The causal arrows from genotype, environment and management to plant phenotype are double headed.

Cause-and-effect arrows are drawn from genotype (G), environment (E), and agronomic management (M) to the plant phenotype in crop stands in a useful but incomplete framework that informs research questions, experimental design, statistical analysis, data interpretation, modelling, and breeding and agronomic applications. Here we focus on the overlooked bidirectionality of these arrows. The phenotype-to-genotype arrow includes increased mutation rates in stressed phenotypes, relative to basal rates.

Heat stress from current and predicted increases in temperature impairs lambing rates and birth weights in the Australian sheep flock.

Livestock heat stress threatens production, particularly in semi-arid, arid and tropical regions. Using established temperature thresholds for sheep, we modelled +1 °C and +3 °C temperature increases over the historical baseline, estimating that 2.1 million potential lambs are lost annually due to heat stress alone, increasing to 2.

Review of the impact of heat stress on reproductive performance of sheep.

Heat stress significantly impairs reproduction of sheep, and under current climatic conditions is a significant risk to the efficiency of the meat and wool production, with the impact increasing as global temperatures rise. Evidence from field studies and studies conducted using environmental chambers demonstrate the effects of hot temperatures (≥ 32 °C) on components of ewe fertility (oestrus, fertilisation, embryo survival and lambing) are most destructive when experienced from 5 d before until 5 d after oestrus. Temperature controlled studies also demonstrate that ram fertility, as measured by rates of fertilisation and embryo survival, is reduced when mating occurs during the period 14 to 50 d post-heating.

Placing the power of real options analysis into the hands of natural resource managers - taking the next step.

This paper explores heuristic methods with potential to place the analytical power of real options analysis into the hands of natural resource managers. The complexity of real options analysis has led to patchy or ephemeral adoption even by corporate managers familiar with the financial-market origins of valuation methods. Intuitively accessible methods for estimating the value of real options have begun to evolve, but their evaluation has mostly been limited to researcher-driven applications.