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At least 181 records · Page 10

Evidence-based target setting informs blue carbon strategies for nationally determined contributions

The magnitude and pace of global climate change demand ambitious and effective implementation of nationally determined contributions (NDCs). Nature-based solutions present an efficient approach to achieving mitigation, adaptation and resilience goals. Yet few nations have quantified the diverse benefits of nature-based solutions to evaluate and select ecosystem targets for their NDCs. Here we report on Belize’s pursuit of innovative, evidence-based target setting by accounting for multiple benefits of blue carbon strategies. Through quantification of carbon storage and sequestration and optimization of co-benefits, we explore time-bound targets and prioritize locations for mangrove protection and restoration. We find increases in carbon benefits with larger mangrove investments, while fisheries, tourism and coastal risk-reduction co-benefits grow initially and then plateau. We identify locations, currently lacking protected status, where prioritizing blue carbon strategies would provide the greatest delivery of co-benefits to communities. These findings informed Belize’s updated NDCs to include an additional 12,000 ha of mangrove protection and 4,000 ha of mangrove restoration, respectively, by 2030. Our study serves as an example for the more than 150 other countries that have the opportunity to enhance greenhouse gas sequestration and climate adaptation by incorporating blue carbon strategies that provide multiple societal benefits into their NDCs.

54 ENVIRONMENTAL SCIENCES↗

Large Trees Dominate Carbon Storage in Forests East of the Cascade Crest in the United States Pacific Northwest

Large-diameter trees store disproportionally massive amounts of carbon and are a major driver of carbon cycle dynamics in forests worldwide. In the temperate forests of the western United States, proposed changes to Forest Plans would significantly weaken protections for a large portion of trees greater than 53 cm (21 inches) in diameter (herein referred to as “large-diameter trees”) across 11.5 million acres (~4.7 million ha) of National Forest lands. This study is among the first to report how carbon storage in large trees and forest ecosystems would be affected by a proposed policy. We examined the proportion of large-diameter trees on National Forest lands east of the Cascade Mountains crest in Oregon and Washington, their contribution to overall aboveground carbon (AGC) storage, and the potential reduction in carbon stocks resulting from widespread harvest. We analyzed forest inventory data collected on 3,335 plots and found that large trees play a major role in the accumulated carbon stock of these forests. Tree AGC (kg) increases sharply with tree diameter at breast height (DBH; cm) among five dominant tree species. Large trees accounted for 2.0 to 3.7% of all stems (DBH ≥ 1” or 2.54 cm) among five tree species; but held 33 to 46% of the total AGC stored by each species. Pooled across the five dominant species, large trees accounted for 3% of the 636,520 trees occurring on the inventory plots but stored 42% of the total AGC. A recently proposed large-scale vegetation management project that involved widespread harvest of large trees, mostly grand fir, would have removed ~44% of the AGC stored in these large-diameter trees, and released a large amount of carbon dioxide to the atmosphere. Given the urgency of keeping additional carbon out of the atmosphere and continuing carbon accumulation from the atmosphere to protect the climate system, it would be prudent to continue protecting ecosystems with large trees for their carbon stores, and also for their co-benefits of habitat for biodiversity, resilience to drought and fire, and microclimate buffering under future climate extremes.

21-inch rule↗

A Comprehensive Framework for Valuation of Ecosystem Services in the Context of Hydropower

While models to value ecosystem services exist, they suffer from a lack of “portability” in the sense that a single modelling framework developed for one site cannot be imported and applied to another. Additionally, benefit estimations are often fragmented, incomplete, incomparable, and in heterogenous metrics, thus preventing aggregation to arrive at one comprehensive value. In the context of hydropower, the methods, as well as the metrics used to value the associated ecosystem services, vary between stakeholders (e.g., competing water users, agencies, etc.), detracting from the ability to assess the total value of a hydropower project, water management schemes, or comparing value between competing water users. Further, current methods to value water neglect non-market ecosystem services’ values by failing to account for externalities, resulting in misallocation of costs (e.g., obligatory stakeholder payments for water use) and misinterpretation of hydropower benefits. The benefit-cost ratios in hydropower development are often incomplete because non-market benefits are excluded (e.g., benefits, such as fish habitat resiliency and agricultural water reliability, derived from hydropower development). An approach to enable consistent, standardized hydropower benefit-cost analyses does not currently exist. This paper conceptualizes a methodology to standardize ecosystem services valuation in the context of hydropower projects through the integration of the U.S. Environmental Protection Agency’s existing Final Ecosystem Goods and Services Classification System framework and economic valuation techniques, and demonstrates the applicability of this methodology through a limited proof-of-concept application (the New Waddell Plant, a pumped hydroelectric energy storage facility in Phoenix, AZ). The beauty of our proposed framework lies in its ability to be imported and applied to any other pumped storage facility after accounting for site-specific features.

