Spring phenology of temperate ecosystems is highly sensitive to climate change, generating various impacts on many important terrestrial surface biophysical processes. Although various prognostic models relying on environmental variables of temperature and photoperiod have been developed for spring phenology, comprehensive ecosystem-scale evaluations over large landscapes and long-time periods remain lacking. Further, environmental variables other than temperature and photoperiod might also importantly constrain spring phenology modelling but remain under-investigation. To address these issues, we leveraged around 20-years datasets of environmental variables (from Daymet and GLDAS products) and the spring phenology metric (i.e., the greenup date) respectively derived from MODIS and PhenoCams across 108 sites in the Northern and Eastern United States. We firstly cross-compared MODIS-derived greenup date with official PhenoCams product with high accuracy (R2 = 0.70). Then, we evaluated the three prognostic models (i.e., Growing Degree Date (GDD), Sequential (SEQ) and optimality-based (OPT)) with MODIS-derived spring phenology, assessed the model residuals and their associations with soil moisture, rainfall, and solar radiation, and revised the two photoperiod-relevant models (SEQ, OPT) by replacing the daylength variable with solar radiation, which was found to contribute the most to model residuals. We found that 1) all models demonstrated good capability in characterizing spring phenology, with OPT performing the best (RMSE = 8.04 ± 5.05 days), followed by SEQ (RMSE = 10.57 ± 7.77 days) and GDD (RMSE = 10.84 ± 8.42 days), 2) all models displayed high model residuals showing tight correlation with solar radiation (r = 0.45–0.75), and 3) the revised models that included solar radiation significantly performed better with an RMSE reduction by 22.08%. Such results are likely because solar radiation better constrains early growing season plant photosynthesis than photoperiod, supporting the hypothesis of spring phenology as an adaptive strategy to maximize photosynthetic carbon gain (approximated by solar radiation) while minimizing frost damage risk (captured by temperature). Collectively, our study reveals the underappreciated importance of solar radiation in constraining spring phenology of temperate ecosystems, and suggests ways to improve spring phenology modelling and other phenology-related ecological processes.

The North Central Regional Invasive Species and Climate Change (NC RISCC) network includes >100 members working at the nexus of climate change and invasive species. In late 2021, the NC RISCC leadership team surveyed regional practitioners working on issues related to invasive species management to understand their priorities and practices. Survey participants represented a variety of entities, with the most representation from: county government, academia/universities, federal government, non-governmental organizations (NGOs), and state government. They also represented all seven states in the NC region: CO, WY, MT, ND, SD, KS, and NE. Key findings include: Many practitioners in the NC RISCC network report having at least a moderate understanding of the interactions between climate change and invasive species and sometimes integrate climate change information into their invasive species management work. Major barriers to incorporation of climate change information into invasive species management include time, funding, and capacity. Practitioners spend most of their time on current invasive species (as opposed to future potential invasive species), which is reflected in the common species of interest. Practitioners rank native community resilience, environmental degradation, and range shifting species (researchers) or agricultural production (managers) as top priorities for invasive species management and research in a changing climate. Practitioners tend to use different scientific products depending on whether they are primarily a researcher or a manager, but both groups regularly use scientific literature.

The objectives of the North Central RISCC are to: connect researchers, managers, and other stakeholders to conduct priority research including synthesizing existing information, and to ultimately reduce the impacts of invasive species in a changing climate. On April 6th and 7th 2022, the NC RISCC held its first Science Integration Workshop, aiming to build regional and national connections, increase interest in the network, and showcase local work in management and research. This workshop, held virtually, helped establish and connect the community, raise awareness, and bridge the invasive species and climate change fields.

Successful conservation of ecosystems in a changing climate requires actionable research that directly supports the rethinking and revising of management approaches to address changing risks and opportunities. As an important first step toward actionable research, we reviewed and synthesized grassland management-related documents to identify broadly shared questions that, if answered, would help to support collective conservation of the grasslands in the northern Great Plains of the United States in a changing climate. A Management Priorities Working Group reviewed 183 grassland-relevant management documents and identified 70 questions. Feedback was iteratively provided by a Climate and Ecology Working Group, an Advisory Committee, and representatives from grassland management agencies and organizations. The identified questions generally fall under 15 topics: land conversion; restoration; disturbance regimes; woody encroachment; herbaceous invasives; grazing; water quality, quantity, and availability; animal species; private land; public understanding; legal and policy changes; economic incentives; coordination across management entities; accessibility of science and tools; and novel ways of thinking. These questions can inform a research agenda for researchers looking to conduct actionable science in the Great Plains grassland ecosystems. Both the approach and the questions presented here can also be adapted and applied in other regions and ecosystems.

Tribal Partnership Science (TPS) is a rapidly growing field that brings together biophysical and social scientists, federally recognized tribes, and federal land management agencies. TPS is essential for addressing complex environmental challenges facing tribes and their homelands. In recent years, a proliferation of methods, frameworks, and guidance for TPS has emerged from diverse scientific disciplines, geographies, and management contexts. This has made it difficult for scientists to keep up with the latest developments and to apply them effectively. This project will synthesize, pragmatize, and tailor the science-to-date for TPS in the contiguous United States (CONUS). Specifically, we will produce a cohesive set of manuscripts addressing the following topics: Preconditions for programmatic level actualization of indigenous knowledge in management settings A coevolutionary approach to co-stewardship between tribes and land management within which IK and WS can be more effectively bridged Roadmap of methods for bridging indigenous knowledge and western science Ethical guidance for TPS These end-user-oriented manuscripts will be published and further disseminated through public presentations and networking with the Bureau of Indian Affairs (BIA) and other relevant agencies. This project will make a significant contribution to the field of TPS by providing scientists with the tools and knowledge they need to apply TPS effectively. The project will also help to build capacity for TPS within the Department of the Interior (DOI) to better meet the needs of tribes, tribal lands, and our federal lands at large.

