Specific niche requirements underpin multidecadal range edge stability, but may introduce barriers for climate change adaptation

Aim: To investigate some of the environmental variables underpinning the past and present distribution of an ecosystem engineer near its poleward range edge. Location: >500 locations spanning >7,400 km around Ireland. Methods: We collated past and present distribution records on a known climate change indicator, the reef-forming worm Sabellaria alveolata (Linnaeus, 1767) in a biogeographic boundary region over 182 years (1836–2018). This included repeat sampling of 60 locations in the cooler 1950s and again in the warmer 2000s and 2010s. Using species distribution modelling, we identified some of the environmental drivers that likely underpin S. alveolata distribution towards the leading edge of its biogeographical range in Ireland. Results: Through plotting 981 records of presence and absence, we revealed a discontinuous distribution with discretely bounded sub-populations, and edges that coincide with the locations of tidal fronts. Repeat surveys of 60 locations across three time periods showed evidence of population increases, declines, local extirpation and recolonization events within the range, but no evidence of extensions beyond the previously identified distribution limits, despite decades of warming. At a regional scale, populations were relatively stable through time, but local populations in the cold Irish Sea appear highly dynamic and vulnerable to local extirpation risk. Contemporary distribution data (2013–2018) computed with modelled environmental data identified specific niche requirements which can explain the many distribution gaps, namely wave height, tidal amplitude, stratification index, then substrate type. Main conclusions: In the face of climate warming, such specific niche requirements can create environmental barriers that may prevent species from extending beyond their leading edges. These boundaries may limit a species’ capacity to redistribute in response to global environmental change

Distolambrus maltzami (Miers, 1881) (Brachyura: Parthenopidae) with observed and modelled distribution in the North-east Atlantic

We present the distribution of the parthenopid crab species Distolambrus maltzami from the North-east Atlantic with a first record from UK seas. The distribution of D. maltzami in the Celtic-Biscay area in the eastern Atlantic, is both described based on recent records from survey data and estimated from modelling its environmental niche. The predicted probability of occurrence is greatest in areas with fluctuating tidal currents and water masses that are rich in chlorophyll-a, cold (minimum bottom temperature lower than 10°C) and oxygen-rich. We include a simple key to distinguish the two parthenopid crab species previously encountered in the region and highlight the importance of a multidisciplinary approach to fisheries data collection

A preliminary model of iron fertilisation by baleen whales and Antarctic krill in the Southern Ocean: Sensitivity of primary productivity estimates to parameter uncertainty

International audienceLarge marine animals may play a crucial role in storing and recycling bioavailable iron in surface waters by consuming iron-rich prey and subsequent defecation of iron that is excess to their requirements. This biological recycling of iron could enhance primary productivity in iron-limited waters. However, quantifying the effects of marine animals on ocean primary productivity remains challenging because of a limited understanding of the key biogeochemical processes involved. In this paper, we develop a preliminary model that explores these uncertainties and examines the potential effects of historical populations of blue, fin and humpback whales, and the biomass of Antarctic krill required to support the whale populations, on primary productivity in the Southern Ocean.ăăOur results suggest that, despite conservative estimates for key processes in our model, pre-exploitation populations of blue whales and, to a lesser extent fin and humpback whales, could have contributed to iron recycling, resulting in enhanced phytoplankton production in iron-limited Southern Ocean waters. Iron-rich defecation by un-exploited whale populations in the Southern Ocean, and the biomass Antarctic krill required to support them, could have resulted in a contribution to primary productivity of between 1.5 × 10−4 to 23.4 g C m−2 yr−1 (blue whales), 1.4 × 10−4 to 13.9 g C m−2 yr−1 (fin whales), and 2.4 × 10−5 to 1.7 g C m−2 yr−1 (humpback whales). However, only when all parameter estimates are at their upper limits does there appear to be this significant role for whales in enhancing primary productivity, and thus we need to assess the likelihood of these values arising.ăăThe high degree of uncertainty around the magnitude of these increases in primary productivity is mainly due to our limited quantitative understanding of key biogeochemical processes. To reduce uncertainty regarding the effect of whales on Southern Ocean primary productivity, future research will need to refine our understanding of five influential model parameters: iron content in krill; krill consumption rates by whales; persistence of whale faecal iron in the photic zone; bioavailability of this retained iron; and the carbon-to-iron ratio of phytoplankton

Subtidal Microphytobenthos: A Secret Garden Stimulated by the Engineer Species Crepidula fornicata

