Tree Island Response to Fire and Flooding in the Short-Hydroperiod Marl Prairie Grasslands of the Florida Everglades

Within the marl prairie grasslands of the Florida Everglades, USA, the combined effects of fire and flooding usually lead to very significant changes in tree island structure and composition. Depending on fire severity and post-fire hydroperiod, these effects vary spatially and temporally throughout the landscape, creating a patchy post-fire mosaic of tree islands with different successional states. Through the use of the Normalized Difference Vegetation Index (NDVI) and three predictor variables (marsh water table elevation at the time of fire, post-fire hydroperiod, and tree island size), along with logistic regression analysis, we examined the probability of tree island burning and recovering following the Mustang Corner Fire (May to June 2008) in Everglades National Park. Our data show that hydrologic conditions during and after fire, which are under varying degrees of management control, can lead to tree island contraction or loss. More specifically, the elevation of the marsh water table at the time of the fire appears to be the most important parameter determining the severity of fire in marl prairie tree islands. Furthermore, in the post-fire recovery phase, both tree island size and hydroperiod during the first year after the fire played important roles in determining the probability of tree island recovery, contraction, or loss.

Influência das condições ambientais no verdor da vegetação da caatinga frente às mudanças climáticas

The Caatinga biome, a semi-arid climate ecosystem found in northeast Brazil, presents low rainfall regime and strong seasonality. It has the most alarming climate change projections within the country, with air temperature rising and rainfall reduction with stronger trends than the global average predictions. Climate change can present detrimental results in this biome, reducing vegetation cover and changing its distribution, as well as altering all ecosystem functioning and finally influencing species diversity. In this context, the purpose of this study is to model the environmental conditions (rainfall and temperature) that influence the Caatinga biome productivity and to predict the consequences of environmental conditions in the vegetation dynamics under future climate change scenarios. Enhanced Vegetation Index (EVI) was used to estimate vegetation greenness (presence and density) in the area. Considering the strong spatial and temporal autocorrelation as well as the heterogeneity of the data, various GLS models were developed and compared to obtain the best model that would reflect rainfall and temperature influence on vegetation greenness. Applying new climate change scenarios in the model, environmental determinants modification, rainfall and temperature, negatively influenced vegetation greenness in the Caatinga biome. This model was used to create potential vegetation maps for current and future of Caatinga cover considering 20% decrease in precipitation and 1 °C increase in temperature until 2040, 35% decrease in precipitation and 2.5 °C increase in temperature in the period 2041-2070 and 50% decrease in precipitation and 4.5 °C increase in temperature in the period 2071-2100. The results suggest that the ecosystem functioning will be affected on the future scenario of climate change with a decrease of 5.9% of the vegetation greenness until 2040, 14.2% until 2070 and 24.3% by the end of the century. The Caatinga vegetation in lower altitude areas (most of the biome) will be more affected by climatic changes.

Assessing trends in land use change in the Borana rangeland Ethiopia as one cause of greenhouse gas emissions and carbon sequestration variations

