ABSTRACT
Leaf coloring and fall mark the end of the growing season (EOS), playing essential roles in nutrient cycling, resource allocation, ecological interactions, and as climate change indicators. However, understanding future changes in autumn phenology is challenging due to the multitude of likely environmental cues and substantial variations in timing caused by different derivation methods. Yet, it remains unclear whether these two factors are independent or if methodological uncertainties influence the environmental cues determined. We derived start of growing season (SOS) and EOS at a mixed beech forest in Central Germany for the period 2000-2020 based on four different derivation methods using a unique long-term data set of in-situ data, canopy imagery, eddy covariance measurements, and satellite remote sensing data and determined their influence on a predictor analysis of leaf senescence. Both SOS and EOS exhibited substantial ranges in mean onset dates (39.5 and 28.6 days, respectively) across the different methods, although inter-annual variations and advancing SOS trends were similar across methods. Depending on the data, EOS trends were advanced or delayed, but inter-annual patterns correlated well (mean r = .46). Overall, warm, dry, and less photosynthetically productive growing seasons were more likely to be associated with a delayed EOS, while colder, wetter, and more photosynthetically productive vegetation periods resulted in an earlier EOS. In addition, contrary to recent results, no clear influence of pre-solstice vegetation activity on the timing of senescence was detected. However, most notable were the large differences in sign and strength of potential drivers both in the univariate and multivariate analyses when comparing derivation methodologies. The results suggest that an ensemble analysis of all available phenological data sources and derivation methods is needed for general statements on autumn phenology and its influencing variables and correct implementation of the senescence process in ecosystem models.
Subject(s)
Cues , Ecosystem , Seasons , Temperature , Forests , Climate ChangeABSTRACT
Winter tourism is an important economic factor in the European Alps, which could be exposed to severely changing meteorological conditions due to climate change in the future. The extent to which meteorology influences winter tourism figures has so far been analyzed mainly based on monthly or seasonal data and in relation to skier numbers. Therefore, we record for the first time daily visitor numbers at five Bavarian winter tourism destinations based on 1518 webcam images using object detection and link them to meteorological and time-related variables. Our results show that parameters such as temperature, cloud cover or sunshine duration, precipitation, snow depth, wind speed, and relative humidity play a role especially at locations that include other forms of winter tourism in addition to skiing. In the ski resorts studied, on the other hand, skiing is mostly independent of current weather conditions, which can be attributed mainly to artificial snowmaking. Moreover, at the webcam sites studied, weekends and vacation periods had an equal or even stronger influence on daily visitor numbers than the current weather conditions. The extent to which weather impacts the (future) visitor numbers of a winter tourism destination must therefore be investigated individually and with the inclusion of non-meteorological variables influencing human behavior.
Subject(s)
Recreation , Weather , Humans , Seasons , Snow , TemperatureABSTRACT
Tree phenology is a major component of the global carbon and water cycle, serving as a fingerprint of climate change, and exhibiting significant variability both within and between species. In the emerging field of drone monitoring, it remains unclear whether this phenological variability can be effectively captured across numerous tree species. Additionally, the drivers behind interspecific variations in the phenology of deciduous trees are poorly understood, although they may be linked to plant functional traits. In this study, we derived the start of season (SOS), end of season (EOS), and length of season (LOS) for 3099 individuals from 74 deciduous tree species of the Northern Hemisphere at a unique study site in southeast Germany using drone imagery. We validated these phenological metrics with in-situ data and analyzed the interspecific variability in terms of plant functional traits. The drone-derived SOS and EOS showed high agreement with ground observations of leaf unfolding (R2â¯=â¯0.49) and leaf discoloration (R2â¯=â¯0.79), indicating that this methodology robustly captures phenology at the individual level with low temporal and human effort. Both intra- and interspecific phenological variability were high in spring and autumn, leading to differences in the LOS of up to two months under almost identical environmental conditions. Functional traits such as seed dry mass, chromosome number, and continent of origin played significant roles in explaining interspecific phenological differences in SOS, EOS, and LOS, respectively. In total, 55â¯%, 39â¯%, and 45â¯% of interspecific variation in SOS, EOS, and LOS could be explained by the Boosted Regression Tree (BRT) models based on functional traits. Our findings encourage new research avenues in tree phenology and advance our understanding of the growth strategies of key tree species in the Northern Hemisphere.
