Predictability and constraints on the structure of ecological communities in the context of climate change

Ecologists must increasingly balance the need for accurate predictions about how ecosystems will be affected by climate change, against the fact that making such predictions at the ecosystem-level may be infeasible. Although information about responses of individual species to a changing environment is increasing, scaling such information to the community level is challenging. To date, predicting responses of ecological communities to climate change is constrained by limited theoretical and empirical knowledge about the response of communities and ecosystems to change. My dissertation addresses several knowledge gaps in our understanding of community structure under climate change. This research draws from a rich experimental tradition in the species-diverse model ecosystem of the US Pacific Northwest rocky intertidal to test ecological theory. In Chapter 2, I assessed whether the response of multiple species of coralline algae to global change could be predicted from basic first principles of chemistry, physiology, and ecology. Given the rate of global change, and the time-consuming process of experimentally determining species responses to climate change, I hypothesized that species can be grouped using existing theory, either by their evolutionary relatedness or by their ecological traits, such that climate responses are similar within a group. Such a scheme would greatly reduce the number of experiments needed to characterize species climate vulnerability, requiring the characterization of the response of groups of species to climate change, rather than individual species. Using a suite of five co-occurring species of intertidal articulated coralline algae (Corallina vancouveriensis, Corallina officinalis, Bossiella plumosa, Bossiella orbiginiana, and Calliarthron tuberculosum), I applied this framework to generate ten mutually exclusive hypotheses that could explain organismal response to ocean acidification, a consequence of global climate change that threatens marine calcifying species. I found that all species had similar responses to ocean acidification, and that responses were generally predicted by the body size of the individual. Despite the power that such a framework provides in understanding group-level response to climate change, predicting community-level response requires knowledge of how organisms affect one another. In Chapter 3, I quantified species interactions in a series of removal experiments to estimate the reciprocal effects between a canopy-forming intertidal kelp (Saccharina sessilis) and a suite of understory species that persist beneath the kelp canopy. This experiment was replicated in different oceanographic conditions across a large latitudinal gradient, as a step towards understanding how interactions might change with climate change. However, the experiment demonstrated that interactions between the canopy and understory were consistent among different environmental conditions. Furthermore, the strongest effect was that of understory species, particularly articulated coralline turf algae, on the canopy species. The coralline turf algae both facilitated the recruitment of the canopy species and buffered the canopy from abiotic stress during its adult life stage. Combining experimental results and observational surveys, a hypothesized interaction network for these species was constructed, highlighting the importance of direct and indirect species interactions in promoting species coexistence. A long-standing controversy in ecology is whether or not species interactions can be inferred from observational data, as opposed to from experimental tests. Although the rocky intertidal ecosystem is unique for its ease of experimental manipulation, quantifying species interactions experimentally is often difficult or impossible. As an alternative, many have turned to statistical methods to estimate species interactions from observational data, namely, from patterns in species pairwise co-occurrences. In Chapter 4, I examined these co-occurrence methods and their potential relationship to experimentally measured species interactions. I first used a suite of different co-occurrence methods to generate a set of predicted species interactions of macrophytes and invertebrates from observational surveys conducted in the rocky intertidal zone of Oregon. I then compared the predicted species interactions to the same pairwise species interactions determined experimentally and assembled from the literature. Overall, of the seven methods tested, each generated a different set of predicted species interactions from the same data, and all methods predicted interactions that did not match those in the experimental database. Thus, predicting species interactions from patterns in occurrence remains elusive. Importantly, much work remains to be done to understand the link between species co-occurrences and their actual interactions with one another on the landscape. A key limiting frontier in climate change ecology is determining the influence of species interactions on species distributions across the landscape, and the sensitivity of such interactions to changes in climate. Finally, in Chapter 5, I used theory from the published literature and knowledge from my previous chapters to make predictions the recovery of low rocky intertidal communities after a disturbance. The process of community development after disturbance has been studied in many ways, from the successional studies of the early 1900s, to modern community assembly theory. In recent years, a focus on the unpredictability of community assembly has emerged, paying particular attention to the role of historical contingency, or priority effects, in determining the recovery trajectory of a community. Priority effects occur when the arrival of a species after a disturbance inalterably changes the composition of the developing community, driving the assembly of widely different communities at a small spatial scale. I conducted a community assembly experiment in three different low intertidal zone community "types", each characterized by different dominant macrophyte species (Saccharina sessilis, Phyllospadix spp., and algal "turfs"). Replicating this experiment at six sites along the Oregon coast, I found that both regional and local dynamics constrain the recovery of communities after disturbance. Half of the time, the community returned to the state of the nearby community type. The remaining communities were influenced by priority effects that could be predicted based on 1) regional dynamics favoring some species over others, or 2) the timing of arrival of important facilitating species. Overall, understanding the dynamic relationship between the persistence of diverse communities and a changing environment remains one of the challenges of our time. My dissertation highlights some of the challenges in predicting the future composition of communities under climate change, but also provides some ways forward. Integration of experimental, theoretical, and observational studies builds the scaffolding of prediction, whereby understanding the constraints on species physiology, the interactions among species, and community assembly can help frame the context in which predictions are made.Keywords: Rocky Intertidal, Algae, Community Ecology, Ecology, Kelp, Climate Change Ecolog

