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Presents an account of whale watching endeavors in Baja, California, lagoons. (BB)

Mammalian genomes have distinct levels of spatial organization and structure that have been hypothesized to play important roles in transcription regulation. Although much has been learned about these architectural features with ensemble techniques, single-cell studies are showing a new universal trend: Genomes are stochastic and dynamic at every level of organization. Stochastic gene expression, on the other hand, has been studied for years. In this review, we probe whether there is a causative link between the two phenomena. We specifically discuss the functionality of chromatin state, topologically associating domains (TADs), and enhancer biology in light of their stochastic nature and their specific roles in stochastic gene expression. We highlight persistent fundamental questions in this area of research.

Metropolitan Phoenix, Arizona, in the Sonoran Desert, provides an excellent opportunity to understand residents’ preferences for desert-adapted xeric landscaping. While much is known about the relationships between sociodemographics and broad environmental values on xeric landscaping choices, the influence of other variables remains unexplored, especially interactions with and attachments to the desert. We therefore examined the influences of recreational visits to local desert mountain parks and symbolic meanings associated with the native desert on household xeric landscaping preferences. Within a larger study, select questions captured socio-demographics, visitation to desert parks and open spaces, place identity, and xeric landscape preferences. Using Ordinary Least Squares (OLS) regression, we confirmed that homeownership and a shorter residency predicted preference for xeric landscapes. Hispanics were less likely to prefer xeric landscaping. Interestingly, the novel factor of identity with the desert significantly and positively predicted xeric landscaping preference while visitation to desert parks and open spaces did not. Findings provide several important management implications. First, Phoenix has an opportunity to foster connections with the surrounding environment through its extensive desert mountain parks. Increasing connections between residents and the parks may help shift personal preferences to xeric yard types. Park managers might also work to further stress how household decisions can affect the desert environment. Second, park visitation alone may not suffice to create connections with the desert environment. Instead, park managers should focus on creating opportunities for visitors to recognize the unique, living aspects of the parks and build personal relationships with the ecosystem. Interpretation encouraging emotional connections to the desert environment may aid in fostering an identity with the desert. In addition, messaging and signage campaigns that link people to the parks may prove a novel way of combatting lawn water usage within desert cities. Given their opportunities to foster place identity, urban parks may be important influencers in promoting native plant landscaping. In conclusion, connecting people to their surrounding environments can influence preferences for similar landscape types at the household level.

