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Abstract

Scalable indicators are promising to assess ecosystem services. In a large (660 ha) coffee agroforestry farm, we calibrated the relationship between the Normalized Difference Vegetation Index (NDVI), calculated on a High Resolution (HR) satellite image and ground-truth LAI, providing a 2-layer (shade trees and coffee) LAI calibration with LAI 2000 and a new technique based on the cumulative distribution of LAI along transects. The effective and apparent clumping of coffee leaves were computed (0.76 and 0.89, respectively). We also calibrated the relationship between the derived HR-LAI farm map and NDVI from the Moderate Resolution Imaging Spectroradiometer (MODIS) in order to re-construct LAI time-series (2001–2011).

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... data), but growth ceased during the drier period, corresponding also to the minimum leaf area index (LAI). LAI fluctuated seasonally in the farm between 2Á2 and 4Á4 m 2 leaf m À2 soil (Taugourdeau et al., 2014). To comply with the eco-certification criteria of the Rainforest Alliance TM (promoting tall trees to provide more habitats for biodiversity), shade was provided in the coffee plots since 2001 by growing Erythrina poeppigiana (Walp.) ...
... In 2010, trees had an average canopy height of 20 m and a planting density of 7Á4 trees ha À1 . The mean canopy projection was assessed on 570 ha by Taugourdeau et al. (2014) and was 15Á7 6 5Á5 % (mean 6 s.d.). ...
... Integrating the temporal variability is a clear advantage of the sequential coring method over trench excavations and could explain the difference we obtained between the two methods. We encountered higher values of fine root biomass during the wet months, i.e. periods where LAI was also higher (Taugourdeau et al., 2014). We observed that the lowest value of fine root biomass was observed in February, which is the driest month of the year and also corresponds to the minimum LAI. ...
Article
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Background and aims: In Costa Rica, coffee (Coffea arabica) plants are often grown in agroforests. However, it is not known if shade-inducing trees reduce coffee plant biomass through root competition, and hence alter overall net primary productivity (NPP). We estimated biomass and NPP at the stand level, taking into account deep roots and the position of plants with regard to trees. Methods: Stem growth and root biomass, turnover and decomposition were measured in mixed coffee/tree (Erythrina poeppigiana) plantations. Growth ring width and number at the stem base were estimated along with stem basal area on a range of plant sizes. Root biomass and fine root density were measured in trenches to a depth of 4 m. To take into account the below-ground heterogeneity of the agroforestry system, fine root turnover was measured by sequential soil coring (to a depth of 30 cm) over 1 year and at different locations (in full sun or under trees and in rows/inter-rows). Allometric relationships were used to calculate NPP of perennial components, which was then scaled up to the stand level. Key results: Annual ring width at the stem base increased up to 2·5 mm yr(-1) with plant age (over a 44-year period). Nearly all (92 %) coffee root biomass was located in the top 1·5 m, and only 8 % from 1·5 m to a depth of 4 m. Perennial woody root biomass was 16 t ha(-1) and NPP of perennial roots was 1·3 t ha(-1) yr(-1) Fine root biomass (0-30 cm) was two-fold higher in the row compared with between rows. Fine root biomass was 2·29 t ha(-1) (12 % of total root biomass) and NPP of fine roots was 2·96 t ha(-1) yr(-1) (69 % of total root NPP). Fine root turnover was 1·3 yr(-1) and lifespan was 0·8 years. Conclusions: Coffee root systems comprised 49 % of the total plant biomass; such a high ratio is possibly a consequence of shoot pruning. There was no significant effect of trees on coffee fine root biomass, suggesting that coffee root systems are very competitive in the topsoil.
... Agroforestry systems (AFS) are probably the most complex perennial agroecosystems (Mal� ezieux et al., 2009), because they have the most heterogeneous vertical and/or horizontal canopies, and these affect all ecosystem fluxes Vezy et al., 2018). Yet, AFS have the potential to enhance ecosystem services (Jose, 2009;Lin, 2010;Taugourdeau et al., 2014) such as carbon sequestration (Jose and Bardhan, 2012;Oelbermann et al., 2004), and to mitigate climate pressure on crops (Lin, 2007). ...
... Van Oijen et al. (2010)b, andlater Rahn et al. (2018), who further developed the CAF2007 model, proposed a calibration based on an extensive screening of the literature and a sensitivity analysis, but no model evaluation against field data at this stage. Alternatively, we propose a multiple-objective strategy of evaluation in this study, relying on a large range of state and flux variables measured at the same time by the end of the crop rotation, including eddy-covariance fluxes, coffee and shade tree biomass measured at organ scale, necromass, yield, NPP, water balance and energy balance, and finally farm registers to describe management during a complete rotation (Charbonnier et al., , 2017Defrenet, 2016;G� omez-Delgado et al., 2011;Taugourdeau et al., 2014;Vezy et al., 2018). ...
... monitored continuously since 2009 and located on the Aquiares coffee farm. This research site has been intensively studied and described in detail, notably for hydrology and eddy-covariance by G� omez-Delgado et al. (2011); LAI by Taugourdeau et al. (2014); light budget by ; belowground biomass and NPP by Defrenet, 2016, ecosystem biomass, NPP andLUE by Charbonnier et al. (2017); and energy balance, water balance and surface temperature by Vezy et al. (2018). ...
Article
The DynACof model was designed to model coffee agroforestry systems and study the trade-offs to e.g. optimize the system facing climate changes. The model simulates net primary productivity (NPP), growth, yield, mortality, energy and water balance of coffee agroforestry systems according to shade tree species and management. Several plot-scale ecosystem services are simulated by the model, such as production, canopy cooling effect, or potential C sequestration. DynACof uses metamodels derived from a detailed 3D process-based model (MAESPA) to account for complex spatial effects, while running fast. It also includes a coffee flower bud and fruit cohort module to better distribute fruit carbon demand over the year, a key feature to obtain a realistic competition between sinks. The model was parameterized and evaluated using a highly comprehensive database on a coffee agroforestry experimental site in Costa Rica. The fluxes simulated by the model were close to the measurements over a 5-year period (nRMSE = 26.27 for gross primary productivity; 28.22 for actual evapo-transpiration, 53.91 for sensible heat flux and 15.26 for net radiation), and DynACof satisfactorily simulated the yield, NPP, mortality and carbon stock for each coffee organ type over a 35-year rotation.
... Agroforestry systems (AFS) are probably the most complex perennial agroecosystems (Malézieux et al., 2009), because they have the most heterogeneous vertical and/or horizontal canopies, and these affect all ecosystem fluxes Vezy et al., 2018). Yet, AFS have the potential to enhance ecosystem services (Jose, 2009;Lin, 2010;Taugourdeau et al., 2014) such as carbon sequestration (Jose and Bardhan, 2012;Oelbermann et al., 2004), and to mitigate climate pressure on crops (Lin, 2007). ...
... Van Oijen et al. (2010b), and later Rahn et al. (2018), who further developed the CAF2007 model, proposed a Bayesian calibration based on an extensive screening of the literature and a sensitivity analysis, but no model evaluation against field data at this stage. Alternatively, we propose a multipleobjective strategy of evaluation in this study, relying on a large range of state and flux variables measured at the same time by the end of the crop rotation, including eddy-covariance fluxes, coffee and shade tree biomass measured at organ scale, necromass, yield, NPP, water balance and energy balance, and finally farm registers to describe management during a complete rotation Charbonnier et al., 2017;Defrenet et al., 2016;Gómez-Delgado et al., 2011;Taugourdeau et al., 2014;Vezy et al., 2018). ...
... year of the simulation (Figure 4). The leaves of E. poeppigiana shed naturally between January and February in Aquiares and then recover rapidly until May (Taugourdeau et al., 2014). The observed phenology was matched by the model, with a simulated range and dynamic of LAI values close to the observations made in the same plot averaged over the whole measurement period (Taugourdeau et al., 2014). ...
Preprint
Full-text available
The DynACof model was designed to model coffee agroforestry systems and study the trade-offs to e.g. optimize the system facing climate changes. The model simulates net primary productivity (NPP), growth, yield, mortality, energy and water balance of coffee agroforestry systems according to shade tree species and management. Several plot-scale ecosystem services are simulated by the model, such as production, canopy cooling effect, or potential C sequestration. DynACof uses metamodels derived from a detailed 3D process-based model (MAESPA) to account for complex spatial effects, while running fast. It also includes a coffee flower bud and fruit cohort module to better distribute fruit carbon demand over the year, a key feature to obtain a realistic competition between sinks. We compared the model outputs with a highly comprehensive database on a coffee agroforestry farm in Costa Rica. The fluxes simulated by the model were close to the measurements over a 5-year period (RMSE= 1.60 gC m-2 d-1 for gross primary productivity; 0.63 mm d-1 for actual evapo-transpiration, 1.34 MJ m-2 d-1 for sensible heat flux and 1.88 MJ m-2 d-1 for net radiation), and DynACof satisfactorily simulated the yield, NPP, mortality and carbon stock for each coffee organ type over a 35-year rotation. The preprint is archived on ZENODO (https://zenodo.org/record/3246268). DynACof model website: https://vezy.github.io/DynACof
... O.F. Cook trees that have a mean density of 7.4 trees ha −1 ( Figure S1). Average canopy height of E. poeppigiana trees is approximately 20 m resulting in a leaf-area index (LAI) of 0.67 for the entire study area based on LAI measurements taken above the coffee canopy as described by Taugourdeau et al. (2014). E. poeppigiana is native to humid and subhumid tropical lowlands and is characterized by a trunk that is branchless up to a height of 5 m, where it then has a moderately spreading crown (Orwa et al., 2009) that fully defoliates in mid-February during the middle of the dry season (Taugourdeau et al., 2014). ...
... Average canopy height of E. poeppigiana trees is approximately 20 m resulting in a leaf-area index (LAI) of 0.67 for the entire study area based on LAI measurements taken above the coffee canopy as described by Taugourdeau et al. (2014). E. poeppigiana is native to humid and subhumid tropical lowlands and is characterized by a trunk that is branchless up to a height of 5 m, where it then has a moderately spreading crown (Orwa et al., 2009) that fully defoliates in mid-February during the middle of the dry season (Taugourdeau et al., 2014). ...
... Resprouts are selectively pruned every 5 to 6 years as soon as the production of fruiting nodes decreases, which results in a significant reduction in LAI and a strong spatial heterogeneity of the coffee layer (Charbonnier et al., 2017). Coffee LAI is also strongly seasonal ranging between 2.4 during the dry season to 4 in the wet season (Taugourdeau et al., 2014), yet coffee never defoliates like E. poeppigiana. Thus, during the dry season, E. poeppigiana can be fully defoliated, leaving the soil bare, whereas coffee still covers the soil against evaporation. ...
Article
Full-text available
Despite the widely held assumption that trees negatively affect the local water budget in densely planted tree plantations, we still lack a clear understanding of the underlying processes by which canopy cover influences local soil water dynamics in more open, humid tropical ecosystems. In this study, we propose a new conceptual model that uses a combination of stable isotope and soil moisture measurements throughout the soil profile to assess potential mechanisms by which evaporation (of surface soil water and of canopy-intercepted rainfall) affects the relationship between surface soil water isotopic enrichment (lc-excess) and soil water content (SWC). Our conceptual model was derived from soil water data collected under deciduous and evergreen plants in a shade grown coffee agroforestry system in Costa Rica. Reduced soil moisture under shade trees during the “drier” season, coinciding when these trees were defoliated, was largely the result of increase soil water evaporation as indicated by the positive relationship between soil water content and lc-excess of surface soil water. In contrast, the evergreen coffee shrubs had a higher leaf area index during the “drier” season, leading to enhanced rainfall interception and a negative relationship between lc-excess and soil water content. During the wet season, there was no clear relationship between soil water content and between lc-excess of surface soil water. Greater surface soil water under coffee during the dry season may, in part, explain greater preferential flow under coffee compared to under trees in conditions of low rainfall intensities. However, with increasing rainfall intensities during the wet season there was no obvious difference in preferential flow between the two canopy covers. Results from this study indicate that our new conceptual model can be used to help disentangling the relative influence of canopy cover on local soil water isotopic composition and dynamics, yet also stresses the need for additional measurements to better resolve the underlying processes by which canopy structure influences local water dynamics.
