Holocene paleoenvironmental change inferred from two sediment cores collected in the Tibetan lake Taro Co

The Tibetan Plateau, also known as the ‘‘Water Tower of Asia’’ because of its function as a water storage and supply region, responds dramatically to modern climate changes. Paleoecological shifts inferred from lake sediment archives provide essential insights into past climate changes, and the processes that drove those shifts. This is especially true for studies of lakes in endorheic basins on the Tibetan Plateau, where lake level is regulated pre-dominantly by Monsoon intensity. Such water bodies provide excellent opportunities to reconstruct past changes in humidity. Most paleolimnological investigations of lakes on the Tibetan Plateau, however, have involved the study of a single sediment core, making it difficult to discern between changes caused by local events and those caused by lake-wide or regional processes. Here we present results from a paleolimnological study of Lake Taro Co, a currently closed-basin lake in Central Tibet. We compared a sediment record from the central part of the lake to a record from the near-shore area, and present results of sedimentological and bioindicator (chironomid, diatom, pollen) analyses from both records. Results show three periods of lake-wide ecosystem change ([ca. 5250, 5250–2250 and since about 2250 cal year BP), which reflect a continuous drying trend throughout the Middle and Late Holocene. In addition to this lake-wide trend, we identified two local events in the sediment core from the southeastern, nearshore site. These include (1) a hiatus between 12,400 and 5400 cal year BP and (2) an 1800-year period of distinct paleoenvironmental conditions (5400–3600 cal year BP). We hypothesize that both events were caused by relocation of a river in the southeast sector of the lake’s catchment. We propose that the first relocation caused an erosion event that removed sediment, thereby producing the hiatus. During the following 1800 years, the core site may have been located on the river delta, before another river relocation at 3600 cal year BP established the modern prodelta situation. Our study demonstrates the value of using multiple sediment cores from a lake, to better identify processes that control widespread versus local events

Discrete flow pooling problems in coal supply chains

The pooling problem is a nonconvex nonlinear programming problem (NLP) with applications in the refining and petrochemical industries, but also the coal mining industry. The problem can be stated as follows: given a set of raw material suppliers (inputs) and qualities of the supplies, find a cost-minimising way of blending these raw materials in intermediate pools and outputs so as to satisfy requirements on the output qualities. The blending in two stages (in pools and outputs) introduces bilinear constraints. The pooling problem can alternatively be described as a minimum cost network flow problem with additional bilinear constraints to capture the blending of raw materials. In this paper we study a variation of the pooling problem that arises naturally in the coal mining industry and is sometimes referred to as grade targeting. Coal is made-to-order according to customers’ desired product qualities. Deviations from these target qualities result in contractually agreed bonuses and penalties. In the pooling problem variation we study, costs are associated with these bonuses and penalties instead of network flows. While in the original pooling problem we have hard bounds on the qualities and unmet demand is penalised in the objective function, in our coal mining variation we have hard demand constraints and deviations from target qualities are penalised. This makes finding a feasible solution easy, while in the pooling problem finding a nontrivial feasible solution that satisfies the quality requirements is already hard. An implication of this is that we are able to solve larger problem instances than those typically studied in the pooling problem literature. To model the coal blending process accurately, we define a time-expanded network where the intermediate pools represent coal stockpiles over time. Since coal is transported in large quantities, we study the trade-off between continuous and discretized flows in coal blending, i.e., solving a continuous flow problem where arbitrarily small flows are allowed versus solving a discretized flow problem where flows must be in multiples of some basic unit, e.g. trainloads. We also study two exact mixed-integer linear programming (MILP) linearizations of these mixed-integer nonlinear programs (MINLPs), which can be derived from unary and binary expansions of the flow integrality constraint. Such discretizations are typically studied as approximations to an originally continuous problem, however, in our application, a discretized formulation describes the original problem more accurately than a continuous formulation. The paper is organized as follows. In Section 1.1, we introduce the pooling problem and present a variant of the well-known PQ-formulation. In Section 1.2, we extend the pooling problem to model a simplified coal supply chain. After a short literature review on coal supply chains, we present four different problems: the continuous flow problem (a MINLP), in which arbitrarily small flows are allowed, and three discretized flow problems (a MINLP and two MILPs), in which flows must be in multiples of trainloads. The discretization can be achieved by adding integrality constraints for the flow variables. We then show how to overcome the nonlinearity which is inherent in the pooling problem with the use of unary and binary expansions of the integer flow variables, which yields exact MILP reformulations of the discretized MINLP. We conclude the paper with Section 2 where we provide computational results for the four different problems which we solve for a real-life industry setting

Reward abundance interferes with error-based learning in a visuomotor adaptation task

Contains fulltext : 184161.pdf (publisher's version ) (Open Access)The brain rapidly adapts reaching movements to changing circumstances by using visual feedback about errors. Providing reward in addition to error feedback facilitates the adaptation but the underlying mechanism is unknown. Here, we investigate whether the proportion of trials rewarded (the 'reward abundance') influences how much participants adapt to their errors. We used a 3D multi-target pointing task in which reward alone is insufficient for motor adaptation. Participants (N = 423) performed the pointing task with feedback based on a shifted hand-position. On a proportion of trials we gave them rewarding feedback that their hand hit the target. Half of the participants only received this reward feedback. The other half also received feedback about endpoint errors. In different groups, we varied the proportion of trials that was rewarded. As expected, participants who received feedback about their errors did adapt, but participants who only received reward-feedback did not. Critically, participants who received abundant rewards adapted less to their errors than participants who received less reward. Thus, reward abundance negatively influences how much participants learn from their errors. Probably participants used a mechanism that relied more on the reward feedback when the reward was abundant. Because participants could not adapt to the reward, this interfered with adaptation to errors.12 p

Adoption of Community Monitoring Improves Common Pool Resource Management Across Contexts

Pervasive overuse and degradation of common pool resources (CPRs) is a global concern. To sustainably manage CPRs, effective governance institutions are essential. A large literature has developed to describe the institutional design features employed by communities that successfully manage their CPRs. Yet, these designs remain far from universally adopted. We focus on one prominent institutional design feature, community monitoring, and ask whether nongovernmental organizations or governments can facilitate its adoption and whether adoption of monitoring affects CPR use. To answer these questions, we implemented randomized controlled trials in six countries. The harmonized trials randomly assigned the introduction of community monitoring to 400 communities, with data collection in an additional 347 control communities. Most of the 400 communities adopted regular monitoring practices over the course of a year. In a meta-analysis of the experimental results from the six sites, we find that the community monitoring reduced CPR use and increased user satisfaction and knowledge by modest amounts. Our findings demonstrate that community monitoring can improve CPR management in disparate contexts, even when monitoring is externally initiated rather than homegrown. These findings provide guidance for the design of future programs and policies intended to develop monitoring capabilities in communities. Furthermore, our harmonized, multisite trial provides sustainability science with a new way to study the complexity of socioecological systems and builds generalizable insights about how to improve CPR management