13 HYDRO ENERGY↗

Long-Term Persistence of Three Microbial Wildfire Biomarkers in Forest Soils

Long-term monitoring of microbial communities in the rhizosphere of post-fire forests is currently one of the key knowledge gaps. Knowing the time scale of the effects is indispensable to aiding post-fire recovery in vulnerable woodlands, including holm oak forests, that are subjected to a Mediterranean climate, as is the case with forests that are found in protected areas such as the Sierra Nevada National and Natural Park in southeastern Spain. We took rhizosphere soil samples from burned and unburned holm oak trees approximately 3, 6, and 9 years after the 2005 fire that devastated almost 3500 ha in southeastern Spain. We observed that the prokaryotic communities are recovering but have not yet reached the conditions observed in the unburned forest. A common denominator between this fire and other fires is the long-term persistence of three ecosystem recovery biomarkers—specifically, higher proportions of the genera Arthrobacter, Blastococcus, and Massilia in soil microbial communities after a forest fire. These pyrophilous microbes possess remarkable resilience against adverse conditions, exhibiting traits such as xerotolerance, nitrogen mineralization, degradation of aromatic compounds, and copiotrophy in favorable conditions. Furthermore, these biomarkers thrive in alkaline environments, which persist over the long term following forest fires. The relative abundance of these biomarkers showed a decreasing trend over time, but they were still far from the values of the control condition. In conclusion, a decade does not seem to be enough for the complete recovery of the prokaryotic communities in this Mediterranean ecosystem.

54 ENVIRONMENTAL SCIENCES↗

Atmospheric methane consumption in arid ecosystems acts as a reverse chimney and is accelerated by plant-methanotroph biomes

Drylands cover one-third of the Earth’s surface and are one of the largest terrestrial sinks for methane. Understanding the structure–function interplay between members of arid biomes can provide critical insights into mechanisms of resilience toward anthropogenic and climate-change-driven environmental stressors—water scarcity, heatwaves, and increased atmospheric greenhouse gases. This study integrates in situ measurements with culture-independent and enrichment-based investigations of methane-consuming microbiomes inhabiting soil in the Anza-Borrego Desert, a model arid ecosystem in Southern California, United States. The atmospheric methane consumption ranged between 2.26 and 12.73 μmol m 2 h −1 , peaking during the daytime at vegetated sites. Metagenomic studies revealed similar soil-microbiome compositions at vegetated and unvegetated sites, with Methylocaldum being the major methanotrophic clade. Eighty-four metagenome-assembled genomes were recovered, six represented by methanotrophic bacteria (three Methylocaldum , two Methylobacter , and uncultivated Methylococcaceae ). The prevalence of copper-containing methane monooxygenases in metagenomic datasets suggests a diverse potential for methane oxidation in canonical methanotrophs and uncultivated Gammaproteobacteria. Five pure cultures of methanotrophic bacteria were obtained, including four Methylocaldum . Genomic analysis of Methylocaldum isolates and metagenome-assembled genomes revealed the presence of multiple stand-alone methane monooxygenase subunit C paralogs, which may have functions beyond methane oxidation. Furthermore, these methanotrophs have genetic signatures typically linked to symbiotic interactions with plants, including tryptophan synthesis and indole-3-acetic acid production. Based on in situ fluxes and soil microbiome compositions, we propose the existence of arid-soil reverse chimneys, an empowered methane sink represented by yet-to-be-defined cooperation between desert vegetation and methane-consuming microbiomes.

59 BASIC BIOLOGICAL SCIENCES↗

Landscape fragmentation overturns classical metapopulation thinking

Habitat loss and isolation caused by landscape fragmentation represent a growing threat to global biodiversity. Existing theory suggests that the process will lead to a decline in metapopulation viability. However, since most metapopulation models are restricted to simple networks of discrete habitat patches, the effects of real landscape fragmentation, particularly in stochastic environments, are not well understood. To close this major gap in ecological theory, we developed a spatially explicit, individual-based model applicable to realistic landscape structures, bridging metapopulation ecology and landscape ecology. This model reproduced classical metapopulation dynamics under conventional model assumptions, but on fragmented landscapes, it uncovered general dynamics that are in stark contradiction to the prevailing views in the ecological and conservation literature. Notably, fragmentation can give rise to a series of dualities: a) positive and negative responses to environmental noise, b) relative slowdown and acceleration in density decline, and c) synchronization and desynchronization of local population dynamics. Furthermore, counter to common intuition, species that interact locally (“residents”) were often more resilient to fragmentation than long-ranging “migrants.” This set of findings signals a need to fundamentally reconsider our approach to ecosystem management in a noisy and fragmented world.

