Abstract
While an understanding of evolutionary processes in shifting environments is vital in the context of rapid ecological change, one of the most potent selective forces, sexual selection, remains curiously unexplored. Variation in sexual selection across a species range, especially across a gradient of temperature regimes, has the potential to provide a window into the possible impacts of climate change on the evolution of mating patterns. Here, we investigated some of the links between temperature and indicators of sexual selection, using a cold-water pipefish as model. We found that populations differed with respect to body size, length of the breeding season, fecundity, and sexual dimorphism across a wide latitudinal gradient. We encountered two types of latitudinal patterns, either linear, when related to body size, or parabolic in shape when considering variables related to sexual selection intensity, such as sexual dimorphism and reproductive investment. Our results suggest that sexual selection intensity increases toward both edges of the distribution and that the large differences in temperature likely play a significant role. Shorter breeding seasons in the north and reduced periods for gamete production in the south certainly have the potential to alter mating systems, breeding synchrony, and mate monopolization rates. As latitude and water temperature are tightly coupled across the European coasts, the observed patterns in traits related to sexual selection can lead to predictions regarding how sexual selection should change in response to climate change. Based on data from extant populations, we can predict that as the worm pipefish moves northward, a wave of decreasing selection intensity will likely replace the strong sexual selection at the northern range margin. In contrast, the southern populations will be followed by heightened sexual selection, which may exacerbate the problem of local extinction at this retreating boundary.

Abstract
For Precise Agriculture purposes, several steps of a maize crop-system were recorded by the use of a GPS receiver with EGNOS and RTK capabilities. The field is about 35 km far from two GNSS CORS, one from RENEP, operated by IGS, and the other from SERVIR, operated by IGEoE. Both networks disseminate real-time GNSS data streams over the Internet using the NTRIP protocol. The GNSS data streams from RENEP reference stations (including validated station coordinates) provide the user with a real-time access to the ETRS89 and, those same streams from IGEoE, a military institution, are in ITRS, allowing large scale scientific applications. The validation of the EGNOS and the RTK solutions, obtained in the two TRS systems, was achieved by the results from post-processed measurements. RTK solutions, when compared to the post-processed values in the same TRS, show sub-decimeter accuracy what is enough for many of the Precision Agriculture studies. However, the two RTK solutions have a translation with a magnitude of the order of 0.5 m that can be explained by the independence of the ETRS89 on the continental drift. Indeed, at the zone where the field is located, while the ETRFyy Cartesian coordinates have velocities less than 1 mm/year, the ITRFyy Cartesian coordinates have velocities greater than 1 cm/year, what give rise to a point position variation with a magnitude of 2.5 cm/year. In order to correlate the tractor velocity, during a pre-emergence herbicide application, to the terrain slope, the field orthometric heights were obtained by the use of GRS80 ondulations, on a 1.5' x 1.5'grid, in the local Portuguese geoid model GeodPT08. The global precision of this model is estimated in 4 cm, which is within the error for the real time solutions obtained.

Abstract
Olive trees are one of the most economically important perennial crops in Portugal. During the last decade, the Alentejo olive-growing region has suffered a significantly change in the crop production system, with the regional pollen index (RPI) and olive fruit production registering a significant growth. The aim of this study was to ascertain the utility of this highly variable production and pollen data in crop forecasting modeling. Airborne pollen was sampled using a Cour-type trap from 1999 to 2015. A linear regression model fitted with the regional pollen index as the independent variable showed an accuracy of 87% in estimating olives fruit production in Alentejo. However, the average deviation between observed and modeled production was 32% with half of the tested years presenting deviations between 36 and 66%. The low accuracy of this model is a consequence of the great overall variation and significant upward trend observed in both the production and the RPI dataset that conceal the true association between these variables. In order to overcome this problem, a detrend procedure was applied to both time series to remove the trend observed. The regression model fitted with the fruit production and the RPI detrended data showed a lowest forecasting accuracy of 63% but the average deviation between observed and modeled production decrease to 14% with a maximum deviation value of 33%. This procedure allows focusing the analysis on the production fluctuations related to the biological response of the trees rather than with the changes in the production system.