JJL received funding from the Research Foundation Flanders (grant nr. 12P1819N). The project received funding from the Research Foundation Flanders (grants nrs, G018919N, W001919N). JVDH and TWC received funding from DOB Ecology. JA received funding from the University of Helsinki, Faculty of Science (MICROCLIM, grant nr. 7510145) and Academy of Finland Flagship (grant no. 337552). PDF, CM and PV received funding from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (ERC Starting Grant FORMICA 757833). JK received funding from the Arctic Interactions at the University of Oulu and Academy of Finland (318930, Profi 4), Maaja vesitekniikan tuki ry., Tiina and Antti Herlin Foundation, Nordenskiold Samfundet and Societas pro Fauna et Flora Fennica. MK received funding from the Czech Science Foundation (grant nr. 20-28119S) and the Czech Academy of Sciences (grant nr. RVO 67985939). TWC received funding from National Geographic Society grant no. 9480-14 and WW-240R-17. MA received funding from CISSC (program ICRP (grant nr:2397) and INSF (grant nr: 96005914). The Royal Botanic Garden Edinburgh is supported by the Scottish Government's Rural and Environment Science and Analytical Services Division. JMA received funding from the Funding Org. Qatar Petroleum (grant nr. QUEX-CAS-QP-RD-18/19). JMA received funding from the European Union's Horizon 2020 research and innovation program (grant no. 678841) and from the Swiss National Science Foundation (grant no. 31003A_176044). JA was supported by research grants LTAUSA19137 (program INTER-EXCELLENCE, subprogram INTER-ACTION) provided by Czech Ministry of Education, Youth and Sports and 20-05840Y of the Czech Science Foundation. AA was supported by the Ministry of Science and Higher Education of the Russian Federation (grant FSRZ-2020-0014). SN, UAT, JJA, and JvO received funding from the Independent Research Fund Denmark (7027-00133B). LvdB, KT, MYB and RC acknowledge funding from the German Research Foundation within the Priority Program SPP-1803 'EarthShape: Earth Surface Shaping by Biota' (grant TI 338/14-1&2 and BA 3843/6-1). PB was supported by grant project VEGA of the Ministry of Education of the Slovak Republic and the Slovak Academy of Sciences No. 2/0132/18. Forest Research received funding from the Forestry Commission (climate change research programme). JCB acknowledges the support of Universidad Javeriana. JLBA received funding from the Direccion General de Cambio Climatico del Gobierno de Aragon; JLBA acknowledges fieldwork assistance by Ana Acin, the Ordesa y Monte Perdido National Park, and the Servicio de Medio Ambiente de Soria de la Junta de Castilla y Leon. RGB and MPB received funding from BECC - Biodiversity and Ecosystem services in a Changing Climate. MPB received funding from The European Union's Horizon 2020 research and innovation program under the Marie Skodowska-Curie Grant Agreement No. 657627 and The Swedish Research Council FORMAS - future research leaders No. 2016-01187. JB received funding from the Czech Academy of Sciences (grant nr. RVO 67985939). NB received funding from the SNF (grant numbers 40FA40_154245, 20FI21_148992, 20FI20_173691, 407340_172433) and from the EU (contract no. 774124). ICOS EU research infrastructure. EU FP7 NitroEurope. EU FP7 ECLAIRE. The authors from Biological Dynamics of Forest Fragments Project, PDBFF, Instituto Nacional de Pesquisas da Amazonia, Brazil were supported by the MCTI/CNPq/FNDCT - AcAo Transversal no68/2013 - Programa de Grande Escala da Biosfera-Atmosfera na Amazonia - LBA; Project 'Como as florestas da Amazonia Central respondem as variacoes climaticas? Efeitos sobre dinamica florestal e sinergia com a fragmentacAo florestal'. This is the study 829 of the BDFFP Technical Series. to The EUCFLUX Cooperative Research Program and Forest Science and Research Institute-IPEF. NC acknowledges funding by Stelvio National Park. JC was funded by the Spanish government grant CGL2016-78093-R. ANID-FONDECYT 1181745 AND INSTITUTO ANTARTICO CHILENO (INACH FR-0418). SC received funding from the German Research Foundation (grant no. DFG- FZT 118, 202548816). The National Science Foundation, Poland (grant no. UMO-2017/27/B/ST10/02228), within the framework of the 'Carbon dioxide uptake potential of sphagnum peatlands in the context of atmospheric optical parameters and climate changes' (KUSCO2) project. SLC received funding from the South African National Research Foundation and the Australian Research Council. FM, M, KU and MU received funding from Slovak Research and Development Agency (no. APVV-19-0319). Instituto Antartico Chileno (INACH_RT-48_16), Iniciativa Cientifica Milenio Nucleo Milenio de Salmonidos Invasores INVASAL, Institute of Ecology and Biodiversity (IEB), CONICYT PIA APOYO CCTE AFB170008. PC is supported by NERC core funding to the BAS 'Biodiversity, Evolution and Adaptation Team. EJC received funding from the Norwegian Research Council (grant number 230970). GND was supported by NERC E3 doctoral training partnership grant (NE/L002558/1) at the University of Edinburgh and the Carnegie Trust for the Universities of Scotland. Monitoring stations on Livingston Island, Antarctica, were funded by different research projects of the Gobern of Spain (PERMAPLANET CTM2009-10165-E; ANTARPERMA CTM2011-15565-E; PERMASNOW CTM2014-52021-R), and the PERMATHERMAL arrangement between the University of Alcala and the Spanish Polar Committee. GN received funding from the Autonomous Province of Bolzano (ITA). The infrastructure, part of the UK Environmental Change Network, was funded historically in part by ScotNature and NERC National Capability LTS-S: UK-SCAPE; NE/R016429/1). JD was supported by the Czech Science Foundation (GA17-19376S) and MSMT (LTAUSA18007). ED received funding from the Kempe Foundation (JCK-1112 and JCK-1822). The infrastructure was supported by the Ministry of Education, Youth and Sports of the Czech Republic within the National Sustainability Programme I (NPU I), grant number LO1415 and by the project for national infrastructure support CzeCOS/ICOS Reg. No. LM2015061. NE received funding from the German Research Foundation (DFG- FZT 118, 202548816). BE received funding from the GLORIA-EU project no EVK2-CT2000-00056, the Autonomous Province of Bolzano (ITA), from the Tiroler Wissenschaftsfonds and from the University of Innsbruck. RME was supported by funding to the SAFE Project from the Sime Darby Foundation. OF received funding from the German Research Foundation (DFG- FZT 118, 202548816). EFP was supported by the Jardin Botanico Atlantico (SV-20-GIJON-JBA). MF was funded by the German Federal Ministry of Education and Research (BMBF) in the context of The Future Okavango (Grant No. 01LL0912) and SASSCAL (01LG1201M; 01LG1201N) projects. EFL received funding from ANID PIA / BASAL FB210006. RAG received funding from Fondecyt 11170516, CONICYT PIA AFB170008 and ANID PIA / BASAL FB210006. MBG received funding from National Parks (DYNBIO, #1656/2015) and The Spanish Research Agency (VULBIMON, #CGL2017-90040-R). MG received funding from the Swiss National Science Foundation (ICOS-CH Phase 2 20FI20_173691). FG received funding from the German Research Foundation (DFG- FZT 118, 202548816). KG and TS received funding from the UK Biotechnology and Biological Research Council (grant = 206/D16053). SG was supported by the Research Foundation Flanders (FWO) (project G0H1517N). KJ and PH received funding from the EU Horizon2020 INFRAIA project eLTER-PLUS (871128), the project LTER-CWN (FFG, F&E Infrastrukturforderung, project number 858024) and the Austrian Climate Research Program (ACRP7 - CentForCSink - KR14AC7K11960). SH and ARB received funding through iDiv funded by the German Research Foundation (DFG- FZT 118, 202548816). LH received funding from the Czech Science Foundation (grant nr. 20-28119S) and the Czech Academy of Sciences (grant nr. RVO 67985939). MH received funding from the Baden-Wurttemberg Ministry of Science, Research and Arts via the project DRIeR (Drought impacts, processes and resilience: making the in-visible visible). LH received funding from International Polar Year, Weston Foundation, and ArcticNet. DH received funding from Natural Sciences and Engineering Council (Canada) (RGPIN-06691). TTH received funding from Independent Research Fund Denmark (grant no. 8021-00423B) and Villum Foundation (grant no. 17523). Ministry of Education, Youth and Sports of the Czech Republic (projects LM2015078, VAN2020/01 and CZ.02.1.01/0.0/0.0/16_013/0001708). KH, CG and CJD received funding from Bolin Centre for Climate Research, Stockholm University and from the Swedish research council Formas [grant n:o 2014-00530 to KH]. JJ received funding from the Funding Org. Swedish Forest Society Foundation (grant nr. 2018-485-Steg 2 2017) and Swedish Research Council FORMAS (grant nr. 2018-00792). AJ received funding from the German Federal Ministry of Education and Research BMBF (Grant Nr. FKZ 031B0516C SUSALPS) and the Oberfrankenstiftung (Grant Nr. OFS FP00237). ISJ received funding from the Energy Research Fund (NYR-11 - 2019, NYR-18 - 2020). TJ was supported by a UK NERC Independent Research Fellowship (grant number: NE/S01537X/1). RJ received funding from National Science Centre of Poland (grant number: 2016/21/B/ST10/02271) and Polish National Centre for Research and Development (grant number: Pol-Nor/203258/31/2013). VK received funding from the Czech Academy of Sciences (grant nr. RVO 67985939). AAK received funding from MoEFCC, Govt of India (AICOPTAX project F. No. 22018/12/2015/RE/Tax). NK received funding from FORMAS (grants nr. 2018-01781, 2018-02700, 2019-00836), VR, support from the research infrastructure ICOS-SE. BK received funding from the National Research, Development and Innovation Fund of Hungary (grant nr. K128441). Ministry of Education, Youth and Sports of the Czech Republic (projects LM2015078 and CZ.02.1.01/0.0/0.0/16_013/0001708). Project B1-RNM-163-UGR-18-Programa Operativo FEDER 2018, partially funded data collection. Norwegian Research Council (NORKLIMA grants #184912 and #244525) awarded to Vigdis Vandvik. MM received funding from the Czech Science Foundation (grant nr. 20-28119S) and the Czech Academy of Sciences (grant nr. RVO 67985939). Project CONICYT-PAI 79170119 and ANID-MPG 190029 awarded to Roy Mackenzie. This work was partly funded by project MIUR PON Cluster OT4CLIMA. RM received funding from the SNF project number 407340_172433. FM received funding from the Stelvio National Park. PM received funding from AIAS-COFUND fellowship programme supported by the Marie Skodowska- Curie actions under the European Union's Seventh Framework Pro-gramme for Research, Technological development and Demonstration (grant agreement no 609033) and the Aarhus University Research Foundation, Denmark. RM received funding from the Ministry of Education, Youth and Sports of the Czech Republic (project LTT17033). SM and VM received funding from EU FP6 NitroEurope (grant nr. 17841), EU FP7 ECLAIRE (grant nr. 282910), the Ministry of Education and Science of Ukraine (projects nr. 505, 550, 574, 602), GEF-UNEP funded "Toward INMS" project (grant nr. NEC05348) and ENI CBC BSB PONTOS (grant nr. BSB 889). The authors from Biological Dynamics of Forest Fragments Project, PDBFF, Instituto Nacional de Pesquisas da Amazonia, Brazil were supported by the MCTI/CNPq/FNDCT - AcAo Transversal no68/2013 - Programa de Grande Escala da Biosfera-Atmosfera na Amazonia - LBA; Project 'Como as florestas da Amazonia Central respondem as variacoes climaticas? Efeitos sobre dinamica florestal e sinergia com a fragmentacAo florestal'. FJRM was financially supported by the Netherlands Organization for Scientific Research (VICI grant 016.VICI.170.072) and Research Foundation Flanders (FWO-SBO grant S000619N). STM received funding from New Frontiers in Research Fund-Exploration (grant nr. NFRF-2018-02043) and NSERC Discovery. MMR received funding from the Australian Research Council Discovery Early Career Research Award (grant nr. DE180100570). JAM received funding from the National Science Foundation (DEB 1557094), International Center for Advanced Renewable Energy and Sustainability (I-CARES) at Washington University in St. Louis, ForestGEO, and Tyson Research Center. IM-S was funded by the UK Natural Environment Research Council through the ShrubTundra Project (NE/M016323/1). MBN received funding from FORMAS, VR, Kempe Foundations support from the research infrastructures ICOS and SITES. MDN received funding from CONICET (grant nr. PIP 112-201501-00609). Spanish Ministry of Science grant PID2019-110521GB-I00 and Catalan government grant 2017-1005. French National Research Agency (ANR) in the frame of the Cluster of Excellence COTE (project HydroBeech, ANR-10-LABX-45). VLIR-OUS, under the Institutional University Coorperation programme (IUC) with Mountains of the Moon University. Project LAS III 77/2017/B entitled: \"Estimation of net carbon dioxide fluxes exchanged between the forest ecosystem on post-agricultural land and between the tornado-damaged forest area and the atmosphere using spectroscopic and numerical methods\", source of funding: General Directorate of State Forests, Warsaw, Poland. Max Planck Society (Germany), RFBR, Krasnoyarsk Territory and Krasnoyarsk Regional Fund of Science, project number 20-45-242908. Estonian Research Council (PRG609), and the European Regional Development Fund (Centre of Excellence EcolChange). Canada-Denmark Arctic Research Station Early Career Scientist Exchange Program, from Polar knowledge Canada (POLAR) and the Danish Agency for Science and Higher Education. AP received funding from Fondecyt 1180205, CONICYT PIA AFB170008 and ANID PIA / BASAL FB210006. MP received funding from the Funding Org. Knut and Alice Wallenberg Foundation (grant nr. 2015.0047), and acknowledges funding from the Swedish Research Council (VR) with contributing research institutes to both the SITES and ICOS Sweden infrastructures. JP and RO were funded by the Spanish Ministry of Science grant PID2019-110521GB-I00, the fundacion Ramon Areces grant ELEMENTAL-CLIMATE, and the Catalan government grant 2017-1005. MPB received funding from the Svalbard Environmental Protection Fund (grant project number 15/128) and the Research Council of Norway (Arctic Field Grant, project number 269957). RP received funding from the Ministry of Education, Youth and Sports of the Czech Republic (grant INTER-TRANSFER nr. LTT20017). LTSER Zone Atelier Alpes; Federation FREE-Alpes. RP received funding from a Humboldt Fellowship for Experienced Researchers. Prokushkin AS and Zyryanov VI contribution has been supported by the RFBR grant #18-05-60203-Arktika. RPu received founding from the Polish National Science Centre (grant project number 2017/27/B/NZ8/00316). ODYSSEE project (ANR-13-ISV7-0004, PN-II-ID-JRP-RO-FR-2012). KR was supported through an Australian Government Research Training Program Scholarship. Fieldwork was supported by the Global Challenges program at the University of Wollongong, the ARC the Australian Antarctic Division and INACH. DR was funded by the project SUBANTECO IPEV 136 (French Polar Institute Paul-Emile Victor), Zone Atelier CNRS Antarctique et Terres Australes, SAD Region Bretagne (Project INFLICT), BiodivERsa 2019-2020 BioDivClim call 'ASICS' (ANR-20-EBI5-0004). SAR received funding from the Australian Research Council. NSF grant #1556772 to the University of Notre Dame. Pavia University (Italy). OR received funding from EU-LEAP-Agri (RAMSES II), EU-DESIRA (CASSECS), EU-H2020 (SustainSahel), AGROPOLIS and TOTAL Foundations (DSCATT), CGIAR (GLDC). AR was supported by the Russian Science Foundation (Grant 18-74-10048). Parc national des Ecrins. JS received funding from Vetenskapsradet grant nr (No: 2014-04270), ALTER-net multi-site grant, River LIFE project (LIFE08 NAT/S/000266), Flexpeil. Helmholtz Association long-term research program TERENO (Terrestrial Environmental Observatories). PS received funding from the Polish Ministry of Science and Higher Education (grant nr. N N305 304840). AS acknowledges funding by ETH Zurich project FEVER ETH-27 19-1. LSC received funding from NSERC Canada Graduate Scholarship (Doctoral) Program; LSC was also supported by ArcticNet-NCE (insert grant #). Conselho Nacional de Desenvolvimento Cientifico e Tecnologico (141513/2017-9); FundacAo Carlos Chagas Filho de Amparo a Pesquisa do Estado do Rio de Janeiro (E26/200.84/2019). ZS received funding from the SRDA (grants nos. APVV-16-0325 and APVV-20-0365) and from the ERDF (grant no. ITMS 313011S735, CE LignoSilva). JS, MB and CA received funding from core budget of ETH Zurich. State excellence Program M-V \"WETSCAPES\". AfricanBioServices project funded by the EU Horizon 2020 grant number 641918. The authors from KIT/IMK-IFU acknowledge the funding received within the German Terrestrial Environmental Observatories (TERENO) research program of the Helmholtz Association and from the Bavarian Ministry of the Environment and Public Health (UGV06080204000). Deutsche Forschungsgemeinschaft (DFG, German Research Foundation), project number 192626868, in the framework of the collaborative German-Indonesian research project CRC 990 (SFB): 'EFForTS, Ecological and Socioeconomic Functions of Tropical Lowland Rainforest Transformation Systems (Sumatra, Indonesia)'. MS received funding from the Ministry of Education, Youth and Sports of the Czech Republic (grant nr. INTER-TRANSFER LTT19018). TT received funding from the Swedish National Space Board (SNSB Dnr 95/16) and the CASSECS project supported by the European Union. HJDT received funding from the UK Natural Environment Research Council (NERC doctoral training partnership grant NE/L002558/1). German Science Foundation (DFG) GraKo 2010 \"Response\". PDT received funding from the MEMOIRE project (PN-III-P1-1.1-PD2016-0925). Arctic Challenge for Sustainability II (ArCS II; JPMXD1420318865). JU received funding from Czech Science Foundation (grant nr. 21-11487S). TU received funding from the Romanian Ministry of Education and Research (CCCDI - UEFISCDI -project PN-III-P2-2.1-PED-2019-4924 and PN2019-2022/19270201-Ctr. 25N BIODIVERS 3-BIOSERV). AV acknowledge funding from RSF, project 21-14-00209. GFV received funding from the Dutch Research Council NWO (Veni grant, no. 863.14.013). Australian Research Council Discovery Early Career Research Award DE140101611. FGAV received funding from the Portuguese Science Foundation (FCT) under CEECIND/02509/2018, CESAM (UIDP/50017/2020+UIDB/50017/2020), FCT/MCTES through national funds, and the co-funding by the FEDER, within the PT2020 Partnership Agreement and Compete 2020. Ordesa y Monte Perdido National Park. MVI received funding from the Spanish Ministry of Science and Innovation through a doctoral grant (FPU17/05869). JW received funding from the Czech Science Foundation (grant nr. 20-28119S) and the Czech Academy of Sciences (grant nr. RVO 67985939). CR and SW received funding from the Swiss Federal Office for the Environment (FOEN) and the de Giacomi foundation. YY received funding from the National Natural Science Foundation of China (Grant no. 41861134039 and 41941015). ZY received funding from the National Natural Science Foundation of China (grant nr. 41877458). FZ received funding from the Swiss National Science Foundation (grant nr. 172198 and 193645). PZ received funding from the Funding Org. Knut and Alice Wallenberg Foundation (grant no. 2015.0047). JL received funding from (i) the Agence Nationale de la Recherche (ANR), under the framework of the young investigators (JCJC) funding instrument (ANR JCJC Grant project NoANR-19-CE32-0005-01: IMPRINT) (ii) the Centre National de la Recherche Scientifique (CNRS) (Defi INFINITI 2018: MORFO); and the Structure Federative de Recherche (SFR) Condorcet (FR CNRS 3417: CREUSE). Fieldwork in the Arctic got facilitated by funding from the EU INTERACT program. SN, UAT, JJA and JvO would like to thank the field team of the Vegetation Dynamics group for their efforts and hard work. We acknowledge Dominique Tristan for letting access to the field. For the logistic support the crew of INACH and Gabriel de Castilla Station team on Deception Island. We thank the Inuvialuit and Kluane First Nations for the opportunity to work on their land. MAdP acknowledges fieldwork assistance and logistics support to Unidad de Tecnologia Marina CSIC, and the crew of Juan Carlos I and Gabriel de Castilla Spanish Antarctic Stations, as well as to the different colleagues from UAH that helped on the instrument maintenance. ERF acknowledges fieldwork assistance by Martin Heggli. MBG acknowledges fieldwork and technical assistance by P Abadia, C Benede, P Bravo, J Gomez, M Grasa, R Jimenez, H Miranda, B Ponz, J Revilla and P Tejero and the Ordesa and Monte Perdido National Park staff. LH acknowledges field assistance by John Jacobs, Andrew Trant, Robert Way, Darroch Whitaker; we acknowledge the Inuit of Nunatsiavut, and the Co-management Board of Torngat Mountains National Park for their support of this project and acknowledge that the field research was conducted on their traditional lands. We thank our many bear guides, especially Boonie, Eli, Herman, John and Maria Merkuratsuk. AAK acknowledges field support of Akhtar Malik, Rameez Ahmad. Part of microclimatic records from Saxony was funded by the Saxon Switzerland National Park Administration. Tyson Research Center. JP acknowledges field support of Emmanuel Malet (Edytem) and Rangers of Reserves Naturelles de Haute-Savoie (ASTERS). Practical help: Roel H. Janssen, N. Huig, E. Bakker, Schools in the tepaseforsoket, Forskar fredag, Erik Herberg. The support by the Bavarian Forest National Park administration is highly appreciated. LvdB acknowledges CONAF and onsite support from the park rangers from PN Pan de Azucar, PN La Campana, PN Nahuelbuta and from communidad agricola Quebrada de Talca. JL and FS acknowledge Manuel Nicolas and all forest officers from the Office National des Forets (ONF) who are in charge of the RENECOFOR network and who provided help and local support for the installation and maintenance of temperature loggers in the field., Research in global change ecology relies heavily on global climatic grids derived from estimates of air temperature in open areas at around 2 m above the ground. These climatic grids do not reflect conditions below vegetation canopies and near the ground surface, where critical ecosystem functions occur and most terrestrial species reside. Here, we provide global maps of soil temperature and bioclimatic variables at a 1-km2 resolution for 0–5 and 5–15 cm soil depth. These maps were created by calculating the difference (i.e. offset) between in situ soil temperature measurements, based on time series from over 1200 1-km2 p ixels ( summarized f rom 8 519 u nique t emperature sensors) across all the world's major terrestrial biomes, and coarse-grained air temperature estimates from ERA5-Land (an atmospheric reanalysis by the European Centre for Medium-Range Weather Forecasts). We show that mean annual soil temperature differs markedly from the corresponding gridded air temperature, by up to 10°C (mean = 3.0 ± 2.1°C), with substantial variation across biomes and seasons. Over the year, soils in cold and/or dry biomes are substantially warmer (+3.6 ± 2.3°C) than gridded air temperature, whereas soils in warm and humid environments are on average slightly cooler (−0.7 ± 2.3°C). The observed substantial and biome-specific offsets emphasize that the projected impacts of climate and climate change on near-surface biodiversity and ecosystem functioning are inaccurately assessed when air rather than soil temperature is used, especially in cold environments. The global soil-related bioclimatic variables provided here are an important step forward for any application in ecology and related disciplines. Nevertheless, we highlight the need to fill remaining geographic gaps by collecting more in situ measurements of microclimate conditions to further enhance the spatiotemporal resolution of global soil temperature products for ecological applications., FWO G018919N W001919N 12P1819N, DOB Ecology, University of Helsinki, Faculty of Science (MICROCLIM) 7510145, European Research Council (ERC) FORMICA 757833, Arctic Interactions at the University of Oulu, Academy of Finland 318930 337552, Maaja vesitekniikan tuki ry., Tiina and Antti Herlin Foundation, Nordenskiold Samfundet, Societas pro Fauna et Flora Fennica, Grant Agency of the Czech Republic 20-28119S 20-05840Y GA17-19376S 21-11487S, Czech Academy of Sciences RVO 67985939, National Geographic Society 9480-14 WW-240R-17, CISSC (program ICRP) 2397, Iran National Science Foundation (INSF) 96005914, Scottish Government's Rural and Environment Science and Analytical Services Division, Qatar Petroleum QUEX-CAS-QP-RD-18/19, European Union's Horizon 2020 research and innovation program 678841, Swiss National Science Foundation (SNSF), European Commission 172198 193645 31003A_176044, Ministry of Education, Youth & Sports - Czech Republic LTAUSA19137, Ministry of Science and Higher Education of the Russian Federation FSRZ-2020-0014, Independent Research Fund Denmark 8021-00423B 7027-00133B, German Research Foundation (DFG) DFG- FZT 118 202548816 TI 338/14-1 TI 338/14-2 BA 3843/6-1, grant project VEGA of the Ministry of Education of the Slovak Republic Slovak Academy of Sciences 2/0132/18, Forestry Commission, Universidad Javeriana, Direccion General de Cambio Climatico del Gobierno de Aragon, European Union's Horizon 2020 research and innovation program under the Marie Skodowska-Curie Grant 657627 SNF 407340_172433 40FA40_154245 20FI21_148992 20FI20_173691, European Commission 17841 774124, MCTI/CNPq/FNDCT 68/2013, Project 'Como as florestas da Amazonia Central respondem as variacoes climaticas? Efeitos sobre dinamica florestal e sinergia com a fragmentacAo florestal', Spanish Government, European Commission CGL2016-78093-R, ANID-FONDECYT 1181745, National Science Foundation, Poland UMO-2017/27/B/ST10/02228, National Research Foundation - South Africa, Australian Research Council, Slovak Research and Development Agency APVV-19-0319, Instituto Antartico Chileno INACH_RT-48_16 INACH FR-0418, Comision Nacional de Investigacion Cientifica y Tecnologica (CONICYT) PIA APOYO CCTE AFB170008 PIA AFB170008, UK Research & Innovation (UKRI), Natural Environment Research Council (NERC), Research Council of Norway, European Commission 230970, NERC E3 doctoral training partnership grant at the University of Edinburgh NE/L002558/1, Carnegie Trust for the Universities of Scotland, Gobern of Spain PERMAPLANET CTM2009-10165-E ANTARPERMA CTM2011-15565-E PERMASNOW CTM2014-52021-R, University of Alcala, Spanish Polar Committee, Autonomous Province of Bolzano (ITA), ScotNature, NERC National Capability LTS-S: UK-SCAPE NE/R016429/1, Ministry of Education, Youth & Sports - Czech Republic LTAUSA18007, Kempe Foundation JCK-1112 JCK-1822, Ministry of Education, Youth and Sports of the Czech Republic within the National Sustainability Programme I (NPU I) LO1415, project for national infrastructure support CzeCOS/ICOS LM2015061 GLORIA-EU EVK2-CT2000-00056, Tiroler Wissenschaftsfonds, University of Innsbruck, Sime Darby Foundation, Jardin Botanico Atlantico SV-20-GIJON-JBA, Federal Ministry of Education & Research (BMBF) 01LL0912 01LG1201M 01LG1201N, Comision Nacional de Investigacion Cientifica y Tecnologica (CONICYT) CONICYT FONDECYT 11170516 1180205, ANID PIA / BASAL FB210006, National Parks (DYNBIO) 1656/2015, Spanish Research Agency (VULBIMON) CGL2017-90040-R, Swiss National Science Foundation (SNSF) 20FI20_173691, Biotechnology and Biological Sciences Research Council (BBSRC) 206/D16053 FWO G0H1517N, EU Horizon2020 INFRAIA project eLTER-PLUS 871128, project LTER-CWN (FFG, F&E Infrastrukturforderung) 858024, Austrian Climate Research Program ACRP7 - CentForCSink - KR14AC7K11960, iDiv by the German Research Foundation DFG- FZT 118 202548816, Baden-Wurttemberg Ministry of Science, Research and Arts, Weston Foundation, ArcticNet, Natural Sciences and Engineering Research Council of Canada (NSERC) RGPIN-06691, Villum Foundation 17523, Ministry of Education, Youth & Sports - Czech Republic LM2015078 VAN2020/01 CZ.02.1.01/0.0/0.0/16_013/0001708 LTT17033 LTT20017 INTER-TRANSFER LTT19018, Bolin Centre for Climate Research, Stockholm University, Swedish Research Council Swedish Research Council Formas 2014-00530 2018-00792 2016-01187, Swedish Forest Society Foundation 2018-485-Steg 2 2017, Federal Ministry of Education & Research (BMBF) FKZ 031B0516C SUSALPS, Oberfrankenstiftung OFS FP00237, Energy Research Fund NYR-11 - 2019 NYR-18 - 2020, UK NERC Independent Research Fellowship NE/S01537X/1, National Science Centre, Poland 2016/21/B/ST10/02271, Polish National Centre for Research and Development Pol-Nor/203258/31/2013, MoEFCC, Govt of India (AICOPTAX project) 22018/12/2015/RE/Tax, Swedish Research Council Formas 2018-01781 2018-02700 2019-00836, research infrastructure ICOS-SE, National Research, Development and Innovation Fund of Hungary K128441, Programa Operativo FEDER 2018 B1-RNM-163-UGR-18, Norwegian Research Council (NORKLIMA grants) 184912 244525, CONICYT-PAI 79170119, ANID-MPG 190029, project MIUR PON Cluster OT4CLIMA, Stelvio National Park, AIAS-COFUND fellowship programme - Marie Skodowska- Curie actions under the European Union's Seventh Framework Pro-gramme for Research, Technological development and Demonstration 609033, Aarhus University Research Foundation, Denmark, EU FP6 NitroEurope 17841, EU FP7 ECLAIRE 282910, Ministry of Education and Science of Ukraine 505 550 574 602, GEF-UNEP NEC05348, ENI CBC BSB PONTOS BSB 889, Netherlands Organization for Scientific Research (NWO) 016.VICI.170.072, New Frontiers in Research Fund-Exploration NFRF-2018-02043, Natural Sciences and Engineering Research Council of Canada (NSERC), Australian Research Council DE180100570, National Science Foundation (NSF) DEB 1557094, International Center for Advanced Renewable Energy and Sustainability (I-CARES) at Washington University in St. Louis, Smithsonian Institution Smithsonian Tropical Research Institute, Tyson Research Center, UK Natural Environment Research Council through the ShrubTundra Project NE/M016323/1, Swedish Research Council Formas Swedish Research Council, Kempe Foundations - research infrastructure ICOS Kempe Foundations - research infrastructure SITES, Consejo Nacional de Investigaciones Cientificas y Tecnicas (CONICET) PIP 112-201501-00609, Spanish Government PID2019-110521GB-I00, Catalan government 2017-1005, French National Research Agency (ANR) ANR-10-LABX-45, General Directorate of State Forests, Warsaw, Poland, Max Planck Society, Russian Foundation for Basic Research (RFBR), Krasnoyarsk Territory Krasnoyarsk Regional Fund of Science 20-45-242908, Estonian Research Council PRG609, Knut & Alice Wallenberg Foundation 2015.0047, Swedish Research Council, fundacion Ramon Areces grant ELEMENTAL-CLIMATE, Svalbard Environmental Protection Fund 15/128, Research Council of Norway 269957, Humboldt Fellowship for Experienced Researchers, Russian Foundation for Basic Research (RFBR) 18-05-60203-Arktika, Polish National Science Centre 2017/27/B/NZ8/00316, ODYSSEE project (PN-II-ID-JRP-RO-FR-2012) ANR-13-ISV7-0004, Australian Government, Department of Industry, Innovation and Science, Global Challenges program at the University of Wollongong, ARC the Australian Antarctic Division, INACH, project SUBANTECO IPEV 136 (French Polar Institute Paul-Emile Victor), Zone Atelier CNRS Antarctique et Terres Australes, SAD Region Bretagne (Project INFLICT), BiodivERsa 2019-2020 BioDivClim call 'ASICS' ANR-20-EBI5-0004, National Science Foundation (NSF) 1556772, EU-LEAP-Agri (RAMSES II) EU-DESIRA (CASSECS) EU-H2020 (SustainSahel), AGROPOLIS, Total SA, CGIAR, Russian Science Foundation (RSF) 18-74-10048, Swedish Research Council 2014-04270, ALTER-net multi-site grant, River LIFE project LIFE08 NAT/S/000266, Flexpeil, Ministry of Science and Higher Education, Poland N N305 304840, ETH Zurich FEVER ETH-27 19-1, NSERC Canada Graduate Scholarship (Doctoral) Program, ArcticNet-NCE, Conselho Nacional de Desenvolvimento Cientifico e Tecnologico (CNPQ) 141513/2017-9, Fundacao Carlos Chagas Filho de Amparo a Pesquisa do Estado do Rio De Janeiro (FAPERJ) E26/200.84/2019, SRDA APVV-16-0325 APVV-20-0365, ERDF (CE LignoSilva) ITMS 313011S735, ETH Zurich, EU Horizon 2020 641918, German Terrestrial Environmental Observatories (TERENO) research program of the Helmholtz Association, Bavarian Ministry of the Environment and Public Health UGV06080204000 German Research Foundation (DFG) 192626868, Swedish National Space Board (SNSB) 95/16, CASSECS project by the European Union, Natural Environment Research Council (NERC) NE/L002558/1, MEMOIRE project PN-III-P1-1.1-PD2016-0925, Arctic Challenge for Sustainability II (ArCS II) JPMXD1420318865, Consiliul National al Cercetarii Stiintifice (CNCS), Unitatea Executiva pentru Finantarea Invatamantului Superior, a Cercetarii, Dezvoltarii si Inovarii (UEFISCDI) PN-III-P2-2.1-PED-2019-4924 PN2019-2022/19270201, 25N BIODIVERS 3-BIOSERV, Russian Science Foundation (RSF) 21-14-00209., Netherlands Organization for Scientific Research (NWO) 863.14.013, Australian Research Council DE140101611, Portuguese Foundation for Science and Technology CEECIND/02509/2018 CESAM UIDP/50017/2020+UIDB/50017/2020, Portuguese Foundation for Science and Technology European Commission, FEDER, within the PT2020 Partnership Agreement, Compete 2020, Spanish Government FPU17/05869, Swiss Federal Office for the Environment (FOEN), Giacomi foundation, National Natural Science Foundation of China (NSFC) 41861134039 41941015 41877458, French National Research Agency (ANR) ANR-19-CE32-0005-01 Centre National de la Recherche Scientifique (CNRS), Structure Federative de Recherche (SFR) Condorcet (FR CNRS 3417: CREUSE), EU INTERACT program, Inuit of Nunatsiavut, Co-management Board of Torngat Mountains National Park, Saxon Switzerland National Park Administration, Bavarian Forest National Park administration, BECC - Biodiversity and Ecosystem services in a Changing Climate, Research Foundation Flanders (FWO-SBO) S000619N

