Elucidating the Space-Time Structure of Low Level Warm Season Precipitation Processes in the Southern Appalachian Mountains Using Models and Observations

Light rainfall is the baseline input to the annual water budget in mountainous landscapes through the tropics and at mid-latitudes. In the Southern Appalachians, the contribution from light rainfall ranges from 50-60% during wet years to 80-90% during dry years, with convective activity and tropical cyclone input providing most of the interannual variability. The Southern Appalachians is a region characterized by rich biodiversity that is vulnerable to land use/land cover changes due to its proximity to a rapidly growing population. Persistent near surface moisture and associated microclimates observed in this region has been well documented since the colonization of the area in terms of species health, fire frequency, and overall biodiversity. The overarching objective of this research is to elucidate the microphysics of light rainfall and the dynamics of low level moisture in the inner region of the Southern Appalachians during the warm season, with a focus on orographically mediated processes. The overarching research hypothesis is that physical processes leading to and governing the life cycle of orographic fog, low level clouds, and precipitation, and their interactions, are strongly tied to landform, land cover, and the diurnal cycles of flow patterns, radiative forcing, and surface fluxes at the ridge-valley scale. The following science questions will be addressed specifically: 1) How do orographic clouds and fog affect the hydrometeorological regime from event to annual scale and as a function of terrain characteristics and land cover?; 2) What are the source areas, governing processes, and relevant time-scales of near surface moisture convergence patterns in the region?; and 3) What are the four dimensional microphysical and dynamical characteristics, including variability and controlling factors and processes, of fog and light rainfall? The research was conducted with two major components: 1) ground-based high-quality observations using multi-sensor platforms and 2) interpretive numerical modeling guided by the analysis of the in situ data collection. Findings illuminate a high level of spatial – down to the ridge scale - and temporal – from event to annual scale - heterogeneity in observations, and a significant impact on the hydrological regime as a result of seeder-feeder interactions among fog, low level clouds, and stratiform rainfall that enhance coalescence efficiency and lead to significantly higher rainfall rates at the land surface. Specifically, results show that enhancement of an event up to one order of magnitude in short-term accumulation can occur as a result of concurrent fog presence. Results also show that events are modulated strongly by terrain characteristics including elevation, slope, geometry, and land cover. These factors produce interactions between highly localized flows and gradients of temperature and moisture with larger scale circulations. Resulting observations of DSD and rainfall patterns are stratified by region and altitude and exhibit clear diurnal and seasonal cycles.

Sedimentology, age models and stable isotope ratios of sediment cores from the equatorial Pacific

Based on detailed reconstructions of global distribution patterns, both paleoproductivity and the benthic d13C record of CO2, which is dissolved in the deep ocean, strongly differed between the Last Glacial Maximum and the Holocene. With the onset of Termination I about 15,000 years ago, the new (export) production of low- and mid-latitude upwelling cells started to decline by more than 2-4 Gt carbon/year. This reduction is regarded as a main factor leading to both the simultaneous rise in atmospheric CO2 as recorded in ice cores and, with a slight delay of more than 1000 years, to a large-scale gradual CO2 depletion of the deep ocean by about 650 Gt C. This estimate is based on an average increase in benthic d13C by 0.4-0.5 per mil. The decrease in new production also matches a clear 13C depletion of organic matter, possibly recording an end of extreme nutrient utilization in upwelling cells. As shown by Sarnthein et al., [1987], the productivity reversal appears to be triggered by a rapid reduction in the strength of meridional trades, which in turn was linked via a shrinking extent of sea ice to a massive increase in high-latitude insolation, i.e., to orbital forcing as primary cause.