The slipper limpet Crepidula fornicata is an emblematic invasive species along the northeast Atlantic coast. This gregarious gastropod lives in stacks of several individuals and forms extended beds in shallow subtidal areas. The effects of this engineer species on the colonized habitat can be physical (e.g., presence of hard-shell substrates with uneven topography) or biological (e.g., nutrient enrichment by direct excretion or via biodeposition). We hypothesized that through biological activity, nutrient fluxes at the sediment-water interface are enhanced, leading to stimulated primary productivity by microphytobenthos (MPB) associated with Crepidula beds. To test this fertilization hypothesis, we conducted a 10-day mesocosm experiment using C. fornicata (live and dead) placed on top of sieved and homogenized sediment collected in situ. We used hyperspectral imaging to non-invasively map the development of MPB biomass, and to assess the potential influence of C. fornicata and its spatial extent. Our results showed that live C. fornicata significantly promote MPB growth through both physical and biological effects, with the biological effect dominating over the pure physical one. The highest stimulation was observed on the shells, suggesting that dissolved metabolic products excreted by C. fornicata were likely the main factor stimulating MPB growth in our short-term experiment. Our findings provide first direct evidence that stimulation of MPB growth by the biological activity of larger benthic epifauna occurs not only in intertidal but also in shallow subtidal habitats. More research is needed to assess the contribution of this fertilization effect to the trophic functioning of subtidal benthic systems

Applying landscape metrics to species distribution model predictions to characterize internal range structure and associated changes

Distributional shifts in species ranges provide critical evidence of ecological responses to climate change. Assessments of climate-driven changes typically focus on broad-scale range shifts (e.g. poleward or upward), with ecological consequences at regional and local scales commonly overlooked. While these changes are informative for species presenting continuous geographic ranges, many species have discontinuous distributions—both natural (e.g. mountain or coastal species) or human-induced (e.g. species inhabiting fragmented landscapes)—where within-range changes can be significant. Here, we use an ecosystem engineer species (Sabellaria alveolata) with a naturally fragmented distribution as a case study to assess climate-driven changes in within-range occupancy across its entire global distribution. To this end, we applied landscape ecology metrics to outputs from species distribution modelling (SDM) in a novel unified framework. SDM predicted a 27.5% overall increase in the area of potentially suitable habitat under RCP 4.5 by 2050, which taken in isolation would have led to the classification of the species as a climate change winner. SDM further revealed that the latitudinal range is predicted to shrink because of decreased habitat suitability in the equatorward part of the range, not compensated by a poleward expansion. The use of landscape ecology metrics provided additional insights by identifying regions that are predicted to become increasingly fragmented in the future, potentially increasing extirpation risk by jeopardising metapopulation dynamics. This increased range fragmentation could have dramatic consequences for ecosystem structure and functioning. Importantly, the proposed framework—which brings together SDM and landscape metrics—can be widely used to study currently overlooked climate-driven changes in species internal range structure, without requiring detailed empirical knowledge of the modelled species. This approach represents an important advancement beyond predictive envelope approaches and could reveal itself as paramount for managers whose spatial scale of action usually ranges from local to regional

Integrated modelling to support decision-making for marine social-ecological systems in Australia

Policy- and decision-makers require assessments of status and trends for marine species, habitats, and ecosystems to understand if human activities in the marine environment are sustainable, particularly in the face of global change. Central to many assessments are statistical and dynamical models of populations, communities, ecosystems, and their socioeconomic systems and management frameworks. The establishment of a national system that could facilitate the development of such model-based assessments has been identified as a priority for addressing management challenges for Australia's marine environment. Given that most assessments require cross-scale information, individual models cannot capture all of the spatial, temporal, biological, and socioeconomic scales that are typically needed. Coupling or integrating models across scales and domains can expand the scope for developing comprehensive and internally consistent, system-level assessments, including higher-level feedbacks in social-ecological systems. In this article, we summarize: (i) integrated modelling for marine systems currently being undertaken in Australia, (ii) methods used for integration and comparison of models, and (iii) improvements to facilitate further integration, particularly with respect to standards and specifications. We consider future needs for integrated modelling of marine social-ecological systems in Australia and provide a set of recommendations for priority focus areas in the development of a national approach to integrated modelling. These recommendations draw on-and have broader relevance for-international efforts around integrated modelling to inform decision-making for marine systems

Specific niche requirements underpin multidecadal range edge stability, but may introduce barriers for climate change adaptation