Nearshore marine habitats are critical for a variety of commercially important fish species, but assessing fish communities in these habitats is costly and time-intensive. Here, we leverage eDNA metabarcoding to characterize nearshore fish communities near Juneau, Alaska, USA, a high-latitude environment with large tidal swings, strong currents, and significant freshwater input. We investigated whether species richness and community composition differed across three habitat types (sand beaches, eelgrass beds, and rocky shorelines) and between high and low tides. Additionally, we tested whether replication of field samples and PCR reactions influenced either species richness or composition. We amplified a 12S mitochondrial locus in our samples and identified 188 fish amplicon sequence variants (ASVs), corresponding to 21 unique taxa, with approximately half of these resolved to single species. Species richness and composition inferred from eDNA differed substantially among habitats, with rock habitats containing fewer taxa and fewer overall detections than sand and eelgrass habitats. The effect of tide was more subtle and suggested a habitat-tide interaction, with differences in taxa between tides largely isolated to sand habitats. Power analyses indicated that additional field sampling is useful to detect subtle changes in species richness such as those due to tide. PCR replicates typically identified a small number of additional taxa. The most notable result from our study was that shore morphology appeared to substantially influence community structure. Rocky shorelines sloped quickly into deep water, while sand and eelgrass habitats descended much more gradually. We hypothesize that differences in taxa observed among habitats were largely due to lack of mixing between bottom and surface water, providing further evidence that eDNA transport is minimal and that many marine eDNA detections are derived from highly localized sampling locations. We suggest that future studies could explore the extent to which habitat and nearshore physical processes influence eDNA detections.