54 ENVIRONMENTAL SCIENCES↗

Summary: Nuclear Energy Critical Material Waste Reduction and Supply Chain Solutions Enabled by Advanced Manufacturing

In September 2020, the U.S. government issued an executive order to address the threat to the domestic supply chain from its reliance on critical minerals (CMs) from foreign competitors and to support the domestic mining and processing industry. A national strategy on CMs with impact on the U.S. Department of Energy’s (DOE’s) vision for 2021–2031 was developed. This vision embraces science and technology to re-establish U.S. competitiveness in the CM and material supply chains by (a) scientific innovation and technologies to ensure resilient and secure CMs and maintain a domestic material supply chain, (b) building a long-term minerals and materials innovation ecosystem to foster new capabilities to mitigate CM supply chain challenges, (c) increasing private sector adoption for sustaining the domestic CM supply chain, and (d) coordinating with international partners and federal agencies to diversify global supply chains and ensure the adoption of best practices for sustainable mining and processing (DOE 2021).

36 MATERIALS SCIENCE↗

Predicting Biomass Yields of Advanced Switchgrass Cultivars for Bioenergy and Ecosystem Services Using Machine Learning

The production of advanced perennial bioenergy crops within marginal areas of the agricultural landscape is gaining interest due to its potential to sustainably produce feedstocks for biofuels and bioproducts while also improving the sustainability and resilience of commodity crop production. However, predicting the biomass yields of this production system is challenging because marginal areas are often relatively small and spread around agricultural fields and are typically associated with various abiotic conditions that limit crop production. Machine learning (ML) offers a viable solution as a biomass yield prediction tool because it is suited to predicting relationships with complex functional associations. The objectives of this study were to (1) evaluate the accuracy of commonly applied ML algorithms in agricultural applications for predicting the biomass yields of advanced switchgrass cultivars for bioenergy and ecosystem services and (2) determine the most important biomass yield predictors. Datasets on biomass yield, weather, land marginality, soil properties, and agronomic management were generated from three field study sites in two U.S. Midwest states (Illinois and Iowa) over three growing seasons. The ML algorithms evaluated in the study included random forests (RFs), gradient boosting machines (GBMs), artificial neural networks (ANNs), K-neighbors regressor (KNR), AdaBoost regressor (ABR), and partial least squares regression (PLSR). Coefficient of determination (R 2 ) and mean absolute error (MAE) were used to evaluate the predictive accuracy of the tested algorithms. Results showed that the ensemble methods, RF (R 2 = 0.86, MAE = 0.62 Mg/ha), GBM (R 2 = 0.88, MAE = 0.57 Mg/ha), and GBM (R 2 = 0.78, MAE = 0.66 Mg/ha), were the most accurate in predicting biomass yields of the Independence, Liberty, and Shawnee switchgrass cultivars, respectively. This is in agreement with similar studies that apply ML to multi-feature problems where traditional statistical methods are less applicable and datasets used were considered to be relatively small for ANNs. Consistent with previous studies on switchgrass, the most important predictors of biomass yield included average annual temperature, average growing season temperature, sum of the growing season precipitation, field slope, and elevation. This study helps pave the way for applying ML as a management tool for alternative bioenergy landscapes where understanding agronomic and environmental performance of a multifunctional cropping system seasonally and interannually at the sub-field scale is critical.

