A Dynamic Optimisation Model of Weed Control

It is argued in this paper that static approaches to weed management, where the benefits and costs are only considered within a single season, are inappropriate for assessing the economic benefits of weed control technologies. There are carryover effects from weed management as weeds that escape control in one season may reproduce and replenish weed populations in following seasons. Consequently, it is appropriate to view weed control in the context of a resource management problem where the goal is to determine the optimal inter-temporal level of weed control that maximises economic benefits over some pre-determined period of time. A dynamic optimisation model for weed control is presented. Using the tools of comparative static analysis and Pontryagin's maximum principle, the conditions for optimal input use (ie weed control) are compared for static and dynamic situations. It is shown that a higher level of input use for a given weed population is optimal using a dynamic framework than would be derived under a static framework. The analysis is further extended by the incorporation of uncertainty and shows that the optimal level of weed control is also affected by uncertainty in herbicide efficacy and the survival of weed seeds produced. A case study of the optimal long-term management under deterministic and stochastic conditions of an annual cropping weed, Avena fatua, is presented.weed control, resource economics, optimal control, dynamic programming, wild oats, Farm Management,

Rational Arithmetic Mathematica Functions to Evaluate the One-sided One-sample K-S Cumulative Sample Distribution

One of the most widely used goodness-of-fit tests is the Kolmogorov-Smirnov (KS) family of tests which have been implemented by many computer statistical software packages. To calculate a p value (evaluate the cumulative sampling distribution), these packages use various methods including recursion formulae, limiting distributions, and approximations of unknown accuracy developed over thirty years ago. Based on an extensive literature search for the one-sided one-sample K-S test, this paper identifies two direct formulae and five recursion formulae that can be used to calculate a p value and then develops two additional direct formulae and four iterative versions of the direct formulae for a total of thirteen formulae. To ensure accurate calculation by avoiding catastrophic cancelation and eliminating rounding error, each formula is implemented in rational arithmetic. Linear search is used to calculate the inverse of the cumulative sampling distribution (find the confidence interval bandwidth). Extensive tables of bandwidths are presented for sample sizes up to 2, 000. The results confirm the hypothesis that as the number of digits in the numerator and denominator integers of the rational number test statistic increases, the computation time also increases. In comparing the computational times of the thirteen formulae, the direct formulae are slightly faster than their iterative versions and much faster than all the recursion formulae. Computational times for the fastest formula are given for sample sizes up to fifty thousand.

Rational Arithmetic Mathematica Functions to Evaluate the Two-Sided One Sample K-S Cumulative Sampling Distribution

One of the most widely used goodness-of-fit tests is the two-sided one sample Kolmogorov-Smirnov (K-S) test which has been implemented by many computer statistical software packages. To calculate a two-sided p value (evaluate the cumulative sampling distribution), these packages use various methods including recursion formulae, limiting distributions, and approximations of unknown accuracy developed over thirty years ago. Based on an extensive literature search for the two-sided one sample K-S test, this paper identifies an exact formula for sample sizes up to 31, six recursion formulae, and one matrix formula that can be used to calculate a p value. To ensure accurate calculation by avoiding catastrophic cancelation and eliminating rounding error, each of these formulae is implemented in rational arithmetic. For the six recursion formulae and the matrix formula, computational experience for sample sizes up to 500 shows that computational times are increasing functions of both the sample size and the number of digits in the numerator and denominator integers of the rational number test statistic. The computational times of the seven formulae vary immensely but the Durbin recursion formula is almost always the fastest. Linear search is used to calculate the inverse of the cumulative sampling distribution (find the confidence interval half-width) and tables of calculated half-widths are presented for sample sizes up to 500. Using calculated half-widths as input, computational times for the fastest formula, the Durbin recursion formula, are given for sample sizes up to two thousand.

Arbitrary Precision Mathematica Functions to Evaluate the One-Sided One Sample K-S Cumulative Sampling Distribution

Efficient rational arithmetic methods that can exactly evaluate the cumulative sampling distribution of the one-sided one sample Kolmogorov-Smirnov (K-S) test have been developed by Brown and Harvey (2007) for sample sizes n up to fifty thousand. This paper implements in arbitrary precision the same 13 formulae to evaluate the one-sided one sample K-S cumulative sampling distribution. Computational experience identifies the fastest implementation which is then used to calculate confidence interval bandwidths and p values for sample sizes up to ten million.