Made available in DSpace on 2022-04-28T19:52:06Z (GMT). No. of bitstreams: 0 Previous issue date: 2022-03-18 Urbanization transforms environments in ways that alter biological evolution. We examined whether urban environmental change drives parallel evolution by sampling 110,019 white clover plants from 6169 populations in 160 cities globally. Plants were assayed for a Mendelian antiherbivore defense that also affects tolerance to abiotic stressors. Urban-rural gradients were associated with the evolution of clines in defense in 47% of cities throughout the world. Variation in the strength of clines was explained by environmental changes in drought stress and vegetation cover that varied among cities. Sequencing 2074 genomes from 26 cities revealed that the evolution of urban-rural clines was best explained by adaptive evolution, but the degree of parallel adaptation varied among cities. Our results demonstrate that urbanization leads to adaptation at a global scale. Department of Biology University of Toronto Mississauga ON Centre for Urban Environments University of Toronto Mississauga ON Department of Biology University of North Carolina, Chapel Hill Department of Biology University of Louisiana LA Department of Biology Queen's University ON Department of Biology Concordia University QC Department of Biological Sciences DePaul University Department of Biology DePauw University IN Department of Urban Design and Planning, University of Washington, Seattle, WA, USA Colegio de Ciencias Biológicas y Ambientales Universidad San Francisco de Quito USFQ Department of Genetics University of Georgia Department of Ecology and Genetics Evolutionary Biology Centre Uppsala University Field Science Center for Northern Biosphere Hokkaido University Natural History Museum Zoology University of New England NSW Programa de Pós-Graduação em Geografia da UFMT campus de Rondonópolis Department of Botany and Biodiversity Research Centre University of British Columbia Graduate Program in Genome Sciences and Technology Genome Sciences Centre University of British Columbia Department of Microbiology and Immunology University of British Columbia Red de Biología Evolutiva Instituto de Ecología A. C. School of the Environment Yale University CT Departamento de Ciencias Ecológicas Universidad de Chile, Facultad de Ciencias Instituto de Ecología y Biodiversidad Universidad de Chile Department of Biology Mount Allison University Red de Ecoetología Instituto de Ecología A. C. Department of Biology University of Ottawa ON Department of Zoology University of Cambridge Department of Biology, Washington University in St. Louis, St. Louis, MO, USA Department of Biology University of Miami FL Centro de Investigación en Recursos Naturales y Sustentabilidad (CIRENYS) Universidad Bernardo O'Higgins Department of Biology, University of La Verne, La Verne, CA, USA Département des sciences du bois et de la forêt Université Laval QC Evolution & Ecology Research Centre School of Biological Earth and Environmental Sciences UNSW Sydney NSW Department of Biology Ghent University Department of Biology Monmouth University West Long Branch Centre for Ecology Evolution and Environmental Changes Faculdade de Ciências Universidade de Lisboa Lisboa Department of Biology KU Leuven School of Agriculture and Environment Wildlife and Ecology group Massey University, Palmerston North Department of Biological Sciences University of Cape Town Institute of Landscape Ecology University of Münster Gosnell School of Life Sciences, Rochester Institute of Technology, Rochester, NY, USA Department of Biological Sciences University of Alberta AB Louis Calder Center and Department of Biological Sciences, Fordham University, Armonk, NY, USA Departamento de Ecología Tropical, Universidad Autónoma de Yucatán, Mérida, Yucatán, México School of Life Sciences University of Sussex Department of Ecology Environment and Plant Sciences Stockholm University iBIOTROP Instituto de Biodiversidad Tropical Universidad San Francisco de Quito Department of Biology, San Francisco State University, San Francisco, CA, USA Unidad de Recursos Naturales, Centro de Investigación Científica de Yucatán AC, Mérida, Yucatán, México School of Ecological and Environmental Sciences East China Normal University Shanghai Engineering Research Center of Sustainable Plant Innovation Centre for Ecosystem Science School of Biological Earth and Environmental Sciences UNSW Sydney NSW Department of Ecology and Evolutionary Biology University of Michigan MI Department of Biosciences Rice University TX IFEVA Universidad de Buenos Aires Facultad de Agronomía, CONICET Biology Department Saint Mary's University NS Department of Biological Sciences, Universidad de los Andes Department of Biology and Biochemistry University of Houston TX Université de Rennes Department of Zoology and Biodiversity Research Centre University of British Columbia Department of Environmental Studies Dordt University Sioux Center IA Department of Biology Minneapolis Community and Technical College MN Department of Natural Sciences Ecology and Environment Research Centre Manchester Metropolitan University Instituto de Investigaciones en Ecosistemas y Sustentabilidad UNAM Department of Botany School of Biology Aristotle University of Thessaloniki Faculty of Biological and Environmental Science Organismal & Evolutionary Biology Research Programme University of Helsinki Institute of Biodiversity Animal Health and Comparative Medicine University of Glasgow Department of Biology Hendrix College Department of Ecological Science Vrije Universiteit Amsterdam Departamento de Ciencias Biológicas y Agropecuarias Universidad Técnica Particular de Loja Departamento de Biologia Universidade Federal de Santa Maria (UFSM) Department of Plant Sciences School of Biology College of Science University of Tehran NTNU University Museum Norwegian University of Science and Technology Red de Estudios Moleculares Avanzados Instituto de Ecología A. C. School of Biological Sciences, University of Reading, Whiteknights Park, Reading, Berkshire, UK Department of Biology Northern Arizona University AZ Department of Biological Sciences MacEwan University AB Max Planck Institute for Plant Breeding Research Departamento de Ecología Evolutiva Instituto de Ecología Universidad Nacional Autónoma de México Max Planck Institute of Molecular Plant Physiology Potsdam-Golm BIO5 Institute University of Arizona AZ Alaska Center for Conservation Science University of Alaska Anchorage Tropical Diversity, Royal Botanical Garden of Edinburgh Département de biologie Université de Moncton Department of Biological Sciences University of Manitoba MB Departments of Microbiology & Statistics University of Manitoba MB Department of Biology University of New Brunswick Department of Biology Kalamazoo College MI BioProtection Research Centre Lincoln University Departamento de Ciencias Facultad de Artes Liberales Universidad Adolfo Ibáñez Department of Ecology Evolution Behaviour University of Minnesota MN Department of Biological Sciences Brock University Department of Environmental Toxicology, University of California, Davis, CA, USA ICB - University of Talca School of Molecular and Life Science Curtin University College of Science Health Engineering and Education Murdoch University, Murdoch School of Life and Environmental Sciences University of Sydney NSW School of Biological Sciences, Monash University, Melbourne, VIC, Australia Department of Biological Sciences Wayne State University MI Department of Biology Western Oregon University, OR School of Natural Resources and the Environment University of Arizona AZ Departamento de Ecología Humana, Cinvestav Mérida Departamento de Ciencias Biológicas y Departamento de Ecología y Biodiversidad Facultad de Ciencias de la Vida, Universidad Andrés Bello Institute of Ecology and Biodiversity (IEB) Department of Biology Lund University Department of Biology Norwegian University of Science and Technology Escuela Superiro de Desarrollo Sustentable Universidad Autónoma de Guerrero -CONACYT Clarkson Secondary School Peel District School Board ON Homelands Sr. Public School Peel District School Board ON Department of Biological Sciences University of Illinois at Chicago Dufferin-Peel Catholic District School Board, St. James Catholic Global Learning Centre Department of Biosciences University of Calgary AB Ecological Processes Branch U.S. Army ERDC-CERL Department of Biology, Oberlin College, Oberlin, OH, USA Escuela Nacional de Estudios Superiores Unidad Morelia UNAM Institute of Evolution and Ecology University of Tübingen Tübingen Department of Evolutionary Biology and Environmental Studies University of Zurich, Winterthurerstrasse Urban Wildlife Institute Department of Conservation and Science, Lincoln Park Zoo Departamento de Ecología Universidad Católica de la Santísima Concepción Department of Biological Sciences University of Denver CO Department of Biological Sciences Mississippi State University MS Department of Biology Center for Computational & Integrative Biology Rutgers University-Camden Kunming Institute of Botany Chinese Academy of Sciences Department of Chemistry & Biochemistry Laurentian University ON Ministry of Education Key Laboratory for Biodiversity Science and Ecological Engineering College of Life Sciences Beijing Normal University School of BioSciences, University of Melbourne, Melbourne, VIC, Australia Posgrado en Ciencias Biológicas Universidad Nacional Autónoma de México Department of Biological Sciences, Auburn University, Auburn, AL, USA Department of Entomology and Nematology, University of California, Davis, CA, USA Department of Biology University of New Mexico NM Department of Biology University of Wisconsin - Eau Claire Agriculture Institute Iranian Research Organization for Science and Technology (IROST) Department of Biology Colby College ME Instituto de Biología Universidad de Antioquia Department of Biology University of Massachusetts Boston MA Agricultural Biology Colorado State University CO Departamento de Biología Vegetal y Ecología Facultad de Biología Universidad de Sevilla, Av. Reina Mercedes s/n Facultad de Estudios Interdisciplinarios Centro GEMA- Genómica Universidad Mayor Evolutionary Ecology Group Naturalis Biodiversity Center Department of Biology and Chemistry Nipissing University ON, North Bay Center for Ecological Research Kyoto University Bonanza Creek Long Term Ecological Research Program University of Alaska Fairbanks Department of Botany and Molecular Evolution Senckenberg Research Institute and Natural History Museum Frankfurt Departamento de Biodiversidade Instituto de Biociências Univ Estadual Paulista - UNESP Nelson Institute for Environmental Studies University of Wisconsin-Madison WI Department of Biology, California State University, Northridge, Los Angeles, CA, USA Department of Ecology Swedish University of Agricultural Sciences Facultad de Ciencias y Biotecnologia Universidad CES Department of Biology Hofstra University Faculty of Biosciences and Aquaculture Nord University, Bodø Division of Biological Sciences, University of California San Diego, San Diego, CA, USA Department of Biology University of Richmond VA Estación de Biodiversidad Tiputini Colegio de Ciencias Biológicas y Ambientales Universidad San Francisco de Quito USFQ Department of Biological Sciences Institute of Environment Florida International University FL Agronomy Department University of Almería Department of Biological Sciences and Center for Urban Ecology and Sustainability Butler University IN Department of Biological Sciences Louisiana State University LA Faculty of Biological Sciences, Goethe University Frankfurt Institute of Biology Leiden Leiden University Department of Biological and Environmental Science University of Jyväskylä Jyväskylä Department of Biology University of Louisville KY Organization for Programs on Environmental Science University of Tokyo CNRS AgroParisTech Ecologie Systématique et Evolution, Université Paris-Saclay Department of Biology, Providence College, Providence, RI, USA General Zoology Institute for Biology Martin Luther University Halle-Wittenberg International Arctic Research Center University of Alaska Fairbanks Science, Technology and Society Department, Rochester Institute of Technology, Rochester, NY, USA SLU Swedish Species Information Centre Swedish University of Agricultural Sciences Department of Biology Westfield State University MA Centre of New Technologies University of Warsaw Department of Biology, Stanford University, Stanford, CA, USA Plant Biology Department Michigan State University MI Biology Department Davidson College College of Horticulture and Forestry Sciences/ Hubei Engineering Technology Research Center for Forestry Information Huazhong Agricultural University School of Life Sciences Technical University of Munich School of Life Sciences Lanzhou University Institute of Ecology and Evolution University of Bern Department of Evolution Ecology and Behaviour University of Liverpool Departamento de Biodiversidade Instituto de Biociências Univ Estadual Paulista - UNESP

