Agriculture plays a crucial role in the economic development in Morocco, contributing to 14% of the national gross domestic product. However, this sector is facing various challenges, including ...climate change. This study aims to assess relevant indicators that may affect land suitability, water demand, and crop growing season duration under climate change. Further, it may be used as a decision support tool in the Chtouka area known for its irrigated agriculture. The approach proposed, the spatial distribution of land based on suitability, is founded on the multiple-criteria decision-making method of four parameters; soil texture, temperature, land use, and slope. The duration of the length of crop season was simulated using the concept of growing degree days. The projection of land suitability for 2031–2050 indicated an important decrease of 12.11% of “highly suitable” agricultural land under the RCP4.5 emission scenario and a significant increase of 4.68% of “highly unsuitable” land, according to the RCP8.5 emission scenario compared to the baseline (1985–2005). The projected growing degree days in 2031–2050 showed a strong shortening in the growing period length compared to the baseline 1985–2006, mainly under the RCP8.5 emission scenario, with a reduction from 8% to 21% depending on crops. Moreover, crop water productivity indicated that berries were over 50% less water productive than other vegetable crops for almost the same amount of applied irrigation water. These findings highlight the vulnerability of agriculture to climate change, which requires important political and management efforts to sustain agricultural activity.
Alpine plants have evolved a tight seasonal cycle of growth and senescence to cope with a short growing season. The potential growing season length (GSL) is increasing because of climate warming, ...possibly prolonging plant growth above- and belowground. We tested whether growth dynamics in typical alpine grassland are altered when the natural GSL (2-3 months) is experimentally advanced and thus, prolonged by 2-4 months. Additional summer months did not extend the growing period, as canopy browning started 34-41 days after the start of the season, even when GSL was more than doubled. Less than 10% of roots were produced during the added months, suggesting that root growth was as conservative as leaf growth. Few species showed a weak second greening under prolonged GSL, but not the dominant sedge. A longer growing season under future climate may therefore not extend growth in this widespread alpine community, but will foster species that follow a less strict phenology.
Crop type maps were created without the traditional need for in-season training data across the Corn Belt and Great Plains regions of the United States. This was accomplished through machine learning ...of historical land cover information, paired with a time-series of multi-spectral satellite imagery composites spanning the growing season, to develop rulesets, which were used for real-time prediction in the current year. Specifically, a decade's worth of annual 30 m resolution crop specific maps, known as the Cropland Data Layer (CDL), provided the foundation, and prior and current year's satellite imagery from Landsat 7 and 8 and Sentinel-2a and -2b built upon it. Four modeling scenarios, all using random forests, were performed to understand the crop mapping abilities of the datasets independently and combined. They were 1) use of CDLs only (i.e. prediction based solely on crop rotation history) 2) use of Landsat 7 and 8 bottom-of-atmosphere surface reflectance imagery only, 3) use of Sentinel-2a and -2b top-of-atmosphere imagery only, and 4) integration of the CDL, Landsat, and Sentinel-2 information together in a unified effort. Furthermore, the model runs were generated monthly, beginning in April, through the growing season to provide understanding of classification performance as a function of time. The 2020 crop year, relatively normal in terms of planting and weather, was used for the test. Accuracy statistics were generated by randomly sampling 50 counties and comparing those classification outputs to the actual 2020 CDL. Pixel-level results showed that prediction by midsummer using only the CDL information provided a crop type map with corn and soybean consumer and producer agreement above 70% and winter wheat just below 50%. The early season imagery-based classifications were markedly worse. However, as Landsat or Sentinel-2 imagery accumulated through July, those classifications became significantly better than those reliant on the use of the CDL information only. Ultimately, the very best crop maps resulted from integrating the CDLs with a full season's worth of Landsat and Sentinel-2 imagery. At that point in late September, the corn and soybean agreements were around 85% and winter wheat near 70%. All analysis was performed within Google Earth Engine cloud-based public imagery repository and high-performance computing system. The classification outputs provide practitioners with US crop type maps in near real-time.
•Pre-growing season crop type maps were generated by modeling crop rotation history.•Those maps were improved within-season by including Landsat and Sentinel-2 imagery.•Mid-July was the time at which the imagery brought improvement to the initial maps.•Best case pixel-level agreement with the Cropland Data Layer was 79% overall.•The classification methodology did not use within-season training data.