Holocene precipitation change in different monsoon sub-regions (time-slices and transient data) simulated by different global climate models, with links to model results

The recently proposed global monsoon hypothesis interprets monsoon systems as part of one global-scale atmospheric overturning circulation, implying a connection between the regional monsoon systems and an in-phase behaviour of all northern hemispheric monsoons on annual timescales (Trenberth et al., 2000). Whether this concept can be applied to past climates and variability on longer timescales is still under debate, because the monsoon systems exhibit different regional characteristics such as different seasonality (i.e. onset, peak, and withdrawal). To investigate the interconnection of different monsoon systems during the pre-industrial Holocene, five transient global climate model simulations have been analysed with respect to the rainfall trend and variability in different sub-domains of the Afro-Asian monsoon region. Our analysis suggests that on millennial timescales with varying orbital forcing, the monsoons do not behave as a tightly connected global system. According to the models, the Indian and North African monsoons are coupled, showing similar rainfall trend and moderate correlation in rainfall variability in all models. The East Asian monsoon changes independently during the Holocene. The dissimilarities in the seasonality of the monsoon sub-systems lead to a stronger response of the North African and Indian monsoon systems to the Holocene insolation forcing than of the East Asian monsoon and affect the seasonal distribution of Holocene rainfall variations. Within the Indian and North African monsoon domain, precipitation solely changes during the summer months, showing a decreasing Holocene precipitation trend. In the East Asian monsoon region, the precipitation signal is determined by an increasing precipitation trend during spring and a decreasing precipitation change during summer, partly balancing each other. A synthesis of reconstructions and the model results do not reveal an impact of the different seasonality on the timing of the Holocene rainfall optimum in the different sub-monsoon systems. They rather indicate locally inhomogeneous rainfall changes and show, that single palaeo-records should not be used to characterise the rainfall change and monsoon evolution for entire monsoon sub-systems.

Investigating the potential magnetic origin of wind variability in OB stars

In this thesis, the origin of large-scale structures in hot star winds, believed to be responsible for the presence of discrete absorption components (DACs) in the absorption troughs of ultraviolet resonance lines, is constrained using both observations and numerical simulations. These structures are understood as arising from bright regions on the stellar surface, although their physical cause remains unknown. First, we use high quality circular spectropolarimetric observations of 13 well-studied OB stars to evaluate the potential role of dipolar magnetic fields in producing DACs. We perform longitudinal field measurements and place limits on the field strength using Bayesian inference, assuming that it is dipolar. No magnetic field was detected within this sample. The derived constraints statistically refute any significant dynamical influence from a magnetic dipole on the wind for all of these stars, ruling out such fields as a cause for DACs. Second, we perform numerical simulations using bright spots constrained by broadband optical photometric observations. We calculate hydrodynamical wind models using three sets of spot sizes and strengths. Co-rotating interaction regions are yielded in each model, and radiative transfer shows that the properties of the variations in the UV resonance lines synthesized from these models are consistent with those found in observed UV spectra, establishing the first consistent link between UV spectroscopic line profile variability and photometric variations and thus supporting the bright spot paradigm (BSP). Finally, we develop and apply a phenomenological model to quantify the measurable effects co-rotating bright spots would have on broadband optical photometry and on the profiles of photopheric lines in optical spectra. This model can be used to evaluate the existence of these spots, and, in the event of their detection, characterize them. Furthermore, a tentative spot evolution model is presented. A preliminary analysis of its output, compared to the observed photometric variations of xi Persei, suggests the possible existence of “active longitudes” on the surface of this star. Future work will expand the range of observational diagnostics that can be interpreted within the BSP, and link phenomenology (bright spots) to physical processes (magnetic spots or non-radial pulsations).