The mammalian liver's regenerative ability has led researchers to engineer animals as incubators for expansion of human hepatocytes. The expansion properties of human hepatocytes in immunodeficient...

Network analyses rarely include fitness components, such as germination, to tie invasive plants to population‐level effects on the natives. We address this limitation in a previously studied network of flower visitors around a suite of native and invasive plants that includes an endemic plant at Badlands National Park, South Dakota, USA. Eriogonum visheri coflowers with two abundant invasive plants, Salsola tragus and Melilotus officinalis, as well as a common congener, E. pauciflorum. Network analyses had suggested strong linkages between E. visheri and S. tragus and E. pauciflorum, with a weaker link to M. officinalis. We measured visitation, pollen deposited on stigmas, achene weight and germination over three field seasons (two for germination) in four populations (two in the final season) of E. visheri and applied in situ pollen treatments to E. visheri, adding pollen from other flowers on the same plant; flowers on other E. visheri plants; S. tragus, M. officinalis, or E. pauciflorum; open pollination; or excluding pollinators. Insect visitation to E. visheri was not affected by floral abundance of any of the focal species. Most visitors were halictid bees; one of these (Lasioglossum packeri) was the only identified species to visit E. visheri all three years. Ninety‐seven percent of pollen on collected E. visheri stigmas was conspecific, but 22% of flowers had >1 grain of E. pauciflorum pollen on stigmas and 7% had >1 grain of S. tragus pollen, Eriogonum visheri (Visher's buckwheat) is a rare endemic plant of management concern in the northern Great Plains. Two invasive species, Melilotus officinalis (yellow sweetclover) and Salsola tragus (Russian thistle) and an abundant congener (E. pauciflorum; fewflower buckwheat) occur and coflower with E. visheri, suggesting that they might interfere with pollination of the rare species. We found no evidence of pollination interference by either of the invasive species. In addition, evidence suggests that the abundant congener may provide an alternative resource to support pollinators that also visit the rarer species.

