Remotely-Sensed Early Warning Signals of a Critical Transition in a Wetland Ecosystem

The response of an ecosystem to external drivers may not always be gradual and reversible. Discontinuous and sometimes irreversible changes, called 'regime shifts' or 'Critical transitions', can occur. The likelihood of such shifts is expected to increase for a variety of ecosystems, and it is difficult to predict how close an ecosystem is to a critical transition. Recent modelling studies identified indicators of impending regime shifts that can be used to provide early warning signals of a critical transition. The identification of such transitions crucially depends on the ability to monitor key ecosystem variables, and their success may be limited by lack of appropriate data. Moreover, empirical demonstrations of the actual functioning of these indicators in real-world ecosystems are rare. This paper presents the first study which uses remote sensing data to identify a critical transition in a wetland ecosystem. In this study, we argue that a time series of remote sensing data can help to characterize and determine the timing of a critical transition. This can enhance our abilities to detect and anticipate them. We explored the potentials of remotely sensed vegetation (NDVI), water (MNDWI), and vegetation- water (VWR) indices, obtained from time series of MODIS satellite images to characterize the stability of a wetland ecosystem, Dorge Sangi, near the lake Urmia, Iran, that experienced a regime shift recently. In addition, as a control case, we applied the same methods to another wetland ecosystem in Lake Arpi, Armenia which did not experience a regime shift. We propose a new composite index (MVWR) based on combining vegetation and water indices, which can improve the ability to anticipate a critical transition in a wetland ecosystem. Our results revealed that MVWR in combination with autocorrelation at-lag-1 could successfully provide early warning signals for a critical transition in a wetland ecosystem, and showed a significantly improved performance compared to either vegetation (NDVI) or water (MNDWI) indices alone.Peer reviewe

When is variable importance estimation in species distribution modelling affected by spatial correlation?

Species distribution models are generic empirical techniques that have a number of applications. One of these applications is to determine which environmental conditions are most important for a species. The calculation of this variable importance depends on a number of assumptions, including that the observations that are used to estimate the models are independent of each other. Spatial autocorrelation, which is a common feature most environmental factors confounds this assumption. Besides, many species distribution models are trained using a number of explanatory variables that have different levels of spatial autocorrelation. In this study we quantified the effects of differences in spatial autocorrelation in explanatory variables and the type of species responses to environmental gradients on variable importance estimations in species distribution models. We simulated data for both environmental predictors and species, so that we were in control of the true contribution of every variable in the model and the importance that could be estimated after fitting the models. We found that spatial autocorrelation in the predictors inflated the variable importance estimates, but only when the response of species to the environmental gradients is linear. This inflation effect was larger when the environmental preferences of species coincided with the dominant environmental conditions in a study site. Additionally we find that unimodal responses to the predictors yield systematically a higher variable importance compared to linear responses. We conclude that the type of response to environmental conditions and the relative levels of spatial autocorrelation in the environmental variables cause most bias in relative variable importance estimations. In this way, this study helps to clarify in a systematic and controlled approach how to make proper inferences about variable importance in species distribution models.Peer reviewe

Restoration of SMN in Schwann cells reverses myelination defects and improves neuromuscular function in spinal muscular atrophy

Spinal muscular atrophy (SMA) is a neuromuscular disease caused by low levels of SMN protein, primarily affecting lower motor neurons. Recent evidence from SMA and related conditions suggests that glial cells can influence disease severity. Here, we investigated the role of glial cells in the peripheral nervous system by creating SMA mice selectively overexpressing SMN in myelinating Schwann cells (Smn(−/−);SMN2(tg/0);SMN1(SC)). Restoration of SMN protein levels restricted solely to Schwann cells reversed myelination defects, significantly improved neuromuscular function and ameliorated neuromuscular junction pathology in SMA mice. However, restoration of SMN in Schwann cells had no impact on motor neuron soma loss from the spinal cord or ongoing systemic and peripheral pathology. This study provides evidence for a defined, intrinsic contribution of glial cells to SMA disease pathogenesis and suggests that therapies designed to include Schwann cells in their target tissues are likely to be required in order to rescue myelination defects and associated disease symptoms

