Improvements in
ex situ
storage of genetic and reproductive materials offer an alternative for endangered livestock breed conservation. This paper presents a dataset for current
ex situ
collections and
in situ
population for 179 Spanish livestock breeds of seven species, cattle, sheep, pig, chicken, goat, horse and donkey.
Ex situ
data was obtained via survey administered to 18 functioning gene banks in Spain and relates to the reproductive genetic materials (semen doses) of 210 livestock breeds distributed across the gene banks.
In situ
data combines CENSUS information with linear regression techniques and relates to the geographic distribution of 179 Spanish autochthonous livestock breeds (2009-2018), and
in situ
population projections and extinction probabilities (2019-2060). We use a decision variable defining an “acceptable level of risk” that allows decision makers to specify tolerable levels of
in situ
breed endangerment when taking
ex situ
collection and storage decisions.
Improvements in ex situ storage of genetic and reproductive materials offer an alternative for endangered livestock breed conservation, but collections should be optimized cost-effectively to avoid duplication, and with reference to the sustainability of in situ breeds. We developed a multi-period chance-constrained optimization model to rationalize collections of endangered livestock breeds at risk of in situ extinction in Spain. The model configures collections by determining the least-cost optimal collection locations, timing and material quantities (semen doses). A decision variable defining an "acceptable level of risk" allows decision makers to specify tolerable levels of in situ breed endangerment when taking ex situ collection and storage decisions. Using data from 18 gene banks we demonstrate how collections can be rationalized, and derive cost curves relating marginal ex situ collection cost and accepted probability of in situ extinction covering the period 2018 to 2060. The modelling framework can be replicated in countries seeking to rationalize ex situ collections under limited conservation budgets and uncertain in situ extinction risks.
Feeding cattle with on-pasture supplementation or feedlot diets can increase animal efficiency and system profitability while minimizing environmental impacts. However, cattle system profit margins are relatively small and nutrient supply accounts for most of the costs. This paper introduces a nonlinear profit-maximizing diet formulation problem for beef cattle based on well-established predictive equations. Nonlinearity in predictive equations for nutrient requirements poses methodological challenges in the application of optimization techniques. In contrast to other widely used diet formulation methods, we develop a mathematical model that guarantees an exact solution for maximum profit diet formulations. Our method can efficiently solve an often-impractical nonlinear problem by solving a finite number of linear problems, that is, linear time complexity is achieved through parametric linear programming. Results show the impacts of choosing different objective functions (minimizing cost, maximizing profit and maximizing profit per daily weight gain) and how this may lead to different optimal solutions. In targeting improved ration formulation on feedlot systems, this paper demonstrates how profitability and nutritional constraints can be met as an important part of a sustainable intensification production strategy.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.