Landnutzungsänderungen sind eine wesentliche Ursache von Treibhausgasemissionen. Die Umwandlung von Ökosystemen mit permanenter natürlicher Vegetation hin zu Ackerbau mit zeitweise vegetationslosem Boden (z.B. nach der Bodenbearbeitung vor der Aussaat) führt häufig zu gesteigerten Treibhausgasemissionen und verminderter Kohlenstoffbindung. Weltweit dehnt sich Ackerbau sowohl in kleinbäuerlichen als auch in agro-industriellen Systemen aus, häufig in benachbarte semiaride bis subhumide Rangeland Ökosysteme. Die vorliegende Arbeit untersucht Trends der Landnutzungsänderung im Borana Rangeland Südäthiopiens. Bevölkerungswachstum, Landprivatisierung und damit einhergehende Einzäunung, veränderte Landnutzungspolitik und zunehmende Klimavariabilität führen zu raschen Veränderungen der traditionell auf Tierhaltung basierten, pastoralen Systeme. Mittels einer Literaturanalyse von Fallstudien in ostafrikanischen Rangelands wurde im Rahmen dieser Studie ein schematisches Modell der Zusammenhänge von Landnutzung, Treibhausgasemissionen und Kohlenstofffixierung entwickelt. Anhand von Satellitendaten und Daten aus Haushaltsbefragungen wurden Art und Umfang von Landnutzungsänderungen und Vegetationsveränderungen an fünf Untersuchungsstandorten (Darito/Yabelo Distrikt, Soda, Samaro, Haralo, Did Mega/alle Dire Distrikt) zwischen 1985 und 2011 analysiert. In Darito dehnte sich die Ackerbaufläche um 12% aus, überwiegend auf Kosten von Buschland. An den übrigen Standorten blieb die Ackerbaufläche relativ konstant, jedoch nahm Graslandvegetation um zwischen 16 und 28% zu, während Buschland um zwischen 23 und 31% abnahm. Lediglich am Standort Haralo nahm auch „bare land“, vegetationslose Flächen, um 13% zu. Faktoren, die zur Ausdehnung des Ackerbaus führen, wurden am Standort Darito detaillierter untersucht. GPS Daten und anbaugeschichtlichen Daten von 108 Feldern auf 54 Betrieben wurden in einem Geographischen Informationssystem (GIS) mit thematischen Boden-, Niederschlags-, und Hangneigungskarten sowie einem Digitales Höhenmodell überlagert. Multiple lineare Regression ermittelte Hangneigung und geographische Höhe als signifikante Erklärungsvariablen für die Ausdehnung von Ackerbau in niedrigere Lagen. Bodenart, Entfernung zum saisonalen Flusslauf und Niederschlag waren hingegen nicht signifikant. Das niedrige Bestimmtheitsmaß (R²=0,154) weist darauf hin, dass es weitere, hier nicht erfasste Erklärungsvariablen für die Richtung der räumlichen Ausweitung von Ackerland gibt. Streudiagramme zu Ackergröße und Anbaujahren in Relation zu geographischer Höhe zeigen seit dem Jahr 2000 eine Ausdehnung des Ackerbaus in Lagen unter 1620 müNN und eine Zunahme der Schlaggröße (>3ha). Die Analyse der phänologischen Entwicklung von Feldfrüchten im Jahresverlauf in Kombination mit Niederschlagsdaten und normalized difference vegetation index (NDVI) Zeitreihendaten dienten dazu, Zeitpunkte besonders hoher (Begrünung vor der Ernte) oder niedriger (nach der Bodenbearbeitung) Pflanzenbiomasse auf Ackerland zu identifizieren, um Ackerland und seine Ausdehnung von anderen Vegetationsformen fernerkundlich unterscheiden zu können. Anhand der NDVI Spektralprofile konnte Ackerland gut Wald, jedoch weniger gut von Gras- und Buschland unterschieden werden. Die geringe Auflösung (250m) der Moderate Resolution Imaging Spectroradiometer (MODIS) NDVI Daten führte zu einem Mixed Pixel Effect, d.h. die Fläche eines Pixels beinhaltete häufig verschiedene Vegetationsformen in unterschiedlichen Anteilen, was deren Unterscheidung beeinträchtigte. Für die Entwicklung eines Echtzeit Monitoring Systems für die Ausdehnung des Ackerbaus wären höher auflösende NDVI Daten (z.B. Multispektralband, Hyperion EO-1 Sensor) notwendig, um kleinräumig eine bessere Differenzierung von Ackerland und natürlicher Rangeland-Vegetation zu erhalten. Die Entwicklung und der Einsatz solcher Methoden als Entscheidungshilfen für Land- und Ressourcennutzungsplanung könnte dazu beitragen, Produktions- und Entwicklungsziele der Borana Landnutzer mit nationalen Anstrengungen zur Eindämmung des Klimawandels durch Steigerung der Kohlenstofffixierung in Rangelands in Einklang zu bringen.

Spatial distribution of triatomines in domiciles of an urban area of the Brazilian Southeast Region

Reports of triatomine infestation in urban areas have increased. We analysed the spatial distribution of infestation by triatomines in the urban area of Diamantina, in the state of Minas Gerais, Brazil. Triatomines were obtained by community-based entomological surveillance. Spatial patterns of infestation were analysed by Ripley’s K function and Kernel density estimator. Normalised difference vegetation index (NDVI) and land cover derived from satellite imagery were compared between infested and uninfested areas. A total of 140 adults of four species were captured (100 Triatoma vitticeps, 25 Panstrongylus geniculatus, 8 Panstrongylus megistus, and 7 Triatoma arthurneivai specimens). In total, 87.9% were captured within domiciles. Infection by trypanosomes was observed in 19.6% of 107 examined insects. The spatial distributions of T. vitticeps, P. geniculatus, T. arthurneivai, and trypanosome-positive triatomines were clustered, occurring mainly in peripheral areas. NDVI values were statistically higher in areas infested by T. vitticeps and P. geniculatus. Buildings infested by these species were located closer to open fields, whereas infestations of P. megistus and T. arthurneivai were closer to bare soil. Human occupation and modification of natural areas may be involved in triatomine invasion, exposing the population to these vectors.

