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Abstract Plant responses to water stress is a major uncertainty to predicting terrestrial ecosystem sensitivity to drought. Different approaches have been developed to represent plant water stress. Empirical approaches (the empirical soil water stress (or Beta) function and the supply‐demand balance scheme) have been widely used for many decades; more mechanistic based approaches, that is, plant hydraulic models (PHMs), were increasingly adopted in the past decade. However, the relationships between them—and their underlying connections to physical processes—are not sufficiently understood. This limited understanding hinders informed decisions on the necessary complexities needed for different applications, with empirical approaches being mechanistically insufficient, and PHMs often being too complex to constrain. Here we introduce a unified framework for modeling transpiration responses to water stress, within which we demonstrate that empirical approaches are special cases of the full PHM, when the plant hydraulic parameters satisfy certain conditions. We further evaluate their response differences and identify the associated physical processes. Finally, we propose a methodology for assessing the necessity of added complexities of the PHM under various climatic conditions and ecosystem types, with case studies in three typical ecosystems: a humid Midwestern cropland, a semi‐arid evergreen needleleaf forest, and an arid grassland. Notably, Beta function overestimates transpiration when VPD is high due to its lack of constraints from hydraulic transport and is therefore insufficient in high VPD environments. With the unified framework, we envision researchers can better understand the mechanistic bases of and the relationships between different approaches and make more informed choices. 

Abstract Restoring and preserving the world's forests are promising natural pathways to mitigate some aspects of climate change. In addition to regulating atmospheric carbon dioxide concentrations, forests modify surface and near‐surface air temperatures through biophysical processes. In the eastern United States (EUS), widespread reforestation during the 20th century coincided with an anomalous lack of warming, raising questions about reforestation's contribution to local cooling and climate mitigation. Using new cross‐scale approaches and multiple independent sources of data, we uncovered links between reforestation and the response of both surface and air temperature in the EUS. Ground‐ and satellite‐based observations showed that EUS forests cool the land surface by 1–2°C annually compared to nearby grasslands and croplands, with the strongest cooling effect during midday in the growing season, when cooling is 2–5°C. Young forests (20–40 years) have the strongest cooling effect on surface temperature. Surface cooling extends to the near‐surface air, with forests reducing midday air temperature by up to 1°C compared to nearby non‐forests. Analyses of historical land cover and air temperature trends showed that the cooling benefits of reforestation extend across the landscape. Locations surrounded by reforestation were up to 1°C cooler than neighboring locations that did not undergo land cover change, and areas dominated by regrowing forests were associated with cooling temperature trends in much of the EUS. Our work indicates reforestation contributed to the historically slow pace of warming in the EUS, underscoring reforestation's potential as a local climate adaptation strategy in temperate regions. 

Abstract Widespread shifts in land cover and land management (LCLM) are being incentivized as tools to mitigate climate change, creating an urgent need for prognostic assessments of how LCLM impacts surface energy balance and temperature. Historically, observational studies have tended to focus on how LCLM impacts surface temperature (T_surf), usually at annual timescales. However, understanding the potential for LCLM change to confer climate adaptation benefits, or to produce unintended adverse consequences, requires careful consideration of impacts on bothT_surfand the near-surface air temperature (T_a,local) when they are most consequential for ecosystem and societal well-being (e.g. on hot summer days). Here, long-term data from 130 AmeriFlux towers distributed between 19–71 °N are used to systematically explore LCLM impacts on bothT_surfandT_a,local, with an explicit focus on midday summer periods when adaptive cooling is arguably most needed. We observe profound impacts of LCLM onT_surfat midday, frequently amounting to differences of 10 K or more from one site to the next. LCLM impacts onT_a,localare smaller but still significant, driving variation of 5–10 K across sites. The magnitude of LCLM impacts on bothT_surfandT_a,localis not well explained by plant functional type, climate regime, or albedo; however, we show that LCLM shifts that enhance ET or increase canopy height are likely to confer a local mid-day cooling benefit for bothT_surfandT_a,localmost of the time. At night, LCLM impacts on temperature are much smaller, such that averaging across the diurnal cycle will underestimate the potential for land cover to mediate microclimate when the consequences for plant and human well-being are most stark. Finally, during especially hot periods, land cover impacts onT_a,localandT_surfare less coordinated, and ecosystems that tend to cool the air during normal conditions may have a diminished capacity to do so when it is very hot. We end with a set of practical recommendations for future work evaluating the biophysical impacts and adaptation potential of LCLM shifts. 

Windthrow, or the uprooting of trees by extreme wind gusts, is a natural forest disturbance that creates microhabitats, turns over soil, alters hydrology, and removes carbon from the above-ground carbon stock. Long recurrence intervals between extreme wind events, however, make direct observations of windthrow rare, challenging our understanding of this important disturbance process. To overcome this difficulty, we present an approach that uses the geomorphic record of hillslope topographic roughness as a proxy for the occurrence of windthrow. The approach produces a probability function of the number of annual windthrow events for a maximum wind speed, allowing us to explore how windthrow or tree strengths may change due to shifting wind climates. Slight changes to extreme wind speeds may drive comparatively large changes in windthrow production rates or force trees to respond and change the distribution. We also highlight that topographic roughness has the potential to serve as an important archive of extreme wind speeds. 

Eddy covariance measurement systems provide direct observation of the exchange of greenhouse gases between ecosystems and the atmosphere, but have only occasionally been intentionally applied to quantify the carbon dynamics associated with specific climate mitigation strategies. Natural climate solutions (NCS) harness the photosynthetic power of ecosystems to avoid emissions and remove atmospheric carbon dioxide (CO2), sequestering it in biological carbon pools. In this perspective, we aim to determine which kinds of NCS strategies are most suitable for ecosystem-scale flux measurements and how these measurements should be deployed for diverse NCS scales and goals. We find that ecosystem-scale flux measurements bring unique value when assessing NCS strategies characterized by inaccessible and hard-to-observe carbon pool changes, important non-CO2 greenhouse gas fluxes, the potential for biophysical impacts, or dynamic successional changes. We propose three deployment types for ecosystem-scale flux measurements at various NCS scales to constrain wide uncertainties and chart a workable path forward: “pilot”, “upscale”, and “monitor”. Together, the integration of ecosystem-scale flux measurements by the NCS community and the prioritization of NCS measurements by the flux community, have the potential to improve accounting in ways that capture the net impacts, unintended feedbacks, and on-the-ground specifics of a wide range of emerging NCS strategies.