No full-text available
To read the full-text of this research,
you can request a copy directly from the authors.
Leaf area index as an indicator of ecosystem services and management practices: An application for coffee agroforestry
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).
... 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). ...
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.
... 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. ...
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.
... 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). ...
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
... 1,2 To guarantee the investment made in the coffee crop implantation and production stages, the monitoring of coffee trees must be done continuously to make decisions regarding preventive or corrective interventions in a timely manner. [3][4][5][6] A dynamic way of monitoring the development of coffee crop was using spectral signatures acquired through orbital sensor systems, which responded differently according to the crop characteristics in the field, either by varying the phenological phases or by varying the vegetative vigor due to the occurrence of pests, diseases, and weeds. 7 By associating data from orbital sensor systems with remote sensing processing techniques, it was possible to obtain information on spectral responses of coffee trees, in order to follow changes in the landscape matrix during the monitoring period. ...
... 17,20,21 The application of modeling techniques based on time series of coffee plant vegetation index can be a method to reduce the confusion of classifying algorithms of agricultural crops, assisting in the decision making of protocols for preventive or corrective management. 6,22 Based on the assumption that a standard spectral-temporal signature can collaborate with the detection of coffee pest organisms, based on the coffee crop predicted and observed signatures, this work aimed to characterize the spectral dynamics of the vegetative development of coffee fields under different irrigation systems and evaluate the use of EVI to distinguish signatures and evaluate the accuracy of the prediction obtained from the temporal modeling of this index. ...
The coffee crop spectral behavior identification throughout its cycle can contribute to its development monitoring under pest incidence. We aim to identify coffee development through time signatures of enhanced vegetation index (EVI), as well as to evaluate the use of seasonal autoregressive integrated moving average (SARIMA) models to identify coffee trees spectrum-time patterns under different irrigation management and design future scenarios. Three coffee fields were selected under different irrigation systems, whose EVI data of 8 years were obtained from the moderate resolution image spectroradiometer sensor. Each coffee crop model was subjected to residual autocorrelation test and classified according to information criteria, while its accuracy was assessed by means of prediction error measures and agreement index. The estimated and observed EVI values were similar, even for the predicted year. However, in agricultural years during which coffee diseases occurred, the crops showed vegetative vigor below the expected.We concluded that SARIMA models enabled the establishment of a reliable spectral signature expected for coffee crop, which could help with crop management defining, regardless of the irrigation system adopted. Based on the evaluation of divergence between expected and observed spectral signatures, early signs of coffee underdevelopment were detected, which could reduce economic loss risks on its commercial chain.
... The agronomic yield cycles among trainings are about 4-5 years in high-density and 6-9 in low-density plantations in monoculture (Androcioli-Filho, 2002;Gokavi et al., 2019). Whatever the cultivation system, coffee tree production and yield cycles are regulated by diverse systems of trainings and renovations (Taugourdeau et al., 2014), which have essential roles to maintain enough yield throughout the tree lifespan, to permit that berries remain easily accessible from the ground for harvest and to permit the entry of sunlight and air in low layers, thereby minimizing the pest/disease incidence and increasing whole-canopy photosynthesis (Boorah et al., 2016). ...
... Leaves of orthotropic axes respect an opposite-decussate phyllotaxy, and the plagiotropic axes exhibit decussate-phyllotaxy, as at orthotropic axes, but both internode torsion and petiole angle reorientation, result in dorsiventral phyllotaxy (Dengler, 1999). Every year, carbon investments in foliage expansion precedes investments in berry formation, expansion, and maturation (Taugourdeau et al., 2014;Rakocevic et al., 2020). ...
In horticulture, different planting designs can be used to optimize the plant production. In the coffee tree, we assumed that different planting densities and spatial patterns may impact the growth of all branching order axes, which in turn would impact the berry production. The aim of this study was to quantify and compare axes growth, leaf area, berry distribution and yield in four production years, depending on four planting designs. Experimental data were collected in the 1st, 2nd, 6th and 7th production years (PY), on Coffea arabica trees planted in two high densities (6000 or 10,000 plants ha − 1) and planting patterns (square or rectangular). Coffee architecture was described from metamer to axis, layer, and plant scales. Metamer number per axis, axes number and cumulated length, together with berry distribution, were compared along 40 cm-thick layers of plant vertical profile, depending on the planting design. In the 1st and 2nd PY, plants were formed by two layers, with axes of 4th order appearing in layer 1. In the 2nd PY, the 3rd order axes which had a crucial role in total berry production , were about 3-4 folds more numerous than 2nd order axes in layer 1. In the 6th and 7th PY, the plants included five layers and five branching orders. The leaf area index, 2nd-4th order axes length, berry distribution and yield were shown to depend on both planting design and PY. Both planting patterns under 10,000 plants ha-1 and rectangular planting pattern under 6000 plants ha − 1 could be recommended for high production up to 7th PY, while the square planting pattern under 6000 plants ha − 1 must be pruned after 6th PY.
... The agronomic yield cycles among trainings are about 4-5 years in high-density and 6-9 in low-density plantations in monoculture (Androcioli-Filho, 2002;Gokavi et al., 2019). Whatever the cultivation system, coffee tree production and yield cycles are regulated by diverse systems of trainings and renovations (Taugourdeau et al., 2014), which have essential roles to maintain enough yield throughout the tree lifespan, to permit that berries remain easily accessible from the ground for harvest and to permit the entry of sunlight and air in low layers, thereby minimizing the pest/disease incidence and increasing whole-canopy photosynthesis (Boorah et al., 2016). ...
... Leaves of orthotropic axes respect an opposite-decussate phyllotaxy, and the plagiotropic axes exhibit decussate-phyllotaxy, as at orthotropic axes, but both internode torsion and petiole angle reorientation, result in dorsiventral phyllotaxy (Dengler, 1999). Every year, carbon investments in foliage expansion precedes investments in berry formation, expansion, and maturation (Taugourdeau et al., 2014;Rakocevic et al., 2020). ...
In horticulture, different planting designs can be used to optimize the plant production. In the coffee tree, we assumed that different planting densities and spatial patterns may impact the growth of all branching order axes, which in turn would impact the berry production. The aim of this study was to quantify and compare axes growth, leaf area, berry distribution and yield in four production years, depending on four planting designs. Experimental data were collected in the 1st, 2nd, 6th and 7th production years (PY), on Coffea arabica trees planted in two high densities (6000 or 10,000 plants ha −1) and planting patterns (square or rectangular). Coffee architecture was described from metamer to axis, layer, and plant scales. Metamer number per axis, axes number and cumu-lated length, together with berry distribution, were compared along 40 cm-thick layers of plant vertical profile, depending on the planting design. In the 1st and 2nd PY, plants were formed by two layers, with axes of 4th order appearing in layer 1. In the 2nd PY, the 3rd order axes which have a crucial role in total berry production, were about 3-4 folds more numerous than 2nd order axes in layer 1. In the 6th and 7th PY, the plants included five layers and five branching orders. The leaf area index, 2nd-4th order axes length, berry distribution and yield were shown to depend on both planting design and PY. Both planting patterns under 10,000 plants ha-1 and rectangular planting pattern under 6000 plants ha −1 could be recommended for high production up to 7th PY, while the square planting pattern under 6000 plants ha −1 must be pruned after 6th PY.
... For example, the mapping of AFS has been mainly done using high resolution imagery such as Quickbird or WorldView 2 using visual interpretation (Bégué et al. 2015), classification algorithms based on textural features (Gomez et al. 2010;Lelong et al. 2014), or a combination of different remote sensing products from Landsat, MODIS or IKONOS (Zomer et al. 2007). Mapping of canopy structure, such as leaf area index or above-ground biomass in tropical AFS however requires multispectral information, such as provided by MODIS and Sentinel-2 (Taugourdeau et al. 2014;Karlson et al. 2020). While the aforementioned studies are distributed around the tropics, there is no study to our knowledge about remote sensing of AFS in the Andean region. ...
... While CC, LAI and AGB have been successfully estimated in AFS around the world using multispectral sensors (e.g. Hansen et al. 2013;Dube and Mutanga 2015;Korhonen et al. 2017) and high resolution images (see Taugourdeau et al. 2014), to our knowledge this is the first study doing so in the Andean region. Even more, AFS in Colombia are frequently classified as forests in land-use classifications and hence no quantification or monitoring of their extent exists. ...