Wavelength Orthogonal Photodynamic Networks

The ability of light to remotely control the properties of soft matter materials in a dynamic fashion has fascinated material scientists and photochemists for decades. However, only recently has our ability to map photochemical reactivity in a finely wavelength resolved fashion allowed for different colors of light to independently control the material properties of polymer networks with high precision, driven by monochromatic irradiation enabling orthogonal reaction control. The current concept article highlights the progress in visible light-induced photochemistry and explores how it has enabled the design of polymer networks with dynamically adjustable properties. We will explore current applications ranging from dynamic hydrogel design to the light-driven adaptation of 3D printed structures on the macro- and micro-scale. While the alternation of mechanical properties via remote control is largely reality for soft matter materials, we herein propose the next frontiers for adaptive properties, including remote switching between conductive and non-conductive properties, hydrophobic and hydrophilic surfaces, fluorescent or non-fluorescent, and cell adhesive vs. cell repellent properties

RAFT-based polystyrene and polyacrylate melts under thermal and mechanical stress

Although controlled/living radical polymerization processes have significantly facilitated the synthesis of well-defined low polydispersity polymers with specific functionalities, a detailed and systematic knowledge of the thermal stability of the products-highly important for most industrial processes-is not available. Linear polystyrene (PS) carrying a trithiocarbonate mid-chain functionality (thus emulating the structure of the Z-group approach via reversible addition-fragmentation chain transfer (RAFT) based macromolecular architectures) with various chain lengths (20 kDa ≤ Mn,SEC ≤ 150 kDa, 1.27 ≤ Crossed D sign = Mw/Mn ≤ 1.72) and chain-end functionality were synthesized via RAFT polymerization. The thermal stability behavior of the polymers was studied at temperatures ranging from 100 to 200 C for up to 504 h (3 weeks). The thermally treated polymers were analyzed via size exclusion chromatography (SEC) to obtain the dependence of the polymer molecular weight distribution on time at a specific temperature under air or inert atmospheres. Cleavage rate coefficients of the mid-chain functional polymers in inert atmosphere were deduced as a function of temperature, resulting in activation parameters for two disparate Mn starting materials (Ea = 115 ± 4 kJ·mol-1, A = 0.85 × 109 ± 1 × 109 s-1, M n,SEC = 21 kDa and Ea = 116 ± 4 kJ·mol -1, A = 6.24 × 109 ± 1 × 109 s-1, Mn,SEC = 102 kDa). Interestingly, the degradation proceeds significantly faster with increasing chain length, an observation possibly associated with entropic effects. The degradation mechanism was explored in detail via SEC-ESI-MS for acrylate based polymers and theoretical calculations suggesting a Chugaev-type cleavage process. Processing of the RAFT polymers via small scale extrusion as well as a rheological assessment at variable temperatures allowed a correlation of the processing conditions with the thermal degradation properties of the polystyrenes and polyacrylates in the melt. © 2013 American Chemical Society.C.B.-K and M.W. gratefully acknowledge financial support from the German Research Council (DFG). M.L.C gratefully acknowledges generous allocations of supercomputing time from the Australian National Computing Facility, financial support from the Australian Research Council (ARC) Centre of Excellence for Free-radical Chemistry and Biotechnology and an ARC Future Fellowship. C.B.-K. acknowledges additional funding from the Karlsruhe Institute of Technology (KIT) in the context of the Helmholtz programs