The release of a captive-raised female African Elephant <em>(Loxodonta africana</em>) in the Okavango Delta, Botswana

Wild female elephants live in close-knit matrilineal groups and housing captive elephants in artificial social groupings can cause significant welfare issues for individuals not accepted by other group members. We document the release of a captive-raised female elephant used in the safari industry because of welfare and management problems. She was fitted with a satellite collar, and spatial and behavioural data were collected over a 17-month period to quantify her interactions with the wild population. She was then monitored infrequently for a further five-and-a-half years. We observed few signs of aggression towards her from the wild elephants with which she socialized. She used an area of comparable size to wild female elephants, and this continued to increase as she explored new areas. Although she did not fully integrate into a wild herd, she had three calves of her own, and formed a social unit with another female and her calf that were later released from the same captive herd. We recommend that release to the wild be considered as a management option for other captive female elephants

Genomic islands of divergence in the Yellow Tang and the Brushtail Tang Surgeonfishes.

The current ease of obtaining thousands of molecular markers challenges the notion that full phylogenetic concordance, as proposed by phylogenetic species concepts, is a requirement for defining species delimitations. Indeed, the presence of genomic islands of divergence, which may be the cause, or in some cases the consequence, of speciation, precludes concordance. Here, we explore this issue using thousands of RAD markers on two sister species of surgeonfishes (Teleostei: Acanthuridae), Zebrasoma flavescens and Z.&nbsp;scopas, and several populations within each species. Species are readily distinguished based on their colors (solid yellow and solid brown, respectively), yet populations and species are neither distinguishable using mitochondrial markers (cytochrome c oxidase 1), nor using 5193 SNPs (pairwise Φst&nbsp;=&nbsp;0.034). In contrast, when using outlier loci, some of them presumably under selection, species delimitations, and strong population structure follow recognized taxonomic positions (pairwise Φst&nbsp;=&nbsp;0.326). Species and population delimitation differences based on neutral and selected markers are likely due to local adaptation, thus being consistent with the idea that these genomic islands of divergence arose as a consequence of isolation. These findings, which are not unique, raise the question of a potentially important pathway of divergence based on local adaptation that is only evident when looking at thousands of loci

The embedding of the spacetime in five dimensions: an extension of Campbell-Magaard theorem

We extend Campbell-Magaard embedding theorem by proving that any n-dimensional semi-Riemannian manifold can be locally embedded in an (n+1)-dimensional Einstein space. We work out some examples of application of the theorem and discuss its relevance in the context of modern higher-dimensional spacetime theories.Comment: 22pages, Revte

Book reviews

Teaching/Communication/Extension/Profession,

Evolution of Cooperative Thought, Theory, and Purpose

The evolution of agricultural cooperative thought, theory, and purpose in the United States is reviewed from the standpoint of the reemergence of interest in how cooperatives can provide some of the security and benefits that might be lost with gradual phasing out of federal government farm support programs. By accomplishing group action for self-help, the early development of cooperatives drew considerable attention from economists, social theorists, and politicians. Alternative schools of cooperative thought developed, but most proponents of cooperatives regarded them as having enormous potential to provide a public service role in building a more economically stable and democratic society This paper also surveys how cooperative theory was developed more rigorously in the post-WWII period. It has provided better analytical tools for understanding how and why cooperatives have changed in response to technological and economic developments, as well as to social trends, like individualism. Given the new perspectives on cooperative theory and the scope of changes in how cooperatives operate and are structured, cooperatives have even greater potential for coordinating self-help actions, but this potential needs the support of cooperative education services.Agribusiness,

Modelling the Dynamics of Weed Management Technologies

An appropriate economic framework for valuing the benefits of weed management technologies is to treat weeds as a renewable resource stock problem. Consequently, the weed seed bank is defined as a renewable resource that changes through time due to management and seasonal conditions. The goal of decision-makers is to manage this (negative) resource so as to maximise returns over some pre-specified period of time. A modelling framework is presented for evaluating the biological and economic effects of weed management. The framework includes population dynamics, water balance, crop growth, pasture growth and crop/pasture rotation models for measuring the physical interactions between weeds and the environment. These models link in with numerical optimal control, dynamic programming and stochastic dynamic programming models for determination of optimal decision rules and measuring economic impact over time of policy scenarios.weeds, modelling, dynamic analysis., Land Economics/Use,