In the Colombian Andes, agroforestry is a traditional form of agriculture, characterized by a heterogeneous and often diversified composition of trees and crops. This form of land use provides important ecosystem services, such as carbon sequestration, reduction of soil erosion and the maintenance of biodiversity by providing a structural complex habitat. Satellite remote sensing is widely used for studying land use patterns and forest cover, however the discrimination between agroforestry systems and forests is still a challenge, especially in heterogeneous landscapes and in rough terrain. Here, we aim to advance the remote sensing of agroforestry systems using field measurements of vegetation structure in combination with Sentinel-2 images. We use spectral and textural variables derived from Sentinel-2 imagery to predict above ground biomass (AGB), leaf area index (LAI) and canopy closure (CC). The relationship between predicted and observed values obtained from Random Forest regression models showed good fits: for AGB with an R2 = 0.92 and relative RMSE = 34%; for LAI with an R2 = 0.91 and relative RMSE = 19%; and for CC an R2 = 0.89 and relative RMSE = 9%. This allowed us to map these important ecosystem variables at landscape scale and establish empirical thresholds, with which a discrimination of agroforestry systems from forests was possible with an accuracy of 94%. Our results suggest that the relationship between vegetation structure and the spectral information obtained by Sentinel-2 can contribute to the detection and characterization of agroforestry systems and thus help quantifying the ecosystem services and biodiversity conservation potential provided by this type of tropical agriculture.
... 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. ...
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.
... The Leaf Area Index (LAI) is one of the most fundamental vegetation biophysical parameters, defined as a dimensionless measure of the one-sided leaf area (m 2 ) per unit ground surface area (m 2 ) (Asner et al., 2003;Chen et al., 1992). LAI has long been reported as a good indicator for several agronomic, ecological, and hydrological applications (Reyes-González et al., 2019;Charbonnier, 2013;Viña et al., 2011;Jung et al., 2010;Fassnacht et al., 1997;Taugourdeau et al., 2014;Van den Hurk et al., 2003;Jarlan et al., 2008;Mourad et al., 2020). ...
The main objective of this article was to investigate the correlation between actual crop yield and Sentinel-2 Leaf Area Index (LAI) for the further possibility of predict model creating. To do so, the following steps have been done. Step 1 – the dataset of actual crop yield was collected for 2364 fields in Ukraine represented with maize, soy, sunflower, winter wheat, winter rapeseed and winter barley. Step 2 – the dataset of Sentinel-2 LAI was collected for 2016-2018 period according to the actual crop yield available. Step 3 – LAI preprocessing (spatial averaging, temporal interpolation/extrapolation to fill the time series gaps, smoothing time series dynamics, temporal averaging). In order to accomplish the process of filling the gaps for the LAI time series, the regular time series dynamics of LAI with a 1-day interval were created using 4 methods: linear interpolation, spline interpolation, LOCF (Last Observation Carried Forward) and ARIMA (AutoRegressive Integrated Moving Average). The time series smoothing process have been accomplish using the local polynomial regression (LOESS) function with different degrees of smoothing. The LAI dynamics preprocessing step did not strongly affect the improvement of the correlation coefficients. Thus, the smoothing process for the time series LAI dynamics at the 0.1 degree of smoothing according to the LOCF and ARIMA gap-filling methods of improved correlation coefficients by 0.01 on average. Step 4 – actual yield values were related to preprocessed satellite-based LAI (correlation of actual yields and LAI). A strong relationship was not indicated (with averaged by vegetation periods correlation coefficient of 0.4 for maize, 0.52 – soy, 0.39 – sunflower, 0.86 – winter barley, 0.54 – winter rapeseed and 0.5 – winter wheat). Since the reliability of obtained correlation coefficients also depends on how many observed data points were in the sample, the hypothesis test of the "significance of the correlation coefficient" has been performed and shows the significance level of p < 0.05 for all crops except winter barley (there is insufficient evidence to conclude that high correlation coefficient of 0.86 for this crop is significant). The average correlation coefficient for all crops is about 0.5 (p < 0.05) which is considered low/moderate. Thus, an attempt to create a linear crop yield prediction model using only Leaf Area Index (LAI) derived from Sentinel-2 will not be effective (based on the cases considered).
... forest plantation or forest). The good fit of LAI prediction models in this study could serve as an indicator of key ecosystem characteristics like habitat complexity (Rutten et al. 2015) and ecosystem services (Taugourdeau et al. 2014) in the Andean region. ...
Agroforestry systems (AFS) are important for biodiversity conservation outside protected areas. The presence of shade trees in AFS form structurally complex habitats that provide food for many species. Habitat complexity is considered an essential biodiversity variable and its characterization is now possible using remote sensing techniques, including 3D point clouds derived from images obtained with unmanned aerial vehicles (UAVs). However, studies evaluating the relationship between canopy structure and variables derived from 3D clouds are rare for AFS, especially for the tropical Andes. Here, we show how six important variables of canopy structure can be predicted across a canopy structure gradient from AFS with cacao and coffee to a natural forest using characteristics extracted from the 3D point clouds and multiple linear regression. For leaf area index the best model obtained an R² of 0.82 with a relative RMSE = 24%, for canopy cover an R² of 0.81 and relative RMSE = 13%, for above-ground biomass an R² of 0.81 and relative RMSE = 10%, the density of shade trees was predicted with an R² of 0.66 and relative RMSE = 34%, the mean height and the standard deviation of height in the canopy obtained an R² of 0.82 and 0.79 respectively, and relative RMSE of 18% for both. The approach presented in this study allows an accurate characterization of the canopy structure of AFS using UAVs, which can be useful for assessing above-ground biomass and biodiversity in tropical agricultural landscapes to monitor sustainable management practices and derive payments for ecosystem services.
... While unpruned Cordia and Albizia trees have contrasting tree water use patterns (Buyinza et al. 2019), the water use interactions in managed coffee agroforestry systems have not been explored in similar systems. The impact of the semi-deciduous nature of Cordia and Albizia trees has also been overlooked, yet tree leafing phenology can directly impact agroforestry tree growth and water use (Taugourdeau et al. 2014). Understanding the relationship between tree leafing phenology and tree water use can also inform appropriate management options for agroforestry trees in smallholder farms. ...
Tree pruning is an important tree management option for reducing shading effects and altering whole-tree water use in smallholder farming systems. In this study, sap flow meters (SFM1s) were used to monitor whole- tree water use in Cordia africana (Cordia), Albizia coriaria (Albizia) and Coffea arabica (coffee) trees in two farms in Eastern Uganda. Overstory trees were subjected to a 50% pruning regime at a 6-month interval over a period of 20 months (July 2018–February 2020). Analysis of variance General Linear Model was performed to assess the influence of tree species, management, season and their interaction on mean daily sap flow. Pairwise Pearson correlation coefficients between daily sap flow and leaf phenology were also obtained. Pruning altered the synchrony in the vegetative phenology of Albizia trees, as leaf cover changes occurred earlier in pruned trees than in unpruned trees. Pruned Cordia and Albizia trees respectively used 22.8% and 50.1% less water than unpruned trees whose average daily water use was 76.5L day⁻¹ and 133.7L day⁻¹ respectively. Episodes of reverse flows were observed in Albizia trees (pruned and unpruned) and the pruned Cordia during certain periods of the year. There was a statistically significant main effect of tree species, pruning, season and their interaction on daily tree water use (P < 0.05). Coffee used 0.1 to 4.3 L of water per day over the 20-month period. While unshaded coffee used more water than shaded coffee, coffee growing under pruned trees used more water than coffee under unpruned trees. This could have resulted from more transpiration pull in coffee resulting from increased radiation with reduced shading. Subsequently, canopy pruning reduced the water demand of the tree component and resulted in recharge in the crop-rooting zone, although this seemed to appear later following consistent pruning. The study findings demonstrate that agroforestry tree canopy pruning can regulate water use in smallholder agroforestry systems, the benefits of other tree products notwithstanding.
... Potential plant growth simulation depends on RUE, LAI, and the light extinction coefficient (k) used to calculate the fraction of light intercepted by leaves [37]. LAI has already been shown to be a promising indicator of coffee yield, especially when combined with other data such as fertilizer use and precipitation [38]. ...
