The dynamic global vegetation model MC1 simulates plant growth and biogeochemical cycles, vegetation type, wildfire, and their interactions. The model simulates competition between trees and grasses (including other herbaceous species), as affected by differential access to light and water, and fire-caused tree mortality (Bachelet et al., 2000; 2001). MC1 projects the dynamics of lifeforms, including evergreen and deciduous needleleaf and broadleaf trees, as well as C3 and C4 grasses. However, the model can also be parameterized for a particular dominant species of the associated lifeform. For this project we used two versions of MC1, both of which modified the standard code to improve the simulation of potential evapotranspiration (PET).For the western northern Great Plains (NGP) the model was calibrated to project the observed ecotone between ponderosa pine and grasslands at Wind Cave National Park in the Black Hills of South Dakota; full documentation of this version of the code is described by King et al. (2013a). In this case the evergreen needleleaf life form corresponds to ponderosa pine (Pinus ponderosa). For the eastern NGP we recalibrated MC1 so that the evergreen needleleaf lifeform corresponds to juniper; principally eastern redcedar (Juniperus virginiana), but also to Rocky Mountain juniper (Juniperus scopularum), which is present in the western and central NGP.

Assessments of vegetation response to climate change have generally been made only by equilibrium vegetation models that predict vegetation composition under steady-state conditions. These models do not simulate either ecosystem biogeochemical processes or changes in ecosystem structure that may, in turn, act as feedbacks in determining the dynamics of vegetation change. MC1 is a new dynamic global vegetation model created to assess potential impacts of global climate change on ecosystem structure and function at a wide range of spatial scales from landscape to global. This new tool allows us to incorporate transient dynamics and make real time predictions about the patterns of ecological change. MC1 was created by combining physiologically based biogeographic rules defined in the MAPSS model with a modified version of the biogeochemical model, CENTURY. MC1 also includes a fire module, MCFIRE, that mechanistically simulates the occurrence and impacts of fire events.

Abstract (from http://www.srmjournals.org/doi/abs/10.2111/REM-D-13-00079.1):  Big sagebrush,  Artemisia tridentata  Nuttall (Asteraceae), is the dominant plant species of large portions of semiarid western North America. However, much of historical big sagebrush vegetation has been removed or modified. Thus, regeneration is recognized as an important component for land management. Limited knowledge about key regeneration processes, however, represents an obstacle to identifying successful management practices and to gaining greater insight into the consequences of increasing disturbance frequency and global change. Therefore, our objective is to synthesize knowledge about natural big sagebrush regeneration. We identified and characterized the controls of big sagebrush seed production, germination, and establishment. The largest knowledge gaps and associated research needs include quiescence and dormancy of embryos and seedlings; variation in seed production and germination percentages; wet-thermal time model of germination; responses to frost events (including freezing/thawing of soils), CO2  concentration, and nutrients in combination with water availability; suitability of microsite vs. site conditions; competitive ability as well as seedling growth responses; and differences among subspecies and ecoregions. Potential impacts of climate change on big sagebrush regeneration could include that temperature increases may not have a large direct influence on regeneration due to the broad temperature optimum for regeneration, whereas indirect effects could include selection for populations with less stringent seed dormancy. Drier conditions will have direct negative effects on germination and seedling survival and could also lead to lighter seeds, which lowers germination success further. The short seed dispersal distance of big sagebrush may limit its tracking of suitable climate; whereas, the low competitive ability of big sagebrush seedlings may limit successful competition with species that track climate. An improved understanding of the ecology of big sagebrush regeneration should benefit resource management activities and increase the ability of land managers to anticipate global change impacts.

VisTrails is an open-source management and scientific workflow system designed to integrate the best of both scientific workflow and scientific visualization systems. Developers can extend the functionality of the VisTrails system by creating custom modules for bundled VisTrails packages. The Invasive Species Science Branch of the U.S. Geological Survey (USGS) Fort Collins Science Center (FORT) and the U.S. Department of the Interior’s North Central Climate Science Center have teamed up to develop and implement such a module—the Software for Assisted Habitat Modeling (SAHM). SAHM expedites habitat modeling and helps maintain a record of the various input data, the steps before and after processing, and the modeling options incorporated in the construction of an ecological response model. There are four main advantages to using the SAHM:VisTrails combined package for species distribution modeling: (1) formalization and tractable recording of the entire modeling process; (2) easier collaboration through a common modeling framework; (3) a user-friendly graphical interface to manage file input, model runs, and output; and (4) extensibility to incorporate future and additional modeling routines and tools. In order to meet increased interest in the SAHM:VisTrails package, the FORT offers a training course twice a year. The course includes a combination of lecture, hands-on work, and discussion. Please join us and other ecological modelers to learn the capabilities of the SAHM:VisTrails package.

