Search Results (33)

The application of dolomitic limestone is a recommended practice for improving pastures established on acidic soils. On the other hand, pasture availability should determine the adjustment of the biotic load. The aim of this study is to evaluate the potential of pasture plant community composition as an indicator to assess the effects of intensification strategies in the Montado ecosystem, specifically soil pH correction and/or increasing animal stocking rate. Forty-eight sampling areas of a biodiverse pasture were monitored on a 4-ha plot located at the Mitra farm (Évora district; southern Portugal). The experimental design included four treatments: with and without limestone application (respectively, DL and WDL) × traditional low stocking rate (LSR, 7 sheep ha⁻¹) and high stocking rate (HSR, 18 sheep ha⁻¹). Floristic composition, structural parameters, and diversity metrics were recorded and analyzed using multivariate statistical tools. Pasture diversity was assessed through the computation of richness indices, with plant species identified as ecological indicators representative of each study area. The results showed Rumex pulcher, Trifolium subterraneum, Plantago lanceolata, and Lolium rigidum as botanical indicators of the four treatments of this study, respectively, LSR in untreated soil, HSR in untreated soil, HSR in treated soil, and LSR in treated soil. The results also show that soil amendment led to a more distinct and stable pasture floristic composition (PFC) compared to untreated areas. Conversely, the stocking rate (SR) played a secondary but still ecologically relevant role. Notably, HSR appears to reduce the need for lime application to achieve a balanced floristic composition and desirable plant community structure, potentially lowering soil amendment costs without compromising pasture quality. In LSR areas, the application of lime was essential to significantly improve the floristic richness, the vegetation cover, and the presence of legumes. Full article

The objective of this study was to determine how application of dolomitic limestone and stocking methods (continuous stocking or deferred stocking) affect the soil compaction, sheep grazing location, height, and nutritional value of pastures when the pasture growth rate is at its maximum. A 4 ha field at Mitra farm—University of Évora—was divided into four plots: P1 and P2—without application of dolomitic limestone, continuous stocking (CS), and deferred stocking (DS), respectively—and P3 and P4—with application of dolomitic limestone, DS (2.3 AUE), and CS (1 AUE), respectively. In DS, animals were placed and removed from the plots depending on the height of the pasture (entry ≥ 10 cm; removal ≤ 5 cm). Throughout the pasture’s vegetative cycle, several measurements of pasture height and cut were carried out. From the beginning of March to the beginning of June, animal behavior was observed (animals’ activity grazing and location) by trained observers through binoculars on six dates. The results show the following: (i) the application of dolomitic limestone combined with CS provided higher values of pasture height; (ii) there were no significant differences in pasture quality between treatments; (iii) DS led to 50% more sheep grazing days that CS; (iv) there were no significant differences in soil compaction between CS and DS; and (v) the stocking methods and the application of dolomitic limestone did not seem to change the grazing pattern between treatments. This study constitutes a basis to support more informed decisions by agricultural managers and may also contribute to maintaining balance in the Montado ecosystem, as well as increasing the efficiency of livestock production systems based on rainfed pastures. Full article

This study evaluates two expedient electronic sensors, a rising plate meter (RPM) and a “Grassmaster II” capacitance probe (GMII), to estimate pasture dry matter (DM, in kg ha⁻¹). The sampling process consisted of sensor measurements, followed by pasture collection and a laboratory reference analysis. In this comparative study, carried out throughout the 2023/2024 pasture growing season, a total of 288 pasture samples were collected in two phases (calibration and validation). The calibration phase (n = 144) consisted of measurements on three dates (6 December 2023, 29 February and 10 May 2024) in 48 georeferenced sampling areas of the experimental field “Eco-SPAA” (“M_G” field), located at Mitra farm (Évora, Portugal). This pasture is a permanent mixture of various botanical species (grasses, legumes, and others) grazed by sheep, and is representative of biodiverse dryland pastures. The validation phase (n = 144) was carried out between December 2023 and April 2024 in 18 field tests (each with eight pasture samples), in three types of representative pastures: the same mixture for grazing (“M_G” field), a commercial and annual mixture for cutting (mowing) and conservation (“M_M” field), and legumes for grazing (“L_G” field). The best estimation model for DM was obtained based on measurements carried out in February in the case of the GMII probe (R² = 0.61) and December 2023 and February 2024 in the case of RPM (R² = 0.76). The estimation decreased very significantly for both sensors based on measurements carried out in May (spring). The validation phase showed greater accuracy (less RMSE) in “M_G” field tests (RMSE of 735.4 kg ha⁻¹ with GMII and 512.3 kg ha⁻¹ with the RPM). The results open perspectives for other works that would allow the testing, calibration, and validation of these electronic sensors in a wider range of pasture production conditions, in order to improve their accuracy as decision-making support tools in pasture management. Full article