Coffee (Coffea species) and Cocoa (Theobroma cacao) are important cash crops grown in the tropics but traded globally. This study was conducted to apply the ALMANAC model to these crops for the first time, and to test its ability to simulate them under agroforestry management schemes and varying precipitation amounts. To create this simulation, coffee was grown on a site in Kaua’i, Hawai’i, USA, and cocoa was grown on a site in Sefwi Bekwai, Ghana. A stand-in for a tropical overstory tree was created for agroforestry simulations using altered parameters for carob, a common taller tropical tree for these regions. For both crops, ALMANAC was able to realistically simulate yields when compared to the collected total yield data. On Kaua’i, the mean simulated yield was 2% different from the mean measured yield, and in all three years, the simulated values were within 10% of the measured values. For cocoa, the mean simulated yield was 3% different from the mean measured yield and the simulated yield was within 10% of measured yields for all four available years. When precipitation patterns were altered, in Ghana, the wetter site showed lower percent changes in yield than the drier site in Hawai’i. When agroforestry-style management was simulated, a low Leaf Area Index (LAI) of the overstory showed positive or no effect on yields, but when LAI climbed too high, the simulation was able to show the detrimental effect this competition had on crop yields. These simulation results are supported by other literature documenting the effects of agroforestry on tropical crops. This research has applied ALMANAC to new crops and demonstrated its simulation of different management and environmental conditions. The results show promise for ALMANAC’s applicability to these scenarios as well as its potential to be further tested and utilized in new circumstances.
... The data could be used to upscale vegetation variables from the field variable to a larger scale using satellite images. Indeed, it is possible to use very high spatial resolution images to produce intermediate vegetation maps, and thus calibrate these maps to satellite images with a lower resolution (Taugourdeau et al., 2014). ...
Unmanned aerial vehicles (UAVs) are widely used to assess the vegetation of an ecosystem. This report presents three data sets from UAVs used on a savannah-type ecosystem in Senegal. Two data sets contain an orthomosaic and a surface and terrain digital model (UAV outputs), along with associated field measurements on the tree and herbaceous layers, while the third data set contains an orthomosaic and digital surface model, along with field measurements on the herbaceous layers. One data set was compiled over the entire rainy season on the same plot (plot dataset). One was compiled across a landscape at the 7000 ha Dahra Djoloff research center (CRZ-dahra Centre de recherche zootechnique de Dahra). The third data set was compiled across Senegal from the North to the Southeast of the country with wide variability in climate and soil conditions. All the data sets are in Open Access in the Zenodo repository. These data sets could be used in many different studies: calibration between field measurements and UAV outputs on a large scale, or used as an intermediate step between field and satellite images. K E Y W O R D S savannah, Senegal, tree, Uav Résumé Les véhicules aériens sans pilote (UAV) sont largement utilisés pour évaluer la végétation
... forest plantation or forest). The good t of LAI prediction models in this study could serve as an indicator of key ecosystem characteristics like habitat complexity (Rutten et al., 2015) and ecosystem services (Taugourdeau et al., 2014) The inclusion of land-use type as an additive term in the multiple linear regression model resulted in signi cant improvements for prediction of all canopy structure variables. This indicates differences in canopy structure (or architecture) between land-use types that surprisingly cannot be captured by the 3D variables generated in this study. ...
Agroforestry systems (AFS) are important for biodiversity conservation outside protected areas. The presence of shade trees in AFS form structurally complex habitats that provide food for many species. Habitat complexity is considered an essential biodiversity variable and its characterization is now possible using remote sensing techniques, including 3D point clouds derived from images obtained with unmanned aerial vehicles (UAVs). However, studies evaluating the relationship between canopy structure and variables derived from 3D clouds are rare for AFS, especially for the tropical Andes. Here, we show how six important variables of canopy structure can be predicted across a canopy structure gradient from AFS with cacao and coffee to a natural forest using characteristics extracted from the 3D point clouds and multiple linear regression. For leaf area index the best model obtained an R² of 0.82 with a relative RMSE = 24%, for canopy cover an R² of 0.81 and relative RMSE = 13%, for above-ground biomass (AGB) an R² of 0.81 and relative RMSE = 10%, the density of shade trees was predicted with an R² of 0.66 and relative RMSE = 34%, the mean height and the standard deviation of height in the canopy obtained an R² of 0.82 and 0.79 respectively, and relative RMSE of 18% for both. The approach presented in this study allows an accurate characterization of the canopy structure of AFS using UAVs, which can be useful for assessing above-ground biomass and biodiversity in tropical agricultural landscapes to monitor sustainable management practices and derive payments for ecosystem services.
... In terms of the regional distribution of studies, the main concentration of ELA studies has been in United States, China, Germany, Italy, and other north temperate countries, with the number of studies in the literature exceeding 12. However, ELA research in the tropics, where agroforestry (cocoa and coffee) is better developed, does not receive as much attention as research in temperate regions [70,71]. The reasons for this phenomenon are the influence of natural conditions and socioeconomic differences, and also national policy support and the attention of research institutions that play an important role in it [72]. ...
Since the 1950s, the rapid depletion of natural capital due to human activities has led to a growing global demand for ecological and socioeconomic sustainability, driving the development of agroforestry. Although agroforestry ecosystems can maintain sustainable land resources and maximize land productivity, their quality continues to fluctuate. Moreover, there is no clear review of studies addressing the impact of the evolution of agroforestry landscape patterns on their ecosystems , and to fill this gap, we conducted an inclusive review. A total of 163 publications related to agroforestry ecosystem quality and landscape patterns (ELA) that met a set of inclusion criteria were obtained through the Scopus database using the literature review method of searching, appraisal, and synthesis report. The objectives were to summarize the research progress on ELA, reveal the dynamic coupling mechanism between landscape pattern evolution and ecosystem quality, explore the role of landscape pattern optimization in ecological processes and services in agroforestry, and suggest future research and policy directions. Although the understanding of landscape patterns and ecological processes has been deepened, there are limitations in the study of scales, habitats, and other aspects. It is emphasized that understanding the interaction between agroforestry and other landscape elements in spatiotemporal organization is a prerequisite for promoting sustainable benefits, and that the challenges of spatiotemporal dynamics are integrated to scientifically optimize agroforestry landscape patterns. Finally, it is necessary to gain revelations based on the coupling relationship of ELA, through scientific management of agroforestry landscapes, in order to sustainably consolidate the effectiveness of karst rocky desertification (KRD) control and to enhance human welfare.
... The trees were simply represented by two cylinders: a narrow S. Dupont et al. one of 6.0 m height and 0.5 m diameter representing the trunk, and above a larger one of 3.0 m diameter representing the tree crown. While the modeled crop has similar characteristics as the coffee layer of the agroforestry system in Costa Rica (Taugourdeau et al., 2014), the shade trees differ significantly from the Erythrina poepigiana. The modeled trees are smaller, narrower and have a lighter leaf area density, but their density per hectare is larger. ...
Agroforestry systems associating trees with crops are gaining a growing interest due to their environmental benefits in a context of climate change and biodiversity loss. Still, the impact of trees on the wind dynamics within agroforestry systems remains poorly understood despite the key role played by the wind in energy and mass exchanges, including disease and pest propagation. Here, we present the first detailed analysis of the wind dynamics over agroforestry systems, combining in situ measurements and instantaneous airflow simulations, with a numerical application on spore-like particle dispersion from an infection point source at crop top. Simulations reproduce remarkably well most characteristics of the turbulent wind flow within the agroforestry system. Simulations reveal the presence of two inflection points on the mean wind velocity profile, at crop and tree tops, both inducing the development of mixing-layer type eddies, controlling most of the turbulent exchanges within the agroforestry system. Relative to the local wind, the turbulence at the crop scale is more intense and intermittent in presence of trees. With increasing tree density, the turbulence at crop top becomes dominated by tree-scale motions developing at tree top. The presence of trees has a different impact on particle dispersion according to the particle size and the wind intensity. Trees accentuate the vertical and transversal dispersal of submicron spores while they enhance the short-range deposition of coarser spores on crops, the more as the wind is low, and thus limit the long-range dispersal of coarse spores. Finally, a simple parameterization of the mean wind velocity vertical profile is proposed for agroforestry systems, depending only on the foliage densities and heights of the tree and crop layers. This parameterization leads to an indication of the agroforestry system efficiency to limit spore propagation through an estimation of the Rouse number at crop top.
... This reflects focus on ecosystem service conservation and policy development with regard to AF in temperate zones of the European region (Plieninger et al., 2015;Elbakidze et al., 2021). Attention has also been given to ecosystem services provided by cocoa and coffee AF in the tropics (Taugourdeau et al., 2014;Cerda et al., 2020). The USA, India, the UK, and Indonesia have published cumulatively >17 publications, and China and Brazil have >10 publications. ...
