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Abstract ContextClimate change is altering suitable habitat distributions of many species at high latitudes. Fleshy fruit-producing plants (hereafter, “berry plants”) are important in arctic food webs and as subsistence resources for human communities, but their response to a warming and increasingly variable climate at a landscape scale has not yet been examined. ObjectivesWe aimed to identify environmental determinants of berry plant distribution and predict how climate change might shift these distributions. MethodsWe used species distribution models to identify characteristics and predict the distribution of suitable habitat under current (2006–2013) and future climate conditions (2081–2100; representative concentration pathways 4.5, 6.0, & 8.5) for five berry plant species:Vaccinium uliginosumL.,Empetrum nigrumL.,Rubus chamaemorusL.,Vaccinium vitis-idaeaL., andViburnum edule(Michx.) Raf.. ResultsElevation, soil characteristics, and January and July temperatures were important drivers of habitat distributions. Future suitable habitat predictions showed net declines in suitable habitat area for all species modeled under almost all future climate scenarios tested. ConclusionsOur work contributes to understanding potential geographic shifts in suitable berry plant habitat with climate change at a landscape scale. Shifting and retracting distributions may alter where communities can harvest, suggesting that access to these resources may become restricted in the future. Our prediction maps may help inform climate adaptation planning as communities anticipate shifting access to harvesting locations. 

Abstract Although hydropower produces a relatively small portion of the electricity we use in the United States, it is a flexible and dispatchable resource that serves various critical functions for managing the electricity grid. Climate-induced changes to water availability will affect future hydropower production, and such changes could impact how the areas where the supply and demand of electricity are balanced, called balancing authority areas, are able to meet decarbonization goals. We calculate hydroclimate risk to hydropower at the balancing authority scale, which is previously underexplored in the literature and has real implications for decarbonization and resilience-building. Our results show that, by 2050, most balancing authority areas could experience significant changes in water availability in areas where they have hydropower. Balancing areas facing the greatest changes are located in diverse geographic areas, not just the Western and Northwestern United States, and vary in hydropower generation capacity. The range of projected changes experienced within each balancing area could exacerbate or offset existing hydropower generation deficits. As power producers and managers undertake increasing regional cooperation to account for introducing more variable renewable energy into the grid, analysis of risk at this regional scale will become increasingly salient. 

Abstract Crop N decision support tools are typically based on either empirical relationships that lack mechanistic underpinnings or simulation models that are too complex to use on farms with limited input data. We developed an N mineralization model for corn that lies between these endpoints; it includes a mechanistic model structure reflecting microbial and texture controls on N mineralization but requires just a few simple inputs: soil texture soil C and N concentration and cover crop N content and carbon to nitgrogen ratio (C/N). We evaluated a previous version of the model with an independent dataset to determine the accuracy in predictions of unfertilized corn (Zea maysL.) yield across a wider range of soil texture, cover crop, and growing season precipitation conditions. We tested three assumptions used in the original model: (1) soil C/N is equal to 10, (2) yield does not need to be adjusted for growing season precipitation, and (3) sand content controls humification efficiency (ε). The best new model used measured values for soil C/N, had a summertime precipitation adjustment, and included both sand and clay content as predictors ofε(root mean square error [RMSE] = 1.43 Mg ha⁻¹;r² = 0.69). In the new model, clay has a stronger influence than sand onε, corresponding to lower predicted mineralization rates on fine‐textured soils. The new model had a reasonable validation fit (RMSE = 1.71 Mg ha⁻¹;r² = 0.56) using an independent dataset. Our results indicate the new model is an improvement over the previous version because it predicts unfertilized corn yield for a wider range of conditions. 

Abstract: The Pittsburgh Metropolitan Region in Western Pennsylvania, U.S., like many cities glob-ally, historically has an inequitably distributed urban forest and faced street tree biodiversity challenges. Additionally, Pittsburgh faces several barriers and threats to maintaining and expanding its urban tree cover, including pests, diseases, social acceptance, built environment obstacles, and climate change. To address these concerns, in 2012, Pittsburgh created an Urban Forest Master Plan setting equitable forest cover and biodiversity benchmarks. This paper documents the status of achieving these benchmarks and uses microclimate simulations to assess the capacity of these benchmarks in mitigating future mean radiant temperatures. Results demonstrate that the story of Pittsburgh’s urban forest cover, street tree biodiversity, and age diversity is complex, but inequities are primarily driven by income. However, if Pittsburgh can achieve its forest cover benchmarks, it can reduce its neighbourhoods’ 2050 mean radiant temperature below 2010 temperatures, even under climate change-fuelled extreme heat events. The process and results reported in this paper allow designers and decision-makers to calibrate localized urban forest benchmarks more effectively based on various future scenarios while ensuring the equitable distribution of heat mitigation. 

