behavior can advance our understanding of leisure activities.
The Society for Ecological Restoration (SER) is an international non-profit organization with members in 70 countries. SER advances the science, practice and policy of ecological restoration to sustain biodiversity, improve resilience in a changing climate, and re-establish an ecologically healthy relationship between nature and culture. SER is a dynamic global network, linking researchers, practitioners, land managers, community leaders and decision-makers to restore ecosystems and the human communities that depend on them. Via its members, publications, conferences, policy work, and outreach, SER defines and delivers excellence in the field of ecological restoration.
The impacts of climate extremes on terrestrial ecosystems are poorly understood but important for predicting carbon cycle feedbacks to climate change. Coupled climate-carbon cycle models typically assume that vegetation recovery from extreme drought is immediate and complete, which conflicts with the understanding of basic plant physiology. We examined the recovery of stem growth in trees after severe drought at 1338 forest sites across the globe, comprising 49,339 site-years, and compared the results with simulated recovery in climate-vegetation models. We found pervasive and substantial "legacy effects" of reduced growth and incomplete recovery for 1 to 4 years after severe drought. Legacy effects were most prevalent in dry ecosystems, among Pinaceae, and among species with low hydraulic safety margins. In contrast, limited or no legacy effects after drought were simulated by current climate-vegetation models. Our results highlight hysteresis in ecosystem-level carbon cycling and delayed recovery from climate extremes.
Abstract Carbon allocation plays a critical role in forest ecosystem carbon cycling. We reviewed existing literature and compiled annual carbon budgets for forest ecosystems to test a series of hypotheses addressing the patterns, plasticity, and limits of three components of allocation: biomass , the amount of material present; flux , the flow of carbon to a component per unit time; and partitioning , the fraction of gross primary productivity (GPP) used by a component. Can annual carbon flux and partitioning be inferred from biomass ? Our survey revealed that biomass was poorly related to carbon flux and to partitioning of photosynthetically derived carbon, and should not be used to infer either. Are component fluxes correlated ? Carbon fluxes to foliage, wood, and belowground production and respiration all increased linearly with increasing GPP (a rising tide lifts all boats). Autotrophic respiration was strongly linked to production for foliage, wood and roots, and aboveground net primary productivity and total belowground carbon flux (TBCF) were positively correlated across a broad productivity gradient. How does carbon partitioning respond to variability in resources and environment ? Within sites, partitioning to aboveground wood production and TBCF responded to changes in stand age and resource availability, but not to competition (tree density). Increasing resource supply and stand age, with one exception, resulted in increased partitioning to aboveground wood production and decreased partitioning to TBCF. Partitioning to foliage production was much less sensitive to changes in resources and environment. Overall, changes in partitioning within a site in response to resource supply and age were small (<15% of GPP), but much greater than those inferred from global relationships. Across all sites, foliage production plus respiration, and total autotrophic respiration appear to use relatively constant fractions of GPP – partitioning to both was conservative across a broad range of GPP – but values did vary across sites. Partitioning to aboveground wood production and to TBCF were the most variable – conditions that favored high GPP increased partitioning to aboveground wood production and decreased partitioning to TBCF. Do priorities exist for the products of photosynthesis ? The available data do not support the concept of priorities for the products of photosynthesis, because increasing GPP increased all fluxes. All facets of carbon allocation are important to understanding carbon cycling in forest ecosystems. Terrestrial ecosystem models require information on partitioning, yet we found few studies that measured all components of the carbon budget to allow estimation of partitioning coefficients. Future studies that measure complete annual carbon budgets contribute the most to understanding carbon allocation.