Agroforestry (AF) has become an important strategy in reconciling the contradictory requirements of environmental protection and economic development in ecologically fragile areas, and whose multiple ecosystem services provide effective ways to promote the restoration of degraded ecosystems in the region. However, agroforestry ecosystem services (AFES) are usually constrained by their generative elements (vulnerability, structure, function, and ecological assets) and service management—both crucial for informed decision-making which enhances AFES supply capacity and AF sustainable management. Karst rocky desertification (KRD) is a typical case in an ecologically fragile area, and within the KRD region greatly relevant for promoting AFES as a strategy for restoring degraded regional ecosystems and for achieving sustainable development goals. In this study, a total of 164 publications related to AFES that met a set of inclusion criteria were obtained through the Scopus database using the literature review method of searching, appraisal, synthesis, and analysis. From the systematic literature review results, (i) we found that the number of relevant publications generally exhibited a year-on-year growth trend, with AFES generation elements being the most common topic (68.11 % of publications), and service management research being the second most common (31.89 % of publications); (ii) we summarised the main progress and landmark results of AFES generation elements and service management research and explored the relevant key scientific questions; and (iii) the above information enlightened the key improvement areas of KRD control ecosystem within three aspects: natural environment, agricultural development, and human-environment relationship. This study provides agroforestry practitioners and relevant decision-makers with information for improving and managing the supply capacity of AFES, and also presents important insights on the KRD control ecosystem to land degradation restoration technicians.
... NPP plays an important role in carbon cycling and reflects on the quality of the terrestrial ecosystem (Field et al., 1998;Zhu et al., 2007). In practice, FVC and NPP are regarded as the indicators of carbon sequestration services as they represent the vegetation dynamics and productivity (Sha et al., 2020;Mu et al., 2021); in contrast, LAI and ET can be used as indicators of water provision service as they affect the hydraulic processes of ET, infiltration, aquifer recharge, and streamflow (Taugourdeau et al., 2014;Chang et al., 2017). As aforementioned, FVC, LAI, ET, and NPP are the key indicators in linking ecosystem functioning and climate feedbacks. ...
In recent decades, the influence of climate change and human activities on the ecosystem services (ES) in the Qinghai–Tibet Plateau (QTP) has been extensively investigated. However, few studies focus on linear traffic corridor area, which is heavily affected by human activities. Taking the Golmud–Lhasa national highway corridor as a case, this study investigated the land-use and land-cover change (LUCC) and spatiotemporal variations of ES indicators using ecosystem indices of fractional vegetation cover (FVC), leaf area index (LAI), evapotranspiration (ET), and net primary productivity (NPP) from 2000 to 2020. The results indicated that LUCC was faster in the last decade, mostly characterized by the conversion from grassland to unused land. In buffer within 3000 m, the proportions of productive areas represented the increased trends with distance. In terms of ES variations, the improved areas outweighed the degraded areas in terms of FVC, LAI, and NPP from 2000 to 2020, mostly positioned in the Qinghai Province. In addition, FVC, LAI, and NPP peaked at approximately 6000 m over time. With regard to influencing factors, precipitation (20.54%) and temperature (14.19%) both positively influenced the spatiotemporal variation of FVC. Nearly 60% of the area exhibited an increased NPP over time, especially in the Qinghai Province, which could be attributed to the temperature increase over the last two decades. In addition, the distance effects of climatic factors on ES indicators exhibited that the coincident effects almost showed an opposite trend, while the reverse effects showed a similar trend. The findings of this study could provide a reference for the ecological recovery of traffic corridors in alpine fragile areas.
... UAVs or other very high resolution (VHR) remote sensing systems could be used to simplify scaling-up from field measurements and conventional remote sensing systems (Taugourdeau et al., 2014). ...
... UAVs or other very high resolution (VHR) remote sensing systems could be used to simplify scaling-up from field measurements and conventional remote sensing systems (Taugourdeau et al., 2014). ...
Herbaceous aboveground biomass (HAB) is a key indicator of grassland vegetation and indirect estimation tools, such as remote sensing imagery, increase the potential for covering larger areas in a timely and cost-efficient way. Structure from Motion (SfM) is an image analysis process that can create a variety of 3D spatial models as well as 2D orthomosaics from a set of images. Computed from Unmanned Aerial Vehicle (UAV) and ground camera measurements, the SfM potential to estimate the herbaceous aboveground biomass in Sahelian rangelands was tested in this study. Both UAV and ground camera recordings were used at three different scales: temporal, landscape, and national (across Senegal). All images were processed using PIX4D software (pho-togrammetry software) and were used to extract vegetation indices and heights. A random forest algorithm was used to estimate the HAB and the average estimation errors were around 150 g m − ² for fresh mass (20% relative error) and 60 g m − ² for dry mass (around 25% error). A comparison between different datasets revealed that the estimates based on camera data were slightly more accurate than those from UAV data. It was also found that combining datasets across scales for the same type of tool (UAV or camera) could be a useful option for monitoring HAB in Sahelian rangelands or in other grassy ecosystems. K E Y W O R D S 3D model, herbaceous aboveground biomass, savannah ecosystem, Senegal, Unmanned Aerial Vehicle, vegetation index
... Several studies indicated that shade trees on the farmland protect crops from extremely high temperatures (Lin, 2007;Ricci et al., 2013), frosts and hails (Alvarenga et al., 2004), strong winds (Pezzopane et al., 2011) and diversifies income (Chengappa et al., 2017;Jezeer et al., 2017). Shade coffee production systems reduce the incoming solar radiation (Lopez-Bravo et al., 2012), buffer and mitigate the coffee plants from microclimate variability (Gomes et al., 2016) and at optimal level enhance resource capture, such as light (Taugourdeau et al., 2014). These improve the resilience and adaptation of coffee farming systems to climate change and variability and reduce the coffee plants physiological stress (Coltri et al., 2019). ...
Recent climate change models predict that coffee production and the livelihood of millions of farmers will be hardly affected by climate change. Climate changes pronounced in increasing temperature and rainfall variability will reduce the bio-climatic suitable areas, growth and yield of coffee and will induce the occurrence of pests and diseases. Understanding the extent of the climate-driven impact on coffee production and farmers’ adaptation strategies is vital in sustaining coffee productivity. In the form of in-depth analysis, this review begins by contextualizing climate change and coffee production and gives insight into the impact of climate change on coffee suitability areas, growth, yield and the incidence of pests and diseases. It further examines the adaptation strategies pursued by farmers to reduce the impacts of climate change. Site-specific adaptation strategies implemented by farmers to minimize detrimental effects of climate change include (i) selecting appropriate shade tree species and their optimal management, (ii) farmers training, (iii) soil fertility maintenance and protection and (iv) pests and diseases management. Moreover, improving farmers’ access to weather, fair market and technology will enhance their adaptive capacity to climate change. Finally, designing adaptation policies and building the existing practices help the small farmers to pursue climate-resilient coffee production.
... Like defoliation, the lowest level of the process of leaf emergence was defined by the interaction between fruit load (P14, Table 1) and fruit phenology (P15 to P17, Table 1) to account for the influence of the source-sink relationship on leaf dynamics (Avelino et al., 1993;Vezy et al., 2020). Fruit load competes with vegetative growth (DaMatta et al., 2007), and possibly to a greater extent during the final stages of fruit development (Taugourdeau et al., 2014). We next aggregated the input attribute rainfall (P3 , Table 1) as a limiting factor for leaf emergence, followed by the input attribute nutrition (P7 , Table 1) as a stimulating factor for leaf emergence. ...
CONTEXT
Coffee leaf rust (CLR) epidemics on Coffea arabica have led to severe socio-economic crises in Latin America starting in 2008. Until now, the scattered nature of scientific and empirical knowledge of the highly complex CLR-coffee pathosystem has been an obstacle to the development of CLR forecasting models.
OBJECTIVE
To help prevent new severe epidemics, we built ExpeRoya, a qualitative model, based on a review of the scientific literature and expert opinion, to forecast the risk of a monthly increase in the incidence of CLR at plot and landscape levels.
METHODS
We adopted the IPSIM (Injury Profile SIMulator) framework, a qualitative and aggregative modeling approach that describes the effects of the cropping system and the plot environment on injuries, thereby making it possible to incorporate scattered knowledge on the system and all its complexity in a simplified way. Involving experts makes this approach powerful and robust because it builds on empirical knowledge based on a very large number of field observations. We argue that broad expert knowledge provides more accurate information on the manifold interactions in the system than existing quantitative models can. The structure of ExpeRoya was discussed with coffee sector experts in 19 workshops and validated in an online survey with 17 CLR experts.
RESULTS AND CONCLUSIONS
ExpeRoya successfully integrates in a simple way 229 multiple interactions that exist within the CLR-coffee pathosystem based on only 12 input variables easily acquired in the field: one incidence monitoring variable; two meteorological variables (temperature and rainfall), four crop management variables (management of shade cover, fungicide application, nutrition and pruning of coffee trees) and five coffee tree characteristics (dates of flowering, beginning and end of harvest, fruit load and cultivar genetic resistance). Coffee institutes in Honduras and Nicaragua now use ExpeRoya, hosted by the platform Pergamino (https://www.redpergamino.net/app-experoya), to assist them in preparing their monthly CLR warning bulletins for growers. ExpeRoya is an improved forecasting model of CLR by fully incorporating the main biophysical factors affecting CLR at the plot and landscape levels.