... The portion of interest in the Aquiares plot has an area of approximately 1.3 ha, but is surrounded by similar plantations within the 660-ha Aquiares coffee farm. Resprouts are pruned selectively every five to six years (as soon as they become less productive), thereby creating a Coffea layer whose foliage is very heterogeneous horizontally (Charbonnier, 2013;Taugourdeau et al., 2014). Stand-scale values (Table 1) of sensible-heat flux (H, W m −2 ), latent-heat flux (LE, W m −2 ), net radiation (R n , W m −2 ), and foliage temperature (T canopy ,°C) were retrieved from the FLUXNET 2015 dataset (CR-AqC 2009. ...
... The Aquiares site was parameterized following Charbonnier (2013) for the part concerning the light interception. LAI dynamics of Coffea and Erythrina were reported in Taugourdeau et al. (2014). Photosynthesis parameters were obtained from Charbonnier (2013). ...
... Our results show that the two management practices at the CATIE site (Coffea in full sun, or shaded by C + E) had a relatively similar leaf + soil evaporation because the leaf evaporation doubled in the shaded plot due to a higher LAI, while the soil evaporation halved because of shading. LAI's effect (via shade-tree density) upon the partitioning between green water (evapotranspiration) and blue water (infiltration, aquifer recharge, streamflow) has already been stressed by Taugourdeau et al. (2014) in the same region. The partitioning can affect water management dramatically at regional scale because of its influence upon the extent to which rainfall recycles back into the atmosphere, as opposed to entering soil water stocks. ...
... At the plot level and for various ecosystems, LAI can be considered an important parameter to analyze coffee ecosystem services (Taugourdeau et al., 2014). An increase of LAI due to shade-grown coffee interfere with the microclimate (Barradas & Fanjul, 1986;Ong et al., 2000), evapotranspiration (Padovan et al., 2018), hydrological behavior (Gómez-Delgado et al., 2011), erosion control (Ataroff & Monasterio, 1997), biomass and growth (Rodríguez-López et al., 2014) production (Alves et al., 2016) and net primary productivities (Defrenet et al., 2016;Charbonnier et al., 2017). ...
... The study of Coffee LAI, a parameter derived from MODIS sensor (Moderate Resolution Imaging Spectroradiometer) realized by Taugourdeau et al. (2014) in the central Caribbean region, reports that the seasonal variation of the LAI ranged from 2.4 to 4.4. The authors indicate that, for perennial crops such as coffee, LAI may vary seasonally due to abiotic factors such as drought, shade, temperatures, and biological factors, such as diseases and overproduction, or even by pruning or fertilization. ...
... Also sometimes some periods in a year, the locally measured coffee shrub experience higher soil evaporation (E) than leaf area transpiration (T) and Kc serves the critical purpose of representing averaged E and T process (Pereira et al., 2015b). In this work, the negative correlation between the two biophysical variables analyzed (Figure 7) may be acceptable (or reasonable) since the estimated Kc values by Allen et al. (1998); Doorenbos and Pruitt (1977); Flumignan et al. (2011);and Sato et al. (2007); and the LAI values by Taugourdeau et al. (2014); Pereira et al. (2011) were consistent with the results. ...
Article
Full-text available
Robust monitoring techniques for perennial crops have become increasingly possible due to technological advances in the area of Remote Sensing (RS), and the products are available through the European Space Agency (ESA) initiative. RS data provides valuable opportunities for detailed assessments of crop conditions at plot level using high spatial, spectral, and temporal resolution. This study addresses the monitoring of coffee at the plot level using RS, analyzing the relationship between the spatio-temporal variability of the Leaf Area Index (LAI) and the crop coefficient (Kc); the Kc being a biophysical variable that integrates the potential hydrological characteristics of an agroecosystem compared to the reference crop. Daily and one-year Kc were estimated using the relation of crop evapotranspiration and reference. ESA Sentinel-2 images were pre-analyzed and atmospherically corrected, and Top-of-the-Atmosphere (TOA) reflections converted to Top-of-the-Canopy (TOC) reflectance. The TOCs resampled at the 10m resolution, and with the angles corresponding to the directional information at the time of the acquisition, the LAI was estimated using the trained neural network available in the Sentinel Application Platform (SNAP). During 75% of the monitored days, Kc ranged between 1.2 and 1.3 and, the LAI analyzed showed high spatial and temporal variability at the plot level. Based on the relationship between the biophysical variables, the LAI variable can substitute the Kc and be used to monitor the water conditions at the production area as well as analyze spatial variability inside that area. Sentinel-2 products could be more useful in monitoring coffee in the farm production area.
... Pruning results in (1) multi-stemmed stumps with heterogeneous resprout ages; (2) the absence of ca. 2-3 years of fruit production before the young resprout is able to flower; and (3) dynamic variations of intra-specific competition Taugourdeau et al. 2014). We hypothesize here that the most-important variables impacting NPP and C-allocation at the plant scale are resprout age, shade intensity, initial fruit load and intraspecific competition. ...
... Coffee seedlings were initially planted during the 1970s at 6300 locations ha À1 with one or two seedlings per location. The residual density during our experiment was 5580 locations ha À1 (Taugourdeau et al. 2014). The plantation is managed as an uneven-aged coppice with one to three resprouts per stump, and one to two stumps per location. ...
... Coffee LAI was recorded daily by proxy detection with a NDVI sensor (Pontailler & Hymus 2003) located on an eddycovariance tower, after calibration with direct records and monthly LAI2000 transects, showing an exponential fit (LAI coffee,measured = 0.00289 * e (8.945*NDVI) ; n = 304; RMSE = 0.51; P < 2e À16 ) (Charbonnier et al. 2013, Eqn 1;Taugourdeau et al. 2014). It varied from 1.6 to 4.5 m 2 m À2 , with a mean of 3.5 m 2 m À2 . ...
... Pruning results in (1) multi-stemmed stumps with heterogeneous resprout ages; (2) the absence of ca. 2-3 years of fruit production before the young resprout is able to flower; and (3) dynamic variations of intra-specific competition Taugourdeau et al. 2014). We hypothesize here that the most-important variables impacting NPP and C-allocation at the plant scale are resprout age, shade intensity, initial fruit load and intraspecific competition. ...
... Coffee seedlings were initially planted during the 1970s at 6300 locations ha À1 with one or two seedlings per location. The residual density during our experiment was 5580 locations ha À1 (Taugourdeau et al. 2014). The plantation is managed as an uneven-aged coppice with one to three resprouts per stump, and one to two stumps per location. ...
... Coffee LAI was recorded daily by proxy detection with a NDVI sensor (Pontailler & Hymus 2003) located on an eddycovariance tower, after calibration with direct records and monthly LAI2000 transects, showing an exponential fit (LAI coffee,measured = 0.00289 * e (8.945*NDVI) ; n = 304; RMSE = 0.51; P < 2e À16 ) (Charbonnier et al. 2013, Eqn 1;Taugourdeau et al. 2014). It varied from 1.6 to 4.5 m 2 m À2 , with a mean of 3.5 m 2 m À2 . ...
Article
Full-text available
In agroforestry systems, shade trees strongly affect the physiology of the undergrown crop. However, a major paradigm is that the reduction in absorbed photosynthetically active radiation is, to a certain extent, compensated by an increase in light-use efficiency, thereby reducing the difference in net primary productivity between shaded and non-shaded plants. Due to the large spatial heterogeneity in agroforestry systems and the lack of appropriate tools, the combined effects of such variables have seldom been analysed, even though they may help understand physiological processes underlying yield dynamics. In this study, we monitored net primary productivity, during two years, on scales ranging from individual coffee plants to the entire plot. Absorbed radiation was mapped with a 3D-model (MAESPA). Light-use efficiency and net assimilation rate were derived for each coffee plant individually. We found that although irradiance was reduced by 60% below crowns of shade trees, coffee light-use efficiency increased by 50%, leaving net primary productivity fairly stable across all shade levels. Variability of aboveground net primary productivity of coffee plants was caused primarily by the age of the plants and by intraspecific competition among them (drivers usually overlooked in the agroforestry literature) rather than by the presence of shade trees.
... Success in the combined provision of goods and services by agroforestry systems depends on delicate equilibria between the plant species involved, which can oscillate between competition and facilitation depending on the species involved, their management, or the environmental conditions (Jose 2009;De Beenhouwer et al. 2013;Taugourdeau et al. 2014). No combination of crop and tree species exists that can be used everywhere. ...
... Numerous processes are closely interrelated, so it is difficult to parameterize one process without having previously parameterized other connected processes. Measurements on diverse processes in coffee agroforestry systems have been carried out in experiments and in commercial plantations for some years now (van Oijen et al. 2010a;Haggar et al. 2011;Charbonnier et al. 2013;Meylan et al. 2013;Taugourdeau et al. 2014;Gagliardi et al. 2015;Padovan et al. 2015;Villatoro-Sánchez et al. 2015;Defrenet et al. 2016). This parameterization, necessary as it is to use a model with reasonable confidence, cannot be done everywhere. ...
Article
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Coffee is often grown in production systems associated with shade trees that provide different ecosystem services. Management, weather and soil conditions are spatially variable production factors. CAF2007 is a dynamic model for coffee agroforestry systems that takes these factors as inputs and simulates the processes underlying berry production at the field scale. There remain, however, uncertainties about process rates that need to be reduced through calibration. Bayesian statistics using Markov chain Monte Carlo algorithms is increasingly used for calibration of parameter-rich models. However, very few studies have employed multi-site calibration, which aims to reduce parameter uncertainties using data from multiple sites simultaneously. The main objectives of this study were to calibrate the coffee agroforestry model using data gathered in long-term experiments in Costa Rica and Nicaragua, and to test the calibrated model against independent data from commercial coffee-growing farms. Two sub-models were improved: calculation of flowering date and the modelling of biennial production patterns. The modified model, referred to as CAF2014, can be downloaded at https://doi.org/10.5281/zenodo.3608877. Calibration improved model performance (higher R2, lower RMSE) for Turrialba (Costa Rica) and Masatepe (Nicaragua), including when all experiments were pooled together. Multi-site and single-site Bayesian calibration led to similar RMSE. Validation on new data from coffee-growing farms revealed that both calibration methods improved simulation of yield and its bienniality. The thus improved model was used to test the effect of N fertilizer and shade in different locations on coffee yield.
... We calibrated the relationship between the Normalized Difference Vegetation Index (NDVI), calculated on a High Resolution (HR) satellite image and ground-truth LAI, providing a 2-layer (shade trees and coffee) LAI calibration with LAI 2000 and a new technique based on the cumulative distribution of LAI along transects. We also calibrated the relationship between the derived HR-LAI farm map and NDVI from the Moderate Resolution Imaging Spectroradiometer (MODIS) in order to re-construct LAI time-series (2001-2011) (Le , Taugourdeau et al., 2014. ...
... The relationship between LAI and hydrological services was modelled. When LAI was doubled from 3.8 to 7.6, river streamflow was reduced by 17%, evapotranspiration was increased by 60%, superficial runoff was decreased by 1% and the amount of water flowing through the Aquifer was reduced by 20% (Taugourdeau et al., 2014). ...