![Figure][1] Free image. This Landsat 5 image of the southeastern corner of the Black Sea is part of the general U.S. archive that will be accessible for free under the new USGS policy. CREDIT: BOSTON UNIVERSITY CENTER FOR REMOTE SENSING We are entering a new era in the Landsat Program, the oldest and most venerable of our Earth-observing satellite programs. With little fanfare, the U.S. Geological Survey (USGS) has begun providing imagery for free over the Internet. Throughout the history of the Landsat Program, the cost and access to imagery has always limited our ability to study our planet and the way it is changing. Beginning with a pilot program to provide “Web-enabled” access to Landsat 7 images of the United States that were collected between 2003 and this year, the USGS now plans to provide top-quality image products for free upon request for the entire U.S. archive, including over 2 million images back to Landsat 1 (1972) [for details and schedules, see ([1][2])]. The release by NASA and the USGS in January 2008 of a new Landsat Data Distribution Policy ([2][3]) was a key step to this goal. Free imagery will enable reconstruction of the history of Earth's surface back to 1972, chronicling both anthropogenic and natural changes during a time when our population doubled and the impacts of climate change became noticeable. The Landsat Science Team: 1. 1.[↵][4]USGS Technical Announcement ([http://landsat.usgs.gov/images/squares/USGS\_Landsat\_Imagery_Release.pdf][5]). 2. 2.[↵][6]Landsat Missions ([http://ldcm.usgs.gov/pdf/Landsat\_Data\_Policy.pdf][7]). [1]: pending:yes [2]: #ref-1 [3]: #ref-2 [4]: #xref-ref-1-1 View reference 1. in text [5]: http://landsat.usgs.gov/images/squares/USGS_Landsat_Imagery_Release.pdf [6]: #xref-ref-2-1 View reference 2. in text [7]: http://ldcm.usgs.gov/pdf/Landsat_Data_Policy.pdf
Climate change is expected to drive increased tree mortality through drought, heat stress, and insect attacks, with manifold impacts on forest ecosystems. Yet, climate-induced tree mortality and biotic disturbance agents are largely absent from process-based ecosystem models. Using data sets from the western USA and associated studies, we present a framework for determining the relative contribution of drought stress, insect attack, and their interactions, which is critical for modeling mortality in future climates. We outline a simple approach that identifies the mechanisms associated with two guilds of insects - bark beetles and defoliators - which are responsible for substantial tree mortality. We then discuss cross-biome patterns of insect-driven tree mortality and draw upon available evidence contrasting the prevalence of insect outbreaks in temperate and tropical regions. We conclude with an overview of tools and promising avenues to address major challenges. Ultimately, a multitrophic approach that captures tree physiology, insect populations, and tree-insect interactions will better inform projections of forest ecosystem responses to climate change.
Space and airborne sensors have been used to map area burned, assess characteristics of active fires, and characterize post-fire ecological effects. Confusion about fire intensity, fire severity, burn severity, and related terms can result in the potential misuse of the inferred information by land managers and remote sensing practitioners who require unambiguous remote sensing products for fire management. The objective of the present paper is to provide a comprehensive review of current and potential remote sensing methods used to assess fire behavior and effects and ecological responses to fire. We clarify the terminology to facilitate development and interpretation of comprehensible and defensible remote sensing products, present the potential and limitations of a variety of approaches for remotely measuring active fires and their post-fire ecological effects, and discuss challenges and future directions of fire-related remote sensing research.
We use eddy covariance measurements of net ecosystem productivity (NEP) from 21 FLUXNET sites (153 site-years of data) to investigate relationships between phenology and productivity (in terms of both NEP and gross ecosystem photosynthesis, GEP) in temperate and boreal forests. Results are used to evaluate the plausibility of four different conceptual models. Phenological indicators were derived from the eddy covariance time series, and from remote sensing and models. We examine spatial patterns (across sites) and temporal patterns (across years); an important conclusion is that it is likely that neither of these accurately represents how productivity will respond to future phenological shifts resulting from ongoing climate change. In spring and autumn, increased GEP resulting from an 'extra' day tends to be offset by concurrent, but smaller, increases in ecosystem respiration, and thus the effect on NEP is still positive. Spring productivity anomalies appear to have carry-over effects that translate to productivity anomalies in the following autumn, but it is not clear that these result directly from phenological anomalies. Finally, the productivity of evergreen needleleaf forests is less sensitive to phenology than is productivity of deciduous broadleaf forests. This has implications for how climate change may drive shifts in competition within mixed-species stands.