Transferability of Regional Permafrost Disturbance Susceptibility Modelling Using Generalized Linear and Generalized Additive Models

To effectively assess and mitigate risk of permafrost disturbance, disturbance-p rone areas can be predicted through the application of susceptibility models. In this study we developed regional susceptibility models for permafrost disturbances using a field disturbance inventory to test the transferability of the model to a broader region in the Canadian High Arctic. Resulting maps of susceptibility were then used to explore the effect of terrain variables on the occurrence of disturbances within this region. To account for a large range of landscape charac- teristics, the model was calibrated using two locations: Sabine Peninsula, Melville Island, NU, and Fosheim Pen- insula, Ellesmere Island, NU. Spatial patterns of disturbance were predicted with a generalized linear model (GLM) and generalized additive model (GAM), each calibrated using disturbed and randomized undisturbed lo- cations from both locations and GIS-derived terrain predictor variables including slope, potential incoming solar radiation, wetness index, topographic position index, elevation, and distance to water. Each model was validated for the Sabine and Fosheim Peninsulas using independent data sets while the transferability of the model to an independent site was assessed at Cape Bounty, Melville Island, NU. The regional GLM and GAM validated well for both calibration sites (Sabine and Fosheim) with the area under the receiver operating curves (AUROC) N 0.79. Both models were applied directly to Cape Bounty without calibration and validated equally with AUROC's of 0.76; however, each model predicted disturbed and undisturbed samples differently. Addition- ally, the sensitivity of the transferred model was assessed using data sets with different sample sizes. Results in- dicated that models based on larger sample sizes transferred more consistently and captured the variability within the terrain attributes in the respective study areas. Terrain attributes associated with the initiation of dis- turbances were similar regardless of the location. Disturbances commonly occurred on slopes between 4 and 15°, below Holocene marine limit, and in areas with low potential incoming solar radiation

Modeling long-term variability and change of soil moisture and groundwater level - from catchment to global scale

The water stored in and flowing through the subsurface is fundamental for sustaining human activities and needs, feeding water and its constituents to surface water bodies and supporting the functioning of their ecosystems. Quantifying the changes that affect the subsurface water is crucial for our understanding of its dynamics and changes driven by climate change and other changes in the landscape, such as in land-use and water-use. It is inherently difficult to directly measure soil moisture and groundwater levels over large spatial scales and long times. Models are therefore needed to capture the soil moisture and groundwater level dynamics over such large spatiotemporal scales. This thesis develops a modeling framework that allows for long-term catchment-scale screening of soil moisture and groundwater level changes. The novelty in this development resides in an explicit link drawn between catchment-scale hydroclimatic and soil hydraulics conditions, using observed runoff data as an approximation of soil water flux and accounting for the effects of snow storage-melting dynamics on that flux. Both past and future relative changes can be assessed by use of this modeling framework, with future change projections based on common climate model outputs. By direct model-observation comparison, the thesis shows that the developed modeling framework can reproduce the temporal variability of large-scale changes in soil water storage, as obtained from the GRACE satellite product, for most of 25 large study catchments around the world. Also compared with locally measured soil water content and groundwater level in 10 U.S. catchments, the modeling approach can reasonably well reproduce relative seasonal fluctuations around long-term average values. The developed modeling framework is further used to project soil moisture changes due to expected future climate change for 81 catchments around the world. The future soil moisture changes depend on the considered radiative forcing scenario (RCP) but are overall large for the occurrence frequency of dry and wet events and the inter-annual variability of seasonal soil moisture. These changes tend to be higher for the dry events and the dry season, respectively, than for the corresponding wet quantities, indicating increased drought risk for some parts of the world.

Spatio-temporal Variability of Atmospheric Ozone over Indian Subcontinent and its Relation to Meteorological Parameters