Conference Paper
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Eight years of monitoring ecophysiology and ecosystem services (ES) in a large coffee farm of Costa Rica yields a range of practical applications for the farmer and stakeholders, thanks to numerous scientific actors and disciplines contributing to our collaborative observatory (Coffee-Flux). • A lot of ecosystem services depend on the soil properties, such as runoff/infiltration, water and nutrient storage capacity. It is essential to relate hydrological and soil conservation services to the soil type since this might have even more importance than the crop itself for ES. Regarding the use of fertilizer, we show that some soils may have a large storage capacity, allowing producing coffee at normal yields with just a reduced, or even a minimum amount of fertilizers, for instance when the economic conditions are unfavourable. Also, due to the soil variability within the farm, it is possible to adjust fertilization to micro-local conditions and reduce the total expenses and risks of leaching of N to the environment. VNIRS and MIR are promising broadband tools for screening the variability in soils. Adjusting N fertilizer to the optimum will also considerably reduce the N2O emissions and improve the GHG balance of the farm. • Pesticides-fungicides: we show that an adequate amount of shade trees allows reducing the severity of the whole complex of leaf diseases. This also should reduce expenses and impacts on the ecosystem. • Roots: a simple survey of basal area at collar allows estimating the belowground biomass and the average age of a plantation, to judge of its market value and to decide when to replace it. • Also starch plays a key role in the trophic equilibrium between the perennial parts of the coffee plant (aerial stump, belowground stump, coarse roots) and its ephemeral parts (resprout, leaves, fruits, fine roots). Coffee plants accumulate starch in the stumps by the end of the life of their resprout, as a strategy for survival. Breeding plants with less starch build-up capacity would probably allow increasing the fraction of productive years during the lifespan of the resprouts. • Coffee farms are probably much closer to C neutrality than currently admitted using the C-Neutrality protocol. We stress the prevailing role of coffee plants + litter + soil in the ecosystem C balance. If those are excluded from the calculations as done so far, coffee farms are GHG sources, by definition. We argue that either full assessments (as proposed here, at the ecosystem level, including trees, coffee, litter, soil and roots) or consensus on “sequestration factors” (the counterpart of emission factors) would allow performing a more realistic assessment of the GHG balance. • Finally, we bring new data confirming that shade trees offer numerous ecosystem services when adequately managed for the local context. As compared to full sun conditions, they may (i) reduce laminar erosion by a factor of ca. 2, (ii) increase the atmospheric N2 fixation and the % of N recycled into the system, thus reducing the fertilizer requirements, (iii) reduce the severity of the leaf disease complex, (iv) increase C sequestration, (v) improve the microclimate, and (vi) be a large part of the solution to face climate changes. All this is possible without negative effects on profitability or yield if managed properly.
... Errors in NDVI values could largely be due to the mixture of information available on soil, other vegetation, and different plant intervals. Furthermore, the NDVI values can change depending on the phenological characteristics, the climatic factors and the management (Taugourdeau et al. 2014). As a result of the lack of an appropriate monitoring method, many studies for coffee leaf rust have focused on the development of disease-resistant varieties and pest control. ...
... The horizontal axis of each graph is NDVI values in the farm, Here, we should stress that the individual use of NDVI and σ NDVI is unfavourable for the damage discrimination. NDVI as the damaged indicator is insufficient since the values have a yearly change; the NDVI values can change depending on the phenological characteristics, the climatic factors and the management of coffee plants (Taugourdeau et al. 2014). Besides, the use of σ NDVI alone is inadequate for monitoring, because a distribution arises in the NDVI values depending on management after felling coffee plants to prevent infection spread, as indicated by aeronautical photos of damaged farms. ...
Article
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Coffee leaf rust is for the coffee industry potentially one of the causes of a sustainability crisis. Currently, on-site disease detection is the only effective method to fell coffee trees for prevention of the infection. However, accurate infection detection over wide areas is difficult when conducted by ground surveys. Here, we examine the application of a remote sensing method. The Normalized Difference Vegetation Index (NDVI) values of coffee farms were computed using satellite images and compared with the results of the ground truth. We found that the standard deviation of the NDVI value (σNDVI) in damaged farms increases as the average NDVI value decreases. This fact implies that the disease progresses in-homogeneously inside a damaged area. In the present analysis, up to 94.1% of the damaged farms were discriminated by combining the NDVI and σNDVI thresholds when 75.0% of the damaged farms had NDVI values under 0.732 and σNDVI over 0.044. Our monitoring method enabled us to take early-stage countermeasures against the infection, and it could be applied to other vegetation diseases.
... In the same model, LAI serves to model the relative light capture by crops or trees and determines their growth rate (Hussain et al., 2015a(Hussain et al., , 2015b. LAI, thus, significantly contributes to plant growth and agronomic models (Taugourdeau et al., 2014) from plantation via watershed to landscape scale hydrological cycles and carbon storage potential. However the accuracy of determining LAI dynamics in growing crops or plantations remains a challenge due to the spatial and temporal variability, stand heterogeneity and stratification as well as seasonal and inter-annual variability (Bréda, 2003). ...
... Indirect measuring techniques for LAI include the use of field-based non-destructive optical or spectral methods (reviewed by Bréda, 2003) and satellite based remote sensing. Several authors have reported using remote sensing techniques, most commonly NDVI measurements, in combination with LAI from ground truth activities (Pradeep et al., 2014, Rusli and Majid, 2014, Taugourdeau et al., 2014. NASA e.g. is offering global datasets of MODIS based LAI. ...
Article
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In order to estimate water use, water requirements and carbon sequestration of tropical plantation systems such as rubber it is adamant to have accurate information on leaf area development of the plantation as the main determinant of evapotranspiration. Literature commonly suggests a number of different methods on how to obtain leaf area index (LAI) information from tree plantation systems. Methods include destructive measurements of leaf area at peak LAI, indirect methods such as gap fraction methods (i.e. Hemiview and LAI 2000) and radiation interception methods (i.e. SunScan) or litter fall traps. Published values for peak LAI in rubber plantation differ widely and show no clear trend to be explained by management practices or the influence of local climate patterns. This study compares four methods for determining LAI of rubber plantations of different ages in Xishuangbanna, Yunnan, PR China. We have tested indirect measurement techniques such as light absorption and gap fraction measurements and hemispherical image analysis against litter fall data in order to obtain insights into the reliability of these measuring techniques for the use in tropical tree plantation systems. In addition, we have included data from destructive harvesting as a comparison. The results presented here clearly showed that there was no consistent agreement between the different measurements. Site, time of the day and incoming radiation all had a significant effect on the results depending on the devices used. This leaves us with the conclusion that the integration of published data on LAI in rubber into broad ranging assessments is very difficult to accomplish as the accuracy of the measurements seems to be very sensitive to a number of factors. This diminishes the usefulness of literature data in estimating evapotranspiration from rubber plantations and the induced environmental effects, both on local as well as regional levels.
... Phenological information supports crop productivity and crop management (Sakamoto et al., 2005;Couto Junior et al., 2013). Vegetation indices (VIs) are sensitive to phenological changes and have been used to correlate with agricultural productivity (Bolton & Friedl, 2013;Kogan et al., 2013;Fu et al., 2014), to estimate attributes such as Foliar Area Index that can be related to agricultural yield (Rembold et al., 2013;Taugourdeau et al., 2014;Jiang et al., 2014;Li et al., 2017;Liaqat et al., 2017) or to be incorporated into modeling (Padilla et al., 2012;Meroni et al., 2013;Kowalik et al., 2014). The incorporation of remote sensing data to the modeling improves the estimation of the agricultural yield, since a multispectral evaluation of the cultures state within a certain area can be obtained favoring the study of the relations of the plant with the environment (Delécolle et al., 1992;Rudorff & Batista, 1990). ...
... As reinforced by Rezende et al. (2014) and Taugourdeau et al. (2014), because it is a complex analysis target, the research on indirect methods of measuring coffee agronomic parameters is scarce. In this context, the objective of this study was to evaluate the relationship between yield of coffee crops and vegetation indexes with and without topographic correction derived from the OLI / Landsat-8 sensor for the 2013/2014 and 2014/2015 crops. ...
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The reflectance values of a coffee crop are influenced by several factors such as planting direction, crop spacing, time of the year, plant age and topography which reduces the accuracy of the estimates derived from remote sensing data. In this context were evaluated the relationships between coffee productivity and values of NDVI, SAVI and NDWI vegetation indexes with and without topographic reflectance correction for different coffee phenological phases for the crop years 2013/2014 (low productivity) and 2014/2015 (high productivity). The evaluations were made through the standard deviation of vegetation indices (VIs), linear relationship between the cosine factor and the VIs and between VIs and coffee productivity. The best phenological phases of coffee to determine productivity from spectral indexes were the stages of dormancy and flowering. The results indicated that the NDVI was the best index to estimate the productivity of coffee trees with coefficient of determination (R2) that ranged from 0.58 to 0.90. There was an increase in R2 between productivity and NDVI with topographic correction in the dormancy phase in the year of low productivity; between productivity and NDVI with topographic correction in the flowering phase in the year of high productivity; and between productivity and SAVI and NDWI with topographic corrections in the flowering phase in the year of high productivity.
... The farm is situated at 1020 m above sea level on the slopes of Turrialba Volcano, where the dominant soil type are Andisols (USDA 1999). From 1973 to 2009, mean annual rainfall at the site was approximately 3014 mm, with the lowest monthly rainfall (below 200 mm month -1 ) occurring between February and April (Taugourdeau et al. 2014). At the site individual coffee plants of a single genotype (C. ...
... arabica var. Caturra) are intercropped with both free-growing and pruned Erythrina poeppigiana (Fabaceae), which are the most widely planted shade tree species used in agroforestry throughout Costa Rica (Haggar et al. 2011;Taugourdeau et al. 2014). At the farm, coffee is planted at densities of 5000 trees ha -1 , and intercropped with E. poeppigiana, which are planted at densities of 3 trees ha -1 . ...
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Intraspecific variation in leaf functional traits has gained widespread attention as a means to evaluate, predict, and manage plant responses to environmental conditions, however there are considerable uncertainties regarding the extent and drivers of intraspecific trait variation (ITV) in domesticated plants. In a coffee (Coffea arabica) agroforestry system, we quantified ITV in seven leaf traits [i.e. area (LA), mass per area (LMA), dry matter content (LDMC), thickness (Lth), nitrogen concentrations (LNC), maximum photosynthetic rate on area and mass bases (Asat, Amass, respectively)] across managed gradients of soil fertility and light availability. Leaf physiological traits (Asat, Amass), as well as LA, showed the greatest extent of variation within coffee, while morphological traits (LMA, LDMC, Lth) and leaf N were less variable. All traits differed significantly as a function of light and fertilization treatment, however light was more influential in driving ITV in coffee leaves. Low light availability resulted in greater ITV for physiological leaf traits (Asat and Amass), while high light constrained ITV in most morphological-(LA, LMA, LDMC), physiological-(Asat, Amass) and chemical-(LNC) traits. Fertilization treatments did not induce systematic shifts in the extent of ITV. In addition, shade management treatments explained 9.2% of the variation in multivariate trait syndromes, while nutrient management regimes explained only 2.9%. Our results indicate that highly heterogeneous aboveground resource environments such those created by agroforestry, results in greater ITV for key crop physiological parameters. Based on ecological theory, such patterns indicate that management systems promoting resource heterogeneity should promote higher rates of resource partitioning, and greater resource-use efficiency in agroecosystems.
... Eleven measurements were made for each treatment throughout the seasons. The total leaf area for each plant and measurement was determined using Eq. 1 [33,38]: ...