Extensive livestock farming plays a crucial role in the economy of agrosilvopastoral systems of the southwestern Iberian Peninsula (known as dehesas and montados in Spanish and Portuguese, respectively) as well as providing essential ecosystem services. The existence of livestock in these areas heavily relies on the effective management of natural resources (annual pastures and water stored in ponds built ad hoc). The present work aims to assess the water availability in these ponds by developing equations to estimate the water volume based on the surface area, which can be quantified by means of remote sensing techniques. For this purpose, field surveys were carried out in September 2021, 2022 and 2023 at ponds located in representative farms, using unmanned aerial vehicles (UAVs) equipped with RGB sensors and survey-grade global navigation satellite systems and inertial measurement units (GNSS-IMU). These datasets were used to produce high-resolution 3D models by means of Structure-from-Motion and Multi-View Stereo photogrammetry, facilitating the estimation of the stored water volume within a Geographic Information System (GIS). The Volume–Area–Height relationships were calibrated to allow conversions between these parameters. Regression analyses were performed using the maximum volume and area data to derive mathematical models (power and quadratic functions) that resulted in significant statistical relationships (r² > 0.90, p < 0.0001). The root mean square error (RMSE) varied from 1.59 to 17.06 m³ and 0.16 to 3.93 m³ for the power and quadratic function, respectively. Both obtained equations (i.e., power and quadratic general functions) were applied to the estimated water storage in similar water bodies using available aerial or satellite imagery for the period from 1984 to 2021. Full article

The Montado ecosystem is an important agri-forestry system in Portugal, occupying about 8% of the total area of the country. However, this biodiverse ecosystem is threatened due to factors such as shrub encroachment. In this context, the development of tools for characterizing and monitoring Montado areas is crucial for their conservation. In this study, we developed a deep convolutional neural network algorithm based on the U-net architecture to identify regions with trees, shrubs, grass, bare soil, or other areas in Montado areas using high-resolution RGB and near-infrared orthophotos (with a spatial resolution of 25 cm) from seven experimental sites in the Alentejo region of Portugal (six used for training/validation and one for testing). To optimize the model’s performance, we performed hyperparameter tuning, which included adjusting the number of filters, dropout rate, and batch size. The best model achieved an overall classification performance of 0.88 and a mean intersection of the union of 0.81 on the test set, indicating high accuracy and reliability of the model in identifying and delineating land cover classes in the Montado ecosystem. The developed model is a powerful tool for identifying the status of the Montado ecosystem regarding shrub encroachment and facilitating better future management. Full article

The cork oak tree (Quercus suber L.) symbolizes the Montado landscape in Portugal and is a central element in the country’s social and economic history. In recent decades, the loss of thousands of cork oaks has been reported, revealing the ongoing decline of these agroforestry ecosystems. This emblematic tree of the Mediterranean Basin is host to the soil-born root pathogen Phytophthora cinnamomi, an active cork oak decline driver. In this framework, the early diagnosis of trees infected by the oomycete by non-invasive methods should contribute to the sustainable management of cork oak ecosystems, which motivated this work. Gas exchange and visible/near-infrared (400–1100 nm) reflectance spectroscopy measurements were conducted on leaves of both control and P. cinnamomi inoculated plants. These measurements were taken at 63, 78, 91, 126, and 248 days after inoculation. Additionally, at the end of the experiment, biochemical assays of pigments, sugars, and starch were performed. The spectroscopic measurements proved effective in distinguishing between control and inoculated plants, while the standard gas exchange and biochemistry data did not exhibit clear differences between the groups. The spectral data were examined both daily and globally, utilizing the PARAFAC method applied to a three-way array of samples × wavelengths × days. The separation of the two plant groups was attributed to variations in water content (4v (O−H)); shifts in the spectra red edge; and structural modifications in the epidermal layer and leaves’ mesophyll. These spectral signatures can assist in the field identification of cork oaks that are interacting with P. cinnamomi. Full article