Alternate furrow irrigation of four fresh-market tomato cultivars under semi-arid condition of Ethiopia – Part II: Physiological response

Understanding the variation in physiological response to deficit irrigation together with better knowledge on physiological characteristics of different genotypes that contribute to drought adaptation mechanisms would be helpful in transferring different irrigation technologies to farmers. A field experiment was carried to investigate the physiological response of four tomato cultivars (Fetan, Chali, Cochoro and ARP Tomato d2) to moderate water deficit induced by alternate furrow irrigation (AFI) and deficit irrigation (DI) under semi-arid condition of Ethiopia during 2013 and 2014. The study also aimed at identifying physiological attributes to the fruit yield of tomato under different deficit irrigation techniques. A factorial combination of irrigation treatments and cultivar were arranged in a complete randomized design with three replicates. Results showed that stomatal conductance (g_s) was significantly reduced while photosynthetic performance measured as chlorophyll fluorescence (Fv’/Fm’), relative water content (RWC) and leaf ash content remained unaffected under deficit irrigations. Significant differences among cultivars were found for water use efficiency (WUE), g_s, chlorophyll content (Chl_SPAD), normal difference vegetation index (NDVI), leaf ash content and fruit growth rate. However, cultivar differences in WUE were more accounted for by the regulation of g_s, therefore, g_s could be useful for breeders for screening large numbers of genotypes with higher WUE under deficit irrigation condition. The study result also demonstrated that cultivar with traits that contribute to achieve higher yields under deficit irrigation strategies has the potential to increase WUE.

Seasonal dynamics and operational monitoring of hedgerow olive tree transpiration in response to applied water

We used 2012 sap flow measurements to assess the seasonal dynamics of daily plant transpiration (ETc) in a high-density olive orchard (Olea europaea L. cv. ‘Arbequina’) with a well-watered (HI) control treatment A to supply 100 % of the crop water needs, and a moderately (MI) watered treatment B that replaced 70% of crop needs. To assure that treatment A was well-watered, we compared field daily ETc values against ETc obtained with the Penman-Monteith (PM) combination equation incorporating the Orgaz et al. (2007) bulk daily canopy conductance (gc) model, validated for our non-limiting conditions. We then tested the hypothesis of indirectly monitoring olive ETc from readily available vegetation index (VI) and ground-based plant water stress indicator. In the process we used the FAO56 dual crop coefficient (Kc) approach. For the HI olive trees we defined Kcb as the basal transpiration coefficient, and we related Kcb to remotely sensed Soil Adjusted Vegetation Index (SAVI) through a Kcb-SAVI functional relationship. For the MI treatment, we defined the actual transpiration ETc as the product of Kcb and the stress reduction coefficient Ks obtained as the ratio of actual to crop ETc, and we correlated Ks with MI midday stem water potential (ψst) values through a Ks-ψ functional relationship. Operational monitoring of ETc was then implemented with the ETc = Kcb(SAVI)Ks(ψ)ETo relationship stemmed from the FAO56 approach and validated taking as inputs collected SAVI and ψst data reporting to year 2011. Low validation error (6%) and high goodness-of-fit of prediction were observed (R2 = 0.94, RSME = 0.2 mm day-1, P = 0.0015), allowing to consider that under field conditions it is possible to predict ETc values for our hedgerow olive orchards if SAVI and water potential (ψst) values are known.

Adaptive strategies of two Portuguese grapevines varieties (Aragonês. syn. Tempranillo and Trincadeira) face drought: physiological and structural responses.

At Mediterranean regions and particularly in southern Portugal, it is imperative to identify grape varieties more adapted to warm and dry climates in order to overcome future climatic changes. Two Vitis vinifera genotypes, Aragonez (syn. Tempranillo) and Trincadeira, were selected to assess their physiological responses to soil water stress. Vines were subjected to four irrigation regimes: irrigated during all phenological cycle, non-irrigated during all phenological cycle, non irrigated until veraison, irrigated after veraison. Predawn leaf water potential was much higher in Trincadeira than Aragonez in non- irrigated plants. This result is in accordance with its higher stomatal control efficiency in this variety (Trincadeira). Photosynthetic capacity (Amax at saturating light intensity) decreased due to stomatal and biochemical limitations under water stress. However, recovery capacity of leaf water status after irrigation was faster in Trincadeira. Yield and yield x Brix increased when irrigation occurred after veraison, particularly in Trincadeira. These results show that Trincadeira presents a drought adaptation than Aragonez. Ratio of variable to maximum fluorescence Fv/Fm and total leaf chlorophyll related with leaf water potential for both species. Reflectance Normalized Difference Vegetation Index (NDVI705), Red Edge Inflexion Point Index and Photochemical Reflectance Index were related with irrigation treatment. Relative water content and specific leaf area were similar between varieties. In conclusion, we suggested that there is variation among the genotypes and the main physiological parameters for variety selection, for drought, were leaf water potential, stomatal conductance and reflectance indexes.

