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Forest disturbances, such as an eastern spruce budworm ( Choristoneura fumiferana ) outbreak, impact the strength and persistence of forest carbon sinks. Salvage harvests are a typical management response to widespread tree mortality, but the decision to salvage mortality has large implications for the fate of carbon stocks (including forest carbon and harvested wood products) in the near and long terms. In this study, we created decision-support models for salvage harvesting based on carbon after an eastern spruce budworm outbreak. We used lasso regression to determine which stand characteristics (e.g., basal area) are the best predictors of carbon 40 years after an outbreak in both salvage and no salvage scenarios. We modeled carbon at year 40 for different treatment scenarios and discount rates. Treatment scenarios represent residual stand conditions that may be present when an outbreak occurs. Economic discount rates were applied to 40-year carbon values to account for near and long-term carbon storage aspects. We found that the volume and size of eastern spruce budworm host species are significant predictors of salvage preference based on carbon. We found overall that salvaging less volume is recommended to avoid major swings in carbon budgets and that discounting carbon values to apply weight to near or long-term sequestration greatly affects whether salvaging is preferred. Lasso models are constructed for the northeastern US, however, similar concepts may be applied beyond our study area and potentially for other insect outbreaks similar to spruce budworm, such as mountain pine beetle ( Dendroctonus ponderosae ) or hemlock woolly adelgid ( Adelges tsugae ). From a policy standpoint widespread salvaging could create a large carbon emissions deficit with the risk of not being fully replenished within a desired timeframe. Since salvaging is often financially driven, especially for private landowners, carbon market payments or incentives for not salvaging is a consideration for future policy. 

A notable characteristic of terrain in non‐urbanized deglaciated areas of northeastern North America is the microtopography created by processes related to surficial geology, deglaciation and mechanical disturbances to surface materials from excavating events, most of which are caused by tree throw in the modern landscape. The features are often on the scale of 1–4 m across and decimetres to a metre in depth, appearing as ‘puddles’ during intense or high‐magnitude precipitation events. Generalized storage capacity values have been summarized in textbooks for varied landscape conditions, but surprisingly little information is available about how microtopography and related surface water storage varies in dominant physiographic settings in deglaciated landscapes defined by slope, surficial geology and land cover conditions. The increasing availability of elevation data at a horizontal resolution of 2 m or higher has made it possible to remotely evaluate differences in terrain elevation and quantify upland surface water storage capacity from relatively small topographic depressions. Here, we describe and quantify these topographic features in several coastal and inland watersheds in the state of Maine (USA) with measurements of depression volume calculated from digital elevation models (DEMs) using a pit filling approach. Results show that microtopographic storage capacity varies with slope and land cover conditions in deglaciated terrain of northeastern North America. Basin‐average surface water depression storage capacity estimates range from ~4 mm to as low as 0.2 mm. Human interventions such as clearing land for agriculture are associated with lower microtopographic surface water storage capacity than forested landscapes in the region.

 

Ovarian cancer is especially deadly, challenging to treat, and has proven refractory to known immunotherapies. Cytokine therapy is an attractive strategy to drive a proinflammatory immune response in immunologically cold tumors such as many high grade ovarian cancers; however, this strategy has been limited in the past due to severe toxicity. We previously demonstrated the use of a layer‐by‐layer (LbL) nanoparticle (NP) delivery vehicle in subcutaneous flank tumors to reduce the toxicity of interleukin‐12 (IL‐12) therapy upon intratumoral injection. However, ovarian cancer cannot be treated by local injection as it presents as dispersed metastases. Herein, we demonstrate the use of systemically delivered LbL NPs using a cancer cell membrane‐binding outer layer to effectively target and engage the adaptive immune system as a treatment in multiple orthotopic ovarian tumor models, including immunologically cold tumors. IL‐12 therapy from systemically delivered LbL NPs shows reduced severe toxicity and maintained anti‐tumor efficacy compared to carrier‐free IL‐12 or layer‐free liposomal NPs leading to a 30% complete survival rate.

 

Aging infrastructure and growing interests in river restoration have led to a substantial rise in dam removals in the United States. However, the decision to remove a dam involves many complex trade-offs. The benefits of dam removal for hazard reduction and ecological restoration are potentially offset by the loss of hydroelectricity production, water supply, and other important services. We use a multiobjective approach to examine a wide array of trade-offs and synergies involved with strategic dam removal at three spatial scales in New England. We find that increasing the scale of decision-making improves the efficiency of trade-offs among ecosystem services, river safety, and economic costs resulting from dam removal, but this may lead to heterogeneous and less equitable local-scale outcomes. Our model may help facilitate multilateral funding, policy, and stakeholder agreements by analyzing the trade-offs of coordinated dam decisions, including net benefit alternatives to dam removal, at scales that satisfy these agreements.