Restoring and preventing losses of the world’s forests are promising natural pathways to mitigate 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 the question of whether reforestation contributed to biophysical cooling and slowed local climate change. Using new cross-scale approaches and multiple independent sources of data, our analysis 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, with the strongest cooling effect during midday in the growing season, when cooling is 2 to 5 °C. Young forests aged 25-50 years have the strongest cooling effect on surface temperature, which extends to the near-surface air, with forests reducing midday air temperature by up to 1 °C. Our analyses of historical land cover and air temperature trends showed that the cooling benefits of reforestation extend across the landscape. Locations predominantly 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 that reforestation contributed to the historically slow pace of warming in the EUS, highlighting the potential for reforestation to provide local climate adaptation benefits in temperate regions worldwide.

Earth system models (ESMs) and mesoscale models have come to employ increasingly complex parameterization schemes for the atmospheric boundary layer (ABL), requiring surface boundary conditions for numerous higher order turbulence statistics. Of particular interest is the potential temperature variance (PTV), which is used not only as a boundary condition itself but also to close boundary conditions of other statistics. The existing schemes in ESMs largely rely on the assumptions of Monin-Obukhov similarity theory (MOST), and are not necessarily applicable over complex and heterogeneous surfaces where large scale circulations and roughness sub-layer effects may cause deviations from MOST. The National Ecological Network (NEON) is used here to evaluate existing parameterizations for the surface boundary of PTV, note key deficiencies, and explore possible remedies. The results indicate that existing schemes are acceptable over a variety of surface conditions provided the analysis of a priori filters out low frequency variability not associated with turbulent time scales. There was, however, significant inter-site variability in observed similarity constants and a significant bias when compared to the textbook values of these parameters. Existing models displayed the poorest performance over heterogeneous sites, and rough landscapes. Attempts to use canopy structure and surface roughness characteristics to improve the results confirmed a relation between these variables and PTV, but failed to significantly improve the predictive power of the models. The results did not find strong evidence indicating that large scale circulations caused substantial deviations from textbook models, although additional analysis is required to assess their full impacts.

Channel networks increase in complexity as the importance of erosion grows compared to diffusion by soil creep, giving rise to a channelization cascade. In this cascade, smaller channels join to form progressively larger ones with an alternation of ridges and valleys involving a multitude of wavelengths. Simulations of landscape evolution models and laboratory experiments are used to uncover the signature of such a cascade in the wavenumber spectrum of elevation fluctuations. Power spectra at intermediate distances from the boundaries are characterized by a peak wavenumber (the most energetic mode) that is related to the quasi-cyclic valleys superimposed on power-law scaling with exponent ($\alpha$) across a wide range of smaller scales. Dimensional analysis and self-similarity arguments are used to reveal the controlling factors on $\alpha$, showing that $\alpha$ is uniquely linked to the power-law relation (with exponent $m$) between erosion potential and the specific drainage area via $\alpha = 2m -3$.

Water inside plants forms a continuous chain from water in soils to the water evaporating from leaf surfaces. Failures in this chain result in reduced transpiration and photosynthesis and these failures are caused by soil drying and/or cavitation-induced xylem embolism. Xylem embolism and plant hydraulic failure share a number of analogies to “catastrophe theory” in dynamical systems. These catastrophes are often represented in the physiological and ecological literature as tipping points or alternative stable states when control variables exogenous (e.g. soil water potential) or endogenous (e.g. leaf water potential) to the plant are allowed to slowly vary. Here, plant hydraulics viewed from the perspective of catastrophes at multiple spatial scales is considered with attention to bubble expansion (i.e. cavitation), organ-scale vulnerability to embolism, and whole-plant biomass as a proxy for transpiration and hydraulic function. The hydraulic safety-efficiency tradeoff, hydraulic segmentation and maximum plant transpiration are examined using this framework. Underlying mechanisms for hydraulic failure at very fine scales such as pit membranes, intermediate scales such as xylem network properties and at larger scales such as soil-tree hydraulic pathways are discussed. Lacunarity areas in plant hydraulics are also flagged where progress is urgently needed.