Article
Rapid and reliable measurements of leaf area index (LAI) of soybeans are important for modelling biophysical processes, energy and water flux and management of weeds in the plant communities. AccuPAR LP 80 and central leaflet width method were used in computing green LAI (gLAI) of two varieties of row spaced rainfed soybeans: TGX 1448 2E and TGX 1440 1E for two seasons. There were five levels of soil fertility which generated 2 by 5 factorial experiments that were arranged in a randomised complete block design. The gLAI estimated during the initial, development, reproductive and maturity of the crop was compared using regression analysis. The gLAI obtained by the methods was significantly correlated (0.77 ≤ r² ≤ 0.99, p < 0.0001; standard error of estimate, 0.05 ≤ SEE ≤ 0.67) in the two seasons. Pooled over the seasons and dataset, the two methods were linearly correlated (r² = 0.89, p < 0.0001; SEE = 0.53). Degree of agreement ranged from 0.96 to 1.00 in the seasons. Regression coefficients ranged from 0.50 to 1.21, while the intercepts were between − 0.15 and 0.78 which indicates deviation from 1:1 line. Mean biased error ranged from − 1.74 to 0.19. AccuPAR LP 80 underestimated LAI from flowering or LAI ≥ 1.11 m² m⁻² and overestimated it during initial and late seasons. Considering the overall performance of the sensor and the rapid measurements, the sensor gave reliable and useful LAI for row spaced rainfed soybeans.
... Traditionally, some important crop traits, including leaf area index, leaf chlorophyll and yield were measured manually with ground based equipment or sensors (Gitelson, 2004;Sankaran et al., 2015a;Taugourdeau et al., 2014), which are time consuming and labor intensity (Bellvert et al., 2014). The field based devices usually take measurement in a small scale, such as several leaves, plant parts, and may result in substantial measurement error due to the variation within crops. ...
Article
In this study, three different sensing technologies were evaluated for their performance in monitoring pinto beans crop stress at early stages. Treatments involved replicate pinto bean field plots with 50% and 100% irrigation throughout the season. Eight different pinto bean cultivars were seeded on the plots prepared with either strip or conventional tillage method. Evaluated technologies were a handheld linear ceptometer, and multi-spectral proximal and aerial remote sensing technologies. Spatial resolutions of the aerial remote sensing images acquired from 100 m above ground level (AGL) and the proximal sensing images acquired at 6.7 m AGL were 35.2 and 5.6 mm·pixel⁻¹, respectively. Crop indictors of leaf area index (LAI), green normalized difference vegetation index (GNDVI) and canopy cover (CC) were extracted from the data of ceptometer and multispectral sensors collected at the early stages of pinto beans on July of 2015. Results show that spatial coverage of aerial remote sensing was thus 700 times larger than that of proximal remote sensing utilized in this study. GNDVI and CC data from both aerial and proximal remote sensing was able to discriminate crops with different irrigation and tillage treatment significantly at 5% level. Similarly, leaf area index (LAI) from ground sensor (ceptometer) was also able to distinguish effects of different irrigations, but could not differentiate tillage treatments. Correlation trends showed that the aerial remote sensing and ground sensing based indicators were strongly related with crop yield compared to proximal remote sensing based indicators. Although data were collected for natural light variations, possibly latter sensing module had more predominant light variation effect on image quality at different imaging times on given imaging day.
... Coffee plants are deeply rooted, down to 4 m (Defrenet et al., 2016). Coffee leaf area index varies seasonally between 2.4 and 4.4 m 2 m −2 and approximately 0.67 m 2 m −2 for the shade trees (Taugourdeau et al., 2014). ...
Article
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Stable isotope variations are extremely useful for flow partitioning within the hydrologic cycle but remain poorly understood throughout the tropics, particularly in watersheds with rapidly infiltrating soils, such as Andisols in Central America. This study examines the fluctuations of stable isotope ratios (δ¹⁸O and δ²H) in the hydrologic components of a tropical coffee agroforestry watershed (~1 km²) with Andisol soils in Costa Rica. Samples were collected in precipitation, groundwater, springs, and stream water over two years. The Local Meteoric Water Line for the study site was δ²H = 8.5 δ¹⁸O + 18.02 (r² = 0.97, n=198). The isotope ratios in precipitation exhibited an enriched trend during the dry season and a notable depletion at the beginning of the wet season. The δ¹⁸O compositions in groundwater (average = ‐6.4‰, σ = 0.7) and stream water (average = ‐6.7‰, σ = 0.6) were relatively stable over time, and both components exhibited more enriched values in 2013, which was the drier year. No strong correlation was observed between the isotope ratios and the precipitation amount at the event or daily time‐step, but a correlation was observed on a monthly scale. Stream water and base flow hydrograph separations based on isotope end‐member estimations showed that pre‐event water originating from base flow was prevalent. However, isotope data indicate that event water originating from springs appears to have been the primary driver of initial rises in stream flow and peak flows. These results indicate that isotope sampling improves the understanding of water balance components, even in a tropical humid location, where significant variations in rainfall challenge current modeling efforts. Further research using fine‐scale hydrometric and isotopic data would enhance understanding the processes driving spring flow generation in watersheds.
... La principal limitante para esta estimación, es el tiempo requerido para registrar el largo y/o el ancho de cada hoja, dependiendo de la edad de la planta (15). Taugourdeau et al. (26), estimaron el área foliar de una planta de café (C. arabica L.), multiplicando el número de hojas por el promedio de área foliar evaluado en cada 20ª hoja medida. ...
Article
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Los modelos que describen relaciones alométricas, basados en el conteo de hojas, son métodos no destructivos, fáciles y económicos para estimar el área foliar en árboles. Con este propósito se realizaron mediciones del área foliar, censando las hojas en varios árboles de café Variedad Castillo® (Coffea arabica L.) de diferentes edades, estableciendo y validando la relación entre el área foliar de la rama y el número de hojas en ella, a través de una regresión lineal simple, con coeficientes de regresión diferentes de cero, según prueba de t, al 5%. Posteriormente, se evaluó la estimación del área foliar a nivel de árbol con respecto a los valores observados. Además, con la información registrada se determinó el número de ramas por árbol en las cuales deben contarse el número de hojas, para estimar el área foliar del árbol, con un error menor del 20%, y se estableció una primera relación entre el área foliar y la producción en café cereza verde, con un coeficiente de determinación del 78,3%.
... The main use of RS data in ES mapping is still land cover classification (de Araujo Barbosa et al., 2015). Some studies obtain ES from RS data, but apply relatively phenomenological relationships between ES and RS proxies (e.g., vegetation indices) that do not follow the ES cascade and limit their applicability across ecosystems (Krishnaswamy et al., 2009;Taugourdeau et al., 2014). Only a few recent ES mapping studies applied advanced RS products (e.g. ...
Article
Spatially well-informed decisions are essential to sustain and regulate processes and ecosystem services (ES), and to maintain the capacity of ecosystems to supply services. However, spatially explicit ES information is often lacking in decision-making, or exists only as ES maps based on categorical land cover data. Remote sensing (RS) opens new pathways to map ES, in particular biophysical ES supply. We developed an observation-based concept for spatially explicit and continuous ES mapping at landscape scale following the biophysical part of the ES cascade. We used Earth observations in combination with in situ data to map ecosystem properties, functions, and biophysical ES supply. We applied this concept in a case study to map two ES: carbon dioxide regulation and food supply. Based on Earth observations and in situ data, we determined the ecosystem property Sun-Induced chlorophyll Fluorescence (SIF) to indicate ecosystem state and applied scaling models to estimate gross primary production (GPP) as indicator for ecosystem functioning and consequently carbon dioxide regulation and food supply as ES.
... Nevertheless, for their formulation, it should not only be considered as a technological issue but also should include the environmental, social, institutional, and economic aspects related to sustainability (Spangenberg, 2004). Indicators can be applied to natural elements, such as the environment (Zhang, 2015), ecosystems (Fu et al., 2015), forest management (Gossner et al., 2014), water (Lobato et al., 2015;Perez et al., 2014) and land (Zhao et al., 2013;Rosén et al., 2015), as well as to socio-economic-institutional issues related to water resources, i.e. water economic value (Hellegers et al., 2010), urban water systems (Spiller, 2016), governance (Norman et al., 2013;Pires and Fidélis, 2015), political framework (Blanchet and Girois, 2012) and management (Taugourdeau et al., 2014). Several authors (Juwana et al., 2012;Spangenberg, 2008;McCool and Stankey, 2004) mention that the rise of sustainable development concepts and environmental concerns have led to an extensive and intense application of indicators by a wide range of users in different contexts. ...
Article
The scientific community strongly recommends the adoption of indicators for the evaluation and monitoring of progress towards sustainable development. Furthermore, international organizations consider that indicators are powerful decision-making tools. Nevertheless, the quality and reliability of the indicators depends on the application of adequate and appropriate criteria to assess them. The general objective of this study was to evaluate how indicators related to water use and management perform against a set of sustainability criteria. Our research identified 170 indicators related to water use and management. These indicators were assessed by an international panel of experts that evaluated whether they fulfil the four sustainability criteria: social, economic, environmental, and institutional. We employed an evaluation matrix that classified all indicators according to the DPSIR (Driving Forces, Pressures, States, Impacts and Responses) framework. A pilot study served to test and approve the research methodology before carrying out the full implementation. The findings of the study show that 24 indicators comply with the majority of the sustainability criteria; 59 indicators are bi-dimensional (meaning that they comply with two sustainability criteria); 86 are one-dimensional indicators (fulfilling just one of the four sustainability criteria) and one indicator do not fulfil any of the sustainability criteria.
... The proper decision making for field management is facilitated by accurate site-specific crop information, which requires timely and high-resolution data for support. Conventionally, crop response to different field managements can be monitored using groundbased sensors, such as a handheld ceptometer to measure leaf area index (Delalieux et al. 2008) and a chlorophyll meter to measure leaf greenness (Gitelson 2004;Taugourdeau et al. 2014). However, such methods are often time-consuming and not suitable for large areas, and may not be adequate to acquire sufficient information for overall crop management. ...
Article
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Site-specific crop management is a promising approach to maximize crop yield with optimal use of rapidly depleting natural resources. Availability of high resolution crop data at critical growth stages is a key for real-time data-driven decisions during the production season. The goal of this study was to evaluate the possibility of using small unmanned aerial system (UAS)-based remote sensing technologies to monitor the crop stress of irrigated pinto beans (Phaseolus vulgaris L.) with varied irrigation and tillage treatments. A small UAS with onboard multispectral and infrared thermal imaging sensors was used to collect data from bean field plots on three growth stages in 2015 and 2016, respectively. Indicators including green normalized vegetation index (GNDVI), canopy cover (CC, ratio of ground covered by crop canopy to the total plot area) and canopy temperature (CT, °C) of crops were extracted from imaging data and correlated with ground-reference crop yield and leaf area index (LAI) estimated with a handheld ceptometer. Results show that GNDVI, CC and CT were able to differentiate crops with full and deficit irrigation treatments at each of the three growth stages in both years. Developed indicators were strongly correlated with to the crop yield with Pearson correlation coefficients (r) of approximate 0.71 and 0.72 for GNDVI and CC, respectively, in the early growth stage (54 days after planting) in both years. Canopy temperature showed even stronger correlation (r > 0.8) with yield at early growth stage. Performance of small UAS-based imagery-based indicators in crop stress monitoring and crop yield estimation was better than or comparable to that of the ground-based LAI estimates, indicating the potential of such remote sensing tool in rapid crop stress monitoring and management.
