Strengthening confidence in climate change impact science

Aim: To assess confidence in conclusions about climate-driven biological change through time, and identify approaches for strengthening confidence scientific conclusions about ecological impacts of climate change. Location: Global. Methods: We outlined a framework for strengthening confidence in inferences drawn from biological climate impact studies through the systematic integration of prior expectations, long-term data and quantitative statistical procedures. We then developed a numerical confidence index (Cindex) and used it to evaluate current practices in 208 studies of marine climate impacts comprising 1735 biological time series. Results: Confidence scores for inferred climate impacts varied widely from 1 to 16 (very low to high confidence). Approximately 35% of analyses were not associated with clearly stated prior expectations and 65% of analyses did not test putative non-climate drivers of biological change. Among the highest-scoring studies, 91% tested prior expectations, 86% formulated expectations for alternative drivers but only 63% statistically tested them. Higher confidence scores observed in studies that did not detect a change or tracked multiple species suggest publication bias favouring impact studies that are consistent with climate change. The number of time series showing climate impacts was a poor predictor of average confidence scores for a given group, reinforcing that vote-counting methodology is not appropriate for determining overall confidence in inferences. Main conclusions: Climate impacts research is expected to attribute biological change to climate change with measurable confidence. Studies with long-term, high-resolution data, appropriate statistics and tests of alternative drivers earn higher Cindex scores, suggesting these should be given greater weight in impact assessments. Together with our proposed framework, the results of our Cindex analysis indicate how the science of detecting and attributing biological impacts to climate change can be strengthened through the use of evidence-based prior expectations and thorough statistical analyses, even when data are limited, maximizing the impact of the diverse and growing climate change ecology literature

Prevention of Wear Particle-Induced Osteolysis by a Novel V-ATPase Inhibitor Saliphenylhalamide through Inhibition of Osteoclast Bone Resorption

Wear particle-induced peri-implant loosening (Aseptic prosthetic loosening) is one of the most common causes of total joint arthroplasty. It is well established that extensive bone destruction (osteolysis) by osteoclasts is responsible for wear particle-induced peri-implant loosening. Thus, inhibition of osteoclastic bone resorption should prevent wear particle induced osteolysis and may serve as a potential therapeutic avenue for prosthetic loosening. Here, we demonstrate for the first time that saliphenylhalamide, a new V-ATPase inhibitor attenuates wear particle-induced osteolysis in a mouse calvarial model. In vitro biochemical and morphological assays revealed that the inhibition of osteolysis is partially attributed to a disruption in osteoclast acidification and polarization, both a prerequisite for osteoclast bone resorption. Interestingly, the V-ATPase inhibitor also impaired osteoclast differentiation via the inhibition of RANKL-induced NF-κB and ERK signaling pathways. In conclusion, we showed that saliphenylhalamide affected multiple physiological processes including osteoclast differentiation, acidification and polarization, leading to inhibition of osteoclast bone resorption in vitro and wear particle-induced osteolysis in vivo. The results of the study provide proof that the new generation V-ATPase inhibitors, such as saliphenylhalamide, are potential anti-resorptive agents for treatment of peri-implant osteolysis

A global database of dissolved organic matter (DOM) concentration measurements in coastal waters (CoastDOM v1)

