Grasses

Savanna ecosystems of the Sahel are heavily affected by climate change, leading to drier subtropical regions. These ecosystems play a fundamental role in food security of the region, so that an improved understanding of how these ecosystems are affected by these weather events is thereby critical. Several studies have assessed the herbaceous production level, dynamics during the rainy season, and biotic and abiotic factors that could impact this production. Some authors argue that rain is the main factor positively influencing the biomass production in semi-arid areas where the rainfall ranges between 200 and 750 mm. This study aims to assess the contribution of some meteorological variables to biomass production in a Sahelian semiarid savannah. From 2008 to 2018, rainfall (mm), soil moisture (%), soil temperature (°C) at 5 cm depth, number of times there was no rain (NTNR), number of rainy days, and the herbaceous biomass were monitored. The contributions of meteorological variables to biomass production were calculated using the XGBoost regression model. The most influential meteorological parameters on herbaceous biomass production are soil temperature, amount, and distribution of rainfall.

Bidens pilosa L. is a cosmopolitan and invasive weed that strongly impacts agricultural systems in tropical regions. In Veracruz, Mexico, its presence extends mainly across mid-elevation zones where coffee, maize, and sugarcane are cultivated. This study characterized the bioclimatic and edaphic determinants of B. pilosa distribution using 581 georeferenced occurrences combined with 19 bioclimatic variables, elevation, and soil data. A Maxent model revealed the highest habitat suitability (0.65–1.0) in the central mountainous region between 800 and 1500 m.a.s.l., particularly under temperate–humid climates (Cfa, Cfb) and Acrisol–Leptosol soils. Principal component and redundancy analyses showed that annual precipitation (BIO12), precipitation of the driest month (BIO14), and temperature seasonality (BIO4) explained 74.7% of the total environmental variance. Cluster analysis identified four distinct ecological groups, confirming broad ecological plasticity. These findings indicate that B. pilosa is not randomly distributed but structured along climatic and soil gradients, with precipitation and elevation as major determinants of its ecological niche. Understanding these relationships provides a quantitative framework for predicting its expansion under future climate scenarios and for designing targeted management strategies in tropical agroecosystems.

The use of plant growth simulation models, such as the Agricultural Crop Simulator (AgS), can support planning and management decisions in pasture-based animal production systems. AgS is a biophysical model that is being developed to focus on crops relevant to the Brazilian economy. Originally, the model was parameterized for Marandu palisadegrass (Urochloa brizantha cv. Marandu) under continuous stocking method and cutting regimes. The objective of this study was to parametrize and evaluate the performance of AgS in simulating Marandu palisadegrass biomass production under rotational stocking methods. Field data from an experiment assessing pre-grazing heights of Marandu palisadegrass grazed by beef cattle was used to evaluate the model. The simulations initially underestimated leaf and total biomass production, regardless of pre-grazing height. These results suggested that differences between cutting and grazing methods make additional model calibration necessary. Differences related to regrowth of leaves were addressed and the new calibration resulted in higher biomass allocation to leaves and stems, reducing the mean error in the 25 cm treatment from −1.001 to −253 kg ha⁻¹ and the rRMSE from 41% to 34%. AgS showed potential for simulating rotational stocking after adjustments were made, and future calibrations should consider different management and environmental conditions.