Special Censuses: Ruminating About Enumerating?

Information about how and why a city should conduct a special census

Fit to Predict? Ecoinformatics for Predicting the Catchability of a Pelagic Fish in Near Real-Time

The ocean is a dynamic environment inhabited by a diverse array of highly migratory species, many of which are under direct exploitation in targeted fisheries. The timescales of variability in the marine realm coupled with the extreme mobility of ocean-wandering species such as tuna and billfish complicates fisheries management. Developing ecoinformatics solutions that allow for near real-time prediction of the distributions of highly mobile marine species is an important step towards the maturation of dynamic ocean management and ecological forecasting. Using 25 years (1990-2014) of NOAA fisheries\u27 observer data from the California drift gillnet fishery, we model relative probability of occurrence (presence-absence) and catchability (total catch) of broadbill swordfish Xiphias gladius in the California Current System (CCS). Using freely-available environmental datasets and open source software, we explore the physical drivers of regional swordfish distribution. Comparing models built upon remotely-sensed datasets with those built upon a data-assimilative configuration of the Regional Ocean Modelling System (ROMS), we explore trade-offs in model construction and address how physical data can affect predictive performance and operational capacity. Swordfish catchability was found to be highest in deeper waters (\u3e1500m) with surface temperatures in the 14-20 degrees C range, isothermal layer depth (ILD) of 20-40m, positive sea surface height anomalies and during the new moon

Integrating Dynamic Subsurface Habitat Metrics Into Species Distribution Models

Species distribution models (SDMs) have become key tools for describing and predicting species habitats. In the marine domain, environmental data used in modeling species distributions are often remotely sensed, and as such have limited capacity for interpreting the vertical structure of the water column, or are sampled in situ, offering minimal spatial and temporal coverage. Advances in ocean models have improved our capacity to explore subsurface ocean features, yet there has been limited integration of such features in SDMs. Using output from a data-assimilative configuration of the Regional Ocean Modeling System, we examine the effect of including dynamic subsurface variables in SDMs to describe the habitats of four pelagic predators in the California Current System (swordfish Xiphias gladius, blue sharks Prionace glauca, common thresher sharks Alopias vulpinus, and shortfin mako sharks lsurus oxyrinchus). Species data were obtained from the California Drift Gillnet observer program (1997-2017). We used boosted regression trees to explore the incremental improvement enabled by dynamic subsurface variables that quantify the structure and stability of the water column: isothermal layer depth and bulk buoyancy frequency. The inclusion of these dynamic subsurface variables significantly improved model explanatory power for most species. Model predictive performance also significantly improved, but only for species that had strong affiliations with dynamic variables (swordfish and shortfin mako sharks) rather than static variables (blue sharks and common thresher sharks). Geospatial predictions for all species showed the integration of isothermal layer depth and bulk buoyancy frequency contributed value at the mesoscale level (\u3c 100 km) and varied spatially throughout the study domain. These results highlight the utility of including dynamic subsurface variables in SDM development and support the continuing ecological use of biophysical output from ocean circulation models

Priorities for synthesis research in ecology and environmental science

ACKNOWLEDGMENTS We thank the National Science Foundation grant #1940692 for financial support for this workshop, and the National Center for Ecological Analysis and Synthesis (NCEAS) and its staff for logistical support.Peer reviewedPublisher PD

Priorities for synthesis research in ecology and environmental science

ACKNOWLEDGMENTS We thank the National Science Foundation grant #1940692 for financial support for this workshop, and the National Center for Ecological Analysis and Synthesis (NCEAS) and its staff for logistical support.Peer reviewedPublisher PD

CropPol: a dynamic, open and global database on crop pollination

Seventy five percent of the world's food crops benefit from insect pollination. Hence, there has been increased interest in how global change drivers impact this critical ecosystem service. Because standardized data on crop pollination are rarely available, we are limited in our capacity to understand the variation in pollination benefits to crop yield, as well as to anticipate changes in this service, develop predictions, and inform management actions. Here, we present CropPol, a dynamic, open and global database on crop pollination. It contains measurements recorded from 202 crop studies, covering 3,394 field observations, 2,552 yield measurements (i.e. berry weight, number of fruits and kg per hectare, among others), and 47,752 insect records from 48 commercial crops distributed around the globe. CropPol comprises 32 of the 87 leading global crops and commodities that are pollinator dependent. Malus domestica is the most represented crop (32 studies), followed by Brassica napus (22 studies), Vaccinium corymbosum (13 studies), and Citrullus lanatus (12 studies). The most abundant pollinator guilds recorded are honey bees (34.22% counts), bumblebees (19.19%), flies other than Syrphidae and Bombyliidae (13.18%), other wild bees (13.13%), beetles (10.97%), Syrphidae (4.87%), and Bombyliidae (0.05%). Locations comprise 34 countries distributed among Europe (76 studies), Northern America (60), Latin America and the Caribbean (29), Asia (20), Oceania (10), and Africa (7). Sampling spans three decades and is concentrated on 2001-05 (21 studies), 2006-10 (40), 2011-15 (88), and 2016-20 (50). This is the most comprehensive open global data set on measurements of crop flower visitors, crop pollinators and pollination to date, and we encourage researchers to add more datasets to this database in the future. This data set is released for non-commercial use only. Credits should be given to this paper (i.e., proper citation), and the products generated with this database should be shared under the same license terms (CC BY-NC-SA). This article is protected by copyright. All rights reserved

Search for gravitational-lensing signatures in the full third observing run of the LIGO-Virgo network

