Differential Maize Yield Hybrid Responses to Stand Density Are Correlated to Their Response to Radiation Reductions Around Flowering

Altered stand density affects maize yields by producing changes in both numerical yield components, kernel number per plant (KNP), and kernel weight (KW). Kernel number is determined by the accumulation of ear biomass during the flowering period, whereas KW is determined by the sink potential established during flowering and the capacity of the plant to fulfill this potential during effective grain filling. Here, we tested if different short shading treatments during different stages around flowering can help discriminate genotypic differences in eco-physiological parameters relevant for maize stand density yield response and associated yield components. Our specific objectives were to: (i) identify hybrids with differential shading stress response, (ii) explore shading effects over eco-physiological parameters mechanistically related to KNP and KW, and (iii) test if shading stress can be used for detecting differential genotypic yield responses to stand density. The objectives were tested using four commercial maize hybrids. Results indicated that KNP was the yield component most related to yield changes across the different shading treatments, and that the specific shading imposed soon after anthesis generated the highest yield reductions. Hybrids less sensitive to shading stress were those that reduced their plant growth rate the least and the ones that accumulated more ear biomass during flowering. Genotype susceptibility to shading stress around flowering was correlated to stand density responses. This indicated that specific shading stress treatments are a useful tool to phenotype for differential stand density responses of commercial hybrids.

Exploiting Plant Functional Diversity in Durum Wheat–Lentil Relay Intercropping to Stabilize Crop Yields under Contrasting Climatic Conditions

Relay intercropping is considered a valuable agroecological practice to increase and stabilize crop yields while ensuring the provision of several ecosystem services as well as sustainability and resilience to changing climatic conditions. However, farmers are still reluctant in the use of intercropping practices since there is a huge knowledge gap regarding the time of sowing, sowing ratio, crop stand density, and cultivar choice. In this study, we carried out a 3-year field experiment in Central Italy to assess the effect of relay intercropping on the agronomic performance and competitiveness of winter durum wheat (Triticum durum Desf. cv. Minosse) and spring lentil (Lens culinaris Medik. cv. Elsa) under a low-input management system, comparing different crop stand types (monocrop vs. intercrop) and target plant densities (350 plants m2—full dose vs. 116 plants m2—1/3 dose). The results revealed that intercropping increased grain yield compared to monocropping: significantly (p < 0.0001) against both monocrops in 2021 and non-significantly against durum wheat in 2019 and 2020. Yield advantage in both intercropping systems ranged between 164 and 648%. Durum wheat competitiveness was stronger in 2019 and 2021, while lentil was the most competitive component in 2020. Intercropping favored P accumulation in durum wheat shoots. There was no difference in grain yield of both crops between the highly- and lowly-dense system in 2020 and 2021. Both intercropping strategies were as effective as mechanical hoeing in controlling weeds and proved beneficial in stabilizing lentil productivity. Further economic analysis capturing the additional costs incurred in intercropping and mechanical weeding would highlight the magnitude of profitability of these systems.

Determining the Optimal Density of Phoebe bournei Plantations Based on Dynamic Programming under Close-to-Nature Management Measures

Close-to-nature management (CTNM) is the most promising option for plantation silviculture and has received widespread attention in recent years. Stand density is a key variable in CTNM, as it directly influences growth and yield. Research for the optimal density that maximizes the total harvest has been ongoing. In this paper, a dynamic programming model was applied to the CTNM of Phoebe bournei plantations for the first time to solve the problem of stand density and target tree density control. This paper took Phoebe bournei plantations in Jindong Forest Farm of Hunan Province as the research object. Based on the data of seven consecutive years from 2015 to 2021, Richard’s growth equation was used to fit the height growth equation and basal area growth equation of Phoebe bournei. Stand growth was divided into five development stages according to the forest growth process and characteristics. Stand density and basal area were selected as two-dimensional state variables, and the maximum total harvest in the entire stand growth process was used as the objective function to establish a dynamic programming model. The optimal stand density and target tree density at each growth stage of the stand under three different site conditions were determined. According to the results obtained, the objective forest shape was designed for the stand under three types of site conditions, which can provide a theoretical basis for the CTNM of Phoebe bournei plantations to make the stand achieve the maximum harvest.