The grey wolf (Canis lupus) was the first species to give rise to a domestic population, and they remained widespread throughout the last Ice Age when many other large mammal species went extinct. Little is known, however, about the history and possible extinction of past wolf populations or when and where the wolf progenitors of the present-day dog lineage (Canis familiaris) lived1–8. Here we analysed 72 ancient wolf genomes spanning the last 100,000 years from Europe, Siberia and North America. We found that wolf populations were highly connected throughout the Late Pleistocene, with levels of differentiation an order of magnitude lower than they are today. This population connectivity allowed us to detect natural selection across the time series, including rapid fixation of mutations in the gene IFT88 40,000–30,000 years ago. We show that dogs are overall more closely related to ancient wolves from eastern Eurasia than to those from western Eurasia, suggesting a domestication process in the east. However, we also found that dogs in the Near East and Africa derive up to half of their ancestry from a distinct population related to modern southwest Eurasian wolves, reflecting either an independent domestication process or admixture from local wolves. None of the analysed ancient wolf genomes is a direct match for either of these dog ancestries, meaning that the exact progenitor populations remain to be located. © 2022, The Author(s). 8028-00005B; IP DKRVO 2019-2023, MK000094862; 220457/Z/20/Z, ERC-2013-StG-337574-UNDEAD, ERC-2019-StG-853272-PALAEOFARM; 075-15-2021-1069; European Molecular Biology Organization, EMBO: 217223/Z/19/Z; Vallee Foundation; Velux Fonden; Wellcome Trust, WT; Francis Crick Institute, FCI: FC001595; Horizon 2020 Framework Programme, H2020: 796877; Medical Research Council, MRC; Natural Environment Research Council, NERC: 210119/Z/18/Z, NE/K003259/1, NE/K005243/1, NE/S00078X/1, NE/S007067/1; Cancer Research UK, CRUK; European Research Council, ERC: 852558; Grantová Agentura České Republiky, GA ČR: 15-06446S; Svenska Forskningsrådet Formas: 2018-01640; Knut och Alice Wallenbergs Stiftelse; Vetenskapsrådet, VR: 681396, BELSPO B2/191/P2/ICHIE; Russian Science Foundation, RSF: 16-18-10265-RNF, 20-17-00033, 21-18-00457-RNF, 310763; Science for Life Laboratory, SciLifeLab; Narodowa Agencja Wymiany Akademickiej, NAWA: PPN/PPO/2018/1/00037 This work was supported by grants to P. Skoglund from the European Research Council (grant no. 852558), the Erik Philip Sörensen Foundation and the Science for Life Laboratory, Swedish Biodiversity Program, made available by support from the Knut and Alice Wallenberg Foundation. A.B., L.S., P. Swali and P. Skoglund were supported by Francis Crick Institute core funding (FC001595) from Cancer Research UK, the UK Medical Research Council and the Wellcome Trust. P. Skoglund was also supported by the Vallee Foundation, the European Molecular Biology Organisation and the Wellcome Trust (217223/Z/19/Z). Computations were supported by SNIC-UPPMAX. We also acknowledge support from Science for Life Laboratory, the Knut and Alice Wallenberg Foundation, the National Genomics Infrastructure funded by the Swedish Research Council and the Uppsala Multidisciplinary Center for Advanced Computational Science for assistance with massively parallel sequencing and access to the UPPMAX computational infrastructure. We thank the Yukon gold mining community and First Nations, including the Tr’ondëk Hwëch’in, for continued support of our palaeontology research in the Yukon Territories, Canada. We thank the Danish National High-Throughput Sequencing Centre and BGI-Europe for assistance in sequencing data generation and the Danish National Supercomputer for Life Sciences–Computerome ( https://computerome.dtu.dk ) for computational resources. We thank National Museum Wales for continued sampling support. M. Germonpré acknowledges support from the Brain.be 2.0 ICHIE project (BELSPO B2/191/P2/ICHIE). M.T.P.G. was supported by the European Research Council (grant no. 681396). M.-H.S.S. was supported by the Velux Foundations through the Qimmeq Project, the Aage og Johanne Louis-Hansens Fond and the Independent Research Fund Denmark (8028-00005B). L.D. acknowledges support from FORMAS (2018-01640). D.W.G.S. received funding for this project from the European Union’s Horizon 2020 research and innovation programme under Marie Skłodowska-Curie grant agreement no. 796877. M.P. was supported by the Polish National Agency for Academic Exchange–NAWA (grant no. PPN/PPO/2018/1/00037). V.J.S. was supported by the University of Zurich’s University Research Priority Program ‘Evolution in Action: From Genomes to Ecosystems’. This research was done with the participation of ZIN RAS (grant no. 075-15-2021-1069). We are grateful to the museum of the Institute of Plant and Animal Ecology UB RAS (Ekaterinburg, Russia) for provision of samples. R.P.J. and C.O’D. were supported by the Standing Committee for Archaeology of the Royal Irish Academy through the Archaeological Excavation Research Grant Scheme. E.Y.P., P.N. and V.V.P. are supported by the Russian Science Foundation (grant no. 16-18-10265-RNF and 21-18-00457-RNF). Y.V.K. was supported by the Russian Science Foundation (grant no. 20-17-00033). M.H. was supported by the European Research Council (consolidator grant GeneFlow no. 310763). M.L.-G. was supported by the Czech Science Foundation GAČR (grant no. 15-06446S) and institutional financing of the Moravian Museum from the Czech Ministry of Culture (IP DKRVO 2019-2023, MK000094862). L.S. is supported by the Sir Henry Wellcome fellowship (220457/Z/20/Z). We thank Staatliches Museum für Naturkunde Stuttgart for sample access. L.F. and G.L. were supported by European Research Council grants (ERC-2013-StG-337574-UNDEAD and ERC-2019-StG-853272-PALAEOFARM) and Natural Environmental Research Council grants (NE/K005243/1, NE/K003259/1, NE/S007067/1 and NE/S00078X/1). L.F. was also supported by the Wellcome Trust (210119/Z/18/Z). This research was funded in whole, or in part, by the Wellcome Trust (FC001595). For the purpose of open access, the author has applied a CC-BY public copyright licence to any author accepted manuscript version arising from this submission.

A candidate-gene high-density single-nucleotide polymorphism (SNP) scanning approach was used to investigate the swine LUMAN/CREB3 locus for polymorphisms in 232 Ontario Yorkshire and 29 Chinese Meishan pigs. Inter- and intra-breed differences in genetic diversity were characterized. In the Yorkshire breed, eight variations (three coding and five non-coding) were identified. Two linkage disequilibrium (LD) blocks (550 bp and ∼4 kb in length) featuring two and three haplotypes, respectively, were reconstructed. In the Meishan breed, six variations (two coding and four non-coding) and one LD block (∼3 kb in length) with three haplotypes were detected. This investigation may provide insight into variable stress responsiveness among pigs.

During Drosophila embryogenesis, the essential pioneer factor Zelda defines hundreds of cis-regulatory regions and in doing so reprograms the zygotic transcriptome. While Zelda is essential later in development, it is unclear how the ability of Zelda to define cis-regulatory regions is shaped by cell-type-specific chromatin architecture. Asymmetric division of neural stem cells (neuroblasts) in the fly brain provide an excellent paradigm for investigating the cell-type-specific functions of this pioneer factor. We show that Zelda synergistically functions with Notch to maintain neuroblasts in an undifferentiated state. Zelda misexpression reprograms progenitor cells to neuroblasts, but this capacity is limited by transcriptional repressors critical for progenitor commitment. Zelda genomic occupancy in neuroblasts is reorganized as compared to the embryo, and this reorganization is correlated with differences in chromatin accessibility and cofactor availability. We propose that Zelda regulates essential transitions in the neuroblasts and embryo through a shared gene-regulatory network driven by cell-type-specific enhancers., The pioneer transcription factor Zelda is essential for the reprogramming of germ cells to totipotent cells of the early Drosophila embryo. Here the authors examine the function of Zelda later in development in the larval brain to show that Zelda promotes the undifferentiated stem-cell fate. They further identify factors that limit the reprogramming capacity of this pioneer factor.

LUMAN/CREB3 is a stress regulatory gene that affects the activity of the hypothalamic–pituitary–adrenal axis in mice and presents a promising avenue for exploring variable stress-responsiveness in pigs. Pigs with similar characteristics to LUMAN-deficient mice, including greater resilience to stress and receptivity to human handling, would be valuable in the pork industry from animal welfare and production efficiency perspectives. We previously identified eight genetic variations and five haplotypes throughout the LUMAN locus in Yorkshire pigs. In this study, we analysed associations between LUMAN variations with behavioural stress response during three tests (open field test, novel object test, and human approach test), physiological stress responsiveness (cortisol), and carcass/meat quality measurements from purebred Yorkshire pigs. Haplotypes A1 and A2 were associated with decreased activity levels in novel environments and greater plasma cortisol concentrations at slaughter. Haplotype A1 was associated with lower carcass scratch scores and meat with lower cooking losses and greater tenderness. Haplotypes B1 and B2 were associated with the opposite traits including increased activity levels in novel environments and characteristics for lower meat quality including greater cooking losses, lower marbling, and paler coloured meat. We conclude that DNA variations in the LUMAN locus could potentially be used as genetic markers for stress resistance and meat quality in pig breeding.

Genetic differentiation has been observed in marine species even when no obvious barriers to gene flow exist, and understanding such differentiation is essential for effective fisheries management. Highly differentiated outlier loci can provide information on how genetic variation might not only contribute to local adaptation but may also be affected by historical demographic events. A locus which aligned to a predicted zona pellucida sperm‐binding protein 3 gene (ZP3) in Atlantic cod (Gadus morhua) was previously identified as the highest outlier based on F ST in a RADseq study of Pacific cod (Gadus macrocephalus) across the West Coast of North America. However, because of the limited length of the RAD sequence and restricted geographic area of sampling, no conclusion on the functional significance of the observed variation was possible. In other marine species, ZP3 is involved in reproductive isolation, local adaptation, and has neofunctionalized as an antifreeze gene, and so it may provide important insights in functional population structure of Pacific cod. Here, we sequenced a 544‐bp region of ZP3 in 230 Pacific cod collected from throughout their geographic range. We observed striking patterns of spatial structuring of ZP3 haplotypes, with a sharp break near Kodiak, Alaska, USA where populations within ~200 km of each other are nearly fixed for different haplotypes, contrasting a pattern of isolation by distance at other genetic markers in this region (F ST = 0.003). Phylogenetic analysis of ZP3 haplotypes revealed that the more southern haplotypes appear to be ancestral, with the northern haplotype evolving more recently, potentially in response to a novel selective pressure as Pacific cod recolonized northern latitudes after glaciation. The sharp break in haplotype frequencies suggests strong selective pressures are operating on small spatial scales and illustrates that selection can create high divergence even in marine species with ample opportunities for gene flow., We document a sharp break in haplotype frequencies for a putative sperm‐binding protein zona pellucida subunit 3 in Pacific cod. Results suggest strong selective pressures are operating on small spatial scales and illustrate that selection can create high divergence even in marine species with ample opportunities for gene flow.

Invasive crayfish can cause shifts in lakes from clear, macrophyte-dominated states to eutrophic, phytoplankton-dominated states because of their burrowing and foraging behavior. While invasive crayfish populations have been linked to declines in water clarity of shallow lakes and wetlands in Asia and Europe, little research has been done on the potential for similar effects of invasive rusty crayfish (Faxonius rusticus) in large temperate lakes of the Midwestern USA. We related F. rusticus abundance in 17 lakes of northern Wisconsin, USA over time (1984‒2018) to measures of lake clarity (chlorophyll a concentration and Secchi disc depth) estimated from remote sensing (Landsat imagery). Contrary to the effects of invasive crayfish in other study systems, we found a weak, positive association between F. rusticus abundance and water clarity. We propose that lake clarity may increase if declines in small fishes caused by F. rusticus lead to population growth of zooplankton and consequent decreases in phytoplankton through a trophic cascade. Alternatively, F. rusticus could be passengers to, rather than drivers of, lake clarity trends, responding positively to increased littoral benthic productivity when lakes are clearer. Future research should aim to determine if F. rusticus causes or responds to changes in water clarity, but should also investigate the impacts of crayfish invasions on water clarity across a greater variety of lentic ecosystems.