Montado is an agro-silvo-pastoral ecosystem characteristic of the south of Portugal and called Dehesa in Spain. Its four fundamental components—soil, pasture, trees, and animals—as well as the climate make Montado a highly complex ecosystem. This review article provides an overview of the state of the art of Montado from the point of view of the agro-silvo-pastoral ecosystem and the scientific work carried out in this context. Thus, the aim is: (i) to describe and characterize the Montado ecosystem, as an agro-silvo-pastoral system; (ii) to reveal experimental tests carried out, technologies used or with the potential to be used in the monitoring of Montado; (iii) to address other technologies, carried out in similar and different agro-silvo-pastoral ecosystems from south Portugal. This review consists of three chapters: (a) components of Montado and their interactions; (b) advanced technologies for monitoring Montado; (c) grazing systems. No review article is known to provide an overview of Montado. Thus, it is essential to carry out research on grazing and its effects on the soil and pasture in the Montado ecosystem. Full article

Deferred grazing (DG) consists in adapting the number of animals and the number of days grazed to the availability of pasture. Compared to continuous grazing (CG), which is based on a permanent and low stocking rate, DG is a management strategy that aims at optimizing the use of the resources available in the Mediterranean Montado ecosystem. This study with sheep grazing, carried out between 2019 and 2021 on a 4 ha pasture in Alentejo region of the Southern of Portugal, assesses the impact of these two grazing management systems on soil compaction as a result of animal trampling. This area of native natural grassland (a dryland pasture, mixture of grasses, legumes, and composite species) was divided into four grazing parks of 1 ha each, two under DG management and two under CG management. At the end of the study, the cone index (CI, in kPa) was measured in the topsoil layer (0–30 cm) with an electronic cone penetrometer at 48 georeferenced areas (12 in each park). The results of CI measurement showed no significant differences between treatments in all depths measured (0–10, 10–20, and 20–30 cm). These findings are encouraging from the point of view of soil conservation and sustainability, revealing good prospects for the intensification of extensive livestock production. Future work should evaluate the long-term impact and consider, at the same time, other ecosystem services and system productivity indicators. Full article

Permanent dryland pastures are the basis of animal feed in extensive grazing systems. Seasonality and inter-annual climatic variability, associated with shallow, acidic, and not very fertile soils, result in low productivity and rapid degradation of pasture quality, which requires the supplementation of animal feed. In this study, carried out in a biodiverse pasture field in the Mediterranean region of southern Portugal, the vegetation index (NDVI, Normalized Difference Vegetation Index) obtained from measurements performed by a proximal optical sensor (PS) and satellite images (RS) was used to assess pasture quality parameters (pasture moisture content, PMC, crude protein, CP, and neutral detergent fiber, NDF). The monitoring was carried out throughout the 2021/2022 pasture growing season. Significant correlations were obtained between the NDVI obtained by PS and RS (R² of 0.84) and the reference values of pasture parameters obtained in laboratory protocols: PMC (R² of 0.88 and 0.78, respectively), CP (R² of 0.67 and 0.63, respectively), and NDF (R² of 0.50 and 0.46, respectively). This case study also demonstrated the spatial and temporal variability of vegetative vigour and, consequently, of pasture quality in the Montado, the characteristic Mediterranean ecosystem. These results show the pertinence of these technologies in supporting the decision-making process of the farm manager, namely, to estimate the supplementation needs of animals in critical phases, especially after the spring production peak and before the autumn production peak. Full article

