From Public Summary: (One of the greatest challenges facing resource managers today is not knowing exactly when, where, and how climate change effects will unfold. In order to plan for this uncertain future, managers have begun to use a tool known as climate change scenario planning, in which data from climate models are used to identify different plausible future climate conditions and their impacts, known as “scenarios,” for a specific area.   In a previous project, we (scientists with the North Central Climate Adaptation Science Center, U.S. Geological Survey, and National Park Service) worked with natural resource managers at Badlands National Park and on surrounding federal and tribal lands to assess how different climate conditions and management activities would affect the area’s resources. To make the results of this work more accessible to managers and the public, the present project produced a National Park Service “Resource Brief” summarizing insights from a scenario planning workshop and an ecological simulation model built specifically for the focus area. The Brief highlights actions that the park can take to address resource management challenges associated with the range of plausible climate futures.   Building on the work at Badlands, we also designed and pilot-tested a process for deeply integrating climate change scenario planning into National Park Service (NPS) Resource Stewardship Strategies. These strategies are part of NPS’s streamlined approach for guiding prioritization of a park’s investments in resource stewardship. The process we designed helped managers at the case study park – Devils Tower National Monument – adjust their resource management goals to be achievable across the range of plausible climate futures, and to prioritize activities that will prepare the park for whatever future climate materializes.   We then documented this integration process as a supplement to standard Resource Stewardship Strategy preparation guidance followed by each park as it develops its Strategy. This allows the lessons learned in this case study to be applied to many other parks across the nation.)  

Abstract: (From: Wiley Online Library) Relative agricultural productivity shocks emerging from climate change will alter regional cropland use. Land allocations are sensitive to crop profits that in turn depend on yield effects induced by changes in climate and technology. We develop and apply an integrated framework to assess the impact of climate change on agricultural productivity and land use for the U.S. Northern Great Plains. Crop‐specific yield‐weather models reveal crop comparative advantage due to differential yield impacts of weather across the region's major crops, i.e., alfalfa, wheat, soybeans and maize. We define crop profits as a function of the weather‐driven yields, which are then used to model land use allocation decisions. This ultimately allows us to simulate the impact of climate change under the RCP4.5 emissions scenario on land allocated to the region's major crops as well as to grass/pasture. Upon removing the trends effects in yields, climate change is projected to lower yields by 33%‐64% over 2031‐’55 relative to 1981–2005, with soybean being the least and alfalfa the most affected crops. Yield projections applied to the land use model at present‐day input costs and output prices reveals that Dakotas’ grass acreage will increase by up to 23%, displacing croplands. Wheat acreage is expected to increase by up to 54% in select south‐eastern counties of North Dakota and South Dakota, where maize/soy acreage had increased by up to 58% during 1995–2016. This article is protected by copyright. All rights reserved

Abstract: (From: https://www.nrs.fs.fed.us/pubs/59158)  Most regions of the United States are projected to experience a higher frequency of severe droughts and longer dry periods as a result of a warming climate. Even if current drought regimes remain unchanged, higher temperatures will interact with drought to exacerbate moisture limitation and water stress. Observations of regional-scale drought impacts and expectations of more frequent and severe droughts prompted a recent state-of-science synthesis (Vose et al. 2016). The current volume builds on that synthesis and provides region-specific management options for increasing resilience to drought for Alaska and Pacific Northwest, California, Hawai‘i and U.S.-Affiliated Pacific Islands, Interior West, Great Plains, Northeast and Midwest, and Southeast.

Introduction (From Parks Stewardship Forum) Managers and scientists widely acknowledge climate change as one of the greatest threats to protected areas in the US and worldwide (Gross et al. 2016). The US National Park Service (NPS) began addressing climate change as early as the 1990s, and in 2010 NPS Director Jonathan Jarvis stated that “climate change is fundamentally the greatest threat to the integrity of our national parks that we have ever experienced” (NPS 2010). Today, parks throughout the NPS system experience impacts of human-caused climate change (e.g., Monahan and Fisichelli 2014; Gonzalez 2018) that threaten iconic park resources. Climate-related impacts include: melting glaciers (e.g., Glacier National Park, Kenai Fjords National Park; Burgess et al. 2013); thermokarst formation effects on archaeological sites (Gates of the Arctic National Park and Preserve; Gagli-oti et al. 2016); loss of Joshua trees (e.g., Joshua Tree National Park; Sweet et al. 2019); and sea-level rise threatening historic lighthouses (e.g., Cape Hatteras National Seashore; Schupp et al. 2015), historic arti-facts (Anderson et al. 2017), and seaside forts (e.g., Dry Tortugas National Park; Schupp et al. 2015). Droughts, heat waves, floods, smoke, and fires associated with increasing temperatures and altered hydrological re-gimes now routinely affect park resources and visitors, and these impacts are in no way unique to US parks—protected area managers worldwide are challenged to rapidly adapt their management to address ongoing and projected climate change.