Indigenous Knowledge (IK) is increasingly involved in the contemporary management of natural resources. Tribal wildlife management programs in the United States may be uniquely positioned to effectively and ethically integrate their IK. While a narrow focus on the body of IK and a particular management activity may suffice for project-level integration efforts, herein we consider how IK integration at the programmatic level may be best supported. We propose a holistic conceptual framework of preconditions including sovereignty, the North American Model management, funding, cultural resources, stakeholder support, and programmatic leadership. We assess the current status and common challenges with each precondition and illustrate their potential roles for a more lasting and pervasive integration of IK into tribal wildlife management programs.    

Accurate characterization of plant phenology is of great importance for monitoring global carbon, water, and energy cycling. Remotely sensed satellite observations have been widely used to estimate land surface phenology across multiple spatial scales in the last three decades. Recent development on satellite solar-induced chlorophyll fluorescence (SIF) observations have opened an opportunity to monitor the seasonality of plant growth from the perspective of photosynthesis phenology. The SIF observations from the TROPOspheric Monitoring Instrument (TROPOMI) with high spatial resolution (up to 7 km × 3.5 km pixels) and near-daily global coverage provide unprecedented opportunity to observe photosynthetic and land surface phenology from space. However, the performance of TROPOMI SIF-derived phenology has not been systematically evaluated. In this study, we used flux tower gross primary productivity (GPP) and PhenoCam green chromatic coordinate (Gcc) data as the benchmark to verify phenology metrics derived from satellite observations. The phenology metrics including the start (SOS), end (EOS), length of growing season (LOS), and the peak of growing season (POS) were estimated from TROPOMI SIF, normalized difference vegetation index (NDVI), enhanced vegetation index (EVI), near‐infrared reflectance of vegetation (NIRv), and Global Vegetation Phenology product (MCD12Q2), and the latter four were obtained from the Moderate Resolution Imaging Spectroradiometer (MODIS) across six vegetation types over North America during the period of 2018–2020. We found that the overall agreements of SIF (R2 ranging from 0.30 to 0.63) against GPP-estimated phenology were stronger than NDVI (0.17–0.41), EVI (0.19–0.39), NIRv (0.23–0.62), and MCD12Q2 (0.19–0.48) derived phenological events. In reference to GPP and Gcc-estimated phenology, SIF also generally has the least error and bias compared to other satellite remote sensing-derived phenology metrics. No significant differences were found between SIF and GPP-derived phenology (P>0.05, two-tailed t-test). In addition, we found that the spatial distribution of SIF-derived phenology reflected the expected latitudinal patterns in phenology dates. SOS, EOS, LOS, and POS observed by MCD12Q2 appeared to be earlier, later, longer, and earlier than TROPOMI SIF-derived phenology, respectively. SIF-based phenological transition dates more closely tracked GPP-based phenology dates, indicating TROPOMI SIF could be a great measure to track photosynthesis seasonality and land surface phenology.    

Forest ecosystems play a major role in sequestering atmospheric carbon dioxide, which can help offset the detrimental effects of anthropogenic carbon emissions. However, climate change has and will continue to affect the phenology of forest ecosystems’ carbon uptake, changing both the “carbon uptake transition date” - when forests shift from being a net carbon source to sink - and the “green-up date” reflecting the onset of bud burst. Previous studies have shown that a forest's carbon uptake transition date correlates to the date when soil temperature warms enough to surpass mean annual air temperature (soil-air temperature model). However, we still don't know if this simple relationship holds across different sites or over longer time periods. In this study, we explore the relationship between climate and both types of phenological transition dates using over 200 site years of data between 1997 and 2022. Using flux tower data from 18 sites across North America and Europe, we derive three potential carbon uptake transition dates corresponding to the dates when 10%, 25%, and 50% of seasonal net ecosystem exchange (NEE) amplitude is reached. Using PhenoCam data, we then derive three potential green-up dates corresponding to when 10%, 25%, and 50% of total seasonal green chromatic coordinate (GCC) is reached (the greenness model). We evaluate our model estimates using concordance coefficients, a metric of agreement between two measures, to determine which process, carbon uptake or budburst, is best predicted by the soil-air temperature model and to what extent. We find that variation in phenological relationships can be attributed to different regional and bioclimatic groups, highlighting potential biome-specific strengths and limitations of the soil-air temperature model. This model offers a simple approach to better understand phenological transitions and identify potential and limitations for a simple universal SOS prediction approach in deciduous forests.

Invasion Potential: The unrealized distribution of invasive species that may occur with future climate conditions. Here the term is used to describe both 1) the potential for an invasive species to invade and 2) the potential for an environment to be invaded. Summary: As Earth’s climate changes, it alters the characteristics of ecosystems which can stress native species, increasing a community’s susceptibility to novel invasions. This can increase the invasion potential of an invasive plant species or region. Whether or not the invasion potential is realized depends on several factors including species interactions (which are difficult to quantify) and the traits of the invasive and native species in the community. Climate and species distribution models can be used to predict invasion potential, and these predictions can inform management decisions to help protect ecosystems from invasive plant species. This management challenge will overview two species specific examples of invasion potential, then outline some general strategies for better management.