09 BIOMASS FUELS↗

Nurseries Best Practices Guide for Energy and Water Efficiency, Renewable Energy, and Resilience

This guide is a compilation of energy and water efficiency, renewable energy, and resilience best practices at United States Forest Service (USFS) nurseries and seed extractory facilities. The Forest Service Nursery System supports the agency’s mission to restore and retain ecosystem health throughout its 193-million acres and ensures the future of biological diversity on federal lands. This guide was developed in partnership with the U.S. Department of Energy’s (DOE’s) National Renewable Energy Laboratory (NREL) and is based on pilot analyses at two western nurseries.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Climate Drives Modeled Forest Carbon Cycling Resistance and Resilience in the Upper Great Lakes Region, USA

Forests dominate the global terrestrial carbon budget, but their ability to continue doing so in the face of a changing climate is uncertain. A key uncertainty is how forests will respond (resistance) and recover from (resilience) to rising levels of disturbance of varying intensities. This knowledge gap can optimally be addressed by integrating manipulative field experiments with ecophysiological modeling. We used the ED-2.2 model to project carbon fluxes for a northern temperate deciduous forest subjected to a real-world disturbance severity manipulation experiment. ED-2.2 was run for 150 years, starting from near bare ground in 1900, and subjected to three disturbance treatments under an ensemble of climate conditions. Both disturbance severity and climate strongly affected carbon fluxes, and interacted with one another. We then calculated metrics of functional ecosystem stability. Modeled gross primary production exhibited a mean resistance of -0.13, -0.23, and -0.42 (unitless) in response to increasing disturbance severity of 45%, 65%, and 85% mortality, respectively; and resilience of 0.002, 0.004, 0.008 (yr-1) respectively. This pattern held true for other carbon fluxes, meaning that in general simulated GPP declined more initially but recovered more quickly from higher mortality. Notably, however, heterotrophic respiration responded more slowly to disturbance, and its highly variable response was affected by different drivers. This work provides insight into how future conditions might affect the functional stability of mature forests in this region under ongoing climate change and changing disturbance regimes.

54 ENVIRONMENTAL SCIENCES↗

Roadmap for the future of extreme wildfire events

Background Extreme wildfire events (EWEs) represent a growing threat globally, posing substantial risks to ecosystems, human communities, and infrastructure. Despite increased recognition of their ecological, social, and economic significance, current definitions of EWEs vary widely, reflecting disciplinary biases and regional contexts. This article emerges from an interdisciplinary workshop convened to reassess and refine the definition of EWEs, examine their impacts across ecological and social dimensions, and identify critical knowledge gaps impeding our understanding of these infrequent but important events. Results Our synthesis highlights significant limitations with existing definitions, particularly their reliance on subjective thresholds and their emphasis on extreme fire behavior alone. EWEs encompass a spectrum of complex, multi-dimensional phenomena that extend beyond immediate biophysical characteristics to include cumulative social, economic, and ecological impacts. These impacts often manifest over extended timeframes and include hazardous environmental contamination, severe geomorphic disturbances, ecosystem transformations, and unintended consequences of post-fire management actions. Current wildfire modeling frameworks inadequately capture these compounding factors, particularly the interactions among social systems, ecological conditions, and extreme fire behavior. To overcome these issues, we advocate for an interdisciplinary and context-sensitive approach to defining and studying EWEs. This revised definition emphasizes wildfires exhibiting anomalies in fire behavior, ecological outcomes, or social impacts relative to historically observed baselines, accommodating variability across different geographic regions and ecological settings. Conclusions Adopting an interdisciplinary framework that integrates biophysical and social sciences will enhance the predictive capability of wildfire models and improve resilience planning and response strategies. Filling identified knowledge gaps—such as limited high-quality empirical fire behavior data and insufficient integration of social dynamics into modeling—will better prepare communities and ecosystems to cope with and adapt to EWEs. This inclusive approach underscores the necessity for collaboration across disciplines and sectors, essential to managing extreme wildfires in an era of increasing climatic and ecological uncertainty.

54 ENVIRONMENTAL SCIENCES↗

A multi-algorithm approach for modeling coastal wetland eco-geomorphology

Coastal wetlands play an important role in the global water and biogeochemical cycles. Climate change makes it more difficult for these ecosystems to adapt to the fluctuation in sea levels and other environmental changes. Given the importance of eco-geomorphological processes for coastal wetland resilience, many eco-geomorphology models differing in complexity and numerical schemes have been developed in recent decades. However, their divergent estimates of the response of coastal wetlands to climate change indicate that substantial structural uncertainties exist in these models. To investigate the structural uncertainty of coastal wetland eco-geomorphology models, we developed a multi-algorithm model framework of eco-geomorphological processes, such as mineral accretion and organic matter accretion, within a single hydrodynamics model. The framework is designed to explore possible ways to represent coastal wetland eco-geomorphology in Earth system models and reduce the related uncertainties in global applications. We tested this model framework at three representative coastal wetland sites: two saltmarsh wetlands (Venice Lagoon and Plum Island Estuary) and a mangrove wetland (Hunter Estuary). Through the model–data comparison, we showed the importance of using a multi-algorithm ensemble approach for more robust predictions of the evolution of coastal wetlands. We also found that more observations of mineral and organic matter accretion at different elevations of coastal wetlands and evaluation of the coastal wetland models at different sites in diverse environments can help reduce the model uncertainty.