Small, isolated populations present a challenge for conservation. The dueling effects of selection and drift in a limited pool of genetic diversity make the responses of small populations to environmental perturbations erratic and difficult to predict. This is particularly true at the edge of a species range, where populations often persist at the limits of their environmental tolerances. Populations of cisco, Coregonus artedi, in inland lakes have experienced numerous extirpations along the southern edge of their range in recent decades, which are thought to result from environmental degradation and loss of cold, well‐oxygenated habitat as lakes warm. Yet, cisco extirpations do not show a clear latitudinal pattern, suggesting that local environmental factors and potentially local adaptation may influence resilience. Here, we used genomic tools to investigate the nature of this pattern of resilience. We used restriction site‐associated DNA capture (Rapture) sequencing to survey genomic diversity and differentiation in southern inland lake cisco populations and compared the frequency of deleterious mutations that potentially influence fitness across lakes. We also examined haplotype diversity in a region of the major histocompatibility complex involved in stress and immune system response. We correlated these metrics to spatial and environmental factors including latitude, lake size, and measures of oxythermal habitat and found significant relationships between genetic metrics and broad and local factors. High levels of genetic differentiation among populations were punctuated by a phylogeographic break and residual patterns of isolation‐by‐distance. Although the prevalence of deleterious mutations and inbreeding coefficients was significantly correlated with latitude, neutral and non‐neutral genetic diversity were most strongly correlated with lake surface area. Notably, differences among lakes in the availability of estimated oxythermal habitat left no clear population genomic signature. Our results shed light on the complex dynamics influencing these isolated populations and provide valuable information for their conservation.

In Gabon, few data exist on extended-spectrum beta-lactamases-producing Enterobacteriaceae (ESBL-PE). This study investigated ESBL-PE prevalence and the associated resistance genes in clinical samples (

La Crosse virus (LACV) is a mosquito-borne orthobunyavirus that causes approximately 60 to 80 hospitalized pediatric encephalitis cases in the United States yearly. The primary treatment for most viral encephalitis, including LACV, is palliative care, and specific antiviral therapeutics are needed. We screened the National Center for Advancing Translational Sciences library of 3,833 FDA-approved and bioactive small molecules for the ability to inhibit LACV-induced death in SH-SY5Y neuronal cells. The top three hits from the initial screen were validated by examining their ability to inhibit virus-induced cell death in multiple neuronal cell lines. Rottlerin consistently reduced LACV-induced death by 50% in multiple human and mouse neuronal cell lines with an effective concentration of 0.16–0.69 µg ml−1 depending on cell line. Rottlerin was effective up to 12 hours post-infection in vitro and inhibited virus particle trafficking from the Golgi apparatus to trans-Golgi vesicles. In human inducible pluripotent stem cell-derived cerebral organoids, rottlerin reduced virus production by one log and cell death by 35% compared with dimethyl sulfoxide-treated controls. Administration of rottlerin in mice by intraperitoneal or intracranial routes starting at 3 days post-infection decreased disease development by 30–50%. Furthermore, rottlerin also inhibited virus replication of other pathogenic California serogroup orthobunyaviruses (Jamestown Canyon and Tahyna virus) in neuronal cell lines. Viral encephalitis caused in mice by La Crosse arbovirus can be treated with rottlerin, which prevents viral trafficking from the Golgi and reduces virus titres and neuronal cell death in the central nervous system.

INTRODUCTION Although vitamin D is intimately involved in bone metabolism, the relationship between vitamin D status, as measured by serum total 25-hydroxyvitamin D [25(OH)D] concentration, and bone mineral density (BMD) is weak, particularly in non-White populations. Measurement of bioavailable 25(OH)D has been suggested as a better indicator of vitamin D status than total 25(OH)D concentration. To date, the bioavailable 25(OH)D biomarker has been explored minimally in athletic populations. The purpose of this study was to investigate the relationship between total and bioavailable 25(OH)D concentrations and BMD in collegiate athletes. METHODS NCAA Division 1 basketball and swimming athletes served as study participants (n = 53; 28 females, 25 males; 28 basketball players, 25 swimmers). All participants completed dual energy x-ray absorptiometry (DXA) scans for analysis of BMD, blood draws for vitamin D measures, and diet/lifestyle questionnaires. RESULTS Overall, total 25(OH)D was 80.0 + 13.9 nmol/L and bioavailable 25(OH)D was 6.0 ± 1.9 nmol/L. There was strong disagreement between total 25(OH)D and bioavailable 25(OH)D concentrations (κ = -0.299; r = -0.129) (p = 0.100); 53% of total participants and 77% of Black participants were classified differently (low vs. normal vitamin D status) based on total and bioavailable 25(OH)D criteria. Black participants had significantly lower total 25(OH)D and higher bioavailable 25(OH)D concentrations than White participants (59.5 vs. 102.5 nmol/L and 7.9 vs. 5.4 nmol/L, respectively) (p < 0.001). Total 25(OH)D and total BMD were not correlated, but bioavailable 25(OH)D and total BMD demonstrated a positive correlation (r = 0.618, p < 0.01). CONCLUSIONS These results suggest that bioavailable 25(OH)D concentration may be a better clinical measure of vitamin D status than total 25(OH)D in collegiate athletes as related to BMD, particularly in Black athletes. Further research on the utility of the bioavailable 25(OH)D biomarker in athletes is needed.

Admixture is a mechanism by which species of long-lived plants may acquire novel alleles. However, the potential role of admixture in the origin and maintenance of tropical plant diversity is unclear. We ask whether admixture occurs in an ecologically important clade of Eschweilera (Parvifolia clade, Lecythidaceae), which includes some of the most widespread and abundant tree species in Amazonian forests. Using target capture sequencing, we conducted a detailed phylogenomic investigation of 33 species in the Parvifolia clade and investigated specific hypotheses of admixture within a robust phylogenetic framework. We found strong evidence of admixture among three ecologically dominant species, E. coriacea, E. wachenheimii and E. parviflora, but a lack of evidence for admixture among other lineages. Accepted species were largely distinguishable from one another, as was geographic structure within species. We show that hybridization may play a role in the evolution of the most widespread and ecologically variable Amazonian tree species. While admixture occurs among some species of Eschweilera, it has not led to widespread erosion of most species' genetic or morphological identities. Therefore, current morphological based species circumscriptions appear to provide a useful characterization of the clade's lineage diversity.

Understanding biodiversity in aquatic systems is critical to ecological research and conservation efforts, but accurately measuring species richness using traditional methods can be challenging. Environmental DNA (eDNA) metabarcoding, which uses high‐throughput sequencing and universal primers to amplify DNA from multiple species present in an environmental sample, has shown great promise for augmenting results from traditional sampling to characterize fish communities in aquatic systems. Few studies, however, have compared exhaustive traditional sampling with eDNA metabarcoding of corresponding water samples at a small spatial scale. We intensively sampled Boardman Lake (1.4 km2) in Michigan, USA, from May to June in 2019 using gill and fyke nets and paired each net set with lake water samples collected in triplicate. We analyzed water samples using eDNA metabarcoding with 12S and 16S fish‐specific primers and compared estimates of fish diversity among methods. In total, we set 60 nets and analyzed 180 1 L lake water samples. We captured a total of 12 fish species in our traditional gear and detected 40 taxa in the eDNA water samples, which included all the species observed in nets. The 12S and 16S assays detected a comparable number of taxa, but taxonomic resolution varied between the two genes. In our traditional gear, there was a clear difference in the species selectivity between the two net types, and there were several species commonly detected in the eDNA samples that were not captured in nets. Finally, we detected spatial heterogeneity in fish community composition across relatively small scales in Boardman Lake with eDNA metabarcoding, but not with traditional sampling. Our results demonstrated that eDNA metabarcoding was substantially more efficient than traditional gear for estimating community composition, highlighting the utility of eDNA metabarcoding for assessing species diversity and informing management and conservation.

Background Although muscle regenerative capacity declines with age, the extent to which this is due to satellite cell-intrinsic changes vs. environmental changes has been controversial. The majority of aging studies have investigated hindlimb locomotory muscles, principally the tibialis anterior, in caged sedentary mice, where those muscles are abnormally under-exercised. Methods We analyze satellite cell numbers in 8 muscle groups representing locomotory and non-locomotory muscles in young and 2-year-old mice and perform transplantation assays of low numbers of hind limb satellite cells from young and old mice. Results We find that satellite cell density does not decline significantly by 2 years of age in most muscles, and one muscle, the masseter, shows a modest but statistically significant increase in satellite cell density with age. The tibialis anterior and extensor digitorum longus were clear exceptions, showing significant declines. We quantify self-renewal using a transplantation assay. Dose dilution revealed significant non-linearity in self-renewal above a very low threshold, suggestive of competition between satellite cells for space within the pool. Assaying within the linear range, i.e., transplanting fewer than 1000 cells, revealed no evidence of decline in cell-autonomous self-renewal or regenerative potential of 2-year-old murine satellite cells. Conclusion These data demonstrate the value of comparative muscle analysis as opposed to overreliance on locomotory muscles, which are not used physiologically in aging sedentary mice, and suggest that self-renewal impairment with age is precipitously acquired at the geriatric stage, rather than being gradual over time, as previously thought.

Pest spillover from wildlands to farms can create conflict between habitat conservation and agricultural production. For example, the key economic pest of hazelnuts in Oregon’s Willamette Valley is the filbertworm (Cydia latiferreana), a moth hosted by the native Oregon white oak (Quercus garryana). Oak habitat near hazelnut orchards can sustain source populations that compound pest load in hazelnuts throughout the growing season. This dynamic is of conservational concern as historical oak habitat has been greatly reduced and what remains is almost entirely on private land, often in proximity to hazelnut orchards. Here, we present a novel strategy to reconcile this regional conflict by using hogs (Sus domesticus) to reduce pest populations through prescribed foraging. From 2018 to 2020 we prescribed hog-foraging in early fall to glean filbertworm-infested acorns from an oak woodland understory. Hogs were both highly successful at reducing the total number of infested acorns and the ratio of infested acorns the following year. Despite an oak-masting year in 2019, foraging reduced both the emerging and adult mating population of filbertworm the following year. We did not measure significant changes in the woodland understory, suggesting intermittent hog-foraging may not entail tradeoffs for understory vegetation. Our results demonstrate that prescribed foraging in oak patches can be an effective strategy to reduce filbertworm source populations. By benefiting both conservation and farmers, this adaptive pest management approach provides a model for similar challenges and conflicts across the agricultural-wildland matrix.