Forest insects and pathogens are the most pervasive and important agents of disturbance in North American forests, affecting an area almost 50 times larger than fire and with an economic impact nearly five times as great. The same attributes that result in an insect herbivore being termed a "pest" predispose it to disruption by climate change, particularly global warming. Although many pest species have co-evolved relationships with forest hosts that may or may not be harmful over the long term, the effects on these relationships may have disastrous consequences. We consider both the data and models necessary to evaluate the impacts of climate change, as well as the assessments that have been made to date. The results indicate that all aspects of insect outbreak behavior will intensify as the climate warms. This reinforces the need for more detailed monitoring and evaluations as climatic events unfold. Luckily, we are well placed to make rapid progress, using software tools, databases, and the models that are already available.
Although trees have responded to global warming in the past - to temperatures higher than they are now - the rate of change predicted in the 21st century is likely to be unprecedented. Greenhouse gas emissions could cause a 3-6°C increase in mean land surface temperature at high and temperate latitudes. Despite this, few experiments have isolated the effects of temperature for this scenario on trees and forests. This review focuses on tree and forest responses at boreal and temperate latitudes, ranging from the cellular to the ecosystem level. Adaptation to varying temperatures revolves around the trade-off between utilizing the full growing season and minimizing frost damage through proper timing of hardening in autumn and dehardening in spring. But the evolutionary change in these traits must be sufficiently rapid to compensate for the temperature changes. Many species have a positive response to increased temperature - but how close are we to the optima? Management is critical for a positive response of forest growth to a warmer climate, and selection of the best species for the new conditions will be of vital importance. Contents Summary 369 I. Introduction 370 II. Photosynthesis and respiration 370 III. Soil organic matter decomposition and mineralization 373 IV. Phenology and frost hardiness 376 V. Whole tree experimental responses to warming 380 VI. Changes in species distribution at warmer temperatures 381 VII. Adaptation and evolution 383 VIII. Ecosystem level responses to warming 387 Acknowledgements 390 References 390 Appendix I. Temperature response functions 399.
As climate changes, the effects of forest diseases on forest ecosystems will change. We review knowledge of relationships between climate variables and several forest diseases, as well as current evidence of how climate, host and pathogen interactions are responding or might respond to climate change. Many forests can be managed to both adapt to climate change and minimize the undesirable effects of expected increases in tree mortality. We discuss four types of forest and disease management tactics – monitoring, forecasting, planning and mitigation – and provide case studies of yellow‐cedar decline and sudden aspen decline to illustrate how forest diseases might be managed in the face of climate change. The uncertainties inherent to climate change effects can be diminished by conducting research, assessing risks, and linking results to forest policy, planning and decision making.
Predicting population-level effects of landscape change depends on identifying factors that influence population connectivity in complex landscapes. However, most putative movement corridors and barriers have not been based on empirical data. In this study, we identify factors that influence connectivity by comparing patterns of genetic similarity among 146 black bears (Ursus americanus), sampled across a 3,000-km(2) study area in northern Idaho, with 110 landscape-resistance hypotheses. Genetic similarities were based on the pairwise percentage dissimilarity among all individuals based on nine microsatellite loci (average expected heterozygosity=0.79). Landscape-resistance hypotheses describe a range of potential relationships between movement cost and land cover, slope, elevation, roads, Euclidean distance, and a putative movement barrier. These hypotheses were divided into seven organizational models in which the influences of barriers, distance, and landscape features were statistically separated using partial Mantel tests. Only one of the competing organizational models was fully supported: patterns of genetic structure are primarily related to landscape gradients of land cover and elevation. The alternative landscape models, isolation by barriers and isolation by distance, are not supported. In this black bear population, gene flow is facilitated by contiguous forest cover at middle elevations.