58 GEOSCIENCES↗

Linking soil phosphorus with forest litterfall resistance and resilience to cyclone disturbance: A pantropical meta-analysis

While tropical cyclone regimes are shifting with climate change, the mechanisms underpinning the resistance (ability to withstand disturbance-induced change) and resilience (capacity to return to pre-disturbance reference) of tropical forest litterfall to cyclones remain largely unexplored pantropically. Single-site studies in Australia and Hawaii suggest that litterfall on low-phosphorus (P) soils is more resistant and less resilient to cyclones. Here, we conducted a meta-analysis to investigate the pantropical importance of total soil P in mediating forest litterfall resistance and resilience to 22 tropical cyclones. We evaluated cyclone-induced and post-cyclone litterfall mass (g/m 2 /day), and P and nitrogen (N) fluxes (mg/m 2 /day) and concentrations (mg/g), all indicators of ecosystem function and essential for nutrient cycling. Across 73 case studies in Australia, Guadeloupe, Hawaii, Mexico, Puerto Rico, and Taiwan, total litterfall mass flux increased from ~2.5 ± 0.3 to 22.5 ± 3 g/m 2 /day due to cyclones, with large variation among studies. Litterfall P and N fluxes post-cyclone represented ~5% and 10% of the average annual fluxes, respectively. Post-cyclone leaf litterfall N and P concentrations were 21.6 ± 1.2% and 58.6 ± 2.3% higher than pre-cyclone means. Mixed-effects models determined that soil P negatively moderated the pantropical litterfall resistance to cyclones, with a 100 mg P/kg increase in soil P corresponding to a 32% to 38% decrease in resistance. Based on 33% of the resistance case studies, total litterfall mass flux reached pre-disturbance levels within one-year post-disturbance. A GAMM indicated that soil P, gale wind duration and time post-cyclone jointly moderate the short-term resilience of total litterfall, with the nature of the relationship between resilience and soil P contingent on time and wind duration. Across pantropical forests observed to date, our results indicate that litterfall resistance and resilience in the face of intensifying cyclones will be partially determined by total soil P.

59 BASIC BIOLOGICAL SCIENCES↗

The effect of increasing temperature on crop photosynthesis: from enzymes to ecosystems

Abstract As global land surface temperature continues to rise and heatwave events increase in frequency, duration, and/or intensity, our key food and fuel cropping systems will likely face increased heat-related stress. A large volume of literature exists on exploring measured and modelled impacts of rising temperature on crop photosynthesis, from enzymatic responses within the leaf up to larger ecosystem-scale responses that reflect seasonal and interannual crop responses to heat. This review discusses (i) how crop photosynthesis changes with temperature at the enzymatic scale within the leaf; (ii) how stomata and plant transport systems are affected by temperature; (iii) what features make a plant susceptible or tolerant to elevated temperature and heat stress; and (iv) how these temperature and heat effects compound at the ecosystem scale to affect crop yields. Throughout the review, we identify current advancements and future research trajectories that are needed to make our cropping systems more resilient to rising temperature and heat stress, which are both projected to occur due to current global fossil fuel emissions.

59 BASIC BIOLOGICAL SCIENCES↗

Forest regeneration within Earth system models: current process representations and ways forward

Earth system models must predict forest responses to global change in order to simulate future global climate, hydrology, and ecosystem dynamics. These models are increasingly adopting vegetation demographic approaches that explicitly represent tree growth, mortality, and recruitment, enabling advances in the projection of forest vulnerability and resilience, as well as evaluation with field data. To date, simulation of regeneration processes has received far less attention than simulation of processes that affect growth and mortality, in spite of their critical role maintaining forest structure, facilitating turnover in forest composition over space and time, enabling recovery from disturbance, and regulating climate-driven range shifts. Here, our critical review of regeneration process representations within current Earth system vegetation demographic models reveals the need to improve parameter values and algorithms for reproductive allocation, dispersal, seed survival and germination, environmental filtering in the seedling layer, and tree regeneration strategies adapted to wind, fire, and anthropogenic disturbance regimes. These improvements require synthesis of existing data, specific field data-collection protocols, and novel model algorithms compatible with global-scale simulations. Vegetation demographic models offer the opportunity to more fully integrate ecological understanding into Earth system prediction; regeneration processes need to be a critical part of the effort.