... Leaf area index (LAI) is extensively applied to observe and monitor ecosystem functions (e.g., vegetation growth, and physiological activity) [1][2][3]. Due to the control of LAI over primary production (e.g., photosynthesis), transpiration, evapotranspiration, energy exchange as well as other physiological characteristics pertinent to the wide range of ecosystem processes, the accurate prediction of LAI has been a concern for a broad spectrum of studies [4][5][6][7][8][9]. Moreover, LAI has lately been suggested as being one of the essential biodiversity variables (EBVs) that are suitable for satellite monitoring, among many other variables [10,11]. ...
Article
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Leaf area index (LAI) has been investigated in multiple studies, either by means of visible/near-infrared and shortwave-infrared or thermal infrared remotely sensed data, with various degrees of accuracy. However, it is not yet known how the integration of visible/near and shortwave-infrared and thermal infrared data affect estimates of LAI. In this study, we examined the utility of Landsat-8 thermal infrared data together with its spectral data from the visible/near and shortwave-infrared region to quantify the LAI of a mixed temperate forest in Germany. A field campaign was carried out in August 2015, in the Bavarian Forest National Park, concurrent with the time of the Landsat-8 overpass, and a number of forest structural parameters, including LAI and proportion of vegetation cover, were measured for 37 plots. A normalised difference vegetation index threshold method was applied to calculate land surface emissivity and land surface temperature and their relations to LAI were investigated. Next, the relation between LAI and eight commonly used vegetation indices were examined using the visible/near-infrared and shortwave-infrared remote sensing data. Finally, the artificial neural network was used to predict the LAI using: (i) reflectance data from the Landsat-8 operational land imager (OLI) sensor; (ii) reflectance data from the OLI sensor and the land surface emissivity; and (iii) reflectance data from the OLI sensor and land surface temperature. A stronger relationship was observed between LAI and land surface emissivity compared to that between LAI and land surface temperature. In general, LAI was predicted with relatively low accuracy by means of the vegetation indices. Among the studied vegetation indices, the modified vegetation index had the highest accuracy for LAI prediction (R 2 CV = 0.33, RMSE CV = 1.21 m 2 m −2). Nevertheless, using the visible/near-infrared and shortwave-infrared spectral data in the artificial neural network, the prediction accuracy of LAI increased (R 2 CV = 0.58, RMSE CV = 0.83 m 2 m −2). The integration of reflectance and land surface emissivity significantly improved the prediction accuracy of the LAI (R 2 CV = 0.81, RMSE CV = 0.63 m 2 m −2). For the first time, our results demonstrate that the combination of Landsat-8 reflectance spectral data from the visible/near-infrared and shortwave-infrared domain and thermal infrared data can boost the estimation accuracy of the LAI in a forest ecosystem. This finding has implication for the prediction of other vegetation biophysical, or possibly biochemical variables using thermal infrared satellite remote sensing data, as well as regional mapping of LAI when coupled with a canopy radiative transfer model.
... Agroforestry systems as an alternative to full sun production are proposed to have numerous benefits including protection of soil and water resources (Beer et al. 1998), reduced erosion and nitrogen leaching (DaMatta 2004;Tully et al. 2012), buffering of climate extremes (Lin 2007), less microclimatic variation (Gomes et al. 2016), higher carbon storage as well as higher local biodiversity (Tscharntke et al. 2011;Ehrenbergerová et al. 2016) and enhanced resource capture, such as light (Taugourdeau et al. 2014). Legume shade tree species have been also shown to compensate for lower external inputs (Nygren et al. 2012) and under sub-optimal growing conditions shaded coffee out-produced full sun and had lower yield bienniality (DaMatta 2004;Vaast et al. 2005). ...
Article
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Greater understanding of the influences on long-term coffee productivity are needed to develop systems that are profitable, while maximizing ecosystem services and lowering negative environmental impacts. We examine a long-term experiment (15 years) established in Costa Rica in 2000 and compare intensive conventional (IC) coffee production under full sun with 19 agroforestry systems combining timber and service tree species with contrasting characteristics, with conventional and organic managements of different intensities. We assessed productivity through coffee yield and coffee morphological characteristics. IC had the highest productivity but had the highest yield bienniality; in the agroforestry systems productivity was similar for moderate conventional (MC) and intensive organic (IO) treatments (yield 5.3 vs 5.0 t/ha/year). Significantly lower yields were observed under shade than full sun, but coffee morphology was similar. Low input organic production (LO) declined to zero under the shade of the non-legume timber tree Terminalia amazonia but when legume tree species were chosen (Erythrina poepiggiana, Chloroleucon eurycyclum) LO coffee yield was not significantly different than for IO. For the first 6 years, coffee yield was higher under the shade of timber trees (Chloroleucon and Terminalia), while in the subsequent 7 years, Erythrina systems were more productive, presumably this is due to lower shade covers. If IC full sun plantations are not affordable or desired in the future, organic production is an interesting alternative with similar productivity to MC management and in LO systems incorporation of legume tree species is shown to be essential.
... Leaf Area Index (LAI) of coffee and shade trees was measured every three months for 2010 and monthly for 2011-2012. Each subplot was measured using a Plant Canopy Analyzer LAI2000 (LI-COR, Lincoln, NE, USA), previously calibrated on another study site with the same coffee variety (Taugourdeau et al., 2014). The LAI for Erythrina and banana shade trees was calibrated by correlating LAI measures with infield measurements of total leaf count per tree, and average leaf width. ...
Article
Intensively managed cropping systems with emphasis on productivity of the main crop can benefit from additional ecosystem services brought by integration of trees in the system − but potential drawbacks must also be accounted for. In an on-farm study, we used a variety of plant, soil and water- related variables to assess the effect of Erythrina spp. and Musa spp. on the provision of ecosystem services in productive, high-quality Coffea arabica plantations in Costa Rica. We found 1) no significant effect of shade trees on coffee production overall; 2) evidence that shade trees do affect flowering and subsequent cherry development, with effects strongly dependent on climate and annual variations in coffee plant physiology; 3) Erythrina shade trees significantly increased soil litter and relative infiltration rate of water in the soil, both linked to soil conservation and decrease in erosion; 4) even in highly fertilized environments, Erythrina trees do fix N which was taken up by adjacent coffee plants. The lack of significant negative effect of shade trees on overall coffee yield and the observation of the provision of other useful services was not unexpected, because of 1) the low density of shade trees in the study site (100–350 trees/ha pruned twice a year on average) and 2) the sensitivity of coffee yields to other interacting effects such as climate, pests and diseases and physiological variations in the plant. Pending further long-term research into the factors affecting coffee yield, we find shade trees provide sufficient ecosystem services to justify their integration in even intensively managed plantations.
... High yielding crop varieties with a significant level of tolerance towards stresses induced by disease, pests, climate change, water shortage and reduced soil fertility have been recognized as crucial needs to feed the burgeoning population [1][2][3]. In this regard, focus has been towards increasing crop yield through timely and precision management of crop inputs [4,5]. However, majorly existing techniques to manage crop stressors have been time-consuming, labor-intensive and most importantly destructive [6,7]. ...
Article
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The pinto bean is one of widely consumed legume crop that constitutes over 42% of the U.S dry bean production. However, limited studies have been conducted in past to assess its quantitative and qualitative yield potentials. Emerging remote sensing technologies can help in such assessment. Therefore, this study evaluates the role of ground-based multispectral imagery derived vegetation indices (VIs) for irrigated the pinto bean stress and yield assessments. Studied were eight cultivars of the pinto bean grown under conventional and strip tillage treatments and irrigated at 52% and 100% of required evapotranspiration. Imagery data was acquired using a five-band multispectral imager at early, mid and late growth stages. Commonly used 25 broadband VIs were derived to capture crop stress traits and yield potential. Principal component analysis and Spearman's rank correlation tests were conducted to identify key VIs and their correlation (rs) with abiotic stress at each growth stage. Transformed difference vegetation index, nonlinear vegetation index (NLI), modified NLI and infrared percentage vegetation index (IPVI) were consistent in accounting the stress response and crop yield at all growth stages (rs > 0.60, coefficient of determination (R²): 0.50–0.56, P < 0.05). Ten other VIs significantly accounted for crop stress at early and late stages. Overall, identified key VIs may be helpful to growers for precise crop management decision making and breeders for crop stress response and yield assessments.
... In the Chiapas Sierra Madre, financial investments in coffee plantations tend to be minimal, fluctuating with the international price of this commodity. Falls in coffee prices lead to reduced profitability and thus limited investment in coffee ecosystem health (Taugourdeau et al. 2014), which in turn may increase plantation vulnerability to pests and diseases. ...
Article
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A recent coffee leaf rust epidemic has generated a severe fall in Coffea arabica production throughout Mexico and Central America. This paper analyzes the social–ecological crisis presented by the Hemileia vastatrix outbreak, with a focus on how global, regional and national dynamics interact with local processes in the Chiapas Sierra Madre of south-eastern Mexico, a biodiversity hotspot with a tradition of smallholder, shade-grown coffee production. We explore the hypothesis that the current coffee rust epidemic is an expression of global environmental change, with implications for legal frameworks and international efforts towards risk management and climate change adaptation. Addressing debates on legal resilience building, we illustrate how mismatches of scale between social–ecological phenomena and legal and institutional arrangements may generate pathological solutions for small-scale coffee producers and shade-grown coffee ecosystems. Thereafter, using the analytical lens of modularity, the paper sheds light on landscape stewardship to reduce the risks of non-resilient characteristics such as isolation, on the one hand, and on the other, over-connectedness of habitat patches in the landscape of importance for ecosystem functions at larger scales. The interdisciplinary framework leads to recognizing the role of institutions and legal arrangements which are not limited to national boundaries in proposing solutions to this social–ecological crisis. We find that matching scales of law with agroforestry systems can be done through a variety of legal and policy instruments to contribute to resilience building. This matching of scales is vital to safeguarding biodiversity’s global benefits and the right of small-scale coffee farmers to a healthy and sustainable environment.
... L'indice foliaire a aussi été utilisé dans la modélisation des services hydrologiques. Lorsqu'il est doublé de 3,8 à 7,6, l'évapotranspiration est augmentée de 60 %, le ruissellement superficiel diminue de 1 %, le débit de la rivière se réduit de 17 % et la quantité d'eau qui traverse l'aquifère est réduite de 20 % ( Taugourdeau et al., 2014). ...
... It is used for the estimation of vegetation parameters (Kerr and Ostrovsky 2003;Pettorelli et al. 2005;Huete et al. 2008;Elhag 2014), forest coverage and its structural application (Demarez et al. 2008;Jensen et al. 2008), crop assessment, monitoring, land surface process simulation, global change studies and yield estimation (Xiao et al. 2016a). Apart from this, long-term temporal LAI is very much important for the study of climate modeling and other problems (Xiao et al. 2016b), global atmosphere/biosphere interactions (Tang et al. 2014), ecosystem services and management practices (Taugourdeau et al. 2014) and so on. ...
Article
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Abstract Vegetation status of Sali River basin has been evaluated in this study applying the Landsat 8 data. Here, NDVI, EVI, GI, LAI, PVI, SI, BI and NDMI have been used to assess vegetation status (VS). Indices have been classifed into fve categories following natural breaks classifcation method. Apart from BI, all the indices represented higher value in forest cover area. Weights for all the themes and sub-themes were assigned following multicriteria decision analysis with consistency ratio of 0.0685, and weighted overlay analysis technique had been employed for the assessment of the vegetation status. Very low, low and moderate VS was found mainly over the water body, urban and agricultural area, which is covering more than half of the basin. The rest of the area is covered with high and very high VS, representing fragmented and dense Sal forest and covering 15.81% and 22.88% basin area, respectively. Accuracy assessment and thorough feld verifcation were done with 90.43% classifcation accuracy. Our result is quite similar to land use land cover map of Bhuvan, ISRO. So, keeping in the view of health of the river basin and vegetation, this area needs urgent attention to control the degradation of vegetation in a scientifc way. Keywords Multi-criteria decision analysis (MCDA) · Leaf Area Index · Normalized Diference Moisture Index · Greenness Index · Perpendicular Vegetation Index · Weighted overlay analysis
... L'indice foliaire a aussi été utilisé dans la modélisation des services hydrologiques. Lorsqu'il est doublé de 3,8 à 7,6, l'évapotranspiration est augmentée de 60 %, le ruissellement superficiel diminue de 1 %, le débit de la rivière se réduit de 17 % et la quantité d'eau qui traverse l'aquifère est réduite de 20 % (Taugourdeau et al., 2014). ...