Measurements of dissolved organic carbon (DOC), nitrogen (DON), and phosphorus (DOP) con-centrations are used to characterize the dissolved organic matter (DOM) pool and are important components ofbiogeochemical cycling in the coastal ocean. Here, we present the first edition of a global database (CoastDOMv1; available at https://doi.org/10.1594/PANGAEA.964012, L\uf8nborg et al., 2023) compiling previously pub-lished and unpublished measurements of DOC, DON, and DOP in coastal waters. These data are complementedby hydrographic data such as temperature and salinity and, to the extent possible, other biogeochemical variables(e.g. chlorophyll a, inorganic nutrients) and the inorganic carbon system (e.g. dissolved inorganic carbon andtotal alkalinity). Overall, CoastDOM v1 includes observations of concentrations from all continents. However,most data were collected in the Northern Hemisphere, with a clear gap in DOM measurements from the SouthernHemisphere. The data included were collected from 1978 to 2022 and consist of 62 338 data points for DOC,20 356 for DON, and 13 533 for DOP. The number of measurements decreases progressively in the sequenceDOC > DON > DOP, reflecting both differences in the maturity of the analytical methods and the greater focuson carbon cycling by the aquatic science community. The global database shows that the average DOC concen-tration in coastal waters (average \ub1 standard deviation (SD): 182 \ub1 314 μmol C L−1; median: 103 μmol C L−1) is13-fold higher than the average coastal DON concentration (13.6 \ub1 30.4 μmol N L−1; median: 8.0 μmol N L−1),which is itself 39-fold higher than the average coastal DOP concentration (0.34 \ub1 1.11 μmol P L−1; median:0.18 μmol P L−1). This dataset will be useful for identifying global spatial and temporal patterns in DOM and willhelp facilitate the reuse of DOC, DON, and DOP data in studies aimed at better characterizing local biogeochem-ical processes; closing nutrient budgets; estimating carbon, nitrogen, and phosphorous pools; and establishing abaseline for modelling future changes in coastal waters

Temperature dependence of CO2-enhanced primary production in the European Arctic Ocean

The Arctic Ocean is warming at two to three times the global rate1 and is perceived to be a bellwether for ocean acidification2, 3. Increased CO2 concentrations are expected to have a fertilization effect on marine autotrophs4, and higher temperatures should lead to increased rates of planktonic primary production5. Yet, simultaneous assessment of warming and increased CO2 on primary production in the Arctic has not been conducted. Here we test the expectation that CO2-enhanced gross primary production (GPP) may be temperature dependent, using data from several oceanographic cruises and experiments from both spring and summer in the European sector of the Arctic Ocean. Results confirm that CO2 enhances GPP (by a factor of up to ten) over a range of 145–2,099 μatm; however, the greatest effects are observed only at lower temperatures and are constrained by nutrient and light availability to the spring period. The temperature dependence of CO2-enhanced primary production has significant implications for metabolic balance in a warmer, CO2-enriched Arctic Ocean in the future. In particular, it indicates that a twofold increase in primary production during the spring is likely in the Arctic

Perceptual Load-Dependent Neural Correlates of Distractor Interference Inhibition

The load theory of selective attention hypothesizes that distractor interference is suppressed after perceptual processing (i.e., in the later stage of central processing) at low perceptual load of the central task, but in the early stage of perceptual processing at high perceptual load. Consistently, studies on the neural correlates of attention have found a smaller distractor-related activation in the sensory cortex at high relative to low perceptual load. However, it is not clear whether the distractor-related activation in brain regions linked to later stages of central processing (e.g., in the frontostriatal circuits) is also smaller at high rather than low perceptual load, as might be predicted based on the load theory.We studied 24 healthy participants using functional magnetic resonance imaging (fMRI) during a visual target identification task with two perceptual loads (low vs. high). Participants showed distractor-related increases in activation in the midbrain, striatum, occipital and medial and lateral prefrontal cortices at low load, but distractor-related decreases in activation in the midbrain ventral tegmental area and substantia nigra (VTA/SN), striatum, thalamus, and extensive sensory cortices at high load.Multiple levels of central processing involving midbrain and frontostriatal circuits participate in suppressing distractor interference at either low or high perceptual load. For suppressing distractor interference, the processing of sensory inputs in both early and late stages of central processing are enhanced at low load but inhibited at high load

Examining the generalizability of research findings from archival data

This initiative examined systematically the extent to which a large set of archival research findings generalizes across contexts. We repeated the key analyses for 29 original strategic management effects in the same context (direct reproduction) as well as in 52 novel time periods and geographies; 45% of the reproductions returned results matching the original reports together with 55% of tests in different spans of years and 40% of tests in novel geographies. Some original findings were associated with multiple new tests. Reproducibility was the best predictor of generalizability—for the findings that proved directly reproducible, 84% emerged in other available time periods and 57% emerged in other geographies. Overall, only limited empirical evidence emerged for context sensitivity. In a forecasting survey, independent scientists were able to anticipate which effects would find support in tests in new samples