Assessment of the spatial variability in Tall wheatgrass forage using LANDSAT 8 satellite imagery to delineate potential management zones

Little information is available on the degree of within-field variability of potential production of Tall wheatgrass (Thinopyrum ponticum) forage under unirrigated conditions. The aim of this study was to characterize the spatial variability of the accumulated biomass (AB) without nutritional limitations through vegetation indexes, and then use this information to determine potential management zones. A 27-×-27-m grid cell size was chosen and 84 biomass sampling areas (BSA), each 2 m(2) in size, were georeferenced. Nitrogen and phosphorus fertilizers were applied after an initial cut at 3 cm height. At 500 °C day, the AB from each sampling area, was collected and evaluated. The spatial variability of AB was estimated more accurately using the Normalized Difference Vegetation Index (NDVI), calculated from LANDSAT 8 images obtained on 24 November 2014 (NDVInov) and 10 December 2014 (NDVIdec) because the potential AB was highly associated with NDVInov and NDVIdec (r (2) = 0.85 and 0.83, respectively). These models between the potential AB data and NDVI were evaluated by root mean squared error (RMSE) and relative root mean squared error (RRMSE). This last coefficient was 12 and 15 % for NDVInov and NDVIdec, respectively. Potential AB and NDVI spatial correlation were quantified with semivariograms. The spatial dependence of AB was low. Six classes of NDVI were analyzed for comparison, and two management zones (MZ) were established with them. In order to evaluate if the NDVI method allows us to delimit MZ with different attainable yields, the AB estimated for these MZ were compared through an ANOVA test. The potential AB had significant differences among MZ. Based on these findings, it can be concluded that NDVI obtained from LANDSAT 8 images can be reliably used for creating MZ in soils under permanent pastures dominated by Tall wheatgrass.

Irrigation management with remote sensing: Evaluating irrigation requirement for maize under Mediterranean climate condition

tWater use control methods and water resources planning are of high priority. In irrigated agriculture, theright way to save water is to increase water use efficiency through better management. The present workvalidates procedures and methodologies using remote sensing to determine the water availability in thesoil at each moment, giving the opportunity for the application of the water depth strictly necessaryto optimise crop growth (optimum irrigation timing and irrigation amount). The analysis is applied tothe Irrigation District of Divor, Évora, using 7 experimental plots, which are areas irrigated by centre-pivot systems, cultivated to maize. Data were determined from images of the cultivated surface obtainedby satellite and integrated with atmosphere and crop parameters to calculate biophysical indicatorsand indices of water stress in the vegetation—Normalized Difference Vegetation Index (NDVI), Kc, andKcb. Therefore, evapotranspiration (ETc) was estimated and used to calculate crop water requirement,together with the opportunity and the amount of irrigation water to allocate. Although remote sensingdata available from satellite imagery presented some practical constraints, the study could contribute tothe validation of a new methodology that can be used for irrigation management of a large irrigated area,easier and at lower costs than the traditional FAO recommended crop coefficients method. The remotesensing based methodology can also contribute to significant saves of irrigation water.

Monitoring pasture variability: optical OptRx® crop sensor versus Grassmaster II capacitance probe