SIGNIFICANCE
ExpeRoya is both a framework and a proof of concept that improves both forecasting and the comprehensive modeling of CLR. ExpeRoya is a powerful yet user-friendly model designed for all actors of the coffee sector, particularly smallholder farmers and extension agents. ExpeRoya is adaptable: users can modify the model according to advances in knowledge and/or their own expertise of the system. ExpeRoya can help prevent future socio-economic crises.
... The expectation of the life of a coffee tree in their natural habitat is up to 100 years, while in plantations it is about 30-40 years (Gokavi et al., 2019). In plantations, tree production and yield cycles are regulated by diverse systems of training and renovations (Taugourdeau et al., 2014;Rakocevic et al., 2021a). In Brazil, about 300,000 ha are planted every year for orchard renovation or for the new area's plantation, which corresponds to 13% of the areas under coffee crops (CONAB, 2021). ...
Increases in water use efficiency (WUE) and the reduction of negative impacts of high temperatures associated with high solar radiation are being achieved with the application of fine particle film of calcined and purified kaolin (KF) on the leaves and fruits of various plant species. KF was applied on young Coffea arabica and Coffea canephora plants before their transition from nursery to full sunlight during autumn and summer. The effects of KF were evaluated through the responses of leaf temperature (Tleaf), net CO2 assimilation rate (A), stomatal conductance (gs), transpiration (E), WUE, crop water stress index (CWSI), index of relative stomatal conductance (Ig), initial fluorescence (F0), and photosynthetic index (PI) in the first 2–3 weeks after the plant transitions to the full sun. All measurements were performed at midday. In Coffea plants, KF decreased the Tleaf up to 6.7�C/5.6�C and reduced the CWSI. The plants that were not protected with KF showed lower A, gs, E, and Ig than those protected with KF. C. canephora plants protected with KF achieved higher WUE compared with those not protected by 11.23% in autumn and 95.58% in summer. In both Coffea sp., KF application reduced F0, indicating reduced physical dissociation of the PSII reaction centers from the lightharvesting system, which was supported with increased PI. The use of KF can be recommended as a management strategy in the transition of Coffea seedlings from the nursery shade to the full sunlight, to protect leaves against the excessive solar radiation and high temperatures, especially in C. canephora during the summer.
... Leaves having lower SLA are usually thicker or denser in stomata. Variation in both leaf thickness and stomatal density are responsible for variation in SLA and this is modified by the local environment (Wilson et al. 1999, Taugourdeau et al. 2014. Higher SLA at lower elevations could imply a reduced drought stress, and an increased leaf water content of the coffee plant. ...
Coffee is an important crop in the global south. However, ongoing changes in the climate system reinforce the need to quantify coffee plants' ecological and eco-physiological traits to assure coffee production in the future. One way to assess how environmental changes affect coffee performance is via leaf traits, most notably leaf carbon and nitrogen concentrations (to reflect the nutrient status), leaf stable carbon isotope composition (δ¹³C) to determine intrinsic water use efficiency (WUEi), and specific leaf area (SLA) to describe carbon gain relative to water loss within a plant canopy as these traits are related to yields. Therefore, we sampled coffee plants growing at contrasting elevations using a space-for-time substitution approach for warming and superimposed a canopy cover gradient to assess whether increasing canopy cover could modulate responses to temperature. Three coffee shrubs were sampled in each of 59 coffee farms in southwest Ethiopia across elevations of 1500–2160 m a.s.l. and along canopy cover gradients from open to deep shade. Soil nutrient concentrations, light availability, soil temperature and moisture were quantified for each coffee shrub. Elevation and shade tree canopy cover significantly and interactively affected WUEi. Elevation was found to be the driving factor for microclimate and soil factors which indirectly influenced both SLA and WUEi. Both of these coffee leaf traits are moderately governed by soil temperature whereas leaf N and C:N are mainly controlled by soil temperature and soil chemical variables. As elevation increased, WUEi kept increasing at light (< 35%) to intermediate shade levels (35–65%), and the values decreased at dense shade levels (65–100%) at high elevations, suggesting that coffee plants growing at high elevations with light shade can assimilate more CO2 with minimum evaporative water loss. SLA declined with elevation. Leaf N and leaf C:N responded negatively and positively to shade canopy cover, respectively. In sum, elevation and canopy cover interactively determined microclimate and coffee leaf traits. Our findings are useful to adjust the intensity of shade, along with other tree-level management tools, to modulate climate-change effects on coffee at the farm level.
... The canopy structure of crops directly affected radiation interception and conversion efficiency and thus reasonable and efficient canopy structure was the basis of high crop production [53,54] . This study showed that the irrigation level and shading cultivation mode notably affected leaf area index (LAI), which was consistent crop canopy structure not only was influenced by its own genetic characteristics and physiological and biochemical processes, but also by the constraints of cultivation measures and environmental conditions [53,55] . DI 1 and S 1 intercept more light radiation by increasing LAI, which was conducive to enhancing photosynthesis and promoting the growth of Arabica coffee. ...
... Other tools than the UAV can be used to assess the woody and herbaceous phytomass. For instance, very-high-resolution-spatial (VHRS) images from satellites have been used to assess tree density (Brandt et al., 2020), and so has the tree-leaf area index (Taugourdeau et al., 2014). However, VHRS remote sensing tools have a lower spatial resolution than onboard UAV sensors. ...
The phytomass of herbaceous and woody plants is the main source of feed for pastoral livestock in the Sahelian savanna. The assessment of the available feedstock plays a key role in national livestock policies and generally requires many field measurements of both herbaceous and woody plants. In this study, we tested the possibility of using a red-green-blue (RGB) unmanned aerial vehicle (UAV) to evaluate the phytomass of both woody and herbaceous species. We thus mapped 38 one hectare plots with a Dji Spark UAV in Northern Senegal. The herbaceous phytomass was measured on the ground. For the woody communities, we evaluated the leaf phytomass using dendrometric parameters combined with allometric equations. We performed partial-least square regressions between UAV-based three-dimension and color indices and phytomass. Results showed a Q² (cross validation results for each response variable) of 0.57 for woody phytomass, 0.68 for herbaceous dry mass, and 0.76 for their fresh mass. This study confirmed the relevance of using low-cost RGB UAV to assess savanna phytomass.
... The following variables were evaluated monthly during the 6-month experiment period: stem height was measured from ground to apex of each plant with a flexometer; stem thickness (diameter) was measured at 1 cm from the ground surface with a digital Vernier; and leaves were counted and measured (length (L) and width (W)) with a flexometer. Leaf area (A) was calculated according to Taugourdeau et al. (2014) using the following formula: ...
Rhizosphere processes are critical for nutrient cycling, maintaining soil quality and sustaining plant growth and productivity. However, our understanding of the interplay between plant roots and other soil ecosystem engineers such as earthworms is still limited. Our objective was to determine the influence of Pontoscolex corethrurus, a common endogeic earthworm, on the bulk and rhizosphere soil chemical properties and on the growth of two economically important coffee species. A six-month mesocosm experiment was implemented to grow Coffea arabica and C. canephora with and without earthworms. We measured plant growth variables (height, stem thickness, number of leaves, leaf area, biomass and chemical composition) and soil physico-chemical parameters in both the rhizosphere and bulk soils. We found that soil properties significantly differed among soil zones (bulk vs. rhizosphere). Contents of total P, H, Ca, C/N ratio and CEC were consistently larger in the bulk soil than in the rhizosphere, while C, N and Mg contents were highest in the rhizosphere soil. Although the presence of earthworms had little effect on plant growth, their influence on plant and soil nutrient contents was stronger and highly dependent on coffee species. In C. arabica, earthworms reduced the depletion of Na and Ca in the rhizosphere, but promoted the accumulation of available P and possibly accelerated plant N uptake in that of C. canephora. These differences may be explained by the indirect effect of earthworms on nutrient dynamics, likely mediated by induced shifts in the rhizosphere microbial community. Our findings contribute to the understanding of nutrient dynamics in the rhizosphere of two coffee species, revealing a complex influence of earthworms in rhizosphere processes, and call for a further understanding of the microbe-mediated impact of earthworms in the rhizosphere of C. arabica and C. canephora.