Gravitational lensing by massive objects along the line of sight to the source causes distortions of gravitational wave-signals; such distortions may reveal information about fundamental physics, cosmology and astrophysics. In this work, we have extended the search for lensing signatures to all binary black hole events from the third observing run of the LIGO--Virgo network. We search for repeated signals from strong lensing by 1) performing targeted searches for subthreshold signals, 2) calculating the degree of overlap amongst the intrinsic parameters and sky location of pairs of signals, 3) comparing the similarities of the spectrograms amongst pairs of signals, and 4) performing dual-signal Bayesian analysis that takes into account selection effects and astrophysical knowledge. We also search for distortions to the gravitational waveform caused by 1) frequency-independent phase shifts in strongly lensed images, and 2) frequency-dependent modulation of the amplitude and phase due to point masses. None of these searches yields significant evidence for lensing. Finally, we use the non-detection of gravitational-wave lensing to constrain the lensing rate based on the latest merger-rate estimates and the fraction of dark matter composed of compact objects

31st Annual Meeting and Associated Programs of the Society for Immunotherapy of Cancer (SITC 2016) : part two

Background The immunological escape of tumors represents one of the main ob- stacles to the treatment of malignancies. The blockade of PD-1 or CTLA-4 receptors represented a milestone in the history of immunotherapy. However, immune checkpoint inhibitors seem to be effective in specific cohorts of patients. It has been proposed that their efficacy relies on the presence of an immunological response. Thus, we hypothesized that disruption of the PD-L1/PD-1 axis would synergize with our oncolytic vaccine platform PeptiCRAd. Methods We used murine B16OVA in vivo tumor models and flow cytometry analysis to investigate the immunological background. Results First, we found that high-burden B16OVA tumors were refractory to combination immunotherapy. However, with a more aggressive schedule, tumors with a lower burden were more susceptible to the combination of PeptiCRAd and PD-L1 blockade. The therapy signifi- cantly increased the median survival of mice (Fig. 7). Interestingly, the reduced growth of contralaterally injected B16F10 cells sug- gested the presence of a long lasting immunological memory also against non-targeted antigens. Concerning the functional state of tumor infiltrating lymphocytes (TILs), we found that all the immune therapies would enhance the percentage of activated (PD-1pos TIM- 3neg) T lymphocytes and reduce the amount of exhausted (PD-1pos TIM-3pos) cells compared to placebo. As expected, we found that PeptiCRAd monotherapy could increase the number of antigen spe- cific CD8+ T cells compared to other treatments. However, only the combination with PD-L1 blockade could significantly increase the ra- tio between activated and exhausted pentamer positive cells (p= 0.0058), suggesting that by disrupting the PD-1/PD-L1 axis we could decrease the amount of dysfunctional antigen specific T cells. We ob- served that the anatomical location deeply influenced the state of CD4+ and CD8+ T lymphocytes. In fact, TIM-3 expression was in- creased by 2 fold on TILs compared to splenic and lymphoid T cells. In the CD8+ compartment, the expression of PD-1 on the surface seemed to be restricted to the tumor micro-environment, while CD4 + T cells had a high expression of PD-1 also in lymphoid organs. Interestingly, we found that the levels of PD-1 were significantly higher on CD8+ T cells than on CD4+ T cells into the tumor micro- environment (p < 0.0001). Conclusions In conclusion, we demonstrated that the efficacy of immune check- point inhibitors might be strongly enhanced by their combination with cancer vaccines. PeptiCRAd was able to increase the number of antigen-specific T cells and PD-L1 blockade prevented their exhaus- tion, resulting in long-lasting immunological memory and increased median survival

A system-wide approach to supporting improvements in seafood production practices and outcomes

Environmental certification and consumer awareness programs are designed to create market incentives for implementing fisheries and aquaculture practices that are more sustainable. Typically focused on particular species and activities, such programs have so far triggered few changes to improve seafood sustainability. Here, we present a conceptual, system-wide fisheries and aquaculture certification program designed to recognize and promote change toward more sustainable and resilient seafood production systems. In contrast to previous efforts, this program concentrates on both ecosystems and various human stakeholders, relies on an adaptive management approach (termed "continual improvement") to enhance outcomes, and considers socioeconomic factors. The goal of this program is to support the restoration and maintenance of healthy ecosystem states and thriving human communities as well as the improvement of whole social-ecological systems

Integrating Dynamic Subsurface Habitat Metrics Into Species Distribution Models

Species distribution models (SDMs) have become key tools for describing and predicting species habitats. In the marine domain, environmental data used in modeling species distributions are often remotely sensed, and as such have limited capacity for interpreting the vertical structure of the water column, or are sampled in situ, offering minimal spatial and temporal coverage. Advances in ocean models have improved our capacity to explore subsurface ocean features, yet there has been limited integration of such features in SDMs. Using output from a data-assimilative configuration of the Regional Ocean Modeling System, we examine the effect of including dynamic subsurface variables in SDMs to describe the habitats of four pelagic predators in the California Current System (swordfish Xiphias gladius, blue sharks Prionace glauca, common thresher sharks Alopias vulpinus, and shortfin mako sharks Isurus oxyrinchus). Species data were obtained from the California Drift Gillnet observer program (1997–2017). We used boosted regression trees to explore the incremental improvement enabled by dynamic subsurface variables that quantify the structure and stability of the water column: isothermal layer depth and bulk buoyancy frequency. The inclusion of these dynamic subsurface variables significantly improved model explanatory power for most species. Model predictive performance also significantly improved, but only for species that had strong affiliations with dynamic variables (swordfish and shortfin mako sharks) rather than static variables (blue sharks and common thresher sharks). Geospatial predictions for all species showed the integration of isothermal layer depth and bulk buoyancy frequency contributed value at the mesoscale level (<100 km) and varied spatially throughout the study domain. These results highlight the utility of including dynamic subsurface variables in SDM development and support the continuing ecological use of biophysical output from ocean circulation models