Broadacre Mapping of Wheat Biomass Using Ground-Based LiDAR Technology

Crop biomass is an important attribute to consider in relation to site-specific nitrogen (N) management as critical N levels in plants vary depending on crop biomass. Whilst LiDAR technology has been used extensively in small plot-based phenomics studies, large-scale crop scanning has not yet been reported for cereal crops. A LiDAR sensing system was implemented to map a commercial 64-ha wheat paddock to assess the spatial variability of crop biomass. A proximal active reflectance sensor providing spectral indices and estimates of crop height was used as a comparison for the LiDAR system. Plant samples were collected at targeted locations across the field for the assessment of relationships between sensed and measured crop parameters. The correlation between crop biomass and LiDAR-derived crop height was 0.79, which is similar to results reported for plot scanning studies and greatly superior to results obtained for the spectral sensor tested. The LiDAR mapping showed significant crop biomass variability across the field, with estimated values ranging between 460 and 1900 kg ha−1. The results are encouraging for the use of LiDAR technology for large-scale operations to support site-specific management. To promote such an approach, we encourage the development of an automated, on-the-go data processing capability and dedicated commercial LiDAR systems for field operation.

Simulating organ biomass variability and carbohydrate distribution in perennial fruit crops: a comparison between the common assimilate pool and phloem carbohydrate transport models

Variability in fruit quality greatly impedes the profitability of an orchard. Modelling can help find the causes of quality variability. However, studies suggest that the common assimilate pool model is inadequate in terms of describing variability in organ biomass. The aim of the current study was to compare the performances of the common assimilate pool and phloem carbohydrate transport models in simulating phloem carbohydrate concentration and organ biomass variability within the whole-plant functional-structural grapevine (Vitis vinifera L.) model that we developed previously. A statistical approach was developed for calibrating the model with a detailed potted experiment that entails three levels of leaf area per vine during the fruit ripening period. Global sensitivity analysis illustrated that carbohydrate allocation changed with the amount of leaf area as well as the limiting factors for organ biomass development. Under a homogenous canopy architecture where all grape bunches were equally close to the carbohydrate sources, the common assimilate pool and phloem transport models produced very similar results. However, under a heterogeneous canopy architecture with variable distance between bunches and carbohydrate sources, the coefficient of variation for fruit biomass rose from 0.01 to 0.17 as crop load increased. These results indicate that carbohydrate allocation to fruits is affected by both the size of crop load and fruit distribution, which is not adequately described by the common assimilate pool model. The new grapevine model can also simulate dynamic canopy growth and be adapted to help optimise canopy architecture and quality variability of other perennial fruit crops.

El Niño as a predictor of round sardinella distribution along the northwest African coast

<p>The El Niño Southern Oscillation (ENSO) produces global marine environment conditions that can cause changes in abundance and distribution of distant fish populations worldwide. Understanding mechanisms acting locally on fish population dynamics is crucial to develop forecast skill useful for fisheries management. The present work addresses the role played by ENSO on the round sardinella population biomass and distribution in the central-southern portion of the Canary Current Upwelling System (CCUS). A combined physical-biogeochemical framework is used to understand the climate influence on the hydrodynamical conditions in the study area. Then, an evolutionary individual-based model is used to simulate the round sardinella spatio-temporal biomass variability. According to model experiments, anomalous oceanographic conditions forced by El Niño along the African coast cause anomalies in the latitudinal migration pattern of the species. A robust anomalous increase and decrease of the simulated round sardinella biomass is identified in winter off the Cape Blanc and the Saharan coast region, respectively, in response to El Niño variations. The resultant anomalous pattern is an alteration of the normal migration between the Saharan and the Mauritanian waters. It is primarily explained by the mod- ulating role that El Niño exerts on the currents off Cape Blanc, modifying therefore the normal migration of round sardinella in the search of acceptable temperature conditions. This climate signature can be potentially predicted up to six months in advance based on El Niño conditions in the Pacific.</p>