Ozone present in the atmosphere not only absorbs the biologically harmful ultraviolet radiation but also is an important ingredient of the climate system. The radiative absorption properties of ozone make it a determining factor in the structure of the atmosphere. Ozone in the troposphere has many negative impacts on humans and other living beings. Another significant aspect is the absorption of outgoing infrared radiation by ozone thus acting as a greenhouse gas. The variability of ozone in the atmosphere involves many interconnections with the incoming and outgoing radiation, temperature circulation etc. Hence ozone forms an important part of chemistry-climate as well as radiative transfer models. This aspect also makes the quantification of ozone more important. The discovery of Antarctic ozone hole and the role of anthropogenic activities in causing it made it possible to plan and implement necessary preventive measures. Continuous monitoring of ozone is also necessary to identify the effect of these preventive steps. The reactions involving the formation and destruction of ozone are influenced significantly by the temperature fluctuations of the atmosphere. On the other hand the variations in ozone can change the temperature structure of the atmosphere. Indian subcontinent is a region having large weather and climate variability which is evident from the large interannual variability of monsoon system over the region. Nearly half of Indian region comprises the tropical region. Most of ozone is formed in the tropical region and transported to higher latitudes. The formation and transport of ozone can be influenced by changes in solar radiation and various atmospheric circulation features. Besides industrial activities and vehicular traffic is more due to its large population. This may give rise to an increase in the production of tropospheric ozone which is greenhouse gas. Hence it becomes necessary to monitor the atmospheric ozone over this region. This study probes into the spatial distribution and temporal evolution of ozone over Indian subcontinent and discusses the contributing atmospheric parameters.

An experiment on the parameter uncertainty of hydrological models with different levels of complexity in a climate change context

La possibilité d’estimer l’impact du changement climatique en cours sur le comportement hydrologique des hydro-systèmes est une nécessité pour anticiper les adaptations inévitables et nécessaires que doivent envisager nos sociétés. Dans ce contexte, ce projet doctoral présente une étude sur l’évaluation de la sensibilité des projections hydrologiques futures à : (i) La non-robustesse de l’identification des paramètres des modèles hydrologiques, (ii) l’utilisation de plusieurs jeux de paramètres équifinaux et (iii) l’utilisation de différentes structures de modèles hydrologiques. Pour quantifier l’impact de la première source d’incertitude sur les sorties des modèles, quatre sous-périodes climatiquement contrastées sont tout d’abord identifiées au sein des chroniques observées. Les modèles sont calés sur chacune de ces quatre périodes et les sorties engendrées sont analysées en calage et en validation en suivant les quatre configurations du Different Splitsample Tests (Klemeš, 1986;Wilby, 2005; Seiller et al. (2012);Refsgaard et al. (2014)). Afin d’étudier la seconde source d’incertitude liée à la structure du modèle, l’équifinalité des jeux de paramètres est ensuite prise en compte en considérant pour chaque type de calage les sorties associées à des jeux de paramètres équifinaux. Enfin, pour évaluer la troisième source d’incertitude, cinq modèles hydrologiques de différents niveaux de complexité sont appliqués (GR4J, MORDOR, HSAMI, SWAT et HYDROTEL) sur le bassin versant québécois de la rivière Au Saumon. Les trois sources d’incertitude sont évaluées à la fois dans conditions climatiques observées passées et dans les conditions climatiques futures. Les résultats montrent que, en tenant compte de la méthode d’évaluation suivie dans ce doctorat, l’utilisation de différents niveaux de complexité des modèles hydrologiques est la principale source de variabilité dans les projections de débits dans des conditions climatiques futures. Ceci est suivi par le manque de robustesse de l’identification des paramètres. Les projections hydrologiques générées par un ensemble de jeux de paramètres équifinaux sont proches de celles associées au jeu de paramètres optimal. Par conséquent, plus d’efforts devraient être investis dans l’amélioration de la robustesse des modèles pour les études d’impact sur le changement climatique, notamment en développant les structures des modèles plus appropriés et en proposant des procédures de calage qui augmentent leur robustesse. Ces travaux permettent d’apporter une réponse détaillée sur notre capacité à réaliser un diagnostic des impacts des changements climatiques sur les ressources hydriques du bassin Au Saumon et de proposer une démarche méthodologique originale d’analyse pouvant être directement appliquée ou adaptée à d’autres contextes hydro-climatiques.

