As pressures from climate change and other anthropogenic stressors, like invasive species, increase, new challenges arise for natural resource managers who are responsible for the health of public lands. One of the greatest challenges these managers face is that the traditional way of managing resources might not be as effective, or in some cases might be ineffective, in light of transformational ecological impacts that exist at the intersection of society and ecosystems. Thus, managers are struggling to understand how they should be managing shared natural resources and landscapes in this new era. This project studies the decision-making process of federal land managers to illuminate how decisions are being navigated and what strategies managers are developing to address challenges. To examine this issue, the project will use a comparative case study design focused on the Kenai Peninsula in Alaska and the East Jemez Landscape in New Mexico, both of which are experiencing transformational ecological change and related management challenges. The project uses semi-structured interviews with natural resource managers from both case study sites to identify important factors shaping manager decision making and to explain factors that differ between them. For instance, how are managers’ choice of strategies influenced by the agency to which they belong? This research will contribute to a new climate adaptation and conservation knowledge base and offer information about how decisions are currently being made on public lands. The findings will help support public land management and conservation efforts and inform researchers as to what type of science would be most usable for managers tackling ecological transformation.

Maintaining the native prairie lands of the Northern Great Plains (NGP), which provide an important habitat for declining grassland species, requires anticipating the effects of increasing atmospheric carbon dioxide (CO2) concentrations and climate change on the region’s vegetation. Specifically, climate change threatens NGP grasslands by increasing the potential encroachment of native woody species into areas where they were previously only present in minor numbers. This project used a dynamic vegetation model to simulate vegetation type (grassland, shrubland, woodland, and forest) for the NGP for a range of projected future climates and relevant management scenarios. Comparing results of these simulations illustrates the sensitivity of woody encroachment projections to climate change factors. Improved understanding of the effects of increasing CO2, climate change, and land management practices on potential woody encroachment will be used to guide management practices to be most effective in protecting grassland habitat in the NGP into the future.

Throughout western North America, warming associated with climate change is leading to both earlier spring peak streamflows and earlier seed dispersal, potentially reducing seedling establishment and in turn reducing the quality of riparian (near-river) forests, which provide critical habitat for diverse birds, mammals, reptiles, amphibians, and insects, and food and shade for fish and other aquatic animals. This project aimed to predict these effects of climate change on cottonwood and willow tree regeneration in western forests by linking models of seed dispersal timing, streamflow hydrology, and seedling establishment, focusing on the upper South Platte River Basin as a study area. Results are expected to help land managers anticipate future changes in riparian wildlife habitat quality, and potentially to respond to these changes by actively re-vegetating high-priority areas, or by working with water management agencies to schedule dam releases that favor cottonwood and willow establishment.

This data set contains output from the dynamic vegetation model MC1, as modified to simulate future woody encroachment in the northern Great Plains, for 23 monthly variables, 63 yearly variables, and 31 multi-year variables. Variables include simulated plant (by growth form) and soil carbon stocks, net primary production, vegetation type, potential and actual evapotranspiration, stream flow, and fuel mass and moisture. Model output is provided for the EQ, Spinup, Historical, and Future stages of MC1 runs; future stages were run for four climate projections crossed with 10 or 11 fire X grazing X CO2 concentration scenarios for the western and eastern portions of the study area, respectively.

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.

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.

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

The U.S. Northern Rocky Mountains support a large number of native wildlife species, and survival of these populations depends on connected landscapes to support current migration and dispersal, as well as future shifts in species’ ranges. However, habitat fragmentation and loss threaten these connections. Land and wildlife managers across the U.S. are faced with decisions focused on reducing risks, like those from habitat fragmentation, to wildlife, ecosystems, and landscapes. Establishing connections between natural landscapes is a frequently recommended strategy for these managers to help wildlife adapt to changing conditions. Working in partnership with state and federal resource managers and private land trusts, this project sought to 1) understand how future climate change may alter habitat composition of landscapes that are expected to serve as important connections for wildlife, 2) understand how wildlife species of concern are expected to respond to changing conditions, 3) develop strategies to help stakeholders manage public and private lands in ways that allow wildlife to continue to move in response to changing conditions, and 4) explore how well existing management plans and conservation efforts are expected to support crucial connections for wildlife under climate change.   

The conversion of grassland to cropland in the Dakotas could imperil wildlife such as nesting waterfowl and contribute to the degradation of water quality in the Mississippi River watershed. However, high crop prices in recent years have contributed to a high rate of grassland to cropland conversion on private lands. In addition to these economic factors, changes in climate could exacerbate the challenge of protecting grasslands, as conditions may become more amenable to row crop production.   The goal of this project was to work with grassland conservation managers to better target the use of funds allocated toward incentivizing grassland preservation in the Dakotas. Researchers identified the vulnerability of crop production to climate change, assessed the likelihood of grassland conversion to cropping, and calculated the costs of protecting grasslands under different future economic and climate scenarios.   Working with land conservation managers, researchers aimed to use these results to identify land parcels where grassland conservation investments would be most effective. For example, researchers aimed to develop a land conversion choice calculator that will compare long-run expected returns from different land uses under alternative climate and economic scenarios. By developing tools such as the land conversion choice calculator, this project is designed to help inform a critical component of grassland conservation – deciding which parcels to target for protection.