... At present, simulation models based on physical phenomena are available to simulate flows involved in the major coffee growth mechanisms of photosynthesis, respiration and transpiration (van Oijen et al., 2010a;Rodríguez et al., 2011;Charbonnier et al., 2013;Vezy et al., 2018Vezy et al., , 2020, and even coffee canopy temperatures under shade trees (Vezy et al., 2018). However, these process models are based on physical phenomena whose descriptors, such as the global radiation extinction coefficient of the trees and tree leaf area index (Taugourdeau et al., 2014), are difficult to measure. Some studies developed simple equations to forecast minimum night crop temperatures, with a view to predicting frost events (Georg, 1978;Lhomme and Guilioni, 2004), but these models were still using complex parameters that were difficult to measure. ...
In Central America, coffee is mainly grown in agroforestry systems. This practice modifies the microclimate, which, in turn, influences coffee growth and development. However, modeling these microclimate modifications is a challenge when trying to predict the development of a disease in the understory crop, based on variables usually monitored in weather stations exposed to full sunlight. Furthermore, critical variables for plant disease development, such as leaf wetness duration and leaf temperatures, are generally not measured by weather stations. In our study, we sought to build models explaining daily minimum and maximum coffee leaf temperatures, daily coffee leaf wetness duration, and minimum and maximum air temperatures in agroforestry systems with a single shade tree species, which are common in Central America, and which were characterized by shade tree height, canopy openness and light gap distribution. The modeled variables were mainly explained by one or more meteorological variables provided by reference weather stations exposed to full sunlight. The presence of shade trees resulted in a buffer effect, reducing daily maximum air and leaf temperatures, and increasing daily minimum air and leaf temperatures. Moreover, except for the daily minimum air temperature under shade, shade tree characteristics affected these microclimatic variables. Indeed, the buffer effect on the daily maximum air temperature increased with shade trees 7 m tall or over, whereas for extreme leaf temperatures, this effect seemed to be further intensified by a dense and homogeneous canopy. The tallest shade trees also tended to provide conditions that reduced coffee leaf wetness duration. The coffee leaf stratum affected the daily maximum leaf temperature, with a top layer intercepting radiation for the lower strata, but had no effect on the daily minimum leaf temperature, detected at night. The models developed were simple equations allowing interpretation of shade tree height, the effects of canopy characteristics on the microclimate and were therefore useful for designing and managing agroforestry system. The more accurate models could be incorporated into an early warning system for coffee pests and diseases in the region.
... Due to the need to protect coffee production, different monitoring techniques have been applied for years, to protect all coffee grower's energy, time and money investments. In order to make large-scale monitoring feasible, the use of remote sensing has grown in recent years (Chemura et al., 2017b;Taugourdeau et al., 2014). ...
Using spectral information, obtained from orbital sensor systems, combined with spectral indices, it's possible to characterize coffee trees conditions with their intrinsic characteristics, which can improve the imaging accuracy and optimize the crop monitoring tasks. However, within center pivot shape, a circular planting orientation is a feature that can difficult to determine coffee yield through remote sensing, resulting in inaccurate inferences about its spectral signature and its yield correlation. The objective of this study was to evaluate the correlation of different phenological stages spectral responses of coffee, under distinct apparent brightness conditions, with the yield sampled in field. The study was carried out on a center pivot irrigated area, located in Presidente Olegário municipality, Minas Gerais, Brazil. Yield data was obtained of 114 georeferenced sample points. Landsat-8 data, obtained between 05/25/2015 and 06/28/2016, were submitted to statistical analysis of Correlation and Multiple Linear Regression in conjunction with yield data. It was observed that the positional arrangement and the planting orientation significantly interfered in the yield estimation. A brightness difference was observed within the collateral area sectors, which raised the coffee plants spectral complexity. This demanded a conditional approach for data analyses and interpretation processes. Based on results, an evidence of good explanatory and predictive relationship with the coffee yield was found for Landsat-8 images when divergent brightness subsets were evaluated separately, raising the forecast accuracy from spectral data. It was concluded that the coffee phenological stages with the highest yield predictive potential are the “dormant bud” and “lead bead” stages.
... As an indicator of overall productivity, green coffee yields averaged 1351 kg ha −1 year −1 (SD = 347 kg N ha −1 year −1 ) between 1994 and 2013. The coffee plants' LAI-an indicator of vegetative vigour-varied seasonally from 2.4 to 4.4 m leaf 2 m soil −2 between 2001 and 2011 (Taugourdeau et al. 2014). ...
In coffee, fruit production on a given shoot drops after some years of high yield, triggering pruning to induce re-sprouting. The timing of pruning is a crucial farmer’s decision affecting yield and labour. A reason explaining fruit production drop could be the exhaustion of resources, particularly the non-structural carbohydrates (NSC).
To test such hypothesis in a Coffea arabica agroforestry system, we measured the concentrations of NSC, carbon (C) and nitrogen (N) in leaves, stems, and stumps of the coffee plants, 2 and 5 years after pruning. We also compared shaded vs. full sun plants. For that purpose, both analytical reference and visible and near infrared reflectance spectroscopy (VNIRS) methods were used.
As expected, concentrations of biochemical variables linked to photosynthesis activity (N, glucose, fructose, sucrose) decreased from leaves to stems, and then to stumps. In contrast, variables linked more closely to plant structure and reserves (total C, C:N ratio, starch concentration) were higher in long-lifespan organs like stumps. Shading had little effect on most measured parameters, contrary to expectations. Concentrations of N, glucose, and fructose were higher in 2-year-old organs. Conversely, starch concentration in perennial stumps was three times higher 5 years after pruning than 2 years after pruning, despite high fruit production. Therefore, the drop in fruit production occurring after 5–6 years was not due to a lack of NSC on plant scale. Starch accumulation in perennial organs concurrently to other sinks, such as fruit growth, could be considered as a ‘survival’ strategy, which may be a relic of the behavior of wild coffee (tropical shade-tolerant plant).
This study confirmed that VNIRS is a promisingly rapid and cost-effective option for starch monitoring (coefficient of determination for validation, R2val = 0.91), whereas predictions were less accurate for soluble sugars, probably due to their too similar spectral signature.
... 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. ...
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). ...
... 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). ...
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). ...
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). ...
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). ...
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.
... 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. ...
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). ...
... 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). ...
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). ...
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 Andean blueberry is a high-Andean wild fruit species consumed in fresh or processed form that has high potential due to its antioxidant capacity. Leaf area describes the photosynthetic capacity of plants and is employed as a variable in multiple physiological studies; however, in Andean blueberry (Vaccinium meridionale Swartz), its direct measurement is costly. The aim of this research was to propose models for estimating the leaf area in young Andean blueberry plants using morphometric variables. In the study, 436 Andean blueberry plants of different ages (10 to 26 months) obtained with different methods of asexual propagation (tissue culture or cuttings) were used. Variables, such as dry weight per organ, leaf area, plant height, number of vegetative shoots and number of leaves, were measured. Simple and multiple regressions were performed and the “weighted least squares” technique was used to meet the regression assumptions. Five models with coefficients of determination (R2) greater than 0.81 were proposed. Two models were of the multiple type and employed the number of leaves together with the dry weight of leaves or the total dry weight as predictor variables. The other models were linear and used total dry weight, dry weight of leaves or number of leaves as explanatory variables of leaf area; the number of leaves was a particularly interesting variable due to its non-destructive nature. The models presented could be a useful tool for estimating leaf area in future studies in Andean blueberry. Key words: average leaf area, regression analysis, weighted least squares, Andean species, Ericaceae
Evaporation (E) and transpiration (Tr) are the key terrestrial water fluxes to the atmosphere and are highly sensitive to land cover change. These ecohydrological fluxes can be measured directly only at small scales, such as individual plants or under laboratory experiments. Modelling is needed to upscale E and Tr estimates to plot, hillslope and catchment scales. However, model-derived ecohydrological water partitioning of E and Tr can be ambiguous, particularly when models are trained using hydrometric data and soil moisture. To test the influence of different types of data (i.e., sap flux-derived Tr, Eddy Covariance-derived actual evapotranspiration (AET) and measured soil water content (SWC)) on model calibration and subsequent water partitioning, we developed the low-parameter plot scale ecohydrology model EcoHydroPlot applied to a data-rich experimental agroforestry plot in humid tropical Costa Rica. The model was able to simulate SWC well when calibrated with any data type, but large differences emerged in the E and Tr flux partitioning. Using only hydrometric data for calibration resulted in parameter configurations that produced greater E over Tr fluxes (Tr/AET < 0.5). The opposite was seen for model calibration using Tr data, resulting in Tr/AET ratios close to the observed ~0.9. Further, using all measurements simultaneously (including AET, SWC and Tr) did not improve simulated water partitioning. We only found minimal differences between sun and shade locations with slightly greater average shaded coffee transpiration at the expense of lower upper SWC, higher deeper SWC and less groundwater recharge compared to sun exposed coffee. This work can inform measurement priorities for applications with relatively simple conceptual ecohydrology models and emphasizes the importance of transpiration estimates beyond tropical environments.