Since 1972, the Landsat program has been continually monitoring the Earth, to now provide 50 years of digital, multispectral, medium spatial resolution observations. Over this time, Landsat data were crucial for many scientific and technical advances. Prior to the Landsat program, detailed, synoptic depictions of the Earth's surface were rare, and the ability to acquire and work with large datasets was limited. The early years of the Landsat program delivered a series of technological breakthroughs, pioneering new methods, and demonstrating the ability and capacity of digital satellite imagery, creating a template for other global Earth observation missions and programs. Innovations driven by the Landsat program have paved the way for subsequent science, application, and policy support activities. The economic and scientific value of the knowledge gained through the Landsat program has been long recognized, and despite periods of funding uncertainty, has resulted in the program's 50 years of continuity, as well as substantive and ongoing improvements to payload and mission performance. Free and open access to Landsat data, enacted in 2008, was unprecedented for medium spatial resolution Earth observation data and substantially increased usage and led to a proliferation of science and application opportunities. Here, we highlight key developments over the past 50 years of the Landsat program that have influenced and changed our scientific understanding of the Earth system. Major scientific and programmatic impacts have been realized in the areas of agricultural crop mapping and water use, climate change drivers and impacts, ecosystems and land cover monitoring, and mapping the changing human footprint. The introduction of Landsat collection processing, coupled with the free and open data policy, facilitated a transition in Landsat data usage away from single images and towards time series analyses over large areas and has fostered the widespread use of science-grade data. The launch of Landsat-9 on September 27, 2021, and the advanced planning of its successor mission, Landsat-Next, underscore the sustained institutional support for the program. Such support and commitment to continuity is recognition of both the historic impact the program, and the future potential to build upon Landsat's remarkable 50-year legacy.
Abstract An intermediate-complexity, quasi–physically based, meteorological model (MicroMet) has been developed to produce high-resolution (e.g., 30-m to 1-km horizontal grid increment) atmospheric forcings required to run spatially distributed terrestrial models over a wide variety of landscapes. The following eight variables, required to run most terrestrial models, are distributed: air temperature, relative humidity, wind speed, wind direction, incoming solar radiation, incoming longwave radiation, surface pressure, and precipitation. To produce these distributions, MicroMet assumes that at least one value of each of the following meteorological variables are available for each time step, somewhere within, or near, the simulation domain: air temperature, relative humidity, wind speed, wind direction, and precipitation. These variables are collected at most meteorological stations. For the incoming solar and longwave radiation, and surface pressure, either MicroMet can use its submodels to generate these fields, or it can create the distributions from observations as part of a data assimilation procedure. MicroMet includes a preprocessor component that analyzes meteorological data, then identifies and corrects potential deficiencies. Since providing temporally and spatially continuous atmospheric forcing data for terrestrial models is a core objective of MicroMet, the preprocessor also fills in any missing data segments with realistic values. Data filling is achieved by employing a variety of procedures, including an autoregressive integrated moving average calculation for diurnally varying variables (e.g., air temperature). To create the distributed atmospheric fields, spatial interpolations are performed using the Barnes objective analysis scheme, and subsequent corrections are made to the interpolated fields using known temperature–elevation, wind–topography, humidity–cloudiness, and radiation–cloud–topography relationships.
We proposed the hydraulic limitation hypothesis (HLH) as a mechanism to explain universal patterns in tree height, and tree and stand biomass growth: height growth slows down as trees grow taller, maximum height is lower for trees of the same species on resource-poor sites and annual wood production declines after canopy closure for even-aged forests. Our review of 51 studies that measured one or more of the components necessary for testing the hypothesis showed that taller trees differ physiologically from shorter, younger trees. Stomatal conductance to water vapour (g(s)), photosynthesis (A) and leaf-specific hydraulic conductance (K L) are often, but not always, lower in taller trees. Additionally, leaf mass per area is often greater in taller trees, and leaf area:sapwood area ratio changes with tree height. We conclude that hydraulic limitation of gas exchange with increasing tree size is common, but not universal. Where hydraulic limitations to A do occur, no evidence supports the original expectation that hydraulic limitation of carbon assimilation is sufficient to explain observed declines in wood production. Any limit to height or height growth does not appear to be related to the so-called age-related decline in wood production of forests after canopy closure. Future work on this problem should explicitly link leaf or canopy gas exchange with tree and stand growth, and consider a more fundamental assumption: whether tree biomass growth is limited by carbon availability.