Ethical issues involving long-term land leases: a soil sciences perspective

As populations grow and arable land becomes increasingly scarce, large-scale long- term land leases are signed at a growing rate. Countries and investors with large amounts of financial resources and a strong agricultural industry seek long-term land leases for agricultural exploitation or investment purposes. Leaders of financially poorer countries often advertise such deals as a fast way to attract foreign capital. Much has been said about the short-term social costs these types of leases involve, however, less has been said about the normative dimension of their long-term environmental impact. We therefore will focus on the likely impact such deals have for soil conservation, by (1) briefly introducing the basics of long-term leasing arrangements by comparing land leases to the renting of buildings, (2) explaining from a soil sciences perspective the difficulties in assessing the current value of an estate and in calculating the damages of soil erosion and degradation, and (3) show how difficult it is to incentivize the conservation of soil quality when one cannot sufficiently and cost-effectively valorize existing environmental capital and eventual future damages. Attempting to oblige tenants through contracts to invest in sustainable stewardship has limited potential when liability payments do not reflect true costs and are hard to enforce

Sampling diffusive transition paths

We address the problem of sampling double-ended diffusive paths. The ensemble of paths is expressed using a symmetric version of the Onsager-Machlup formula, which only requires evaluation of the force field and which, upon direct time discretization, gives rise to a symmetric integrator that is accurate to second order. Efficiently sampling this ensemble requires avoiding the well-known stiffness problem associated with sampling infinitesimal Brownian increments of the path, as well as a different type of stiffness associated with sampling the coarse features of long paths. The fine-feature sampling stiffness is eliminated with the use of the fast sampling algorithm (FSA), and the coarse-feature sampling stiffness is avoided by introducing the sliding and sampling (S&S) algorithm. A key feature of the S&S algorithm is that it enables massively parallel computers to sample diffusive trajectories that are long in time. We use the algorithm to sample the transition path ensemble for the structural interconversion of the 38-atom Lennard-Jones cluster at low temperature.Comment: 13 pages 5 figure