... This Lisbon UHI-LCC model was later compared to the measured UHI intensities of Andrade (2003). LCR is the landscape's ability to regulate thermal comfort due to its form, configuration of structures, patches, and species (Susca et al., 2011;De Carvalho and Szlafsztein, 2019;Kuang et al., 2017;Kuang et al., 2015;Marando et al., 2019;Taugourdeau et al., 2014). ...
Article
Urban land covers affect the thermal characteristics of the city, such as the urban heat island (UHI) effect, potentially increasing energy demand to maintain comfortable indoor and outdoor temperatures. As the land patterns change, the capacity of the landscape to regulate the UHI can change. The aim of this paper is to explore how simulating land cover changes (LCC) may affect UHI using an ecosystem service matrix approach. A LCC model, illustrated in the case study of Lisbon, Portugal, was implemented to estimate the UHI effects over time starting from the modelling of land cover changes associated with the supply of local climate regulation service. Our results show that the capacity of urban landscape to mitigate the UHI effect has decreased since 1990, and will continue to decrease slightly until 2022 although more smoothly than between 1990 and 2000. This is because no substantial land cover changes have occurred after 2000 that required the transition between highest to lowest ecosystem service supplier landscapes. The proposed modelling approach may be refined and used to aiding the decision making process for urban planners in the placement of built structures and green spaces that have the capacity to regulate local climate.
... L'indice foliaire a aussi été utilisé dans la modélisation des services hydrologiques. Lorsqu'il est doublé de 3,8 à 7,6, l'évapotranspiration est augmentée de 60 %, le ruissellement superficiel diminue de 1 %, le débit de la rivière se réduit de 17 % et la quantité d'eau qui traverse l'aquifère est réduite de 20 % ( Taugourdeau et al., 2014). ...
Chapter
Full-text available
Eight years of studying coffee ecophysiology and monitoring ecosystem services (ES) in a large coffee farm in Costa Rica revealed several practical recommendations for farmers and policy makers. The cropping system studied within our collaborative observatory (Coffee-Flux) corresponds to a coffee-based agroforestry system (AFS) under the shade of large trees of Erythrina poeppigiana (16% of canopy cover). A lot of ES and disservices depend on local soil properties (here Andisols), especially erosion/infiltration, water/carbon and nutrient storage capacity. Therefore, for ES assessment, the type of soil is crucial. An adequate density of shade trees (rather low here) reduced the severity of leaf diseases with the prospect of reducing pesticide-fungicide use. A simple inventory of the basal area at collar of the coffee plants allowed estimating the belowground biomass and the average age of the plantation, to judge of its market value and to decide when to replace it. Coffee farms are probably much closer to C neutrality than predicted by the current C-Neutral protocol, which only considers shade trees. More comprehensive assessments, including trees, coffee, litter, soil, and roots in the C balance of the AFS are proposed. Shade trees offer many ES if they are adequately managed in the local context. As compared to full sun conditions, shade trees may (i) reduce laminar erosion by a factor of 2, (ii) increase N2 fixation and the % of N recycled into the system, thus reducing fertilizer requirements, (iii) reduce the severity of leaf diseases, (iv) increase C sequestration, (v) improve the microclimate, and (vi) substantially reduce the effects of climate change. In our case study, no negative effect on coffee yield was found
... L'indice foliaire a aussi été utilisé dans la modélisation des services hydrologiques. Lorsqu'il est doublé de 3,8 à 7,6, l'évapotranspiration est augmentée de 60 %, le ruissellement superficiel diminue de 1 %, le débit de la rivière se réduit de 17 % et la quantité d'eau qui traverse l'aquifère est réduite de 20 % ( Taugourdeau et al., 2014). ...
Chapter
Here we show that spatial tree structure within cacao agroforests influences pest and disease attack intensity of cacao trees. At the plot scale, regular or random spatial organizations of forest trees reduced pest and disease intensity of frosty pod rot in Costa Rica, and mirids in Cameroon. At the individual scale, the number of neighboring cacao trees (at 3.7 m) and neighboring fruit trees (at 4.3 m) negatively influence the individual intensity of frosty pod rot in Costa Rica. Our results reveal the importance of spatial structure in the description of tropical agroforests and in understanding of the mechanisms influencing the agroecological regulation of pest and diseases within these complex systems. Optimization of spatial tree structure when managing tropical agroforests could be an interesting lever for agroecological control of pests and diseases.
... L'indice foliaire a aussi été utilisé dans la modélisation des services hydrologiques. Lorsqu'il est doublé de 3,8 à 7,6, l'évapotranspiration est augmentée de 60 %, le ruissellement superficiel diminue de 1 %, le débit de la rivière se réduit de 17 % et la quantité d'eau qui traverse l'aquifère est réduite de 20 % ( Taugourdeau et al., 2014). ...
... Based on farmers' statements and field evidence, our results confirmed that coffee rust epidemics had economic drivers, that determined crop and disease management, as previously proposed (Avelino et al., 2015), and did not only depend on meteorological aspects and host plant characteristics. Crop management was probably sub-optimum over that period, because management is normally adjusted each year to adapt on-farm investment to the economic context (Taugourdeau et al., 2014), and the coffee crop was not profitable in 2012. International prices dropped sharply (by 55% between September 2011 and December 2013) below the production costs, which reached high levels never seen before at the same time (Avelino et al., 2015). ...
... The leaf area index (LAI) is an important variable used to estimate water, carbon and energy flows. This index is relevant in studies related to the knowledge of phenomena at different scales, such as for the leaf to canopy scale and the calculation of the extinction coefficient of photosynthetically active radiation (kPAR), providing important information for the parameterization of physiological basis models (Sasaki, Imanishi, Ioki, Morimoto, & Kitada, 2008;Taugourdeau et al., 2014). ...
Article
Full-text available
The leaf area index (LAI) is relevant in studies of phenomena at different scales, such as for the leaf to canopy scale and the calculation of the extinction coefficient of photosynthetically active radiation (kPAR), providing input for the parameterization of physiological basis models. The objective of this work was to verify the variation of the LAI and the coffee kPAR subjected to different drip irrigation levels (130, 100, 70, and 40%) and to compare the data obtained from radiation bar linear sensors (SunScan) in the plants that received full irrigation with the values found by other LAI estimation methodologies. The study was conducted in Piracicaba, São Paulo State, Brazil, using the species Coffea arabica cv. Red Catuaí IAC 144; a drip irrigation system was adopted, with the irrigation controlled by tensiometry. The mean LAI values were higher in the L130 (irrigation level of 130%) and L100 (irrigation level of 100%) treatments than those with deficit irrigation depths. The mean kPAR values were lower for the L130 and L100 treatments than the values found in the deficit irrigation depth treatments. When comparing SunScan to other methodologies, the mean error (ME) and absolute mean error (AME) were high.
... Understanding the complex mechanisms with which environmental variables and human agents drive LAI and its variation in forested landscapes is essential to develop suitable management interventions aimed at forest functions and services (Nakamura et al., 2017;Taugourdeau et al., 2014). However, previous studies either work at large spatial scales hampering mechanistic understanding (e.g. ...
Article
The Atlantic Forest, a global biodiversity hotspot, has changed dramatically due to land use pressures causing deforestation, degradation, and forest fragmentation. A major challenge is to understand and potentially mitigate the consequences of these changes, for the capacity of forests to deliver essential environmental services to rural areas. Here, we focus on unraveling the mechanisms underpinning spatial variation in forest leaf area index. Forest leaf area index can be used as an environmental indicator that controls key forest functions underlying environmental services and is also expected to respond to land use change. Specifically, we use Structural Equation Modelling to determine the direct and indirect pathways that link environmental drivers to canopy leaf area index (LAI) variation across forest types in the Atlantic Forest in Southern Brazil. We sampled 240 sample units (each 4000 m²), from a systematic and permanent forest inventory set which covers the State of Santa Catarina in a 10 km × 10 km grid, using hemispherical photographs. Environmental variables were extracted for each sample unit, including climatic and topographic data as well as indicators of anthropogenic pressure. Our results showed that forest types differed in their leaf area index (but not all of them) and that forest canopies show complex responses to environmental drivers, encompassing direct and indirect pathways. A major pathway was the positive effect of ‘Distance to city’ on the ‘Percentage of cropland in the matrix’. This led to a decline in the distance of the sample unit to the forest edge, indirectly reducing LAI, presumably because of elevated tree mortality at the forest edge. ‘Terrain steepness’ and ‘Rainfall in the driest month’ independently affected the ‘Percentage of cropland in the matrix’ and the ‘Distance to forest edge’. Halting forest fragmentation and increasing fragment size by landscape planning will mitigate these anthropogenic LAI declines. This can be achieved with a combination of legal and market mechanisms, like enforcement of the Brazilian Forest Act regulation on buffer zones around water bodies and steep slopes, landscape planning, and payment for environmental services to compensate the farmers for maintaining forest cover on otherwise productive land.
... L'indice foliaire a aussi été utilisé dans la modélisation des services hydrologiques. Lorsqu'il est doublé de 3,8 à 7,6, l'évapotranspiration est augmentée de 60 %, le ruissellement superficiel diminue de 1 %, le débit de la rivière se réduit de 17 % et la quantité d'eau qui traverse l'aquifère est réduite de 20 % (Taugourdeau et al., 2014). ...
... L'indice foliaire a aussi été utilisé dans la modélisation des services hydrologiques. Lorsqu'il est doublé de 3,8 à 7,6, l'évapotranspiration est augmentée de 60 %, le ruissellement superficiel diminue de 1 %, le débit de la rivière se réduit de 17 % et la quantité d'eau qui traverse l'aquifère est réduite de 20 % ( Taugourdeau et al., 2014). ...
... L'indice foliaire a aussi été utilisé dans la modélisation des services hydrologiques. Lorsqu'il est doublé de 3,8 à 7,6, l'évapotranspiration est augmentée de 60 %, le ruissellement superficiel diminue de 1 %, le débit de la rivière se réduit de 17 % et la quantité d'eau qui traverse l'aquifère est réduite de 20 % (Taugourdeau et al., 2014). ...