The economic and environmental sustainability of extensive livestock production systems requires the optimisation of soil management, pasture production and animal grazing. Soil compaction is generally viewed as an indicator of soil degradation processes and a determinant factor in crop productivity. In the Montado silvopastoral ecosystem, characteristic of the Iberian Peninsula, animal trampling is mentioned as a variable to consider in soil compaction. This study aims: (i) to assess the spatial variation in the compaction profile of the 0–0.30 m deep soil layer over several years; (ii) to evaluate the effect of animal trampling on soil compaction; and (iii) to demonstrate the utility of combining various technological tools for sensing and mapping indicators of soil characteristics (Cone Index, CI; and apparent electrical conductivity, EC_a), of pastures’ vegetative vigour (Normalised Difference Vegetation Index, NDVI) and of cows’ grazing zones (Global Positioning Systems, GPS collars). The significant correlation between CI, soil moisture content (SMC) and EC_a and between EC_a and soil clay content shows the potential of using these expedient tools provided by the development of Precision Agriculture. The compaction resulting from animal trampling was significant outside the tree canopy (OTC) in the four evaluated dates and in the three soil layers considered (0–0.10 m; 0.10–0.20 m; 0.20–0.30 m). However, under the tree canopy (UTC), the effect of animal trampling was significant only in the 0–0.10 m soil layer and in three of the four dates, with a tendency for a greater CI at greater depths (0.10–0.30 m), in zones with a lower animal presence. These results suggest that this could be a dynamic process, with recovery cycles in the face of grazing management, seasonal fluctuations in soil moisture or spatial variation in specific soil characteristics (namely clay contents). The NDVI shows potential for monitoring the effect of livestock trampling during the peak spring production phase, with greater vigour in areas with less animal trampling. These results provide good perspectives for future studies that allow the calibration and validation of these tools to support the decision-making process of the agricultural manager. Full article

This work aims to measure and value the ecosystem services of grasslands and croplands covered by pasture-based beef farms in Alentejo. It combines pixel-level data from the Portuguese Mapping and Assessment of Ecosystem Services study and farm-level data from 40 farms. Five ecosystem services were considered: soil protection, carbon sequestration, support to extensive animal production, plant food production and fiber production. Two different approaches for service quantification were used: an “average class” method and a “buffer” approach. Double counting issues were avoided by applying a specific methodology developed for this study. The results obtained were similar for both approaches in the case of grasslands, with an average value between 146 and 176 €/ha/year. For croplands, the average service value oscillated between 40 and 166 €/ha/year. Soil protection was the most valuable service, with over 90% of the total value. Extrapolating these results for the entire region, the five ecosystem services were estimated to be worth between 173 M€ (class method) and 223 M€ (buffer approach). These results suggest that pasture-based beef farms in Alentejo help to provide a significant number of ecosystem services with positive environmental effects that are currently not remunerated by the market. Full article

The Montado is a complex agroforestry–pastoral ecosystem due to the interactions between soil–pasture–trees–animals and climate. The typical Montado soil has an acidic pH and manganese toxicity, which affect the pasture’s productivity and pasture floristic composition (PFC). The PFC, on the other hand, can also be influenced by the type and intensity of grazing, which can lead to significant decreases in the amount of biomass produced and the biodiversity of species in the pasture. The objective of this study was to evaluate the effect of grazing type, by sheep, and different stocking rates on the PFC throughout the vegetative pasture cycle in areas with and without dolomitic limestone application. Thus, four treatments (P1UC to P4TC) were constituted: P1UC—without limestone application (U) and continuous grazing (CG); P2UD—U and deferred grazing (DG); P3TD—with the application of limestone (T) and DG; P4TC—T and CG. In DG plots, the placement and removal of the animals were carried out as a function of the average height of the pasture (placement—10 cm; removal—3 to 5 cm). The PFC was characterized in winter, at the peak of spring and in late spring. The PFC data were subjected to a multilevel pattern analysis (ISA). The combination of rainfall and temperature influenced the pasture growth rates and consequently the height of the pasture at different times of the year. Therefore, with the different growth rates of the pasture throughout the year, the sheep remain for different periods of time in the deferred grazing treatments. In the four treatments, 103 plant species were identified. The most representative botanical families in the four treatments were Asteraceae, Fabaceae and Poaceae. ISA identified 14 bioindicator species: eight for the winter period, three for the late spring vegetative period and three for the TC treatment. Full article

