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We conducted a spatially explicit vulnerability assessment of the forest industry in Maine, USA, to climate change in an effort to (1) advance a spatial framework for assessing forest industry vulnerability and (2) increase our understanding of Maine’s specific vulnerabilities to climate change in order to guide decision-making. We applied a bottom-up indicator approach to evaluate exposure, sensitivity, and adaptive capacity to climate change using both biophysical and social indicators, largely driven by participatory processes. Our approach enabled us to synthesize and aggregate indicators of regional importance to evaluate vulnerability, allowing us to simultaneously examine combinations of potential changes. We found that each Maine county had its own unique combination of exposure, sensitivity, and adaptive capacity indicators, with overall vulnerability highest in the rural northern and western parts of the state, where forest industry activities are most prevalent. However, results also indicate that although increased stress from climate-related changes can negatively affect Maine’s forest via high exposure, reduced sensitivities and increased adaptive capacity have the potential to largely decrease overall vulnerability in many parts of the state.

Forest insects and pathogens have significant impacts on U.S. forests, annually affecting an area nearly three times that of wildfires and timber harvesting combined. However, coupled with these direct effects of forest insects and pathogens are the indirect impacts through influencing forest management practices, such as harvesting. In an earlier study, we surveyed private woodland owners in the northeastern U.S. and 84% of respondents indicated they intended to harvest in at least one of the presented insect invasion scenarios. This harvest response to insects represents a potentially significant shift in the timing, extent, and species selection of harvesting. Here we used the results from the landowner survey, regional forest inventory data, and characteristics of the emerald ash borer (Species: Agrilus planipennis Fairmaire, 1888) invasion to examine the potential for a rapidly spreading invasive insect to alter harvest regimes and affect regional forest conditions. Our analysis suggests that 25% of the woodland parcels in the Connecticut River Watershed in New England may intend to harvest in response to emerald ash borer. If the emerald ash borer continues to spread at its current rate within the region, and therefore the associated management response occurs in the next decade, this could result inmore »an increase in harvest frequencies, from 2.6% year−1 (historically) to 3.7% year−1 through to approximately 2030. If harvest intensities remain at levels found in remeasured Forest Inventory and Analysis plots, this insect-initiated harvesting would result in the removal of 12%–13% of the total aboveground biomass. Eighty-one percent of the removed biomass would be from species other than ash, creating a forest disturbance that is over twice the magnitude than that created by emerald ash borer alone, with the most valuable co-occurring species most vulnerable to biomass loss.« less

Scientists are increasingly engaging with stakeholders to codesign scenarios of land use change necessitating methods to translate the resulting qualitative scenarios into quantitative simulations. We demonstrate a transparent method for translating participatory scenarios to simulations of land use and land cover (LULC) change using the New England Landscape Futures (NELF) project as a case study. The NELF project codesigned four divergent narrative scenarios that contrast with a Recent Trends scenario projecting a continuation of observed changes New England over the past 20 years. Here, we (1) describe the process and utility of translating qualitative scenarios into spatial simulations using a dynamic cellular land change model, (2) evaluate scenario LULC configuration relative to the Recent Trends scenario and to each other, (3) compare the fate of forests within stakeholder‐defined areas of concern, and (4) describe how a user‐inspired outreach tool was developed to make the simulations and analyses accessible to a diverse user group. The associated simulations are strongly divergent in terms of the amount of LULC change and the spatial pattern of change. Among the scenarios, there is a fivefold difference in the amount of high‐density development and a twofold difference in the amount of protected land. Features of themore »simulations can clearly be linked back to the original storylines. Overall, the rate of LULC change has a greater influence on stakeholder areas of concern than the spatial configuration. The simulated scenarios have been integrated into an online mapping tool via a user‐engagement process meeting the needs of a variety of stakeholders.

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In an era of rapid global change, our ability to understand and predict Earth's natural systems is lagging behind our ability to monitor and measure changes in the biosphere. Bottlenecks to informing models with observations have reduced our capacity to fully exploit the growing volume and variety of available data. Here, we take a critical look at the information infrastructure that connects ecosystem modeling and measurement efforts, and propose a roadmap to community cyberinfrastructure development that can reduce the divisions between empirical research and modeling and accelerate the pace of discovery. A new era of data‐model integration requires investment in accessible, scalable, and transparent tools that integrate the expertise of the whole community, including both modelers and empiricists. This roadmap focuses on five key opportunities for community tools: the underlying foundations of community cyberinfrastructure; data ingest; calibration of models to data; model‐data benchmarking; and data assimilation and ecological forecasting. This community‐driven approach is a key to meeting the pressing needs of science and society in the 21st century.