ABSTRACT
OBJECTIVE: The therapeutic options for metastatic pheochromocytomas/paragangliomas (mPPGLs) include chemotherapy with cyclophosphamide/vincristine/dacarbazine (CVD), temozolomide monotherapy, radionuclide therapies, and tyrosine kinase inhibitors such as sunitinib. The objective of this multicenter retrospective study was to evaluate and compare the responses of mPPGLs including those with pathogenic variants in succinate dehydrogenase subunit B (SDHB), to different systemic treatments. DESIGN: This is a retrospective analysis of treatment responses of mPPGL patients (n = 74) to systemic therapies. METHODS: Patients with mPPGLs treated at 6 specialized national centers were selected based on participation in the ENSAT registry. Survival until detected progression (SDP) and disease-control rates (DCRs) at 3 months were evaluated based on imaging reports. RESULTS: For the group of patients with progressive disease at baseline (83.8% of 74 patients), the DCR with first-line CVD chemotherapy was 75.0% (n = 4, SDP 11 months; SDHB [n = 1]: DCR 100%, SDP 30 months), with somatostatin peptide receptor-based radionuclide therapy (PPRT) 85.7% (n = 21, SDP 17 months; SDHB [n = 10]: DCR 100%, SDP 14 months), with 131I-meta-iodobenzylguanidine (131I-MIBG) 82.6% (n = 23, SDP 43 months; SDHB [n = 4]: DCR 100%, SDP 24 months), with sunitinib 100% (n = 7, SDP 18 months; SDHB [n = 3]: DCR 100%, SDP 18 months), and with somatostatin analogs 100% (n = 4, SDP not reached). The DCR with temozolomide as second-line therapy was 60.0% (n = 5, SDP 10 months; SDHB [n = 4]: DCR 75%, SDP 10 months). CONCLUSIONS: We demonstrate in a real-life clinical setting that all current therapies show reasonable efficacy in preventing disease progression, and this is equally true for patients with germline SDHB mutations.
Subject(s)
Adrenal Gland Neoplasms , Brain Neoplasms , Cardiovascular Diseases , Neoplasms, Second Primary , Paraganglioma , Pheochromocytoma , Humans , Pheochromocytoma/pathology , Iodine Radioisotopes/therapeutic use , Retrospective Studies , Cohort Studies , Temozolomide/therapeutic use , Sunitinib/therapeutic use , Paraganglioma/genetics , Succinate Dehydrogenase/genetics , Adrenal Gland Neoplasms/pathology , Somatostatin/therapeutic useABSTRACT
CONTEXT: Pheochromocytomas and paragangliomas (PPGLs) with pathogenic mutations in the succinate dehydrogenase subunit B (SDHB) are associated with a high metastatic risk. Somatostatin receptor 2 (SSTR2)-dependent imaging is the most sensitive imaging modality for SDHB-related PPGLs, suggesting that SSTR2 expression is a significant cell surface therapeutic biomarker of such tumors. OBJECTIVE: Exploration of the relationship between SSTR2 immunoreactivity and SDHB immunoreactivity, mutational status, and clinical behavior of PPGLs. Evaluation of SSTR-based therapies in metastatic PPGLs. METHODS: Retrospective analysis of a multicenter cohort of PPGLs at 6 specialized Endocrine Tumor Centers in Germany, The Netherlands, and Switzerland. Patients with PPGLs participating in the ENSAT registry were included. Clinical data were extracted from medical records, and immunohistochemistry (IHC) for SDHB and SSTR2 was performed in patients with available tumor tissue. Immunoreactivity of SSTR2 was investigated using Volante scores. The main outcome measure was the association of SSTR2 IHC positivity with genetic and clinical-pathological features of PPGLs. RESULTS: Of 202 patients with PPGLs, 50% were SSTR2 positive. SSTR2 positivity was significantly associated with SDHB- and SDHx-related PPGLs, with the strongest SSTR2 staining intensity in SDHB-related PPGLs (P = .01). Moreover, SSTR2 expression was significantly associated with metastatic disease independent of SDHB/SDHx mutation status (P < .001). In metastatic PPGLs, the disease control rate with first-line SSTR-based radionuclide therapy was 67% (n = 22, n = 11 SDHx), and with first-line "cold" somatostatin analogs 100% (n = 6, n = 3 SDHx). CONCLUSION: SSTR2 expression was independently associated with SDHB/SDHx mutations and metastatic disease. We confirm a high disease control rate of somatostatin receptor-based therapies in metastatic PPGLs.