Influence of environmental variability and age on the body condition of small pelagic fish in the Gulf of Lions

Endogenous and environmental variables are fundamental in explaining variations in fish condition. Based on more than 20 yr of fish weight and length data, relative condition indices were computed for anchovy and sardine caught in the Gulf of Lions. Classification and regression trees (CART) were used to identify endogenous factors affecting fish condition, and to group years of similar condition. Both species showed a similar annual cycle with condition being minimal in February and maximal in July. CART identified 3 groups of years where the fish populations generally showed poor, average and good condition and within which condition differed between age classes but not according to sex. In particular, during the period of poor condition (mostly recent years), sardines older than 1 yr appeared to be more strongly affected than younger individuals. Time-series were analyzed using generalized linear models (GLMs) to examine the effects of oceanographic abiotic (temperature, Western Mediterranean Oscillation [WeMO] and Rhone outflow) and biotic (chlorophyll a and 6 plankton classes) factors on fish condition. The selected models explained 48 and 35% of the variance of anchovy and sardine condition, respectively. Sardine condition was negatively related to temperature but positively related to the WeMO and mesozooplankton and diatom concentrations. A positive effect of mesozooplankton and Rhone runoff on anchovy condition was detected. The importance of increasing temperatures and reduced water mixing in the NW Mediterranean Sea, affecting planktonic productivity and thus fish condition by bottom-up control processes, was highlighted by these results. Changes in plankton quality, quantity and phenology could lead to insufficient or inadequate food supply for both species.

Influence of climate variability and stocking strategies on greenhouse gas emissions (GHGE), production and profit of a northern Queensland beef cattle herd

Previous studies of greenhouse gas emissions (GHGE) from beef production systems in northern Australia have been based on models of ‘steady-state’ herd structures that do not take into account the considerable inter-annual variation in liveweight gain, reproduction and mortality rates that occurs due to seasonal conditions. Nor do they consider the implications of flexible stocking strategies designed to adapt these production systems to the highly variable climate. The aim of the present study was to quantify the variation in total GHGE (t CO2e) and GHGE intensity (t CO2e/t liveweight sold) for the beef industry in northern Australia when variability in these factors was considered. A combined GRASP–Enterprise modelling platform was used to simulate a breeding–finishing beef cattle property in the Burdekin River region of northern Queensland, using historical climate data from 1982–2011. GHGE was calculated using the method of Australian National Greenhouse Gas Inventory. Five different stocking-rate strategies were simulated with fixed stocking strategies at moderate and high rates, and three flexible stocking strategies where the stocking rate was adjusted annually by up to 5%, 10% or 20%, according to pasture available at the end of the growing season. Variation in total annual GHGE was lowest in the ‘fixed moderate’ (~9.5 ha/adult equivalent (AE)) stocking strategy, ranging from 3799 to 4471 t CO2e, and highest in the ‘fixed high’ strategy (~5.9 ha/AE), which ranged from 3771 to 7636 t CO2e. The ‘fixed moderate’ strategy had the least variation in GHGE intensity (15.7–19.4 t CO2e/t liveweight sold), while the ‘flexible 20’ strategy (up to 20% annual change in AE) had the largest range (10.5–40.8 t CO2e/t liveweight sold). Across the five stocking strategies, the ‘fixed moderate’ stocking-rate strategy had the highest simulated perennial grass percentage and pasture growth, highest average rate of liveweight gain (121 kg/steer), highest average branding percentage (74%) and lowest average breeding-cow mortality rate (3.9%), resulting in the lowest average GHGE intensity (16.9 t CO2e/t liveweight sold). The ‘fixed high’ stocking rate strategy (~5.9 ha/AE) performed the poorest in each of these measures, while the three flexible stocking strategies were intermediate. The ‘fixed moderate’ stocking strategy also yielded the highest average gross margin per AE carried and per hectare. These results highlight the importance of considering the influence of climate variability on stocking-rate management strategies and herd performance when estimating GHGE. The results also support a body of previous work that has recommended the adoption of moderate stocking strategies to enhance the profitability and ecological stability of beef production systems in northern Australia.