Abstract
Soil erosion is a serious environmental problem. An estimation of the expected soil loss by water-caused erosion can be calculated considering the Revised Universal Soil Loss Equation (RUSLE). Geographical Information Systems (GIS) provide different tools to create categorical maps of soil erosion risk which help to study the risk assessment of soil loss. The objective of this study was to develop a GIS open source application (in QGIS), using the RUSLE methodology for estimating erosion rate at the watershed scale (desktop application) and provide the same application via web access (web application). The applications developed allow one to generate all the maps necessary to evaluate the soil erosion risk. Several libraries and algorithms from SEXTANTE were used to develop these applications. These applications were tested in Montalegre municipality (Portugal). The maps involved in RUSLE method-soil erosivity factor, soil erodibility factor, topographic factor, cover management factor, and support practices-were created. The estimated mean value of the soil loss obtained was 220 ton km(-2) year(-1) ranged from 0.27 to 1283 ton km(-2) year(-1). The results indicated that most of the study area (80 %) is characterized by very low soil erosion level (<321 ton km(-2) year(-1)) and in 4 % of the studied area the soil erosion was higher than 962 ton km(-2) year(-1). It was also concluded that areas with high slope values and bare soil are related with high level of erosion and the higher the P and C values, the higher the soil erosion percentage. The RUSLE web and the desktop application are freely available.

Abstract
METRIC (TM) is a satellite-based surface energy balance model aimed at estimating and mapping crop evapotranspiration (ET). It has been applied to a large range of vegetation types, mostly annual crops. When applied to anisotropic woody canopies, such as olive orchards, extensions are required to algorithms for estimating the leaf area index (LAI), surface temperature, and momentum roughness length (Z(om)). The computation of the radiometric surface temperature needs to consider a three-source condition, thus differentiating the temperature of the canopy (T-c), of the shaded ground surface (T-shadow), and of the sunlit ground surface (T-sunlit). The estimation of the Z(om) for tall and incomplete cover is based upon the LAI and crop height using the Perrier equation. The LAI, Zorn, and temperature derived from METRIC after these adjustments were tested against field collected data with good results. The application of METRIC to a two year set of Landsat images to estimate ET of a super-intensive olive orchard in Southern Portugal produced good ET estimates that compared well with ground-based ET. The analysis of METRIC performance showed a quantitative improvement of ET estimates when applying the three-source condition for temperature estimation, as well as the Z(om) computation with the Perrier equation. Results show that METRIC can be used operationally to estimate and mapping ET of super-intensive olive orchards aiming at improving irrigation water use and management.

Abstract
The estimation of crop evapotranspiration (ETc) from the reference evapotranspiration (ETo) and a standard crop coefficient (K-c) in olive orchards requires that the latter be adjusted to planting density and height. The use of the dual K-c approach may be the best solution because the basal crop coefficient K-cb represents plant transpiration and the evaporation coefficient reproduces the soil coverage conditions and the frequency of wettings. To support related computations for a super intensive olive orchard, the model SIMDualKc was adopted because it uses the dual K-c approach. Alternatively, to consider the physical characteristics of the vegetation, the satellite-based surface energy balance model METRIC (TM) - Mapping EvapoTranspiration at high Resolution using Internalized Calibration - was used to estimate ETc and to derive crop coefficients. Both approaches were compared in this study. SIMDualKc model was calibrated and validated using sap-flow measurements of the transpiration for 2011 and 2012. In addition, eddy covariance estimation of ETc was also used. In the current study, METRIC (TM), was applied to Landsat images from 2011 to 2012. Adaptations for incomplete cover woody crops were required to parameterize METRIC. It was observed that ETc obtained from both approaches was similar and that crop coefficients derived from both models showed similar patterns throughout the year. Although the two models use distinct approaches, their results are comparable and they are complementary in spatial and temporal scales.