Sejak kebakaran hutan dan lahan gambut Tahun 2015, Pemerintah Republik Indonesia membentuk Badan Restorasi Gambut dengan program utama melakukan restorasi gambut dengan berdasarkan pada Pembasahan kembali (P1), Penanaman pohon (P2) dan Pemberdayaan ekonomi masyarakat (P3) di kawasan lahan gambut. Pada aspek penanaman pohon (P1) akan menjadi menarik minat masyarakat bila dapat dilakukan dengan kombinasi dengan tanaman yang bernilai ekonomi sekaligus juga secara ekologi memungkinkan. Hal ini sejalan dengan perubahan paradigma pengelolaan hutan yang juga sekaligus mensejahterakan masyarakat. Secara umum masyarakat dapat melakukan kegiatan usahatani apabila mereka bisa memperoleh penghasilan yang sifatnya harian (diantaranya berupa tanaman semusim) dan juga jangka panjang berupa tanaman tahunan. Secara ekologis, kombinasi pohon dan tanaman pertanian memungkinkan apabila pada awal pertumbuhannya, tutupan tajuk pohon masih memungkinkan masuknya sinar matahari dan tanaman semusim yang dipilih membutuh naungan dalam jumlah tertentu. Tujuan pengimplementasian agroforestri di daerah ini tidak lepas dari pengelolaan yang lebih mudah dibandingkan dengan bentuk usahatani pertanian umumnya seperti padi sawah atau pertanian monokultur lainnya. Agroforestri juga dinilai dapat memberikan banyak alternatif pendapatan dan produk yang lebih banyak bagi masyarakat di Desa Gohong. Kegiatan kegiatan yang didanai oleh BRG dilakukan pada lahan masyarakat yang memiliki pertanaman dengan pola agroforestri baik tanaman karet, sengon maupun pohon lainnya. Kajian berupa karakterisasi sifat lahan gambut dan aspek biofisik lainnya terkait dengan pertumbuhan tanaman seperti pencahayaan, kelembaban, pertumbuhan tanaman serta pendapatan petani saat ini, selain itu juga dilakukan pengamatan terhadap pola agroforestri yang telah dikembangkan tersebut dan upaya perbaikan yang harus dilakukan.
Leaf area index (LAI) is an essential indicator of crop development and growth. For many agricultural applications, satellite-based LAI estimates at the farm-level often require near-daily imagery at medium to high spatial resolution. The combination of data from different ongoing satellite missions, Sentinel 2 (ESA) and Landsat 8 (NASA), provides this opportunity. In this study, we evaluated the leaf area index generated from three methods, namely, existing vegetation index (VI) relationships applied to Harmonized Landsat-8 and Sentinel-2 (HLS) surface reflectance produced by NASA, the SNAP biophysical model, and the THEIA L2A surface reflectance products from Sentinel-2. The intercomparison was conducted over the agricultural scheme in Bekaa (Lebanon) using a large set of in-field LAIs and other biophysical measurements collected in a wide variety of canopy structures during the 2018 and 2019 growing seasons. The major studied crops include herbs (e.g., cannabis: Cannabis sativa, mint: Mentha, and others), potato (Solanum tuberosum), and vegetables (e.g., bean: Phaseolus vulgaris, cabbage: Brassica oleracea, carrot: Daucus carota subsp. sativus, and others). Additionally, crop-specific height and above-ground biomass relationships with LAIs were investigated. Results show that of the empirical VI relationships tested, the EVI2-based HLS models statistically performed the best, specifically, the LAI models originally developed for wheat (RMSE:1.27), maize (RMSE:1.34), and row crops (RMSE:1.38). LAI derived through European Space Agency's (ESA) Sentinel Application Platform (SNAP) biophysical processor underestimated LAI and provided less accurate estimates (RMSE of 1.72). Additionally, the S2 SeLI LAI algorithm (from SNAP biophysical processor) produced an acceptable accuracy level compared to HLS-EVI2 models (RMSE of 1.38) but with significant underestimation at high LAI values. Our findings show that the LAI-VI relationship, in general, is crop-specific with both linear and non-linear regression forms. Among the examined indices, EVI2 outperformed other vegetation indices when all crops were combined, and therefore it can be identified as an index that is best suited for a unified algorithm for crops in semi-arid irrigated regions with heterogeneous landscapes. Furthermore, our analysis shows that the observed height-LAI relationship is crop-specific and essentially linear with an R 2 value of 0.82 for potato, 0.79 for wheat, and 0.50 for both cannabis and tobacco. The ability of the linear regression to estimate the fresh and dry above-ground biomass of potato from both observed height and LAI was reasonable, yielding R 2 :~0.60.
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
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.
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.
The unprecedented high rate of" destruction of natural forests and other natural ecosystem has led scentists to focus on biodiversity conservation in managed landscapes and agroecosystems. Agroforestry Systems renowned for their high tree specis richness and complex vegetation structure, stand out as promising biodiversity conservation tool.
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.
Solar radiation is an important factor for plant growth, being its availability to understory crops strongly modified by trees in an Agroforestry System (AFS). Coffee trees (Coffea arabica - cv. Obatã IAC 1669-20) were planted at a 3.4 x 0.9 m spacing inside and aside rows of monocrops of 12 year-old rubber trees (Hevea spp.), in Piracicaba-SP, Brazil (22° 42'30'' S, 47°38'00'' W - altitude: 546m). One-year-old coffee plants exposed to 25; 30; 35; 40; 45; 80; 90; 95 and 100% of the total solar radiation were evaluated according to its biophysical parameters of solar radiation interception and capture. The Goudriaan (1977) adapted by Bernardes et al. (1998) model for radiation attenuation fit well to the measured data. Coffee plants tolerate a decrease in solar radiation availability to 50% without undergoing a reduction on growth and LAI, which was approximately 2m2.m-2 under this condition. Further reductions on the availability of solar radiation caused a reduction in LAI (1.5m2.m-2), thus poor land cover and solar radiation interception, resulting in growth reduction.
Conduziu-se este trabalho com o objetivo de avaliar progênies de cafeeiro resultantes do cruzamento entre 'Icatu' x 'Catimor', quanto à produtividade e vigor vegetativo e selecionar progênies superiores para avançar no programa de melhoramento dessa população. O delineamento utilizado foi em blocos casualizados com quatro repetições, 30 tratamentos (29 progênies do cruzamento mais a cultivar Rubi MG 1192, utilizada como testemunha). Para análise de variância dos dados adotou-se o esquema de parcela subdividida no tempo. Foram analisados a produção em sacas beneficiadas.ha-1 de seis colheitas 2001/2002 a 2006/2007 e o vigor vegetativo avaliado após a colheita 2006/2007. Os resultados obtidos permitem verificar a presença da variabilidade genética para produção entre as progênies avaliadas, fato confirmado pela alta estimativa da maioria das progênies estudadas, demonstraram que é possível selecionar progênies superiores na população estudada.
Coffee is the second most valuable traded commodity worldwide. Brazil is the world's largest coffee producer, responsible for one third of the world production. A coffee plot exhibits high and low production in alternated years, a characteristic so called biennial yield. High yield is generally a result of suitable conditions of foliar biomass. Moreover, in high production years one plot tends to lose more leaves than it does in low production years. In both cases some correlation between coffee yield and leaf biomass can be deduced which can be monitored through time series of vegetation indices derived from satellite imagery. In Brazil, a comprehensive, spatially distributed study assessing this relationship has not yet been done. The objective of this study was to assess possible correlations between coffee yield and MODIS derived vegetation indices in the Brazilian largest coffee-exporting province. We assessed EVI and NDVI MODIS products over the period between 2002 and 2009 in the south of Minas Gerais State whose production accounts for about one third of the Brazilian coffee production. Landsat images were used to obtain a reference map of coffee areas and to identify MODIS 250 m pure pixels overlapping homogeneous coffee crops. Only MODIS pixels with 100% coffee were included in the analysis. A wavelet-based filter was used to smooth EVI and NDVI time profiles. Correlations were observed between variations on yield of coffee plots and variations on vegetation indices for pixels overlapping the same coffee plots. The vegetation index metrics best correlated to yield were the amplitude and the minimum values over the growing season. The best correlations were obtained between variation on OPEN ACCESS Remote Sens. 2012, 4 2493 yield and variation on vegetation indices the previous year (R = 0.74 for minEVI metric and R = 0.68 for minNDVI metric). Although correlations were not enough to estimate coffee yield exclusively from vegetation indices, trends properly reflect the biennial bearing effect on coffee yield.