Oceanic control of multidecadal variability in an idealized coupled GCM

Idealized ocean models are known to develop intrinsic multidecadal oscillations of the meridional overturning circulation (MOC). Here we explore the role of ocean–atmosphere interactions on this low-frequency variability. We use a coupled ocean–atmosphere model set up in a flat-bottom aquaplanet geometry with two meridional boundaries. The model is run at three different horizontal resolutions (4°, 2° and 1°) in both the ocean and atmosphere. At all resolutions, the MOC exhibits spontaneous variability on multidecadal timescales in the range 30–40 years, associated with the propagation of large-scale baroclinic Rossby waves across the Atlantic-like basin. The unstable region of growth of these waves through the long wave limit of baroclinic instability shifts from the eastern boundary at coarse resolution to the western boundary at higher resolution. Increasing the horizontal resolution enhances both intrinsic atmospheric variability and ocean–atmosphere interactions. In particular, the simulated atmospheric annular mode becomes significantly correlated to the MOC variability at 1° resolution. An ocean-only simulation conducted for this specific case underscores the disruptive but not essential influence of air–sea interactions on the low-frequency variability. This study demonstrates that an atmospheric annular mode leading MOC changes by about 2 years (as found at 1° resolution) does not imply that the low-frequency variability originates from air–sea interactions.

Stochastic simulation of time-series models combined with geostatistics to predict water-table scenarios in a Guarani Aquifer System outcrop area, Brazil

Stochastic methods based on time-series modeling combined with geostatistics can be useful tools to describe the variability of water-table levels in time and space and to account for uncertainty. Monitoring water-level networks can give information about the dynamic of the aquifer domain in both dimensions. Time-series modeling is an elegant way to treat monitoring data without the complexity of physical mechanistic models. Time-series model predictions can be interpolated spatially, with the spatial differences in water-table dynamics determined by the spatial variation in the system properties and the temporal variation driven by the dynamics of the inputs into the system. An integration of stochastic methods is presented, based on time-series modeling and geostatistics as a framework to predict water levels for decision making in groundwater management and land-use planning. The methodology is applied in a case study in a Guarani Aquifer System (GAS) outcrop area located in the southeastern part of Brazil. Communication of results in a clear and understandable form, via simulated scenarios, is discussed as an alternative, when translating scientific knowledge into applications of stochastic hydrogeology in large aquifers with limited monitoring network coverage like the GAS.

Characterizing, modelling and understanding the climate variability of the deep water formation in the North-Western Mediterranean Sea

Observing, modelling and understanding the climate-scale variability of the deep water formation (DWF) in the North-Western Mediterranean Sea remains today very challenging. In this study, we first characterize the interannual variability of this phenomenon by a thorough reanalysis of observations in order to establish reference time series. These quantitative indicators include 31 observed years for the yearly maximum mixed layer depth over the period 1980–2013 and a detailed multi-indicator description of the period 2007–2013. Then a 1980–2013 hindcast simulation is performed with a fully-coupled regional climate system model including the high-resolution representation of the regional atmosphere, ocean, land-surface and rivers. The simulation reproduces quantitatively well the mean behaviour and the large interannual variability of the DWF phenomenon. The model shows convection deeper than 1000 m in 2/3 of the modelled winters, a mean DWF rate equal to 0.35 Sv with maximum values of 1.7 (resp. 1.6) Sv in 2013 (resp. 2005). Using the model results, the winter-integrated buoyancy loss over the Gulf of Lions is identified as the primary driving factor of the DWF interannual variability and explains, alone, around 50 % of its variance. It is itself explained by the occurrence of few stormy days during winter. At daily scale, the Atlantic ridge weather regime is identified as favourable to strong buoyancy losses and therefore DWF, whereas the positive phase of the North Atlantic oscillation is unfavourable. The driving role of the vertical stratification in autumn, a measure of the water column inhibition to mixing, has also been analyzed. Combining both driving factors allows to explain more than 70 % of the interannual variance of the phenomenon and in particular the occurrence of the five strongest convective years of the model (1981, 1999, 2005, 2009, 2013). The model simulates qualitatively well the trends in the deep waters (warming, saltening, increase in the dense water volume, increase in the bottom water density) despite an underestimation of the salinity and density trends. These deep trends come from a heat and salt accumulation during the 1980s and the 1990s in the surface and intermediate layers of the Gulf of Lions before being transferred stepwise towards the deep layers when very convective years occur in 1999 and later. The salinity increase in the near Atlantic Ocean surface layers seems to be the external forcing that finally leads to these deep trends. In the future, our results may allow to better understand the behaviour of the DWF phenomenon in Mediterranean Sea simulations in hindcast, forecast, reanalysis or future climate change scenario modes. The robustness of the obtained results must be however confirmed in multi-model studies.