A marine sediment phytoremediated and homogenized by landfarming was tested for its potential recycle as growing media in horticulture. Two strawberry cultivars, Camarosa and Monterey, were grown on ...remediated sediment alone (TS100), commercial peat/pumice based growing medium (TS0) and a mixture 1:1 in volume of sediment and peat (TS50). Chemical fertility and strawberry production and safety of produced food were monitored for three consecutive productive seasons on the same growing media. During the first year of cultivation, plants grown on sediment-based media showed a significantly lower biomass production and fruit yield compared with peat, mainly due to the sediment low fertility. In the subsequent two years, the plant re-cultivation improved the sediment structure and N mineralization, and on the third cultivation year both strawberry cultivars showed higher fruit productivity and no accumulation of potentially toxic trace metals. The produced fruits did non accumulate high concentrations of trace metals, and risk assessment showed no risks for human health related to the consumption of strawberry produced on sediment-based growing media. We concluded that a phytoremediated sediment could be recycled as an ingredient of soilless growing media for reducing the environmental impact of plant nursery production and posing no risks for human health. These results show that reclaimed sediments could be reconsidered as a component material category in the new EU regulation on fertilizers.
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•Remediated sediments were used for growing strawberry plants for three cultivation cycles.•Sediment-based growing media increased fertility over time compared to peat growing media.•Strawberry on sediments showed higher productivity over time than those grown on peat.•Strawberry fruits had trace metals concentrations similar to those of plants grown on peat.•No risks for human health related to consumption of fruits produced on sediments was observed.
CONTENTS: Summary 30 I. Allocation in perspective 31 II. Topics of this review 32 III. Methodology 32 IV. Environmental effects 33 V. Ontogeny 36 VI. Differences between species 40 VII. Physiology ...and molecular regulation 41 VIII. Ecological aspects 42 IX. Perspectives 45 Acknowledgements 45 References 45 Appendices A1–A4 49 SUMMARY: We quantified the biomass allocation patterns to leaves, stems and roots in vegetative plants, and how this is influenced by the growth environment, plant size, evolutionary history and competition. Dose–response curves of allocation were constructed by means of a meta‐analysis from a wide array of experimental data. They show that the fraction of whole‐plant mass represented by leaves (LMF) increases most strongly with nutrients and decreases most strongly with light. Correction for size‐induced allocation patterns diminishes the LMF‐response to light, but makes the effect of temperature on LMF more apparent. There is a clear phylogenetic effect on allocation, as eudicots invest relatively more than monocots in leaves, as do gymnosperms compared with woody angiosperms. Plants grown at high densities show a clear increase in the stem fraction. However, in most comparisons across species groups or environmental factors, the variation in LMF is smaller than the variation in one of the other components of the growth analysis equation: the leaf area : leaf mass ratio (SLA). In competitive situations, the stem mass fraction increases to a smaller extent than the specific stem length (stem length : stem mass). Thus, we conclude that plants generally are less able to adjust allocation than to alter organ morphology.
A reasonable representation of plant phenology in land surface models (LSMs) is necessary to accurately simulate the momentum, heat, and mass interchanges between land and the atmosphere from ...ecosystem to global scales. Many process‐based phenology algorithms have been developed and coupled to LSMs to describe seasonal vegetation changes. The growing degree day (GDD) and the growing season index (GSI) algorithms are the two most well‐known algorithms used in LSMs for simulating phenophases. However, assessments of these two most commonly used phenology algorithms in LSMs are quite scarce. In this study, these two phenology algorithms were respectively coupled with the Community Land Model (CLM) and the Dynamic Land Model (DLM) to obtain four modeling scenarios. The simulation accuracy of phenophases and gross primary production (GPP) in the four scenarios was assessed against observations at the site scale, focusing on deciduous forests and grasses. The three main findings were as follows: (a) the difference in simulated phenological events between different LSMs coupled with the same phenological algorithm was small and less than 1 day, DLM performed better than CLM; (b) compared with the GSI algorithm and regardless of whether it was coupled with the DLM or CLM model, the GDD model performance was better for spring phenology and worse for autumn phenology; (c) GSI performance was better than GDD for GPP simulation over different vegetation function types across different bioclimatic zones: on average, the root mean square error and the index of agreement were about 8.0% higher and about 6.5% lower, respectively.