This paper is the first of three on the coffee production system consisting of (1) the coffee plant, (2) coffee berry borer (CBB) and (3) the role of CBB parasitoids. A previous simulation model of the coffee plant was developed using data from Brazil where coffee phenology is characterized by distinct seasonal flowering (Gutierrez et al., 1998). In contrast, flowering in Colombia is continuous with low seasonality. To capture the differences in coffee phenology and growth in the two climatic regions, the Gutierrez et al. (1998) model was modified using new data from Colombia.The modifications to the model include:(1)The effect of solar radiation on floral buds initiation;(2)An age structure population model to track the daily input and development of the floral buds;(3)The effect of leaf water potential on breaking dormancy in flower buds, and hence on the timing and intensity of flowering;(4)The incorporation of both the vegetative and the reproductive demands to predict the photosynthetic rate.(5)The effect of low temperature on photosynthesis and defoliation.Other aspects of the model were re-interpreted and refinements made to generalize its structure for use across coffee varieties and geographic areas. The model, without modification, realistically simulates field data from Brazil and two Colombian locations having different varieties, patterns of rainfall and hence flowering phenology.The model will be used as the base trophic level for incorporating CBB and high tropic levels effects, and for the analysis of management options in the coffee production system.
O cafeeiro, depois do petróleo, é a principal mercadoria comercializada no mundo. Nesta revisão, analisam-se aspectos do crescimento e desenvolvimento do cafeeiro, dando-se, também, ênfase aos avanços recentes sobre a (eco)fisiologia da produção de Coffea arabica e C. canephora, que respondem por cerca de 99% da produção mundial de café. Abordam-se (i) os fatores climáticos e requerimentos ambientes, (ii) crescimento da parte aérea e das raízes, (iii) sincronização da floração, frutificação e qualidade da bebida, (iv) competição entre os crescimentos vegetativo e reprodutivo e ocorrência de seca de ramos; (v) fotossíntese e produção, (vi) componentes fisiológicos da produção, (vii) sombreamento e sistemas agroflorestais, e (viii) plantios adensados.
The Best Index Slope Extraction (BISE) is proposed as an alternative to the Maximum Value Composite (MVC) as a way of reducing noise in Normalized Difference Vegetation Index (NDVI) time-series from Advanced Very High Resolution Radiometer (AVHRR) data. The BISE method retains more valuable elements of an NDVI profile than the MVC. NDVI profiles prepared using the BISE method show strong differences in the development characteristics of various West African vegetation types.
Coffee is an extremely important cash crop, yet previous work indicates that satellite mapping of coffee has produced low classification accuracy. This research examines spectral band combinations and ancillary data for evaluating the classification accuracy and the nature of spectral confusion between coffee and other cover types in a Costa Rican study area. Supervised classification using Landsat Enhanced Thematic Mapper (ETM+) with only red, near‐infrared, and mid‐infrared bands had significantly lower classification accuracy compared to datasets that included more spectral bands and ancillary data. The highest overall accuracy achieved was 65%, including a coffee environmental stratification model (CESM). Producer's and user's accuracy was highest for shade coffee plantations (91.8 and 61.1%) and sun coffee (86.2 and 68.4%) with band combination ETM+ 34567, NDVI, cos (i), and including the use of the CESM. Post‐classification stratification of the optimal coffee growing zone based on elevation and precipitation data did not show significant improvement in land cover classification accuracy when band combinations included both the thermal band and NDVI. A forward stepwise discriminant analysis indicated that ETM+ 5 (mid‐infrared band) had the highest discriminatory power. The best discriminatory subset for all woody cover types including coffee excluded ETM+ 3 and 7; however, the land cover accuracy assessment indicated that overall accuracy, as well as producer's and user's accuracy of shade and sun coffee, were slightly improved with the inclusion of these bands. Although spectral separation between coffee crops and woodland areas was only moderately successful in the Costa Rica study, the overall accuracy, as well as the sun and shade coffee producer's and user's accuracy, were higher than reported in previous research.
Significant interest in the concept of sustainable development exists amongst scientists, planners, policy makers and the public, and considerable effort and expenditure is made or envisaged at local, national and international levels to promote a more sustainable society. Until ‘green accounting’ and similar systems are made available and are implemented, the sustainability indicator will be the most effective tool available for monitoring progress towards a more sustainable society. Sustainability indicators are already available but are characterized by a poor or absent theoretical underpinning. This paper addresses this problem by proposing a methodological framework that can be applied to the construction of indicators of sustainable development. In order to be consistent with widely accepted definitions of sustainable development, considerations relating to the measurement of quality of life and ecological integrity are central to the methodology. The methodological framework has relevance to a variety of spatial scales and to geographically diverse areas (urban or rural, developed or developing countries) so that a suite of sustainability indicators can be produced that is tailored to the needs and resources of the indicator user, but which remains rooted firmly in the fundamental principles of sustainable development.
The role of water in the development and yield of the coffee crop (Coffea
arabica L.) is reviewed. A period of water stress, induced either by dry soil or dry air, is needed to prepare flower buds for blossoming that is then stimulated by rain or irrigation. Although attempts have been made to quantify the intensity and duration of stress required, these have not yet been specified in ways that are commercially useful. Water must be freely available during the period of rapid fruit expansion to ensure large, high-quality seed yields. Depending on the time and uniformity of flowering this can occur at times when rainfall is unreliable, particularly in equatorial areas.
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.
The performance of F1 hybrid plants derived from crosses between traditional varieties of Coffea arabica of Latin America with a wild collection of Sudan–Ethiopian origin were studied for yield, fertility and bean weight. Sudan–Ethiopian material possesses resistance to certain diseases, and possibly, better beverage quality. The objective of this breeding programme is to widen the very narrow genetic base of Central American coffee, even while increasing quality and productivity. The hybrid plants were obtained from two factorial crosses made and evaluated in two locations. They were compared in the two field trials using the six maternal lines as controls. Observations were taken on vegetative characters, annual and cumulated yield, dry weight of 100 beans, extent of early abortion as measured by the fraction of peaberries and post-zygotic ovule fertility as measured by the fraction of mature no-floating berries in water (FF). The F1 hybrid population were compared to the populations of maternal lines for the aforementioned variables. An index-based selection was done in the hybrid populations employing three traits, yield, 100-bean weight and the post-zygotic fertility (FF). The performance of the selected hybrids was then compared to those of the best parental control lines in each trial. The hybrid populations yielded 22–47% more than the maternal lines, but hybrids showed significantly more sterility than the parental control lines. Selection in the hybrid populations using the three selected traits led to significant genetic gain for yield and dry weight of 100 beans, and insignificant gain for fertility (FF). When selected on the basis of fertility alone, increase in yield and 100-bean weight were not obtained within the hybrid populations. By applying selection on yield and 100-bean weight, the selected hybrids produced 11–47% higher yields than the best line along with significantly higher or identical 100-bean weight and performed identically for fertility. The yield performance of hybrids between the Latin American material and the wild Sudan–Ethiopian material calls for further selection effort for improving beverage quality.
The profitability of hydropower is affected by soil erosion and sedimentation in dam reservoirs, which are influenced by land use, infiltration and aquifer interactions with surface water. In order to promote the payment of Hydrological Environmental Services (HES) in Costa Rica, a quantitative assessment of the impact of land uses (such as coffee farming) on the functioning of drainage basins is required. This thesis seeks: 1) to study the water balance partitioning in a newly installed coffee agroforestry basin 2) to estimate the water and sediment yield at various spatio-temporal scales: from plot to basin and from event to annual scale; and 3) to simulate the water and sediment yields, at both annual and peakflow scale, by including the surface runoff from hillslopes and roads. The main hydrological, ecophysiological and sediment processes were monitored during one year at the basin (rainfall, streamflow, evapotranspiration, soil humidity, aquifer level, turbidity) and at the plots (surface runoff and erosion). A new eco-hydrological model was developed to close the water balance, and the annual sediment yield was also quantified. Improvements are in progress to take into account the effect of roads in surface runoff generation. The low surface runoff, low plot erosion and low basin sediment yield observed under the current biophysical conditions (andisol) and management practices (no tillage, planted trees, bare soil kept by weeding), offer potential HES by reducing the superficial displacement capacity for fertilizers and pesticides, yielding low sediment loads and regulating streamflow variability through highly efficient mechanisms of aquifer recharge-discharge.
