Forest-linked livelihoods in a globalized world.

Forests have re-taken centre stage in global conversations about sustainability, climate and biodiversity. Here, we use a horizon scanning approach to identify five large-scale trends that are likely to have substantial medium- and long-term effects on forests and forest livelihoods: forest megadisturbances; changing rural demographics; the rise of the middle-class in low- and middle-income countries; increased availability, access and use of digital technologies; and large-scale infrastructure development. These trends represent human and environmental processes that are exceptionally large in geographical extent and magnitude, and difficult to reverse. They are creating new agricultural and urban frontiers, changing existing rural landscapes and practices, opening spaces for novel conservation priorities and facilitating an unprecedented development of monitoring and evaluation platforms that can be used by local communities, civil society organizations, governments and international donors. Understanding these larger-scale dynamics is key to support not only the critical role of forests in meeting livelihood aspirations locally, but also a range of other sustainability challenges more globally. We argue that a better understanding of these trends and the identification of levers for change requires that the research community not only continue to build on case studies that have dominated research efforts so far, but place a greater emphasis on causality and causal mechanisms, and generate a deeper understanding of how local, national and international geographical scales interact.

Heterogeneous Multifrequency Direct Inversion (HMDI) for magnetic resonance elastography with application to a clinical brain exam.

A new viscoelastic wave inversion method for MRE, called Heterogeneous Multifrequency Direct Inversion (HMDI), was developed which accommodates heterogeneous elasticity within a direct inversion (DI) by incorporating first-order gradients and combining results from a narrow band of multiple frequencies. The method is compared with a Helmholtz-type DI, Multifrequency Dual Elasto-Visco inversion (MDEV), both on ground-truth Finite Element Method simulations at varied noise levels and a prospective in vivo brain cohort of 48 subjects ages 18-65. In simulated data, MDEV recovered background material within 5% and HMDI within 1% of prescribed up to SNR of 20 dB. In vivo HMDI and MDEV were then combined with segmentation from SPM to create a fully automated "brain palpation" exam for both whole brain (WB), and brain white matter (WM), measuring two parameters, the complex modulus magnitude |G*| , which measures tissue "stiffness", and the slope of |G*| values across frequencies, a measure of viscous dispersion. |G*| values for MDEV and HMDI were comparable to the literature (for a 3-frequency set centered at 50 Hz, WB means were 2.17 and 2.15 kPa respectively, and WM means were 2.47 and 2.49 kPa respectively). Both methods showed moderate correlation to age in both WB and WM, for both |G*| and |G*| slope, with Pearson's r ≥ 0.4 in the most sensitive frequency sets. In comparison to MDEV, HMDI showed better preservation of recovered target shapes, more noise-robustness, and stabler recovery values in regions with rapid property change, however summary statistics for both methods were quite similar. By eliminating homogeneity assumptions within a fast, fully automatic, regularization-free direct inversion, HMDI appears to be a worthwhile addition to the MRE image reconstruction repertoire. In addition to supporting the literature showing decrease in brain viscoelasticity with age, our work supports a wide range of inter-individual variation in brain MRE results.