Chapter
Full-text available
Résumé. Huit ans de travaux de recherche sur les services écosystémiques dans une grande ferme caféière du Costa Rica (observatoire collaboratif Coffee-Flux, en système agrofo-restier à base de caféiers sous de grands arbres d'Erythrina poeppigiana, surface projetée de couronne de l'ordre de 16 %) ont suggéré plusieurs applications pour les agriculteurs et les décideurs. Il est apparu que de nombreux services écosystémiques dépendaient des propriétés du sol (ici des Andisols), en particulier de l'érosion, de l'infiltration, de la capa-cité de stockage de l'eau et des éléments nutritifs. Nous confirmons qu'il est essentiel de lier les services hydrologiques et de conservation au type de sol en présence. Une densité adéquate d'arbres d'ombrage (plutôt faible ici) permet de réduire la sévérité des mala-dies foliaires avec, en perspective, une réduction de l'usage de pesticides-fongicides. Un simple inventaire de la surface basale au collet des caféiers permet d'estimer la biomasse souterraine et la moyenne d'âge d'une plantation de caféiers, ce qui permet d'évaluer sa Agroforesterie et services écosystémiques en zone tropicale 38 valeur marchande ou de planifier son remplacement. Le protocole de calcul actuel pour la neutralité carbone des systèmes agroforestiers ne prend en compte que les arbres d'om-brage, pas la culture intercalaire. Dans la réalité, si on inclut les caféiers, on se rapproche très probablement de la neutralité. Des évaluations plus complètes, incluant les arbres, les caféiers, la litière, le sol et les racines dans le bilan en carbone du système agroforestier sont proposées. Les arbres d'ombrage offrent de nombreux servies écosystémiques s'ils sont gérés de manière adéquate dans le contexte local. Par rapport aux parcelles en plein soleil, nous montrons qu'ils réduisent l'érosion laminaire d'un facteur 2, augmentent la fixation de l'azote (N 2) atmosphérique et le pourcentage d'azote recyclé dans le système, réduisant ainsi les besoins en engrais. Ils réduisent aussi la sévérité des maladies foliaires, augmentent la séquestration de carbone, améliorent le microclimat et atténuent substan-tiellement les effets des changements climatiques. Dans notre étude de cas, aucun effet négatif sur le rendement n'a été enregistré. Abstract. Eight years of studying coffee ecophysiology and monitoring ecosystem services (ES) in a large coffee farm in Costa Rica revealed several practical recommendations for farmers and policy makers. The cropping system studied within our collaborative observatory (Coffee-Flux) corresponds to a coffee-based agroforestry system (AFS) under the shade of large trees of Erythrina poeppigiana (16 % of canopy cover). A lot of ES and disservices depend on local soil properties (here Andisols), especially erosion/infiltration, water/carbon and nutrient storage capacity. Therefore, for ES assessment, the type of soil is crucial. An adequate density of shade trees (rather low here) reduced the severity of leaf diseases with the prospect of reducing pesticide-fungicide use. A simple inventory of the basal area at collar of the coffee plants allowed estimating the belowground biomass and the average age of the plantation, to judge of its market value and to decide when to replace it. Coffee farms are probably much closer to C neutrality than predicted by the current C-Neutral protocol, which only considers shade trees. More comprehensive assessments, including trees, coffee, litter, soil, and roots in the C balance of the AFS are proposed. Shade trees offer many ES if they are adequately managed in the local context. As compared to full sun conditions, shade trees may (i) reduce laminar erosion by a factor of 2, (ii) increase N2 fixation and the % of N recycled into the system, thus reducing fertilizer requirements, (iii) reduce the severity of leaf diseases, (iv) increase C sequestration, (v) improve the microclimate, and (vi) substantially reduce the effects of climate change. In our case study, no negative effect on coffee yield was found.
... L'indice foliaire a aussi été utilisé dans la modélisation des services hydrologiques. Lorsqu'il est doublé de 3,8 à 7,6, l'évapotranspiration est augmentée de 60 %, le ruissellement superficiel diminue de 1 %, le débit de la rivière se réduit de 17 % et la quantité d'eau qui traverse l'aquifère est réduite de 20 % ( Taugourdeau et al., 2014). ...
Chapter
Full-text available
Régulation des bioagresseurs des cultures dans les systèmes agroforestiers tropicaux, revue des approches bagny beiLhe L., aLLinne c., aveLino J., babin r., brévauLt t., gidoin c., ngo bieng m.a., motisi n., soti v. et ten hooPen g.m. Résumé. Au sein des systèmes agroforestiers tropicaux, de nombreuses interactions se déroulent dans et entre les environnements biotiques et abiotiques. Elles favorisent une régulation naturelle des bioagresseurs des cultures de ces systèmes. Afin d'exploiter au mieux cette régulation naturelle et de limiter les pertes de production, il est primordial de bien comprendre ces interactions. Ce chapitre présente une synthèse d'études de ces mécanismes de régulation, à partir de données empiriques sur des maladies et ravageurs dans des systèmes agroforestiers à base de caféiers, de cacaoyers et de mil au Cameroun, au Costa Rica, au Kenya et au Sénégal. En fonction des caractéristiques biologiques des bioagresseurs et de l'environnement dans lequel ils se développent, des approches multi échelles, de l'arbre au paysage, adaptées aux modèles étudiés ont été utilisées pour évaluer les stratégies de régulation ascendante par les ressources « bottom-up » et descendante par les ennemis naturels « top-down ». Les approches développées ont permis d'évaluer l'effet de la composition et de l'organisation spatiale de la biodiversité associée au sein des systèmes agroforestiers sur les bioagresseurs, l'effet de l'ombrage sur le développement des bioagresseurs et l'effet de la biodiversité végétale associée aux échelles parcelle et paysage sur les communautés d'ennemis naturels et leur efficacité à réguler les bioagres-seurs. Des approches expérimentales et intégratives, d'écologie des communautés et du paysage fondées notamment sur l'étude des traits fonctionnels se sont avérées nécessaires pour estimer au mieux les services de régulation. Abstract. Tropical agroforestry systems are home to complex interactions between and within the biotic and abiotic environments, which govern natural regulation processes of pests and diseases of agricultural crops. In order to optimally exploit these control mechanisms , thereby limiting production losses, it is necessary to improve our understanding Agroforesterie et services écosystémiques en zone tropicale 230 of these interactions within agro-ecosystems. This chapter presents an overview of several studies that looked at naturally occurring control mechanisms in tropical agroforestry systems. This synthesis has been elaborated based on empirical data from studies on the regulation of pests and diseases in coffee, cacao, and millet-based agroforestry systems in Cameroon, Costa Rica, Kenya and Senegal. Based on the biological characteristics of the pest and/or disease and the environment in which they develop, scale dependent approaches, from tree to landscape, appropriate to the models being studied, have been used to evaluate both "bottom-up" and "top-down" control mechanisms. The developed approaches allowed to evaluate: the effects of the composition and spatial organization of associated plant diversity on the regulation of pests and diseases; the effects of shade on the development of pests and diseases and the effects of associated plant biodiversity at plot and landscape level on communities of natural enemies and their efficacy in controlling pests and diseases. Experimental and integrative approaches from population and landscape ecology, taking into account functional traits, are necessary tools to understand regulation services.
... The northwest and northeastern parts of the basin which is high altitude areas and considered as the water towers of the basin seem to be most affected in the LAI values variation. LAI is affected by natural factors (interaction between vegetative and reproductive components, climate) and human factors (pruning of trees, farming, deforestation), while it has been observed that LAI affects partitioning between green water (evapotranspiration) and blue water (infiltration, aquifer recharge, stream flow) making it an important indicator of the ecosystem function and status (Taugourdeau et al. 2014). From the data below, it is evident that there is deforestation along the slopes of Mount Elgon and along the Cherangany ranges which fall along the northwest and northeast of the basin. ...
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Water resources face risks due to water use stress and water scarcity. Collective and integrated actions by different institutions and stakeholders are needed to reduce future water risks. This paper aimed to assess the potential for a water stewardship partnership in River Nzoia Basin to reduce future water risks facing the ecosystem, agriculture, and other sectors by quantifying water risks and mapping stakeholders for a water stewardship partnership in the basin. Water risks were quantified using indicators from remote sensing platforms and secondary sources. Stakeholder mapping was conducted using stakeholder analysis, while stakeholders’ views were collected using questionnaires. The results showed that there is a high fluctuation in the vegetation cover and primary productivity in the basin pointing to a degradation and deforestation. It was also noted that there is an increase in the frequency and severity of drought and high evapotranspiration rates in some parts of the basin due to the low vegetation cover. Combining the results indicated an increase in water risk between 2000 and 2014 in different parts of the basin at a different magnitude of risks. The conducted interviews found that the basin lacked a stewardship program. However, there was a potential for a successful stewardship partnership among stakeholders as most of the stakeholders showed their ability to play a role in the stewardship program. The paper showed a need to form a water stewardship program at the basin to tackle drought, deforestation, and land degradation. The proposed water stewardship program should be built on commitment, transparency, and inclusivity.
... L'indice foliaire a aussi été utilisé dans la modélisation des services hydrologiques. Lorsqu'il est doublé de 3,8 à 7,6, l'évapotranspiration est augmentée de 60 %, le ruissellement superficiel diminue de 1 %, le débit de la rivière se réduit de 17 % et la quantité d'eau qui traverse l'aquifère est réduite de 20 % ( Taugourdeau et al., 2014). ...
Article
Full-text available
Les impacts des karités (Vitellaria paradoxa) sur les contenus du sol en eau, en nutriments et en carbone, ainsi que sur la production associée de maïs pluvial ont été évalués dans un parc agroforestier au Nord-Est du Bénin. Pour ce faire, les résultats des mesures sous houpier et hors houppier ont été comparés. Le rendement de la culture s'est révélé inférieur sous le houppier, malgré des conditions de fertilité et d'humidité du sol qui restaient favorables. Notre hypothèse est que cet effet négatif serait causé par la limitation par le houppier du rayonnement incident sur la culture. De plus, on a observé une contribution significative des arbres à l'enrichissement de la matière organique du sol sur l'ensemble du parc agroforestier. Cet effet positif de la présence des arbres pourrait se traduire par un impact bénéfique sur le rendement du maïs. Pour le vérifier, les rendements obtenus dans les conditions de cette étude devront être comparés aux résultats obtenus dans une situation témoin (sans arbres), toutes choses égales par ailleurs.
... L'indice foliaire a aussi été utilisé dans la modélisation des services hydrologiques. Lorsqu'il est doublé de 3,8 à 7,6, l'évapotranspiration est augmentée de 60 %, le ruissellement superficiel diminue de 1 %, le débit de la rivière se réduit de 17 % et la quantité d'eau qui traverse l'aquifère est réduite de 20 % ( Taugourdeau et al., 2014). ...
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Full-text available
Notre objectif est d'évaluer la contribution des arbustes de Guiera senegalensis aux flux d'eau et de carbone dans un parc agroforestier à petit mil (Pennisetum glaucum L.R. Br.) et dans une jachère. Le site expérimental est situé au sud-ouest du Niger, sur un bassin-versant sahélien de 2 km2. À l'échelle de l'arbuste de Guiera senegalensis, le taux de transpiration foliaire a été déduit de la conductance stomatique et du déficit de pression de vapeur. La dynamique de la biomasse aérienne et souterraine des arbustes a été suivie en saison des pluies, en saison sèche froide et en saison sèche chaude. À l'échelle de la parcelle, les bilans d'eau et d'assimilation du carbone ont été estimés par une modélisation de type "transferts surface-végétation-atmosphère". Le modèle est paramétré à partir de mesures automatiques de terrain selon la méthode des corrélations turbulentes. Le taux de transpiration foliaire et la biomasse aérienne de Guiera ont augmenté dans le parc, de la saison des pluies à la saison sèche chaude, alors qu'ils ont diminué dans la jachère. Les résultats du modèle montrent une activité de la jachère centrée sur la saison des pluies, mais décalée vers le début de la saison sèche pour le parc. À l'échelle de la parcelle, le modèle est capable de bien simuler l'évapotranspiration et l'assimilation de carbone au regard de la période de la croissance active des arbustes dans les deux types de couvert, tout en assurant un haut degré de cohérence avec le contenu en eau du sol.
... L'indice foliaire a aussi été utilisé dans la modélisation des services hydrologiques. Lorsqu'il est doublé de 3,8 à 7,6, l'évapotranspiration est augmentée de 60 %, le ruissellement superficiel diminue de 1 %, le débit de la rivière se réduit de 17 % et la quantité d'eau qui traverse l'aquifère est réduite de 20 % ( Taugourdeau et al., 2014). ...