Grasslands are of key importance for the provision of ecosystem services (ES). Suitable management is essential to guarantee their persistence and functionality. There is a growing interest in innovations such as new technologies aimed at facilitating and improving the management of grasslands while increasing their provision of ES. The uptake of innovations by farmers is a complex process, and relevant socio-economic or technological factors that are crucial to farmers are often overlooked. This information can be useful for increasing the adoption of these innovations through the design of public policies to facilitate them. This paper analyses the relevance of the main innovations that can be applied to the management of the grasslands of Dehesa farms for the farmers and the factors that might affect this relevance. Through questionaries, we gathered information on the relevance that farmers give to the selected innovations and analysed it by cumulative link models. The results show that innovations aimed at increasing the biomass production of grasslands and resilience such as the use of seed mixtures and the use of forage drought-resistant species are considered highly relevant by Dehesa farmers. However, high-tech innovations such as GPS collars were poorly rated which could denote low applicability to the context of Dehesas or the existence of barriers hindering the adoption but also a need for further development and better information on their potential. Characteristics of the farmer and farm such as age, education level, and stocking rate seem to be related to the relevance given to some of the innovations. These results provide insightful information for the implementation and research of relevant grassland-related innovations in the context of Mediterranean Dehesa/Montado systems, as well as for the design of policies supporting them. Full article

Extensive livestock production systems based on improved pastures under Montado of Holm oaks represent an approach in line with the challenges of sustainability and biodiversity. The increasing incorporation of technologies in the monitoring of this ecosystem allows for a better knowledge of the spatial and temporal variability and, consequently, a more economically profitable management. In this study, between July 2020 and June 2021, soil and pastures were monitored in a 20 ha Montado area located in Alentejo (Southern Portugal) and used for extensive grazing of cattle. The survey of soil apparent electrical conductivity (EC_a), the application of algorithms for definition of homogeneous management zones (HMZ), the use of indices obtained from satellite imagery time series to characterize the evolution of pasture quality and the soil and pasture sampling, including the identification of bio-indicator botanical species, were the basis of this exploratory study, allowing a holistic approach to this complex soil-pasture-trees and animals ecosystem. In the near future, this knowledge could represent an important milestone in providing decision-making support systems to farm managers in terms of smart sampling, differential application of fertilizers, amendments or seeds, choosing the best spacing and density of trees in this ecosystem, promoting dynamic grazing, or identifying the animal feed supplementation needs in the critical periods of the year. Full article

The intensification of the Montado mixed ecosystem (agro–silvo–pastoral) is a current endeavor in the context of promoting the sustainability of extensive livestock production in the Mediterranean region. Increased pasture productivity and extensive animal production involves the use of technologies to monitor spatial variability and to implement differentiated management of pasture grazing, fertilization or soil amendment. An intermediate step should lead to the identification and demarcation of areas with similar characteristics (soil and/or crop development), known as homogeneous management zones (HMZ) to implement site-specific management strategies. In this study, soil apparent electrical conductivity (EC_a) and altimetry surveys were carried out in six experimental pasture fields with a non-contact electromagnetic induction sensor (EM38) associated with a Global Navigation Satellite System (GNSS) receiver. These EC_a and topographic maps were used in geostatistical analyses for designing and establishing final classification maps with three HMZ (less, intermediate and more potential). The normalized difference vegetation index (NDVI), obtained from a proximal optical sensor, and soil and biomass sampling were used to validate these HMZ. From a practical perspective, these HMZ are the basis for preparation of fertilizer prescription maps and use of variable rate technology (VRT) in a Precision Agriculture project. Full article