Sorghum is the world’s fifth major cereal in terms of production and acreage. It is expected that its growth will be affected by the increase in air temperature, an important component of global climate change. Our objective was to use the Agricultural Land Management Alternatives with Numerical Assessment Criteria (ALMANAC) model to (a) evaluate the impact of climate warming on forage and grain sorghum production in Argentina and (b) to analyze to what extent yield changes were associated with changes in water or nitrogen stress days. For model calibration, we used previous information related to the morpho-physiological characteristics of both sorghum types and several soil parameters. We then used multiyear field data of sorghum yields for model validation. Yield simulations were conducted under three possible climate change scenarios: 1, 2, and 4 °C increase in mean annual temperature. ALMANAC successfully simulated mean yields of forage and grain sorghum: root mean square error (RMSE): 2.6 and 1.0 Mg ha⁻¹, respectively. Forage yield increased 0.53 Mg ha⁻¹, and grain yield decreased 0.27 Mg ha⁻¹ for each degree of increase in mean annual temperature. Yields of forage sorghum tended to be negatively associated with nitrogen stress (r = −0.94), while grain sorghum yield was negatively associated with water stress (r = −0.99). The information generated allows anticipating future changes in crop management and genetic improvement programs in order to reduce the yield vulnerability.

Rainfall is recognized as a major factor affecting the rate of plant growth development. The impact of changes in amount and variability of rainfall on growth and production of different forage grasses needs to be quantified to determine how climate change can impact rangelands. Comparative studies to evaluate the growth of several perennial forage species at different rainfall rates will provide useful information by identifying forage management strategies under various rainfall scenarios. In this study, the combination of rainfall changes and soil types on the plant growth of 10 perennial forage species was investigated with both the experimental methods, using rainout shelters, and with the numerical methods using the plant growth simulation model, ALMANAC. Overall, most species significantly increased basal diameter and height as rainfall increased. Like measured volume, simulated yields for all species generally increased as rainfall increased. But, large volume and yield increases were only observed between 350 and 850 mm/yr. Simulating all species growing together competing agrees relatively well with observed plant volumes at low rainfall treatment, while simulating all species growing separately was slightly biased towards overestimation on low rainfall effect. Both simulations agree relatively well with observed plant volume at high rainfall treatment

Wetlands provide a wide variety of ecosystem services including water quality remediation, biodiversity refugia, groundwater recharge, and floodwater storage. Realistic estimation of ecosystem service benefits associated with wetlands requires reasonable simulation of the hydrology of each site and realistic simulation of the upland and wetland plant growth cycles. Objectives of this study were to quantify leaf area index (LAI), light extinction coefficient (k), and plant nitrogen (N), phosphorus (P), and potassium (K) concentrations in natural stands of representative plant species for some major plant functional groups in the United States. Functional groups in this study were based on these parameters and plant growth types to enable process‐based modeling. We collected data at four locations representing some of the main wetland regions of the United States. At each site, we collected on‐the‐ground measurements of fraction of light intercepted, LAI, and dry matter within the 2013–2015 growing seasons. Maximum LAI and k variables showed noticeable variations among sites and years, while overall averages and functional group averages give useful estimates for multisite simulation modeling. Variation within each species gives an indication of what can be expected in such natural ecosystems. For P and K, the concentrations from highest to lowest were spikerush (Eleocharis macrostachya), reed canary grass (Phalaris arundinacea), smartweed (Polygonum spp.), cattail (Typha spp.), and hardstem bulrush (Schoenoplectus acutus). Spikerush had the highest N concentration, followed by smartweed, bulrush, reed canary grass, and then cattail. These parameters will be useful for the actual wetland species measured and for the wetland plant functional groups they represent. These parameters and the associated process‐based models offer promise as valuable tools for evaluating environmental benefits of wetlands and for evaluating impacts of various agronomic practices in adjacent areas as they affect wetlands.

While biofuels have been touted as a benefit for growers—with the ability to be planted on marginal lands, for improved wildlife habitat, to sustain soils, and to reduce runoff—there remains to be a general summary of how beneficial they really are. This paper aims to review the environmental effects, feasibility, and economic aspects of using native perennial grasses in North America as biofuels as opposed to traditional annual crops. The Scopus database was used to search for manuscripts relating to each topic. In some instances, very few results appeared, so a second database, Digitop, was also used. Native perennial grasses have been found to sequester carbon and cultivating them can create a carbon sink in the soil. Overall, wildlife benefit more by having native perennial grass for biofuels planted than annual maize and having fewer harvests a season is better for wildlife over the entire year. Economically, growing native perennial grasses can be advantageous especially on marginal land, where it has a comparatively high yield. Although the second-generation biofuel supply chain is susceptible to changing market prices, it can be made more resilient and has advantages, for example resistance against the impacts of drought. Although there are many cultivars to choose from, factors like climate, soil, and genetics can provide pertinent information to match each specimen’s ideal growing conditions to the right location.

As highly productive perennial grasses are evaluated as bioenergy feedstocks, a major consideration is biomass yield stability. Two experiments were conducted to examine some aspects of yield stability for two biofuel species: switchgrass (Panicum vigratum L.) and Miscanthus x giganteus (Mxg). Biomass yields of these species were evaluated under various environmental conditions across the Southern Great Plains (SGP), including some sites with low soil fertility. In the first experiment, measured yields of four switchgrass ecotypes and Mxg varied among locations. Overall, plants showed optimal growth performance in study sites close to their geographical origins. Lowland switchgrass ecotypes and Mxg yields simulated by the ALMANAC model showed reasonable agreement with the measured yields across all study locations, while the simulated yields of upland switchgrass ecotypes were overestimated in northern locations. In the second experiment, examination of different N fertilizer rates revealed switchgrass yield increases over the range of 0, 80, or 160 kg N ha⁻¹ year⁻¹, while Mxg only showed yield increases between the low and medium N rates. This provides useful insights to crop management of two biofuel species and to enhance the predictive accuracy of process-based models, which are critical for developing bioenergy market systems in the SGP.

Although wetlands are an important component of many landscapes, emergent plants have had variable impacts on wetland hydrology. In the present study, similar to what others have done with emergent plants, we investigated the impacts of black willow (Salix nigra Marshall) and Pennsylvania smartweed (Persicaria pensylvanica L.) on water loss from standing water relative to water loss with no emergent plants from 2018 to 2020. Pans were established with soil and standing water for three replications of five treatments: open water control, low population density black willow, high density black willow, low density smartweed, and high density smartweed. Each week during the growing season water levels, water temperature, leaf area index, and height were recorded. Pans were then refilled to the standard level. The assumption was that open water was just evaporation and the increase in water loss in the presence of plants was due to transpiration. Thus, we could partition water loss between evaporation and transpiration by calculating the difference between pans without plants and pans with plants. This difference is the transpiration by the plants. Water temperature was measured to check on any possible shading effect. Open water evaporation was lower than black willow and smartweed evapotranspiration. Mean increases in water use relative to the control were 37% for smartweed and 66% for black willow. These differences were even more dramatic when calculated for only the last 2 years. Smartweed increased water use by 40% and black willow by 92%. Because pans with plants had lower maximum daily water temperatures than those of the control in the summer, the increased water loss with plants was largely due to transpiration. Smartweed transpired more than willows. The willow root system and leaf area greatly increased after the first year, resulting in more water loss and lower summer water temperature. Low and high density treatments did not differ significantly for any metrics gathered, with few exceptions. This evapotranspiration information addresses wetland water balance questions and is useful for process‐based models.