Systemic restoration of UBA1 ameliorates disease in spinal muscular atrophy

Acknowledgments Blood biochemistry analysis and serum analysis were performed by the Easter Bush Pathology Department, University of Edinburgh. Animal husbandry was performed by Centre for Integrative Physiology bio-research restructure technical staff, University of Edinburgh. Assistance with intravenous injections was provided by Ian Coldicott (University of Sheffield) and Hannah Shorrock (University of Edinburgh). Human blood cDNA was a gift to GH from Kathy Evans, University of Edinburgh. Imaging was performed at the IMPACT imaging facility, University of Edinburgh, with technical assistance from Anisha Kubasik-Thayil. The authors would also like to thank Lyndsay Murray for technical discussions relating to qRT-PCR analysis. This work was supported by funding from the SMA Trust and the Anatomical Society (via grants to THG); the Euan MacDonald Centre for Motor Neurone Disease Research (via grants to THG and SHP); the Wellcome Trust (via grants to EJNG and THG); Muscular Dystrophy UK (via grants to THG and CGB); a Elphinstone Scholarship from the University of Aberdeen (to SHP); and The French Muscular Dystrophy Association (via grants to CM and JC).Peer reviewedPublisher PD

The effects of armed conflict on forest cover changes across temporal and spatial scales in the Colombian Amazon

This paper's results show that conflict variables have positive relationships with deforestation in Colombia; yet, they are not among the main variables explaining deforestation

Disruption of Intraflagellar Transport in Adult Mice Leads to Obesity and Slow-Onset Cystic Kidney Disease

SummaryThe assembly of primary cilia is dependant on intraflagellar transport (IFT), which mediates the bidirectional movement of proteins between the base and tip of the cilium. In mice, congenic mutations disrupting genes required for IFT (e.g., Tg737 or the IFT kinesin Kif3a) are embryonic lethal, whereas kidney-specific disruption of IFT results in severe, rapidly progressing cystic pathology [1–3]. Although the function of primary cilia in most tissues is unknown, in the kidney they are mechanosenstive organelles that detect fluid flow through the tubule lumen [4]. The loss of this flow-induced signaling pathway is thought to be a major contributing factor to cyst formation [5–7]. Recent data also suggest that there is a connection between ciliary dysfunction and obesity as evidenced by the discovery that proteins associated with human obesity syndromes such as Alström and Bardet-Biedl localize to this organelle [8]. To more directly assess the importance of cilia in postnatal life, we utilized conditional alleles of two ciliogenic genes (Tg737 and Kif3a) to systemically induce cilia loss in adults. Surprisingly, the cystic kidney pathology in these mutants is dependent on the time at which cilia loss was induced, suggesting that cyst formation is not simply caused by impaired mechanosensation. In addition to the cystic pathology, the conditional cilia mutant mice become obese, are hyperphagic, and have elevated levels of serum insulin, glucose, and leptin. We further defined where in the body cilia are required for normal energy homeostasis by disrupting cilia on neurons throughout the central nervous system and on pro-opiomelanocortin-expressing cells in the hypothalamus, both of which resulted in obesity. These data establish that neuronal cilia function in a pathway regulating satiety responses

Outcomes of surgery and postoperative radiation therapy in managing medullary thyroid carcinoma

Background and Objectives We evaluated the outcomes of surgery with or without postoperative radiation therapy (PORT) in the management of medullary thyroid carcinoma (MTC). Methods From two tertiary cancer centers, 297 consecutive patients with MTC treated with PORT (n = 46) between 1990 and 2016 or surgery alone (n = 251) between 2000 and 2016 were reviewed. Results Ten-year cumulative incidences of locoregional and distant failure were 30.2% and 24.9% in the surgery cohort, and 16.9% and 55.2% in the PORT cohort. In the surgery alone cohort, T4 disease, extrathyroidal extension, N1 disease, extranodal extension (ENE), and residual disease after surgery were associated with local failure. The PORT cohort had significantly higher proportions of patients with T4 disease, N1 disease, ENE, and residual disease. Conclusions High-risk clinical features can help identify patients with MTC at high-risk for local failure after surgery alone. Patients with high-risk clinical features had effective locoregional control after PORT