1. In a recently published paper, Oliva et al. concluded that domestic grazing pressure across Patagonian rangelands approached carrying capacity due to decades of stock adjustment, but that guanaco overpopulation may have altered that balance. The authors argued that unless guanaco numbers are controlled, they will reduce forage available for domestic stock and will negatively affect rangelands. We consider that the herbivore-stock analysis presented is inaccurate and deserves revision, and that the stated conclusions lack empirical support. 2. When the spatial distribution of herbivores is accounted for in the Oliva et al. analysis, domestic stock is far above carrying capacity, indicating that domestic overgrazing continues. 3. Theoretical and empirical evidence on bottom-up regulation and competitive exclusion challenges the supposed guanaco overpopulation and the hypothetical reduction of forage available for livestock. 4. Even if guanaco numbers are reduced, grassland degradation and production losses will continue because their main drivers, domestic overstock and heterogeneous grazing, are still operating. 5. Synthesis and applications. Oversimplified models with poor ecological insight can lead to erroneous conclusions and misguide management decisions. The incorrect inference that Patagonian domestic stock is adjusted to carrying capacity could help to consolidate current domestic overgrazing by reducing incentives to improve livestock management practices. Regarding guanacos, a controversial species in an unfavourable context, control-oriented harvest without a clear justification threatens populations' viability and genuine attempts of productive diversification. Addressing relevant ecological processes, such as niche partitioning, competitive exclusion and population regulation, is essential to correctly assess joint carrying capacity in multi-herbivore systems, as well as to identify the true factors driving degradation processes and to optimize rangeland use on a sustainable basis.

The studies described here were undertaken to characterize the hepatic insulin and glucagon receptors of control (C), pinealectomized (Pn), and melatonin-treated pinealectomized (Pn + Mel) rats. Compared with C rats, an increase in plasma glucose and glucagon levels and a reduction in circulating concentrations of insulin in Pn animals were observed. Melatonin treatment of Pn rats reverses all three parameters toward the normal values. In liver membranes, insulin binding was lower in Pn than in C rats, and glucagon binding was greater in Pn than in C animals; in Pn + Mel rats both insulin and glucagon binding reverse toward the normal values that were observed in C rats. The modifications in hormone binding reflect changes in the number of receptors but not in the affinity constants. The time courses of hormone association and dissociation from liver membranes were similar in all three experimental groups. The degradation of both hormones by liver membranes was similar in all three groups. Insulin receptor degradation also was similar in the three groups, while glucagon receptor degradation was similar in the liver membranes of C and Pn rats but smaller in Pn + Mel animals. These findings suggest that the pineal gland may modulate the circulating levels and liver receptor concentrations of insulin and glucagon. In addition, our results indicate that insulin and glucagon did not induce a down-regulation of liver receptors in Pn rats.

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The Assembly Line Part Feeding Problem (ALPFP) is a complex combinatorial optimisation problem concerned with the delivery of the required parts to the assembly workstations in the right quantities at the right time. Solving the ALPFP includes simultaneously solving two sub-problems, namely tour scheduling and tow-train loading. In this article, we first define the problem and formulate it as a multi-objective mixed-integer linear programming model. Then, we carry out a complexity analysis, proving the ALPFP to be NP-complete. A modified particle swarm optimisation (MPSO) algorithm incorporating mutation as part of the position updating scheme is subsequently proposed. The MPSO is capable of finding very good solutions with small time requirements. Computational results are reported, demonstrating the efficiency and effectiveness of the proposed MPSO.

Different aspects of assembly line optimization have been extensively studied. Part feeding at assembly lines, however, is quite an undeveloped area of research. This study focuses on the optimization of part feeding at mixed-model assembly lines with respect to the Just-In-Time principle motivated by a real situation encountered at one of the major automobile assembly plants in Spain. The study presents a mixed integer linear programming model and a novel simulated annealing algorithm-based heuristic to pave the way for the minimization of the number of tours as well as inventory level. In order to evaluate the performance of the algorithm proposed and validate the mathematical model, a set of generated test problems and two real-life instances are solved. The solutions found by both the mathematical model and proposed algorithm are compared in terms of minimizing the number of tours and inventory levels, as well as a performance measure called workload variation. The results show that although the exact mathematical model had computational difficulty solving the problems, the proposed algorithm provides good solutions in a short computational time.