Measuring functional outcome in upper extremity soft-tissue sarcoma : Validation of the Toronto extremity salvage score and the QuickDASH patient-reported outcome instruments

Interest in functional outcome (FO) and health-related quality of life (HRQL) in extremity soft-tissue sarcoma (STS) patients has increased. The aim of this study was to validate two FO questionnaires for upper extremity STS patients: the Toronto Extremity Salvage Score (TESS) and short version of the Disability of Arm, Shoulder and Hand (QuickDASH), based on Finnish population data. A multi-center study was conducted at two academic sarcoma centers. Surgically treated upper extremity STS patients were invited to participate. Patients completed the TESS and the QuickDASH with HRQL questionnaires the 15D and the QLQ-C30. The scores were analyzed and compared. Fifty-five patients with a mean follow-up period of 4.7 years were included. Mean age was 63 years (standard deviation [SD] 14.6). The mean score for TESS was 88.5 (SD 15.1) and for QuickDASH 17.8 (SD 19.6). The QuickDASH had a statistically significantly better score coverage. A ceiling effect was noted, 27% and 20% for TESS and QuickDASH, respectively. The TESS and QuickDASH scores were strongly correlated ( r =-0.89). The TESS score strongly correlated with the QLQ-C30 ( r = 0.79) and the 15D score ( r = 0.70). The QuickDASH score correlated strongly with the QLQ-C30 score ( r =-0.71) and moderately with the 15D score ( r =-0.56). The TESS score had a statistically significantly stronger correlation with the 15D score than QuickDASH ( p < 0.005). Both the TESS and the QuickDASH provide reliable scores for assessing FO in upper extremity STS patients. The QuickDASH has a better coverage, whereas TESS showed a stronger correlation to HRQL scores. (c) 2022 British Association of Plastic, Reconstructive and Aesthetic Surgeons. Published by Elsevier Ltd. This is an open access article under the CC BY license ( http://creativecommons.org/licenses/by/4.0/ )Peer reviewe

Day-to-day fasting glycaemic variability in DEVOTE: associations with severe hypoglycaemia and cardiovascular outcomes (DEVOTE 2)

Aims/hypothesis The Trial Comparing Cardiovascular Safety of Insulin Degludec vs Insulin Glargine in Patients with Type 2 Diabetes at High Risk of Cardiovascular Events (DEVOTE) was a double-blind, randomised, event-driven, treat-to-target prospective trial comparing the cardiovascular safety of insulin degludec with that of insulin glargine U100 (100 units/ml) in patients with type 2 diabetes at high risk of cardiovascular events. This paper reports a secondary analysis investigating associations of day-to-day fasting glycaemic variability (pre-breakfast self-measured blood glucose [SMBG]) with severe hypoglycaemia and cardiovascular outcomes. Methods In DEVOTE, patients with type 2 diabetes were randomised to receive insulin degludec or insulin glargine U100 once daily. The primary outcome was the first occurrence of an adjudicated major adverse cardiovascular event (MACE). Adjudicated severe hypoglycaemia was the pre-specified secondary outcome. In this article, day-to-day fasting glycaemic variability was based on the standard deviation of the pre-breakfast SMBG measurements. The variability measure was calculated as follows. Each month, only the three pre-breakfast SMBG measurements recorded before contact with the site were used to determine a day-to-day fasting glycaemic variability measure for each patient. For each patient, the variance of the three log-transformed pre-breakfast SMBG measurements each month was determined. The standard deviation was determined as the square root of the mean of these monthly variances and was defined as day-to-day fasting glycaemic variability. The associations between day-to-day fasting glycaemic variability and severe hypoglycaemia, MACE and all-cause mortality were analysed for the pooled trial population with Cox proportional hazards models. Several sensitivity analyses were conducted, including adjustments for baseline characteristics and most recent HbA1c. Results Day-to-day fasting glycaemic variability was significantly associated with severe hypoglycaemia (HR 4.11, 95% CI 3.15, 5.35), MACE (HR 1.36, 95% CI 1.12, 1.65) and all-cause mortality (HR 1.58, 95% CI 1.23, 2.03) before adjustments. The increased risks of severe hypoglycaemia, MACE and all-cause mortality translate into 2.7-, 1.2- and 1.4-fold risk, respectively, when a patient’s day-to-day fasting glycaemic variability measure is doubled. The significant relationships of day-to-day fasting glycaemic variability with severe hypoglycaemia and all-cause mortality were maintained after adjustments. However, the significant association with MACE was not maintained following adjustment for baseline characteristics with either baseline HbA1c (HR 1.19, 95% CI 0.96, 1.47) or the most recent HbA1c measurement throughout the trial (HR 1.21, 95% CI 0.98, 1.49). Conclusions/interpretation Higher day-to-day fasting glycaemic variability is associated with increased risks of severe hypoglycaemia and all-cause mortality

