Timothy Yield and Nutritive Value under Climate Change in Canada

Abstract

Timothy (Phleum pratense L.) is a dominant forage grass in Canada but its performance under projected future climate conditions has not been evaluated. This study combined the grass model CATIMO (Canadian Timothy Model) with baseline (1961–1990) and projected future (2040–2069) climate scenarios to assess the response of timothy to climate change at 10 sites across Canada. Projected future conditions are expected to have the following effects on timothy: (i) earlier growth onset (10‐site average: –21 d; range: –4 to –40 d), date of first harvest (–15 d; –11 to –25 d), and date of second harvest (–20 d; –17 to –29 d), along with a later end to the growing season (+12 d; 0 to +18 d); (ii) increased dry matter (DM) yield at first harvest (+355 kg ha–1; –917 to +826 kg ha–1) but decreased DM yield at second harvest (–427 kg ha–1; +47 to –936 kg ha–1); (iii) increased neutral detergent fiber (NDF) concentration at first harvest (+22 g kg–1 DM; –22 to +94 g kg–1 DM) but a small decrease (–3 g kg–1 DM; +7 to –30 g kg–1 DM) at second harvest; and (iv) decreased NDF digestibility at first harvest (–6 g kg–1 NDF; +7 to –30 g kg–1 NDF) and second harvest (–23 g kg–1 NDF; –11 to –35 g kg–1 NDF). The longer growing season (+581°C‐d to +1219°C‐d) is expected to result in an additional harvest by 2040 to 2069.

How can forage production in Nordic and Mediterranean Europe adapt to the challenges and opportunities arising from climate change?

“…In winter, when solar irradiation is insufficient for photosynthesis in northern latitudes, the carbon-economy and survival of the plants becomes increasingly important when temperatures exceed 5°C and respiration increases. On the other hand, if temperatures remain cool, shorter winters could leave more C and N reserves in spring, increasing survival and spring DM production (Jing et al, 2013;Piva et al, 2013). Higher temperatures in autumn will shift cold acclimation of the plants to a time when less light is available.…”

“…Higher temperatures lead to earlier stem elongation, a faster rate of decline in cell wall digestibility of both vegetative and reproductive tillers during aging, and hence faster decline in the digestibility of forages (Groot et al, 2003;Thorvaldsson et al, 2007;Bertrand et al, 2008;Bloor et al, 2010;Jing et al, 2013). In addition, higher standing biomass is associated with higher stem-to-leaf proportions and lower digestibility, at least in timothy (Bélanger and McQueen 1998;Bélanger et al, 2001), and thus climate change may lead to lower or higher digestibility through its effect on growth rate, stand density and competition for light.…”

Optimal Regulation of the Balance between Productivity and Overwintering of Perennial Grasses in a Warmer Climate

“…Autumn-extended thermal growing seasons, combined with higher atmospheric CO 2 concentrations, have the potential to increase the productivity of perennial grasses in the autumn [6][7][8][9]. However, since the annual variation in temperature lags behind the annual variation in photoperiod, there is less light in autumn than at comparable temperatures in spring (Figure 1).…”

“…For example, in Finland, where the annual mean temperature has most likely increased by at least 2 • C during the last 150 years [3], the thermal growing season was predicted to become one to three months longer by the end of the century as compared to the period 1971-2000 [4]. Such extended growing seasons are expected to contribute to the increase in annual grassland yields in temperate climates [5][6][7][8][9]. Although the prediction models used so far account for drought limitations on growth, they do not account for possible effects of plant survival during seasonal stresses.…”

Upscaling modelled crop yields to regional scale: A case study using DSSAT for spring wheat on the Canadian prairies

“…Climate change impacts on crop productivity in Canada have been evaluated using dynamic crop growth models applied at a limited number of selected locations (Wang et al 2012;Jing et al 2013Jing et al , 2014Smith et al 2013), but the expansion of the impact analysis to include economic implications using regional agro-economic models such as the Canadian Regional Agricultural Model (CRAM) (Webber et al 1986) requires broadscale regional crop yield data. In order to utilize the predictive capabilities of crop growth models in the assessment of impact and the development of adaptation strategies for the agricultural production industry, methodologies are needed to integrate the spatially precise application of crop growth models with regional socioeconomic models such as CRAM.…”