Abstract (from http://onlinelibrary.wiley.com/doi/10.1002/joc.4127/abstract):  Gridded topoclimatic datasets are increasingly used to drive many ecological and hydrological models and assess climate change impacts. The use of such datasets is ubiquitous, but their inherent limitations are largely unknown or overlooked particularly in regard to spatial uncertainty and climate trends. To address these limitations, we present a statistical framework for producing a 30-arcsec (∼800-m) resolution gridded dataset of daily minimum and maximum temperature and related uncertainty from 1948 to 2012 for the conterminous United States. Like other datasets, we use weather station data and elevation-based predictors of temperature, but also implement a unique spatio-temporal interpolation that incorporates remotely sensed 1-km land skin temperature. The framework is able to capture several complex topoclimatic variations, including minimum temperature inversions, and represent spatial uncertainty in interpolated normal temperatures. Overall mean absolute errors for annual normal minimum and maximum temperature are 0.78 and 0.56 °C, respectively. Homogenization of input station data also allows interpolated temperature trends to be more consistent with US Historical Climate Network trends compared to those of existing interpolated topoclimatic datasets. The framework and resulting temperature data can be an invaluable tool for spatially explicit ecological and hydrological modelling and for facilitating better end-user understanding and community-driven improvement of these widely used datasets.

In the North Central U.S., drought is a dominant driver of ecological, economic, and social stress. Drought conditions have occurred in the region due to lower precipitation, extended periods of high temperatures and evaporative demand, or a combination of these factors. This project aimed to improve our understanding of drought in the North Central region and determine what future droughts might look like over the 21st century, as climate conditions change. Researchers evaluated, with the intent to improve, available and emerging data on climate conditions that influence drought (such as changes in temperature, precipitation, evaporative demand, snow and soil moisture), as well as datasets related to the surface water balance (such as evapotranspiration and streamflow). Researchers sought to use these data to identify a range of plausible future climate conditions for the region, known as “scenarios”, to help land managers better understand the threat posed by drought and to plan for its potential impacts. Researchers aimed to make relevant climate datasets available to ecologists and land managers for modeling ecosystem response under different future climate scenarios. This project team is part of the North Central Climate Science Center’s Foundational Science Area Team, which supports foundational research and advice, guidance, and technical assistance to other NC CSC projects as they address climate science challenges that are important for land managers and ecologists in the region.  

In the North Central U.S., temperatures are rising and precipitation patterns are changing, with consequences ranging from more frequent and severe wildfires to prolonged drought to widespread forest pest outbreaks. As a result, land managers are becoming increasingly concerned about how climate change is affecting natural resources and the essential services they provide communities.   The rates and ecological impacts of changing conditions vary across this diverse region, which stretches from the Great Plains to the High Rockies. The goal of this project was to understand how native grasslands, shrublands, and forests will respond to changing conditions. Researchers first modeled how these vegetation types have changed over the past 50 years, then projected how they might change over the next century under different possible future conditions.   Understanding how these native ecosystems may change is critical, particularly in light of the wildlife and communities that depend on them. Species such as the greater sage-grouse, elk, deer, and grizzly bears could lose important habitat if conditions change. Humans could also be impacted – subalpine forests, for example, control snow accumulation and melt, which in turn affect the water supply. The results of this research are meant to be used to support local stakeholders in developing strategies for coping with and adapting to projected changes in vegetation across the North Central region.   This project team is part of the North Central Climate Science Center’s Foundational Science Area Team, which supports foundational research and advice, guidance, and technical assistance to other NC CSC projects as they address climate science challenges that are important for land managers and ecologists in the region.

The north-central region of the U.S. has experienced a series of extreme droughts in recent years, with impacts felt across a range of sectors. For example, the impacts of a 2002 drought are estimated to have resulted in a $3 billion loss to the agricultural sector in Nebraska and South Dakota. Meanwhile, the ecological impacts of drought in the region have included increased tree mortality, surges in the outbreak of pests, and intensifying forest fires.   Located within this region is the Missouri River Basin, an important agricultural production area home to approximately 12 million people, including 28 Native American tribes. Tribal governments and multiple federal agencies manage land and natural resources in the drought-impacted Basin. The goal of this project was to understand how federal and tribal natural resource managers experience and deal with drought in this landscape. To do this, researchers documented how managers perceive drought impacts, how their decisions are affected by these perceptions, and their capacity to respond to and prepare for drought.   This information is expected to enable researchers to determine the types of climate data and tools that will help managers operating under drought conditions. Locally-specific “drought stories” are being developed, detailing historic trends and future projections of drought, as well as the risk perceptions, decisions, and adaptive capacities of local managers. Understanding the different perceptions and impacts of drought felt by managers can help provide a foundation for fostering more collective resource management across the region in the face of future drought. This project team is part of the North Central Climate Science Center’s Foundational Science Area Team, which supports foundational research and advice, guidance, and technical assistance to other NC CSC projects as they address climate science challenges that are important for land managers and ecologists in the region.  

Natural Resource Technical Report NPS/WICA/NRTR—2014/918