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12Scots pine (Pinus sylvestris L.) forests of many inner Alpine valleys have recently displayed a quick loss of 13 vitality. A decline disease has been suggested as the cause, with drought as the main predisposing factor and 14 the additional contribution of biotic agents inciting tree dieback. This study is focused on validated against ancillary ground truth. We: (1) tested whether EVI reductions in Scots pine forests were 19 significantly higher than those of a control species and of a wetter region for the same species, (2) analyzed 20 decline incidence as a function of site and topographic variables, and (3) assessed the relative influence of 21 site and stand structure on decline probability by means of path analysis. Mean EVI in the study area 22 increased due to an early onset of the 2007 growing season. Nevertheless, the incidence of decline was 6.3% 23 and significantly greater for Scots pine than the control species and site. Low-elevation, northerly exposed 24 sites exhibited the highest incidence of decline. 25Path analysis suggested that the most important determi-nants of decline probability were slope, solar 26 radiation, and stand sparseness. 27 28

BackgroundUltrasonography to visualize adrenal gland lesions and evaluate incidentally discovered adrenal masses in dogs has become more reliable with advances in imaging techniques. However, correlations between sonographic and histopathological changes have been elusive. The goal of our study was to investigate which ultrasound features of adrenal gland abnormalities could aid in discriminating between benign and malignant lesions. To this end, we compared diagnosis based on ultrasound appearance and histological findings and evaluated ultrasound criteria for predicting malignancy.ResultsClinical records of 119 dogs that had undergone ultrasound adrenal gland and histological examination were reviewed. Of these, 50 dogs had normal adrenal glands whereas 69 showed pathological ones. Lesions based on histology were classified as cortical adrenal hyperplasia (n = 67), adenocarcinoma (n = 17), pheochromocytoma (n = 10), metastases (n = 7), adrenal adenoma (n = 4), and adrenalitis (n = 4). Ultrasonographic examination showed high specificity (100%) but low sensitivity (63.7%) for identifying the adrenal lesions, which improved with increasing lesion size. Analysis of ultrasonographic predictive parameters showed a significant association between lesion size and malignant tumors. All adrenal gland lesions >20 mm in diameter were histologically confirmed as malignant neoplasms (pheochromocytoma and adenocarcinoma). Vascular invasion was a specific but not sensitive predictor of malignancy. As nodular shape was associated with benign lesions and irregular enlargement with malignant ones, this parameter could be used as diagnostic tool. Bilaterality of adrenal lesions was a useful ultrasonographic criterion for predicting benign lesions, as cortical hyperplasia.ConclusionsAbnormal appearance of structural features on ultrasound images (e.g., adrenal gland lesion size, shape, laterality, and echotexture) may aid in diagnosis, but these features alone were not pathognomic. Lesion size was the most direct ultrasound predictive criterion. Large and irregular masses seemed to be better predictors of malignant neoplasia and lesions <20 mm in diameter and nodular in shape were often identified as cortical hyperplastic nodules or adenomas.

Remote sensing phenological works often use vegetation index (VI) time-series (TS). Since ground-observed phenological metrics occurrences vary by a few days from year to year, TS temporal accuracy became mandatory, but it is less strict in composite data. A technique to recover the temporal accuracy of 250 m 16-day composite VI from the MODIS MOD13Q1 product is proposed, relying on acquisition dates contained in the Composite day of the year layer. We demonstrated that the correction process significantly affected the VI TS during most of the year, especially in spring and autumn when the starting of season (SOS) and the end of the season (EOS) are expected. As a consequence of the TS correction process, SOS estimation showed to be affected too.