Public Summary: The NC CASC has established collaborations across DOI agencies, other federal partners, and tribal communities in the north central United States. These collaborations were driven by stakeholder needs to help managers and user respond to and prepare for the impact of climate change to the resources that they manage. Our main goal here was to enhance the collaborative engagement process to facilitate the development of research that informs climate change adaptation planning. We did this by establishing, in collaboration with tribal representatives, guidelines for tribal engagement and supported a number of tribal entities interested in vulnerability assessment and adaptation planning. We also supported regional drought synthesis work with multiple drought researchers, where we identified the types and scales of drought decision-making on public and tribal lands and the obstacles that hindered drought responses. This was useful to identify needs for more regional, collaborative, and anticipatory drought management, as well as understanding local complexities of drought management with broader generalizations about how drought decisions are made in these contexts. We also led a collaborative social-ecological vulnerability assessment with a Colorado BLM field office to inform their assessment and planning efforts. This led to the development of a process and lessons learned for collaborating with BLM and other public land management agencies to produce locally-informed and relevant climate science, which we argue can provide a useful guide for natural resource managers and researchers looking to engage in collaborative projects with these entities on climate-related management issues. The evaluation of the impact and the approaches used by the NC CASC research team to meet stakeholders need and to transmit information from our research efforts concluded that efforts with early engagement provided useable information of diverse and up-to-date science and technology products. Management groups and decision makers developed greater familiarity with approaches codeveloped with research groups. Shortcomings included short duration of project cycles; lack of capacity to deal multiple issues or obje

Abstract from SpringLink: Many western communities are surrounded by public lands that support land-based and local economies. Bureau of Land Management (BLM) decision-making affects the vulnerability of those land-based livelihoods, especially in the context of climate change. We analyzed Colorado BLM planning documents to evaluate how they are considering climate change, sensitive resources, impacts, and land-based livelihoods in their planning processes using both quantitative word counts and qualitative coding. Documents published in recent years (2011–2015) include more mentions of climate change than older documents (1985–1997). However, the review showed that while climate change is discussed within the National Environmental Policy Act (NEPA) planning documents, the final Resource Management Plans contain few mentions of climate change. Further, there is minimal consideration of how climate change may impact land-based livelihoods. These results prompt questions about the planning process, how climate change considerations are integrated into the final documents, and how that impacts on-the-ground management. The review suggests a need for increased consideration of climate change throughout the BLM’s planning process so that landscapes can be managed with more attention and awareness to climate change and the associated impacts to resources and dependent communities.

The USA National Phenology Network (USA-NPN) and the North Central Climate Science Center (NC CSC) seek to enhance scientific understanding of how climate trends and variability are linked to phenology across spatial scales, with the ultimate goal of being able to understand and predict climate impacts on natural resources. A key step towards achieving this long-term goal is connecting local observations (individual plants or animals) of phenology with those at regional to continental scales (10 km to 10,000 km), which may ultimately be used to better understand phenology across ecosystems and landscapes and thereby inform natural resource management. The specific shorter-term goals of this effort are to process and distribute phenology camera (or “phenocam”) products, and to develop a plan for how these products can help meet longer-term goals. 

Dense time series of Landsat 8 and Sentinel-2 imagery are creating exciting new opportunities to monitor, map, and characterize temporal dynamics in land surface properties with unprecedented spatial detail and quality. By combining imagery from the Landsat 8 Operational Land Imager and the MultiSpectral Instrument on-board Sentinel-2A and -2B, the remote sensing community now has access to moderate (10–30 m) spatial resolution imagery with repeat periods of ~3 days in the mid-latitudes. At the same time, the large combined data volume from Landsat 8 and Sentinel-2 introduce substantial new challenges for users. Land surface phenology (LSP) algorithms, which estimate the timing of phenophase transitions and quantify the nature and magnitude of seasonality in remotely sensed land surface conditions, provide an intuitive way to reduce data volumes and redundancy, while also furnishing data sets that are useful for a wide range of applications including monitoring ecosystem response to climate variability and extreme events, ecosystem modelling, crop-type discrimination, and land cover, land use, and land cover change mapping, among others. To support the need for operational LSP data sets, here we describe a continental-scale land surface phenology algorithm and data product based on harmonized Landsat 8 and Sentinel-2 (HLS) imagery. The algorithm creates high quality times series of vegetation indices from HLS imagery, which are then used to estimate the timing of vegetation phenophase transitions at 30 m spatial resolution. We present results from assessment efforts evaluating LSP retrievals, and provide examples illustrating the character and quality of information related to land cover and terrestrial ecosystem properties provided by the continental LSP dataset that we have developed. The algorithm is highly successful in ecosystems with strong seasonal variation in leaf area (e.g., deciduous forests). Conversely, results in evergreen systems are less interpretable and conclusive.

Monitoring vegetation phenology is critical for quantifying climate change impacts on ecosystems. We present an extensive dataset of 1783 site-years of phenological data derived from PhenoCam network imagery from 393 digital cameras, situated from tropics to tundra across a wide range of plant functional types, biomes, and climates. Most cameras are located in North America. Every half hour, cameras upload images to the PhenoCam server. Images are displayed in near-real time and provisional data products, including timeseries of the Green Chromatic Coordinate (Gcc), are made publicly available through the project web page (https://phenocam.sr.unh.edu/webcam/gallery/). Processing is conducted separately for each plant functional type in the camera field of view. The PhenoCam Dataset v2.0, described here, has been fully processed and curated, including outlier detection and expert inspection, to ensure high quality data. This dataset can be used to validate satellite data products, to evaluate predictions of land surface models, to interpret the seasonality of ecosystem-scale CO2 and H2O flux data, and to study climate change impacts on the terrestrial biosphere.