Key Points
The performance of the growing degree day (GDD) model is better for spring and defoliation phenology compared with growing season index (GSI)
Regarding gross primary production simulation, the GSI model is better than the GDD model
Development of a robust phenology model is needed by considering its mechanisms
Numerous complex systems display the multilayer feature rather than the single or isolated one. It is thus significant to study how these structures emerge and the mechanisms behind them. In this ...paper we propose a novel growing model to explain the formation of multilayer networks, where the network growth and strategy evolution in prisoner’s dilemma game interact and coevolve. We introduce the growing rate to control the ratio of strategy evolution to network growth, and the coupling strength to adjust the connecting density between layers. The simulation results show that besides the scale-free property observed in the resulting networks, the coupling strength is significant to cooperative behaviors. Under the weak coupling strength, the role of network reciprocity works and the resulting networks can preserve a relatively high cooperation level; however, with the increase of coupling strength, the role of network reciprocity fades away or disappears. The strong coupling strength, denoting individuals can obtain more extra payoff from their external circumstance, induces a low cooperation level. In addition, the growing rate also influences cooperative behaviors and a fast growing rate is beneficial to cooperation.
•A growing multilayer model incorporating strategy evolution is proposed.•The ratio of network growth to strategy evolution is adjusted by the growing rate.•The connecting density between layers is controlled by the coupling strength.•The structural properties of resulting networks are revealed.•The effects of growing rate and coupling strength on cooperation are investigated.
BACKGROUND:The Shilla procedure was designed to correct and control early-onset spinal deformity while harnessing a child’s remaining spinal growth. It allows for controlled axial skeletal growth ...within the construct, avoiding the need for frequent surgeries to lengthen implants. We hypothesized that curve characteristics evolve over time after initial apex fusion and placement of the Shilla implants. The purpose of this study was to identify trends in curve evolution after Shilla implantation and understand how these changes influence ultimate outcome.
METHODS:A single-center, retrospective review of all patients with Shilla implants in place for ≥5 years yielded 21 patients. Charts and radiographs were reviewed to compare coronal curve characteristics preoperatively, postoperatively, and at last follow-up to note changes in the apex of the primary curve. Also noted were the development of adjacent compensatory curves, the overall vertical spinal growth, and the need for definitive spinal fusion once skeletal maturity was reached.
RESULTS:Of the 21 patients, the curve apex migrated caudally in 12 patients (57%) and cephalad in 1 patient (5%), with a mean migration of 2.7 vertebral levels. Two patients (10%) developed new, significant compensatory curves (1 caudal and 1 cephalad). All patients demonstrated spinal growth in T1-S1 length following index surgery (mean, 45 mm). At skeletal maturity, 10 patients underwent definitive posterior spinal fusion and instrumentation, and 3 underwent implant removal alone.
CONCLUSIONS:This study constitutes the longest follow-up of Shilla patients evaluating curve and implant behavior. Results of this review suggest that the apex of the fused primary curve shifts in approximately 62% of patients, with nearly all of these (92%) involving a distal migration. Compensatory curves did develop after Shilla placement as well. Overall, these findings represent adding-on distal to the apex after Shilla instrumentation rather than a crankshaft phenomenon about the apex. A better understanding of spinal growth mechanics and outcomes after Shilla placement may improve our ability to appropriately select patients and instrumentation levels.
LEVEL OF EVIDENCE:Level III.
Cassava is a staple crop in many nations due to its adaptability to a wide range of climates. It has expanded across tropical Asia, sub-Saharan Africa, and Latin America. Cassava, noted for its high ...carbohydrate content, is third in carbohydrate content after rice and maize. Cassava - Recent Updates on Food, Feed, and Industry is the second edition of our previous book, Cassava - Biology, Production, and Use. This new edition has four sections. The first section discusses the perspectives of several countries on cassava, including food security and the circular economy. Due to the importance of cassava in many countries, the second section examines recent biotechnological advances as well as soil management and modifications in the improvement of cassava. The third section discusses disease management and control of cassava plants. Due to its widespread use and industrial importance, cassava has been subjected to biological and technological intervention for processing into food, feed, and other industrial matter, which is covered in the final section. We hope that this book will help readers gain advanced knowledge about cassava and learn from experts in the field with multiple perspectives.
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