Predator encounters during early life can elicit behavioral and physiological responses that have fitness consequences during subsequent prey life stages. In threatened lake sturgeon (Acipenser fulvescens) and other lithophilic-spawning fishes, newly hatched larvae (free embryos) are exposed to abundant predators including aquatic insect larvae that co-occupy stream substrates. We investigated stress effects on lake sturgeon larvae after encounters with common aquatic insect predators by quantifying mortality, body size, cortisol levels, and swimming behavior. Free embryos were exposed to either Perlidae (stonefly obligate predators) or Isonychiidae (mayfly filterers and facultative predators) or to no predators (controls). Free embryos that encountered perlids experienced high mortality, elevated cortisol levels, and exhibited cortisol reactivity when subsequently exposed to an acute stressor. Free embryos that encountered isonychiids exhibited elevated mortality, and elevated cortisol and cortisol reactivity relative to controls. Findings indicate that lake sturgeon free embryos are stressed by exposure to members of benthic stream communities during early life stages (predation of nearby conspecifics), and that metrics of stress exhibited threat sensitivity. Data are consistent with predictions that individuals modulate antipredator behavior in response to the intensity of perceived predation threat in the environment. We determined that behavioral outcomes associated with encounters with aquatic insects altered future behavioral trajectories, potentially as an adaptive response that can affect predation rates in subsequent life stages. Results contribute to a broader understanding of how interspecies interactions among co-occurring predator and prey communities may impact individual fitness and fish population recruitment.

Purpose Despite a few recent reports of patients harboring truncating variants in NSD2, a gene considered critical for the Wolf–Hirschhorn syndrome (WHS) phenotype, the clinical spectrum associated with NSD2 pathogenic variants remains poorly understood. Methods We collected a comprehensive series of 18 unpublished patients carrying heterozygous missense, elongating, or truncating NSD2 variants; compared their clinical data to the typical WHS phenotype after pooling them with ten previously described patients; and assessed the underlying molecular mechanism by structural modeling and measuring methylation activity in vitro. Results The core NSD2-associated phenotype includes mostly mild developmental delay, prenatal-onset growth retardation, low body mass index, and characteristic facial features distinct from WHS. Patients carrying missense variants were significantly taller and had more frequent behavioral/psychological issues compared with those harboring truncating variants. Structural in silico modeling suggested interference with NSD2’s folding and function for all missense variants in known structures. In vitro testing showed reduced methylation activity and failure to reconstitute H3K36me2 in NSD2 knockout cells for most missense variants. Conclusion NSD2 loss-of-function variants lead to a distinct, rather mild phenotype partially overlapping with WHS. To avoid confusion for patients, NSD2 deficiency may be named Rauch–Steindl syndrome after the delineators of this phenotype., Genetics in Medicine, 23 (8)

Predicting rupture risk in intracranial aneurysms is among one of the most critical questions in vascular surgery. The processes that govern an aneurysm growth are multifaceted and complex, but may be summarized into three components: hemodynamics, biology, and mechanics. We review and connect the literature in the three disciplines, identifying considerable strides in recent history and current gaps in research. Taken together, the findings from each field elucidate how and why certain aneurysms rupture, whereas others remain stable. These parameters could eventually inform a translatable predictive model that optimizes risk evaluation and physician's decision-making in treatment options for aneurysms.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) utilizes an extensively glycosylated surface spike (S) protein to mediate host cell entry, and the S protein glycosylation plays key roles in altering the viral binding/function and infectivity. However, the molecular structures and glycan heterogeneity of the new O-glycans found on the S protein regional-binding domain (S-RBD) remain cryptic because of the challenges in intact glycoform analysis by conventional bottom-up glycoproteomic approaches. Here, we report the complete structural elucidation of intact O-glycan proteoforms through a hybrid native and denaturing top-down mass spectrometry (MS) approach employing both trapped ion mobility spectrometry (TIMS) quadrupole time-of-flight and ultrahigh-resolution Fourier transform ion cyclotron resonance (FTICR)-MS. Native top-down TIMS-MS/MS separates the protein conformers of the S-RBD to reveal their gas-phase structural heterogeneity, and top-down FTICR-MS/MS provides in-depth glycoform analysis for unambiguous identification of the glycan structures and their glycosites. A total of eight O-glycoforms and their relative molecular abundance are structurally elucidated for the first time. These findings demonstrate that this hybrid top-down MS approach can provide a high-resolution proteoform-resolved mapping of diverse O-glycoforms of the S glycoprotein, which lays a strong molecular foundation to uncover the functional roles of their O-glycans. This proteoform-resolved approach can be applied to reveal the structural O-glycoform heterogeneity of emergent SARS-CoV-2 S-RBD variants as well as other O-glycoproteins in general.

As the range of non-native bigheaded carps (Hypophthalmichthys spp.) continues to expand throughout river systems of the United States, managers are tasked with preventing or slowing the spread of these invasive species. Main stem navigation dams on the upper Mississippi River, long considered a deterrent to fish migration, may slow or prevent the spread of invasive fish species. As discharge increases, hydraulic head (i.e., difference between upstream elevation and downstream elevation) at these navigation dams decreases, which is believed to allow for easier fish passage. We used acoustic telemetry to investigate the occurrence, frequency, and timing of bigheaded carp passage of upper Mississippi River dams, along with factors related to successful dam passage. During 2013 through 2017, adult silver carp (H. molitrix), bighead carp (H. nobilis) and their hybrids (N = 358) were tracked throughout the upper Mississippi River. A total of 1078 dam passages by bigheaded carps (N = 158) were observed past 15 dams. Seventy-eight percent of dam passages occurred during April through July. Cox proportional hazards regression models indicated that both upstream and downstream dam passages by these species were strongly affected by hydraulic head height at the dam and water temperature, with dam passages increasing as hydraulic head decreased and water temperature increased. A few dams rarely experience low hydraulic head and passages of those dams by bigheaded carps were rare. This information can be used by managers to develop strategies (e.g., placement of deterrent technologies, targeted removal efforts) to slow the spread of these invasive species.

Individual specialization within populations is increasingly recognized as important in both ecology and evolution, but researchers working on intraspecific variation in behavior and diet infrequently interact. This may be because individual specialization on diet and behavior was historically difficult to investigate simultaneously on the same individuals. However, approaches like stable isotope analysis that allow hindcasting past field diets for laboratory organisms may provide opportunities to unite these areas of inquiry. Here, we tested the role of intraspecific competition on individual specialization through analysis of both behavior and diet simultaneously. We focused on intraspecific competition as a mechanism that might drive individual specialization of both diet and behavior. We conducted this study in Vilas County, Wisconsin, United States (US), using rusty crayfish Faxonius rusticus from six lakes across a relative abundance gradient. We conducted six assays to measure individual specialization of behavior and used stable isotope analysis to measure individual specialization of diet. We then related both measures of individual specialization to relative abundance of F. rusticus using linear and quadratic models. We found a unimodal relationship between intraspecific competition and individual specialization of diet for F. rusticus, likely because some preferred resources are unavailable to specialize on at the highest densities of this well‐studied crayfish invader. Conversely, we found greater support for a linear relationship between individual specialization of behavior and intraspecific competition, perhaps because specialization by behavior is not inherently resource‐limited. Our results show that dietary and behavioral specialization may exhibit different responses to increased intraspecific competition, and demonstrate a potential technique that can be used to investigate individual specialization of diet and behavior simultaneously for the same individuals and populations., Individual specialization within populations is increasingly recognized as important in both ecology and evolution, but researchers working on intraspecific variation in behavior and diet infrequently interact. Here, we tested the role of intraspecific competition on individual specialization through analysis of both behavior and diet simultaneously. We found a unimodal relationship between intraspecific competition and individual specialization of diet for populations of an invasive crayfish, but we found greater support for a linear relationship between individual specialization of behavior and intraspecific competition, perhaps because specialization by behavior is not inherently resource‐limited.

Animals from urban areas are regularly brought into wildlife rehabilitation centers, providing untapped potential data records to inform management of wildlife species. Although rescues may be considered a wildlife stewardship behavior, not all ‘rescues’ may be warranted. Some animals are more likely to be brought into a rescue center than others, suggesting that human drivers underlying wildlife rehabilitation efforts are important to understand for urban conservation efforts. Literature has primarily focused on understanding the ecological drivers and implications of wildlife rescues. Our study is the first to investigate both the social and ecological drivers of bird rescues using census, household survey, and intake data. In Phoenix metropolitan area, Arizona, USA in 2017–2018, we found doves and common species were sent to the center most often. Altricial species (helpless at hatching) and young birds were more likely to be brought to the center, perhaps due to perceptions of young animals as vulnerable. We found rescues came from neighborhoods with higher incomes and residents with pro-ecological worldviews, perhaps reflecting a perceived responsibility for wildlife. Conversely, few rescues came from neighborhoods with a high percentage of Hispanic/Latinx residents, who often feel more interdependent with nature. Neighborhoods with greater numbers of rescues were more likely to have residents participating in yard stewardship activities as compared to neighborhoods with fewer rescues. Our findings are relevant to understanding drivers of wildlife stewardship actions and for intake centers who wish to reduce the occurrence of people bringing in wildlife that do not need to be rescued.

Tuberculosis (TB) is the leading infectious cause of death among people living with HIV. People living with HIV are more susceptible to contracting Mycobacterium tuberculosis and often have worsened TB disease. Understanding the immunologic defects caused by HIV and the consequences it has on M. tuberculosis coinfection is critical in combating this global health epidemic. We previously showed in a model of SIV and M. tuberculosis coinfection in Mauritian cynomolgus macaques (MCM) that SIV/M. tuberculosis–coinfected MCM had rapidly progressive TB. We hypothesized that pre-existing SIV infection impairs early T cell responses to M. tuberculosis infection. We infected MCM with SIVmac239, followed by coinfection with M. tuberculosis Erdman 6 mo later. Although similar, TB progression was observed in both SIV+ and SIV-naive animals at 6 wk post–M. tuberculosis infection; longitudinal sampling of the blood (PBMC) and airways (bronchoalveolar lavage) revealed a significant reduction in circulating CD4+ T cells and an influx of CD8+ T cells in airways of SIV+ animals. At sites of M. tuberculosis infection (i.e., granulomas), SIV/M. tuberculosis–coinfected animals had a higher proportion of CD4+ and CD8+ T cells expressing PD-1 and TIGIT. In addition, there were fewer TNF-producing CD4+ T cells in granulomas of SIV/M. tuberculosis–coinfected animals. Taken together, we show that concurrent SIV infection alters T cell phenotypes in granulomas during the early stages of TB disease. As it is critical to establish control of M. tuberculosis replication soon postinfection, these phenotypic changes may distinguish the immune dysfunction that arises from pre-existing SIV infection, which promotes TB progression.