Estimation of pasture productivity is an important step for the farmer in terms of planning animal stocking, organizing animal lots, and determining supplementary feeding needs throughout the year. The main objective of this work was to evaluate technologies which have potential for monitoring aspects related to spatial and temporal variability of pasture green and dry matter yield (respectively, GM and DM, in kg/ha) and support to decision making for the farmer. Two types of sensors were evaluated: an active optical sensor(OptRx®, which measures the NDVI, Normalized Difference Vegetation Index) and a capacitance probe (GrassMaster II which estimates plant mass). The results showed the potential of NDVI for monitoring the evolution of spatial and temporal patterns of vegetative growth of biodiverse pasture. Higher NDVI values were registered as pasture approached its greatest vegetative vigor, with a significant fall in the measured NDVI at the end of Spring, when the pasture began to dry due to the combination of higher temperatures and lower soil moisture content. This index was also effective for identifying different plant species (grasses/legumes) and variability in pasture yield. Furthermore, it was possible to develop calibration equations between the capacitance and the NDVI (R2 = 0.757; p < 0.01), between capacitance and GM (R2 = 0.799; p<0.01), between capacitance and DM (R2 = 0.630; p<0.01), between NDVI and GM (R2=0.745; p < 0.01), and between capacitance and DM (R2=0.524; p<0.01). Finally, a direct relationship was obtained between NDVI and pasture moisture content (PMC, in %) and between capacitance and PMC (respectively, R2 = 0.615; p<0.01 and R2=0.561; p <0.01) in Alentejo dryland farming systems.

Avaliação do sensor óptico de vegetação OptRx® na monitorização da variabilidade espacial e temporal de pastagens

estimativa da produtividade das pastagens constitui uma etapa fundamental para o gestor agrícola em termos de planeamento do encabeçamento animal, organização dos lotes de animais e avaliação das necessidades de suplementação alimentar ao longo do ano. O objectivo principal deste trabalho consistiu na avaliação de um sensor óptico activo (“OptRx”, que mede o índice NDVI, “Normalised Difference Vegetation Index”) para monitorizar de forma expedita aspectos relacionados com a variabilidade da pastagem e apoiar a tomada de decisão do gestor agrícola. Os resultados obtidos demonstraram o potencial que apresenta o índice NDVI para monitorizar a evolução do padrão espacial e temporal do estado vegetativo de uma pastagem biodiversa. Índices mais elevados foram registados à medida que a pastagem se aproximava do seu maior vigor vegetativo, notando-se uma quebra significativa destes índices no final da Primavera, quando a pastagem começou a secar em virtude da conjugação de temperaturas mais elevadas com a redução dos teores de humidade no solo. Este índice foi também efectivo na identificação de diferentes famílias botânicas (gramíneas/leguminosas) e diferentes produtividades na pastagem. Por outro lado, foi possível desenvolver equações de calibração do NDVI com a produção de matéria verde e de matéria seca (em kg/ha), tendo sido evidenciada uma relação inversa deste índice com o teor de matéria seca (em %) de pastagens de sequeiro do Alentejo.

Evaluation of DUALEM, OptRx and Grassmaster II sensors for monitoring the spatial variability and the temporal stability of a Mediterranean pasture

Site-specific management (SSM) is a form of precision agriculture whereby decisions on resource application and agronomic practices are improved to better match soil and crop requirements as they vary in the field. SSM enables the identification of regions (homogeneous management zones) within the area delimited by field boundaries. These subfield regions constitute areas that have similar permanent characteristics. Traditional soil and pasture sampling and the necessary laboratory analysis are time-consuming, labour-intensive and cost prohibitive, not viable from a SSM perspective because it needs a large number of soil and pasture samples in order to achieve a good representation of soil properties, nutrient levels and pasture quality and productivity. The main objective of this work was to evaluate technologies which have potential for monitoring aspects related to spatial and temporal variability of soil nutrients and pasture green and dry matter yield (respectively, GM and DM, in kg/ha) and support to decision making for the farmer. Three types of sensors were evaluated in a 7ha pasture experimental field: an electromagnetic induction sensor (“DUALEM 1S”, which measures the soil apparent electrical conductivity, ECa), an active optical sensor ("OptRx®", which measures the NDVI, “Normalized Difference Vegetation Index”) and a capacitance probe ("GrassMaster II" which estimates plant mass). The results indicate the possibility of using a soil electrical conductivity probe as, probably, the best tool for monitoring not only some of the characteristics of the soil, but also those of the pasture, which could represent an important help in simplifying the process of sampling and support SSM decision making, in precision agriculture projects. On the other hand, the significant and very strong correlations obtained between capacitance and NDVI and between any of these parameters and the pasture productivity shows the potential of these tools for monitoring the evolution of spatial and temporal patterns of the vegetative growth of biodiverse pasture, for identifying different plant species and variability in pasture yield in Alentejo dry-land farming systems. These results are relevant for the selection of an adequate sensing system for a particular application and open new perspectives for other works that would allow the testing, calibration and validation of the sensors in a wider range of pasture production conditions, namely the extraordinary diversity of botanical species that are characteristic of the Mediterranean region at the different periods of the year.