Aim To investigate some of the environmental variables underpinning the past and present distribution of an ecosystem engineer near its poleward range edge. Location >500 locations spanning >7,400 km around Ireland. Methods We collated past and present distribution records on a known climate change indicator, the reef‐forming worm Sabellaria alveolata (Linnaeus, 1767) in a biogeographic boundary region over 182 years (1836–2018). This included repeat sampling of 60 locations in the cooler 1950s and again in the warmer 2000s and 2010s. Using species distribution modelling, we identified some of the environmental drivers that likely underpin S. alveolata distribution towards the leading edge of its biogeographical range in Ireland. Results Through plotting 981 records of presence and absence, we revealed a discontinuous distribution with discretely bounded sub‐populations, and edges that coincide with the locations of tidal fronts. Repeat surveys of 60 locations across three time periods showed evidence of population increases, declines, local extirpation and recolonization events within the range, but no evidence of extensions beyond the previously identified distribution limits, despite decades of warming. At a regional scale, populations were relatively stable through time, but local populations in the cold Irish Sea appear highly dynamic and vulnerable to local extirpation risk. Contemporary distribution data (2013–2018) computed with modelled environmental data identified specific niche requirements which can explain the many distribution gaps, namely wave height, tidal amplitude, stratification index, then substrate type. Main conclusions In the face of climate warming, such specific niche requirements can create environmental barriers that may prevent species from extending beyond their leading edges. These boundaries may limit a species’ capacity to redistribute in response to global environmental change

A Novel 8-Predictors Signature to Predict Complicated Disease Course in Pediatric-onset Crohn’s Disease: A Population-based Study

International audienceBackground The identification of patients at high risk of a disabling disease course would be invaluable in guiding initial therapy in Crohn’s disease (CD). Our objective was to evaluate a combination of clinical, serological, and genetic factors to predict complicated disease course in pediatric-onset CD. Methods Data for pediatric-onset CD patients, diagnosed before 17 years of age between 1988 and 2004 and followed more than 5 years, were extracted from the population-based EPIMAD registry. The main outcome was defined by the occurrence of complicated behavior (stricturing or penetrating) and/or intestinal resection within the 5 years following diagnosis. Lasso logistic regression models were used to build a predictive model based on clinical data at diagnosis, serological data (ASCA, pANCA, anti-OmpC, anti-Cbir1, anti-Fla2, anti-Flax), and 369 candidate single nucleotide polymorphisms. Results In total, 156 children with an inflammatory (B1) disease at diagnosis were included. Among them, 35% (n = 54) progressed to a complicated behavior or an intestinal resection within the 5 years following diagnosis. The best predictive model (PREDICT-EPIMAD) included the location at diagnosis, pANCA, and 6 single nucleotide polymorphisms. This model showed good discrimination and good calibration, with an area under the curve of 0.80 after correction for optimism bias (sensitivity, 79%, specificity, 74%, positive predictive value, 61%, negative predictive value, 87%). Decision curve analysis confirmed the clinical utility of the model. Conclusions A combination of clinical, serotypic, and genotypic variables can predict disease progression in this population-based pediatric-onset CD cohort. Independent validation is needed before it can be used in clinical practice

Predicting missing biomarker data in a longitudinal study of Alzheimer disease

Objective:To investigate predictors of missing data in a longitudinal study of Alzheimer disease (AD).Methods:The Alzheimer's Disease Neuroimaging Initiative (ADNI) is a clinic-based, multicenter, longitudinal study with blood, CSF, PET, and MRI scans repeatedly measured in 229 participants with normal cognition (NC), 397 with mild cognitive impairment (MCI), and 193 with mild AD during 2005–2007. We used univariate and multivariable logistic regression models to examine the associations between baseline demographic/clinical features and loss of biomarker follow-ups in ADNI.Results:CSF studies tended to recruit and retain patients with MCI with more AD-like features, including lower levels of baseline CSF Aβ42. Depression was the major predictor for MCI dropouts, while family history of AD kept more patients with AD enrolled in PET and MRI studies. Poor cognitive performance was associated with loss of follow-up in most biomarker studies, even among NC participants. The presence of vascular risk factors seemed more critical than cognitive function for predicting dropouts in AD.Conclusion:The missing data are not missing completely at random in ADNI and likely conditional on certain features in addition to cognitive function. Missing data predictors vary across biomarkers and even MCI and AD groups do not share the same missing data pattern. Understanding the missing data structure may help in the design of future longitudinal studies and clinical trials in AD