Anticipating landscape‐ to regional‐scale impacts of land use on ecosystems and the services they provide is a central challenge for scientists, policymakers, and resource managers. Working with a panel of practitioners and regional experts, we developed and analyzed four plausible but divergent land‐use scenarios that depict the future of Massachusetts from 2010 to 2060 to address two questions: (1) “How do the magnitude and spatial distribution of ecosystem service provisioning vary under the different land‐use regimes?” and (2) “What are the synergies and trade‐offs among direct human uses, ecosystem services, and habitat quality?” Each scenario specifies the detailed prescriptions for the major uses of the forests, including conversion to residential and commercial development, clearing new farmland, shifting silvicultural practices, and designating forests protected from development. We simulated the land‐use scenarios and their interactions with anticipated climate change by coupling statistical models of land use to the LANDIS‐II landscape model and then evaluated the outcomes in terms of the magnitude and spatial distribution of (1) direct human uses of the landscape (residential and commercial development, agricultural, timber harvest), (2) ecosystem services (carbon storage, flood regulation, nutrient retention), and (3) habitat quality (forest tree species composition, interior forest habitat). Across all scenarios, conflicts occurred between dispersed residential development and the supply of ecosystem services and habitat quality. In all but the scenario that envisioned a significant agricultural expansion, forest growth resulted in net increases in aboveground carbon storage, despite the concomitant forest clearing and harvesting. One scenario, called Forests as Infrastructure, showed the potential for synergies between increased forest harvest volume through the sustainable practices that encouraged the maintenance of economically and ecologically important tree species, and carbon storage. This scenario also showed trade‐offs between development density and water quantity and quality at the watershed scale. The process of integrated scenario analysis led to important insights for land managers and policymakers in a populated forested region where there are tensions among development, forest harvesting, and land conservation. More broadly, the results emphasize the need to consider the consequences of contrasting land‐use regimes that result from the interactions between human decisions and spatially heterogeneous landscape dynamics.

Rapid temperature flips are sudden shifts from extreme warm to cold or vice versa–both challenge humans and ecosystems by leaving a very short time to mitigate two contrasting extremes, but are yet to be understood. Here, we provide a global assessment of rapid temperature flips from 1961 to 2100. Warm-to-cold flips favorably follow wetter and cloudier conditions, while cold-to-warm flips exhibit an opposite feature. Of the global areas defined by the Intergovernmental Panel on Climate Change, over 60% have experienced more frequent, intense, and rapid flips since 1961, and this trend will expand to most areas in the future. During 2071–2100 under SSP5-8.5, we detect increases of 6.73–8.03% in flip frequency (relative to 1961–1990), 7.16–7.32% increases in intensity, and 2.47–3.24% decreases in transition duration. Global population exposure will increase over onefold, which is exacerbated in low-income countries (4.08–6.49 times above the global average). Our findings underscore the urgency to understand and mitigate the accelerating hazard flips under global warming.

In order to quantify the effects of forests to oil palm conversion occurring in the tropics on land–atmosphere carbon, water and energy fluxes, we develop a new perennial crop sub-model CLM-Palm for simulating a palm plant functional type (PFT) within the framework of the Community Land Model (CLM4.5). CLM-Palm is tested here on oil palm only but is meant of generic interest for other palm crops (e.g., coconut). The oil palm has monopodial morphology and sequential phenology of around 40 stacked phytomers, each carrying a large leaf and a fruit bunch, forming a multilayer canopy. A sub-canopy phenological and physiological parameterization is thus introduced so that each phytomer has its own prognostic leaf growth and fruit yield capacity but with shared stem and root components. Phenology and carbon and nitrogen allocation operate on the different phytomers in parallel but at unsynchronized steps, separated by a thermal period. An important phenological phase is identified for the oil palm – the storage growth period of bud and "spear" leaves which are photosynthetically inactive before expansion. Agricultural practices such as transplanting, fertilization and leaf pruning are represented. Parameters introduced for the oil palm were calibrated and validated with field measurements of leaf area index (LAI), yield and net primary production (NPP) from Sumatra, Indonesia. In calibration with a mature oil palm plantation, the cumulative yields from 2005 to 2014 matched notably well between simulation and observation (mean percentage error = 3 %). Simulated inter-annual dynamics of PFT-level and phytomer-level LAI were both within the range of field measurements. Validation from eight independent oil palm sites shows the ability of the model to adequately predict the average leaf growth and fruit yield across sites and sufficiently represent the significant nitrogen- and age-related site-to-site variability in NPP and yield. Results also indicate that seasonal dynamics of yield and remaining small-scale site-to-site variability of NPP are driven by processes not yet implemented in the model or reflected in the input data. The new sub-canopy structure and phenology and allocation functions in CLM-Palm allow exploring the effects of tropical land-use change, from natural ecosystems to oil palm plantations, on carbon, water and energy cycles and regional climate.