Phosphoglucose isomerase variability of Cerastoderma glaucum as a model for testing the influence of environmental conditions and dispersal patterns through quantitative ecology approaches

Extreme conditions of coastal lagoons could directly modify the genetic patterns of species. The aim of this work was to investigate the influence of environmental conditions and small scale dispersal patterns on the phosphoglucose isomerase (PGI*) genetic variability of Cerastoderma glaucum from the Mar Menor coastal lagoon. For this purpose, 284 cockles were collected around the perimeter of the lagoon. Vertical polyacrylamide gel electrophoresis was used to scan for PGI* polymorphisms, giving a total of seven alleles. The spatial genetic distribution of the PGI* variability, which seems to be marked by the main circulation in the lagoon, discriminates four hydrological basins. In the central basin, a gradient of allelic composition reflects the circulation forced by the dominant winds and the main channel communicated to the open sea. This result is well supported by the salinity GAM model that defines this gradient. The other three basins are defined by the distribution of fine sand in a more complex model that tries to explain the isolation of the three sites localized inside these basins. The southern, western and northern basins show the lowest degree of interconnection and are considered the most confined areas of the Mar Menor lagoon. This situation agrees with the confinement theory for benthic assemblages in the lagoon. The greater degree of differentiation seen in the Isla del Ciervo population is probably due to recent human intervention on the nearby Marchamalo channel, which has been drained in recent years thus altering the influence of the Mediterranean Sea on the southern basin.

Estimation of leaf area in grapevine cv. Syrah using empirical models

Aiming to obtain empirical models for the estimation of Syrah leaf area a set of 210 fruiting shoots was randomly collected during the 2013 growing season in an adult experimental vineyard, located in Lisbon, Portugal. Samples of 30 fruiting shoots were taken periodically from the stage of inflorescences visible to veraison (7 sampling dates). At the lab, from each shoot, primary and lateral leaves were separated and numbered according to node insertion. For each leaf, the length of the central and lateral veins was recorded and then the leaf area was measured by a leaf area meter. For single leaf area estimation the best statistical models uses as explanatory variable the sum of the lengths of the two lateral leaf veins. For the estimation of leaf area per shoot it was followed the approach of Lopes & Pinto (2005), based on 3 explanatory variables: number of primary leaves and area of the largest and smallest leaves. The best statistical model for estimation of primary leaf area per shoot uses a calculated variable obtained from the average of the largest and smallest primary leaf area multiplied by the number of primary leaves. For lateral leaf area estimation another model using the same type of calculated variable is also presented. All models explain a very high proportion of variability in leaf area. Our results confirm the already reported strong importance of the three measured variables (number of leaves and area of the largest and smallest leaf) as predictors of the shoot leaf area. The proposed models can be used to accurately predict Syrah primary and secondary leaf area per shoot in any phase of the growing cycle. They are inexpensive, practical, non-destructive methods which do not require specialized staff or expensive equipment.