Increasing contribution of climate variables to the explanation of Quercus spp. single-tree biomass variability in Eurasia as related to model deviation from allometry

Лесные экосистемы, являясь поглотителями атмосферного углерода, играют важную роль в сокращении выбросов CO2 и предотвращении потепления климата. Авторы попытались смоделировать биомассу модельных деревьев Quercus L.,используя данные 500 деревьев, распределенных вдоль транс-евразийских гидротермических градиентов. На сегодняшний день предложено несколько моделей биомассы деревьев и древостоев, включающих в качестве независимых переменных как их морфолого-структурные характеристики, так и климатические показатели. Существующие модели позволяют прогнозировать изменения биомассы вследствие сдвигов климатических трендов, но не показывают вклада климатических переменных в объяснение изменчивости биомассы, которая зависит как от вида дерева и древостоя, так и от структуры модели. Разработанные модели показывают, в какой степени отклонение от классической аллометрической модели, вызванное включением дополнительных независимых переменных, увеличивает вклад климатических переменных в объяснение изменчивости биомассы. Этот вклад наибольший, когда модель включает возраст, диаметр ствола, высоту дерева и их совокупный эффект. 3D-интерпретация«лучшей» модели показала пропеллеро-образную зависимость компонентов биомассы дуба от температуры и осадков, форма которой является зеркальным отражением аналогичной зависимости для биомассы деревьев двухвойных сосен и лиственниц. Это может быть связано с особенностями функционирования лиственных и хвойных видов. Forest ecosystems, as sinks of atmospheric carbon, play an important role in reducing CO2 emissions and preventing annual temperatures from rising. We attempted to model Quercus spp. single-tree biomass using the data from 500 sample trees distributed along the trans-Eurasian hydrothermal gradients. Today, several models of the biomass of trees and stands have been proposed, including both morphological-structural characteristics of trees and stands, and climate indicators as independent variables. The models make it possible to predict changes in biomass due to shifts in climate trends, but do not show the contribution of climate variables to the explanation of biomass variability, which depends on both the species of the tree and stand, and the structure of a model. The models designed show to what extent the deviation from the classical allometric model caused by the inclusion of additional independent variables, increases the contribution of climate variables to the explanation of biomass variability. The model shows the greatest contribution when itincludes age, stem diameter, tree height, and their combined effect. The 3D- interpretation of the «best» model showed a propeller-shaped dependence of the components of oak tree biomass on temperatures and precipitation, the shape of which is a mirror image of a similar dependence for the biomass of trees of two-needled pines and larches. This may be due to the functioning traits of leaved and coniferous species.

Using under-ice hyperspectral transmittance to determine land-fast sea-ice algal biomass in Saroma-ko Lagoon, Hokkaido, Japan

Sea ice, which forms in polar and nonpolar areas, transmits light to ice-associated (sympagic) algal communities. To noninvasively study the distribution of sea-ice algae, empirical relations to estimate its biomass from under-ice hyperspectral irradiance have been developed in the Arctic and Antarctica but lack for nonpolar regions. This study examines relationships between normalised difference indices (NDI) calculated from hyperspectral transmittance and sympagic algal biomass in the nonpolar Saroma-ko Lagoon. We analysed physico-biogeochemical properties of snow and land-fast sea ice supporting 27 paired bio-optical measurements along three transects covering an area of over 250 m × 250 m in February 2019. Snow depth (0.08 ± 0.01 m) and ice-bottom brine volume fraction (0.21 ± 0.02) showed low (0.06) and high (0.58) correlations with sea-ice core bottom section chlorophyll a (Chl. a), respectively. Spatial analyses unveiled the patch size of sea-ice Chl. a to be ~65 m, which is in the same range reported from previous studies. A selected NDI (669, 596 nm) explained 63% of algal biomass variability. This reflects the bio-optical properties and environmental conditions of the lagoon that favour the wavelength pair in the orange/red part of the spectrum and suggests the necessity of a specific bio-optical relationship for Saroma-ko Lagoon.