Zero Frequency Current Noise for the Double Tunnel Junction Coulomb Blockade

We compute the zero frequency current noise numerically and in several limits analytically for the coulomb blockade problem consisting of two tunnel junctions connected in series. At low temperatures over a wide range of voltages, capacitances, and resistances it is shown that the noise measures the variance in the number of electrons in the region between the two tunnel junctions. The average current, on the other hand, only measures the mean number of electrons. Thus, the noise provides additional information about transport in these devices which is not available from measuring the current alone.Comment: 33 pages, 10 figure

DEVOTE 3: Temporal relationships between severe hypoglycaemia, cardiovascular outcomes and mortality

Aims/hypothesis The double-blind Trial Comparing Cardiovascular Safety of Insulin Degludec vs Insulin Glargine in Patients with Type 2 Diabetes at High Risk of Cardiovascular Events (DEVOTE) assessed the cardiovascular safety of insulin degludec. The incidence and rates of adjudicated severe hypoglycaemia, and all-cause mortality were also determined. This paper reports a secondary analysis investigating associations of severe hypoglycaemia with cardiovascular outcomes and mortality. Methods In DEVOTE, patients with type 2 diabetes were randomised to receive either insulin degludec or insulin glargine U100 (100 units/ml) once daily (between dinner and bedtime) in an event-driven, double-blind, treat-to-target cardiovascular outcomes trial. The primary outcome was the first occurrence of an adjudicated major adverse cardiovascular event (MACE; cardiovascular death, non-fatal myocardial infarction or non-fatal stroke). Adjudicated severe hypoglycaemia was the pre-specified secondary outcome. In the present analysis, the associations of severe hypoglycaemia with both MACE and all-cause mortality was evaluated in the pooled trial population using time-to-event analyses, with severe hypoglycaemia as a time-dependent variable and randomised treatment as a fixed factor. An investigation with interaction terms indicated that the effect of severe hypoglycaemia on the risk of MACE and all-cause mortality were the same for both treatment arms, and so the temporal association for severe hypoglycaemia with subsequent MACE and all-cause mortality is reported for the pooled population. Results There was a non-significant difference in the risk of MACE for individuals who had vs those who had not experienced severe hypoglycaemia during the trial (HR 1.38, 95% CI 0.96, 1.96; p = 0.080) and therefore there was no temporal relationship between severe hypoglycaemia and MACE. There was a significantly higher risk of all-cause mortality for patients who had vs those who had not experienced severe hypoglycaemia during the trial (HR 2.51, 95% CI 1.79, 3.50; p < 0.001). There was a higher risk of all-cause mortality 15, 30, 60, 90, 180 and 365 days after experiencing severe hypoglycaemia compared with not experiencing severe hypoglycaemia in the same time interval. The association between severe hypoglycaemia and all-cause mortality was maintained after adjustment for the following baseline characteristics: age, sex, HbA1c, BMI, diabetes duration, insulin regimen, hepatic impairment, renal status and cardiovascular risk group. Conclusions/interpretation The results from these analyses demonstrate an association between severe hypoglycaemia and all-cause mortality. Furthermore, they indicate that patients who experienced severe hypoglycaemia were particularly at greater risk of death in the short term after the hypoglycaemic episode. These findings indicate that severe hypoglycaemia is associated with higher subsequent mortality; however, they cannot answer the question as to whether severe hypoglycaemia serves as a risk marker for adverse outcomes or whether there is a direct causal effect