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Respectueux de l'environnement et garantissant une sécurité alimentaire soutenue par la diversification des productions et des revenus qu'ils procurent, les systèmes agroforestiers apparaissent comme un modèle prometteur d'agriculture durable dans les pays du Sud les plus vulnérables aux changements globaux. Cependant, ces systèmes agroforestiers ne peuvent être optimisés qu'à condition de mieux comprendre et de mieux maîtriser les facteurs de leurs productions. L'ouvrage présente un ensemble de connaissances récentes sur les mécanismes biophysiques et socio-économiques qui sous-tendent le fonctionnement et la dynamique des systèmes agroforestiers. Il concerne, d'une part les systèmes agroforestiers à base de cultures pérennes, telles que cacaoyers et caféiers, de régions tropicales humides en Amérique du Sud, en Afrique de l'Est et du Centre, d'autre part les parcs arborés et arbustifs à base de cultures vivrières, principalement de céréales, de la région semi-aride subsaharienne d'Afrique de l'Ouest. Il synthétise les dernières avancées acquises grâce à plusieurs projets associant le Cirad, l'IRD et leurs partenaires du Sud qui ont été conduits entre 2012 et 2016 dans ces régions. L'ensemble de ces projets s'articulent autour des dynamiques des systèmes agroforestiers et des compromis entre les services de production et les autres services socio-écosystémiques que ces systèmes fournissent.
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Clumping index (CI) is a measure of foliage aggregation relative to a random distribution of leaves in space. The CI can help with estimating fractions of sunlit and shaded leaves for a given leaf area index (LAI) value. Both the CI and LAI can be obtained from global Earth Observation data from sensors such as the Moderate Resolution Imaging Spectrometer (MODIS). Here, the synergy between a MODIS-based CI and a MODIS LAI product is examined using the theory of spectral invariants, also referred to as photon recollision probability ('p-theory'), along with raw LAI-2000/2200 Plant Canopy Analyzer data from 75 sites distributed across a range of plant functional types. The p-theory describes the probability (p-value) that a photon, having intercepted an element in the canopy, will recollide with another canopy element rather than escape the canopy. We show that empirically based CI maps can be integrated with the MODIS LAI product. Our results indicate that it is feasible to derive approximate p-values for any location solely from Earth Observation data. This approximation is relevant for future applications of the photon recollision probability concept for global and local monitoring of vegetation using Earth Observation data.
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Leaf area index (LAI) is a key factor that determines a forest ecosystem’s net primary production and energy exchange between the atmosphere and land surfaces. LAI can be measured in many ways, but there has been little research to compare LAI estimated by different methods. In this study, we compared the LAI results from two different approaches, i.e., the dimidiate pixel model (DPM) and an empirical statistic model (ESM) using ZY-3 high-accuracy satellite images validated by field data. We explored the relationship of LAI of Larix principis-rupprechtii Mayr plantations with topographic conditions. The results show that DPM improves the simulation of LAI (r = 0.86, RMSE = 0.57) compared with ESM (r = 0.62, RMSE = 0.79). We further concluded that elevation and slope significantly affect the distribution of LAI. The maximum peak of LAI appeared at an aspect of east and southeast at an elevation of 1700–2000 m. Our results suggest that ZY-3 can satisfy the needs of quantitative monitoring of leaf area indices in small-scale catchment areas. DPM provides a simple and accurate method to obtain forest vegetation parameters in the case of non-ground measurement points.
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Increasing levels of particulate matter (PM) in the atmosphere of megacities is a serious concern due to implications for human exposure and overall environmental quality. Delhi experiences extremely high levels of particulate pollution. The present study sheds light on the seasonal differences in PM removal from the atmosphere by the available forest cover and quantifies this for Delhi. Particulate matter data from 40 stations across Delhi along with leaf area index (LAI) derived from remotely sensed satellite images were used. PM removed in the wet summer period was found to be lower than for the dry winter period in a year. The results highlight an unusual schedule for foliage fall in Delhi, as substantiated by the calculated LAI during the wet summer season and dry winter season. Overall, the study quantitatively evaluates the PM removal potential of forest cover in Delhi and suggests a need for the careful selection of trees in afforestation programmes.
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Water deficiency due to climate change and the world's population growth increases the demand for the water industry to carry out vulnerability assessments. Although many studies have been done on climate change vulnerability assessment, a specific framework with sufficient indicators for water vulnerability assessment is still lacking. This highlights the urgent need to devise an effective model framework in order to provide water managers and authorities with the level of water exposure, sensitivity, adaptive capacity and water vulnerability to formulate their responses in implementing water management strategies. The present study proposes a new approach for water quantity vulnerability assessment based on remote sensing satellite data and GIS ModelBuilder. The developed approach has three layers: (1) data acquisition mainly from remote sensing datasets and statistical sources; (2) calculation layer based on the integration of GIS-based model and the Intergovernmental Panel on Climate Change's vulnerability assessment framework; and (3) output layer including the indices of exposure, sensitivity, adaptive capacity and water vulnerability and spatial distribution of remote sensing indicators and these indices in provincial and regional scale. In total 27 indicators were incorporated for the case study in Vietnam based on their availability and reliability. Results show that the most water vulnerable is the South Central Coast of the country, followed by the Northwest area. The novel approach is based on reliable and updated spatial-temporal datasets (soil water stress, aridity index, water use efficiency, rain use efficiency and leaf area index), and the incorporation of the GIS-based model. This framework can then be applied effectively for water vulnerability assessment of other regions and countries.
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The Atlantic Forest, a global biodiversity hotspot, has changed dramatically due to land 12 use pressures causing deforestation, degradation, and forest fragmentation. A major challenge is 13 to understand and potentially mitigate the consequences of these changes, for the capacity of 14 forests to deliver essential environmental services to rural areas. Here, we focus on unraveling the 15 mechanisms underpinning spatial variation in forest leaf area index. Forest leaf area index can be 16 used as an environmental indicator that controls key forest functions underlying environmental 17 services and is also expected to respond to land use change. Specifically, we use Structural 18 Equation Modelling to determine the direct and indirect pathways that link environmental drivers 19 to canopy leaf area index (LAI) variation across forest types in the Atlantic Forest in Southern 20 Brazil. We sampled 240 sample units (each 4,000 m²), from a systematic and permanent forest 21 inventory set which covers the State of Santa Catarina in a 10 km x 10 km grid, using hemispherical 22 photographs. Environmental variables were extracted for each sample unit, including climatic and 23 topographic data as well as indicators of anthropogenic pressure. Our results showed that forest 24 types differed in their leaf area index (but not all of them) and that forest canopies show complex 25 responses to environmental drivers, encompassing direct and indirect pathways. A major pathway 26 was the positive effect of 'Distance to city' on the 'Percentage of cropland in the matrix'. This led 27 to a decline in the distance of the sample unit to the forest edge, indirectly reducing LAI, 28 presumably because of elevated tree mortality at the forest edge. 'Terrain steepness' and 'Rainfall 29 in the driest month' independently affected the 'Percentage of cropland in the matrix' and the 30 'Distance to forest edge'. Halting forest fragmentation and increasing fragment size by landscape 31 planning will mitigate these anthropogenic LAI declines. This can be achieved with a combination 32 of legal and market mechanisms, like enforcement of the Brazilian Forest Act regulation on buffer 33 zones around water bodies and steep slopes, landscape planning, and payment for environmental 34 services to compensate the farmers for maintaining forest cover on otherwise productive land. 35 Keywords: leaf area index; structural equation model; hemispherical photograph; national forest 36 inventory 37 38
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This research compared coffee plants (Coffea arabica L.) grown in an agroforestry and monoculture systems. Data were collected during two years, on vegetative growth, reproductive development, nutritional status and yield of coffee, besides monitoring air temperature and the tree growth. All trees in agroforestry system increased in growth, resulting in a reduction in the magnitude of the diurnal temperature variation and also maximum temperature. Coffee plants in agroforestry system had less branch growth and leaf production, more persistent and larger leaves, and presented earlier flowering, with a smaller number of productive nodes and flower buds, leading to smaller berry yield than plants in monoculture system. In both systems, the coffee plants showed adequate leaf nutrient levels, except for P and K. The yield of 2443 kg ha-1 of coffee from the monoculture was greater than 515 kg ha-1 of coffee from the agroforestry system.
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Multispectral images were collected by an unmanned aerial vehicle over a commercial coffee plantation during the 2002 harvest season. Selected scenes were georegistered to a base map and a mosaic of the study area was created. Image segmentation was performed to identify and mask soil, shadow, and cloud pixels. The remaining pixels, representing sunlit canopy, were assumed to be a mixture of four components: Green leaf, underripe fruit, ripe fruit, and overripe fruit. Field and laboratory instruments were used to measure the reflectance spectrum of each component. Based on these spectra, a ripeness index was developed for the airborne imagery that involved computing the per-pixel ratio of digital counts in spectral channels centered at 580 and 660 nm. Results were aggregated on a per-field basis. Mean ripeness index per field was significantly correlated with ground-based counts recorded by the grower, and to eventual harvest date. The results suggest that remote sensing methods may provide an alternative, more spatially comprehensive method for monitoring ripeness status and evaluating harvest readiness of this high-value agricultural commodity.
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The arabic coffee (Coffea arabica L.) takes two years to complete the entire phenological cycle of the frutification, unlike most of the other crops, that complete the reproductive cycle in one year. Six different phenological phases, taking a total of two years, are proposed, starting in September of each year. The phases are: 1 st phase: vegetative, with seven months, September to March, with long days; 2 nd phase: also vegetative, April to August, with short days, when occurs the transformation of the vegetative buds of the knots formed in the 1 st phase to reproductive buds. At the end of this phase, July and August, the plants enter in relative dormancy with formation of one or two small pair of leaves, that usually do not flourish. The maturation of the reproductive buds comes after the accumulation of about 350 mm of potential evapotranspiration (ETp), starting by the beginning of April; 3 rd phase: flowering and grain expansion, September to December. Usually the flowering happens about 8 to 15 days after the increase of the water potential inside the floral buds caused by rain or irrigation; 4 th phase: grain formation, January to March; 5 th phase: grain maturation, when about 700 mm of ETp accumulates since the main flowering; 6 th phase: senescence and death of the non-primary productive branches, in July and August.
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Seasonal changes in vegetative growth, leaf gas exchanges, carbon isotope discrimination (Δ) and carbohydrate status were monitored in de-fruited coffee trees (Coffea arabica L.) grown in the field, from October 1998 through September 1999, in Viçosa (20°45′S, 42°15′W, 650 m a.s.l.), southeastern Brazil. Of the total growth over the 12-month study period, 78% occurred in the warm, rainy season (October–March), and 22% during the cool, dry season (April–September). Throughout the active growth period, the rate of net carbon assimilation (A) averaged 8.6 μmol m−2 s−1, against 3.4 μmol m−2 s−1 during the period of reduced growth. In the active period, growth, unlike A or Δ, was strongly negatively correlated with air temperature. In contrast, growth and A were both correlated positively, and Δ correlated negatively, with air temperature during the reduced growth period. However, the depressions of A and growth might have simply run in parallel, without any causal relationship. Changes in A appeared to be largely due to stomatal limitations in the active growing season, with non-stomatal ones prevailing in the slow growth period. Foliar carbohydrates seemed not to have contributed appreciably to changes in growth rates and photosynthesis.
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The ecophysiological constraints on the production of the arabica and robusta coffee under shading or full sunlight are reviewed. These two species, which account for almost all the world’s production, were originally considered shade-obligatory, although unshaded plantations may out-yield shaded ones. As a rule, the benefits of shading increase as the environment becomes less favorable for coffee cultivation. Biennial production and branch die-back, which are strongly decreased under shading, are discussed. The relationships between gas exchange performance and key environmental factors are emphasized. Ecophysiological aspects of high density plantings are also examined.