Climate seasonality limits leaf carbon assimilation and wood productivity in tropical forests.

The seasonal climate drivers of the carbon cy- cle in tropical forests remain poorly known, although these forests account for more carbon assimilation and storage than any other terrestrial ecosystem. Based on a unique combina- tion of seasonal pan-tropical data sets from 89 experimental sites (68 include aboveground wood productivity measure- ments and 35 litter productivity measurements), their asso- ciated canopy photosynthetic capacity (enhanced vegetation index, EVI) and climate, we ask how carbon assimilation and aboveground allocation are related to climate seasonal- ity in tropical forests and how they interact in the seasonal carbon cycle. We found that canopy photosynthetic capacity seasonality responds positively to precipitation when rain- fall is < 2000 mm yr-1 (water-limited forests) and to radia- tion otherwise (light-limited forests). On the other hand, in- dependent of climate limitations, wood productivity and lit- terfall are driven by seasonal variation in precipitation and evapotranspiration, respectively. Consequently, light-limited forests present an asynchronism between canopy photosyn- thetic capacity and wood productivity. First-order control by precipitation likely indicates a decrease in tropical forest pro- ductivity in a drier climate in water-limited forest, and in cur- rent light-limited forest with future rainfall < 2000 mm yr-1.

Development of super early genotypes for the dry bean (Phaseolus vulgaris) as affected by nitrogen management.

The super early genotypes (SEG) of dry bean (Phaseolus vulgaris L.) have a shorter life cycle (65-75 days) when compared with the season length of traditional cultivars (90-100 days). Timing of nitrogen top-dressing fertilization could be different because of this reduction in length of the SEG life cycle. This study aimed at characterizing, by using growth analysis and vegetation index, super early genotypes of dry bean development as affected by timing of nitrogen application. Field experiments were conducted in the 2014 and 2015 growing seasons in central Brazil with a randomized block experimental design with split plots scheme and four replicates. The plots comprised the dry bean genotypes (Colibri ? check cultivar, CNFC 15873, CNFC 15874, and CNFC 15875), and subplots comprised applications of N at different timings: 90 kg of N at sowing, 90 kg N at top-dressing; 45 kg of N at sowing plus 45 kg at top-dressing, with urea as the source of N. We also used a control treatment without N application. The CNFC 15874 super early genotype of dry bean had the higher grain yield (2776 kg ha-1) and differed from the CNFC 15873 genotype (2492 kg ha-1). Nitrogen fertilization allowed higher grain yield (2619 kg ha-1, when applied N at sowing, 2605 kg ha-1, when applied N at sowing and at top-dressing, and 2680 kg ha-1, when applied N at top-dressing) than the control, 2360 kg ha-1 (no N fertilization). The time of N fertilization in super early genotype of dry bean did not affect grain yield.

Avaliação temporal de sistemas pecuários usando o Índice de Vegetação NDVI derivado de imagens Landsat.

A pecuária é responsável por mais de 6% do Produto Interno Bruto. Manejos pecuários têm sido estudados para buscar meios mais eficientes de produção. Nosso objetivo neste trabalho foi avaliar o efeito de sistemas pecuários sobre o índice de vegetação Normalized Difference Vegetation Index (NDVI), para indicar os sistemas mais produtivos em temos de forragem. Duas áreas de produção de gado de corte e uma de gado de leite, localizadas na Embrapa Pecuária Sudeste (São Carlos, SP), foram avaliadas no período de abril de 2013 a agosto de 2015. Na área 1, os maiores valores de NDVI ocorreram no sistema integração lavoura-pecuária-floresta em todos os períodos. Os sistemas integrado pecuária-floresta e intensivo apresentaram valores similares, principalmente nos períodos de seca. Nas situações em que a cobertura principal eram as pastagens foi possível, na maior parte do tempo, separar os sistemas mais produtivos (intensivos) do sistema menos vigoroso (extensivo). Na área 2, o sistema intensivo e de alta lotação animal apresentou os maiores valores de índices de vegetação ao longo de todos os períodos avaliados e foi o mais produtivo. Na área 3, os sistemas de produção intensivo em recuperação e intensivo irrigado apresentaram os maior valores de NDVI na maior parte dos período avaliados, o que indica maior produtividade desses sistemas. De acordo com os resultados obtidos, séries temporais de NDVI têm o potencial de discriminar, entre os sistemas pecuários de produção não integrados, os sistemas mais produtivos (intensivos) dos sistemas menos produtivos (extensivos), principalmente nos períodos de seca.