54 ENVIRONMENTAL SCIENCES↗

The impacts of rising vapour pressure deficit in natural and managed ecosystems

Abstract An exponential rise in the atmospheric vapour pressure deficit (VPD) is among the most consequential impacts of climate change in terrestrial ecosystems. Rising VPD has negative and cascading effects on nearly all aspects of plant function including photosynthesis, water status, growth and survival. These responses are exacerbated by land–atmosphere interactions that couple VPD to soil water and govern the evolution of drought, affecting a range of ecosystem services including carbon uptake, biodiversity, the provisioning of water resources and crop yields. However, despite the global nature of this phenomenon, research on how to incorporate these impacts into resilient management regimes is largely in its infancy, due in part to the entanglement of VPD trends with those of other co‐evolving climate drivers. Here, we review the mechanistic bases of VPD impacts at a range of spatial scales, paying particular attention to the independent and interactive influence of VPD in the context of other environmental changes. We then evaluate the consequences of these impacts within key management contexts, including water resources, croplands, wildfire risk mitigation and management of natural grasslands and forests. We conclude with recommendations describing how management regimes could be altered to mitigate the otherwise highly deleterious consequences of rising VPD.

54 ENVIRONMENTAL SCIENCES↗

Soil properties and biochemical composition of ground-dwelling bee nests in agricultural settings

Soils deliver underrecognized ecosystem services by supplying habitat for ground-dwelling pollinators, such as wild bees and other organisms, that pollinate 80% of insect-pollinated plants and play a critical role in securing resilient pollination provisions. Our objective is to identify soil properties of ground nesting bee nests in agricultural settings of western Oregon, USA. We confirmed ground nesting bee and sand wasp activity in 7 agricultural sites and 1 recreational park. Soils from 17 bee and sand wasp nests were analyzed for pH, particle size distribution, and carbon and nitrogen content. We visually confirmed that 8 of the nesting bees were sweat bees from the Halictidae family and identified a captured bee specimen as Lasioglossum (Dialictus) (Hymenoptera: Halictidae). We located 2 sites with sand wasps where specimens were identified as Cerceris and Bembix (Hymenoptera: Crabronidae). The organic matter composition of three soil samples scraped from the linings of active nests were assessed using Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS). The FTICR-MS results identified unknown lipid compounds in the nest soil samples, which we hypothesize are waterproofing lipids secreted to line cell walls. Bee nests occurred in slightly acidic, bare-ground soils with low rock/vegetation coverage, low organic carbon content (<1%), and exhibited significantly higher silt-plus-clay fractions (>75%) versus data published for bee nests in prior work. Our findings present important implications for textural controls on nest site selection in wet, cool environments and demonstrate the importance of integrating soil properties to improve our understanding of ground-dwelling organisms and associated soil habitats.

59 BASIC BIOLOGICAL SCIENCES↗

Are You Philanthropy-Ready? How to Work with Foundations on Mission-Aligned Community Solar

Community solar is emerging as a popular way to deliver a range of economic and social benefits that go beyond clean energy. The US Department of Energy (DOE) has set a goal for America to deploy enough community solar projects to power the equivalent of five million households by 2025 and create $1 billion in energy bill savings. To reach the goal, DOE has created the Community Power Accelerator, as part of the National Community Solar Partnership (NCSP). The Accelerator is an online ecosystem bringing together developers, lenders, foundations, community organizations, and other stakeholders to support the deployment of mission-aligned community solar. The Accelerator is especially focused on projects that deliver "meaningful benefits" to customers and communities, including: access by low- to moderate-income households; greater bill savings; resilience and grid benefits; community ownership; and local workforce development. Many philanthropic organizations are looking at community solar as a way to capture these benefits in their grant-making and investment programs, while also reducing pollution and promoting environmental justice. To help community-based organizations (CBOs), non-profit organizations, and mission-aligned developers seeking philanthropic support, Berkeley Lab and the National Renewable Energy Lab prepared Are You Philanthropy-Ready? How to Work with Foundations on Mission-Aligned Community Solar. The guide provides an overview of how foundations work, gives tips on what they seek in a fundable project, and provides guidance on crafting effective proposals. In short, this guide aims to help the fund-seeker become philanthropy-ready.

14 SOLAR ENERGY↗