This paper offers paradigmatic insights from an international workshop on Ecological Legacies: Bridge Between Science and Community, in Ecuador, in the summer of 2023. The conference brought together foreign and local scholars, tour operators, village community, and Indigenous leaders in the upper Amazonia region of Ecuador with the goal of developing a vision for a sustainable and regenerative future of the upper Amazon. The conference offered three epistemological contributions to the existing literature in the emergent field of Montology, including addressing issues of (a) understanding the existing linguistic hegemony in describing tropical environments, (b) the redress of mistaken notions on pristine jungle environments, and (c) the inclusion of traditional knowledge and transdisciplinary approaches to understand the junglescape from different perspectives and scientific traditions. Methodologically, the conference bridged the fields of palaeoecological and ethnobotanical knowledge (as part of a wider conversation between science and local communities). Results show that local knowledge should be incorporated into the study of the junglescape and its conservation, with decolonial approaches for tourism, sharing language, methodology, tradition, and dissemination of the forest’s attributes. Our research helped co-create and formulate the “Coca Declaration” calling for a philosophical turn in research, bridging science and ethnotourism in ways that are local, emancipatory, and transdisciplinary. We conclude that facilitating new vocabulary by decolonial heightening of Indigenous perspectives of the junglescape helps to incorporate the notion of different Amazons, including the mountainscape of the Andean–Amazonian flanks. We also conclude that we can no consider Ecuador the country of “pure nature” since we helped demystify pristine nature for foreign tourists and highlighted local views with ancestral practices. Finally, we conclude that ethnotourism is a viable alternative to manage heritagization of the junglescape as a hybrid territory with the ecological legacies of the past and present inhabitants of upper Amazonia. 

Recent studies identifying underlying and proximate drivers of tropical deforestation and forest degradation have applied a multitude of methodologies, with varying and sometimes conflicting results. Divergent results can have implications for evidence-informed programs, policy action, and land use planning since these differences can lead to controversy as to which drivers should be addressed by deforestation and emissions-reduction or conservation programs, in addition to mismatch between the scale of study results and the scale of policy and program implementation. To identify and reconcile divergences between results among different scales and methodological approaches, we systematically reviewed 231 articles in the drivers of deforestation literature and found inconsistency in scale applied within studies (e.g., differences between the stated scale of analysis and scale of article recommendations), and variation in the number and type of drivers identified between studies by methodology. Additionally, global and regional studies tended to feature recommendations that would be difficult to implement, or that targeted large-scale problems lacking specificity. This study clarifies common themes in driver identification and what is needed for drawing contextualized, scale-appropriate conclusions relevant to forest conservation policy and sustainable land use planning. We suggest improvements to recommendations drawn from drivers of deforestation studies and avenues to reconcile divergences in approaches and results, which will support efforts to advance forest conservation and sustainable forest management outcomes. 

Data and working scripts for publication;Hydroclimate risk to electricity balancing throughout the U.S.&; 

The forests of Central Africa constitute the continent’s largest continuous tract of forest, maintained in part by over 200 protected areas across six countries with varying levels of restriction and enforcement. Despite protection, these Central African forests are subject to a multitude of overlapping proximate and underlying drivers of deforestation and degradation, such as conversion to small-scale agriculture. This pilot study explored whether transboundary protected area complexes featuring mixed resource-use restriction categories are effective in reducing the predicted disturbance risk to intact forests attributed to small-scale agriculture. At two transboundary protected area complex sites in Central Africa, we used Google Earth Engine and a suite of earth observation (EO) data, including a dataset derived using a replicable, open-source methodology stemming from a regional collaboration, to predict the increased risk of deforestation and degradation of intact forests caused by small-scale agriculture. For each complex, we then statistically compared the predicted increased risk between protected and unprotected forests for a stratified random sample of 2 km sites (n = 4000). We found varied effectiveness of protected areas for reducing the predicted risk of deforestation and degradation to intact forests attributed to agriculture by both the site and category of protected areas within the complex. Our early results have implications for sustainable agriculture development, forest conservation, and protected areas management and provide a direction for future research into spatial planning. Spatial planning could optimize the configuration of protected area types within transboundary complexes to achieve both forest conservation and sustainable agricultural production outcomes.