Refining and evaluating a Horvitz– Thompson-like stand density estimator in individual tree detection based on airborne laser scanning

Horvitz--Thompson-like stand density estimation is a method for estimating the stand density from tree crown objects extracted from airborne laser scanning data through individual tree detection. The estimator is based on stochastic geometry and mathematical morphology of the (planar) set formed by the detected tree crowns. This set is used to approximate the detection probabilities of trees. These probabilities are then used to calculate the estimate. The method includes a tuning parameter, which needs to be known to apply the method. We present a refinement of the method to allow more general detection conditions than the previous papers and present and discuss the methods for estimating the tuning parameter of the estimator using a functional $k$-nearest neighbors method. We test the model fitting and prediction in two spatially separate data sets and examine the plot-level accuracy of estimation. The estimator produced a $13$\% lower RMSE than the benchmark method in an external validation data set. We also analyze the effects of similarity and dissimilarity of training and validation data to the results.

Variation of White Spruce Carbon Content with Age, Height, Social Classes and Silvicultural Management

The accuracy and precision with which carbon amounts have been accounted for in forests have been questioned. As countries seek to comply with agreements to reduce global warming and industries seek to maximize bioenergy potential, this matter has increased international concern. White spruce (Picea glauca (Moench) Voss) stand density management trials in the Petawawa Research Forest, Ontario, Canada, were sampled to evaluate carbon concentration variation within trees and plots of differing stand density. Sample-drying methodologies were also tested to compare freeze-dried carbon (FDC) and oven-dried carbon (ODC) measurements. The average FDC was 51.80 ± 1.19%, and the corrected freeze-dried carbon content (FDCCOR) was 51.76 ± 1.33%. The average ODC was 49.10 ± 0.92%, and the average volatile carbon fraction (Cvol) was 2.67 ± 1.71%. FDC was higher than ODC (mean of the differences = 2.52) and generally more variable. ODC significantly decreased radially and longitudinally. FDC was significantly affected by thinning, where heavy treatments resulted in the highest FDC amounts compared to medium, light, and control treatments. In addition to reducing carbon content (CC), drying influences wood CC in many ways that are still to be elucidated. The results of this study suggest that ODC should continue to be used within the bioenergy industry, while FDC must become the preferred standard for carbon accounting protocols.

Modeling natural mortality for different plant densities in dendroenergetic trials

Mortality was modelled for three species (Acacia melanoxylon, Eucalyptus camaldulensis, Eucalyptus nitens) at three plantation densities (5000, 7500, and 10000 trees ha-1) in an trial of biomass production for purposes of dendroenergetic. One modelling based on individual tree level and two mortality modelling alternatives were evaluated: four survival probability equations and eight difference equations. The individual tree survival modelling considered a logistic model, is a linear combination of variables to individual tree at current time and the previous time as estimator, being the main variables the variation of the competition index and the variation of basal area growth between the current growth period and the previous growth period. The survival probability alternative used state variables of the stand (age, dominant height, average square diameter) as predictors, whereas the difference equations were adjusted according to age-based changes only. The models to stand levels showed better result than individual tree models, and in general, the mortality models based on difference equations presented better indicators of precision and parsimony. The rate of relative mortality was constant, i.e., (dN/dE)/N, and varied between species, revealing greater mortality, consecutively, in E. nitens, A. melanoxylon, and E. camaldulensis. Although mortality tended to be higher at greater plantation densities, stand density did not significantly affect the parameters of the adjusted models. Highlights The mortality stand level models showed better results than the individual tree models for dendroenergetic crops, and in general, the mortality models based on difference equations presented better precision indicators and parsimony. The survival probability alternative involved state variables of the stand like age, dominant height, and average square diameter as predictors, while the difference equations were fitted according to age-based changes only. Mortality tended to be higher at greater plantation densities, however stand density did not significantly affect the parameters of the mortality equations.