Masting by Eighteen New Zealand Plant Species: The Role of Temperature as a Synchronizing Cue

Masting, the intermittent production of large flower or seed crops by a population of perennial plants, can enhance the reproductive success of participating plants and drive fluctuations in seed-consumer populations and other ecosystem components over large geographic areas. The spatial and taxonomic extent over which masting is synchronized can determine its success in enhancing individual plant fitness as well as its ecosystem-level effects, and it can indicate the types of proximal cues that enable reproductive synchrony. Here, we demonstrate high intra- and intergeneric synchrony in mast seeding by 17 species of New Zealand plants from four families across \u3e150000 km2. The synchronous species vary ecologically (pollination and dispersal modes) and are geographically widely separated, so intergeneric synchrony seems unlikely to be adaptive per se. Synchronous fruiting by these species was associated with anomalously high temperatures the summer before seedfall, a cue linked with the La Niña phase of El Niño–Southern Oscillation. The lone asynchronous species appears to respond to summer temperatures, but with a 2-yr rather than 1-yr time lag. The importance of temperature anomalies as cues for synchronized masting suggests that the timing and intensity of masting may be sensitive to global climate change, with widespread effects on taxonomically disparate plant and animal communities

Identification of the top TESS objects of interest for atmospheric characterization of transiting exoplanets with JWST

Funding: Funding for the TESS mission is provided by NASA's Science Mission Directorate. This work makes use of observations from the LCOGT network. Part of the LCOGT telescope time was granted by NOIRLab through the Mid-Scale Innovations Program (MSIP). MSIP is funded by NSF. This paper is based on observations made with the MuSCAT3 instrument, developed by the Astrobiology Center and under financial support by JSPS KAKENHI (grant No. JP18H05439) and JST PRESTO (grant No. JPMJPR1775), at Faulkes Telescope North on Maui, HI, operated by the Las Cumbres Observatory. This paper makes use of data from the MEarth Project, which is a collaboration between Harvard University and the Smithsonian Astrophysical Observatory. The MEarth Project acknowledges funding from the David and Lucile Packard Fellowship for Science and Engineering, the National Science Foundation under grant Nos. AST-0807690, AST-1109468, AST-1616624 and AST-1004488 (Alan T. Waterman Award), the National Aeronautics and Space Administration under grant No. 80NSSC18K0476 issued through the XRP Program, and the John Templeton Foundation. C.M. would like to gratefully acknowledge the entire Dragonfly Telephoto Array team, and Bob Abraham in particular, for allowing their telescope bright time to be put to use observing exoplanets. B.J.H. acknowledges support from the Future Investigators in NASA Earth and Space Science and Technology (FINESST) program (grant No. 80NSSC20K1551) and support by NASA under grant No. 80GSFC21M0002. K.A.C. and C.N.W. acknowledge support from the TESS mission via subaward s3449 from MIT. D.R.C. and C.A.C. acknowledge support from NASA through the XRP grant No. 18-2XRP18_2-0007. C.A.C. acknowledges that this research was carried out at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration (80NM0018D0004). S.Z. and A.B. acknowledge support from the Israel Ministry of Science and Technology (grant No. 3-18143). The research leading to these results has received funding from the ARC grant for Concerted Research Actions, financed by the Wallonia-Brussels Federation. TRAPPIST is funded by the Belgian Fund for Scientific Research (Fond National de la Recherche Scientifique, FNRS) under the grant No. PDR T.0120.21. The postdoctoral fellowship of K.B. is funded by F.R.S.-FNRS grant No. T.0109.20 and by the Francqui Foundation. H.P.O.'s contribution has been carried out within the framework of the NCCR PlanetS supported by the Swiss National Science Foundation under grant Nos. 51NF40_182901 and 51NF40_205606. F.J.P. acknowledges financial support from the grant No. CEX2021-001131-S funded by MCIN/AEI/ 10.13039/501100011033. A.J. acknowledges support from ANID—Millennium Science Initiative—ICN12_009 and from FONDECYT project 1210718. Z.L.D. acknowledges the MIT Presidential Fellowship and that this material is based upon work supported by the National Science Foundation Graduate Research Fellowship under grant No. 1745302. P.R. acknowledges support from the National Science Foundation grant No. 1952545. This work is partly supported by JSPS KAKENHI grant Nos. JP17H04574, JP18H05439, JP21K20376; JST CREST grant No. JPMJCR1761; and Astrobiology Center SATELLITE Research project AB022006. This publication benefits from the support of the French Community of Belgium in the context of the FRIA Doctoral Grant awarded to M.T. D.D. acknowledges support from TESS Guest Investigator Program grant Nos. 80NSSC22K1353, 80NSSC22K0185, and 80NSSC23K0769. A.B. acknowledges the support of M.V. Lomonosov Moscow State University Program of Development. T.D. was supported in part by the McDonnell Center for the Space Sciences. V.K. acknowledges support from the youth scientific laboratory project, topic FEUZ-2020-0038.JWST has ushered in an era of unprecedented ability to characterize exoplanetary atmospheres. While there are over 5000 confirmed planets, more than 4000 Transiting Exoplanet Survey Satellite (TESS) planet candidates are still unconfirmed and many of the best planets for atmospheric characterization may remain to be identified. We present a sample of TESS planets and planet candidates that we identify as “best-in-class” for transmission and emission spectroscopy with JWST. These targets are sorted into bins across equilibrium temperature Teq and planetary radius Rp and are ranked by a transmission and an emission spectroscopy metric (TSM and ESM, respectively) within each bin. We perform cuts for expected signal size and stellar brightness to remove suboptimal targets for JWST. Of the 194 targets in the resulting sample, 103 are unconfirmed TESS planet candidates, also known as TESS Objects of Interest (TOIs). We perform vetting and statistical validation analyses on these 103 targets to determine which are likely planets and which are likely false positives, incorporating ground-based follow-up from the TESS Follow-up Observation Program to aid the vetting and validation process. We statistically validate 18 TOIs, marginally validate 31 TOIs to varying levels of confidence, deem 29 TOIs likely false positives, and leave the dispositions for four TOIs as inconclusive. Twenty-one of the 103 TOIs were confirmed independently over the course of our analysis. We intend for this work to serve as a community resource and motivate formal confirmation and mass measurements of each validated planet. We encourage more detailed analysis of individual targets by the community.Peer reviewe

Research To Develop Contraceptive Control of Brushtail Possums in New Zealand

Common brushtail possums are serious pests in New Zealand, where they threaten the survival of native plants and animals and spread bovine tuberculosis. A National Science Strategy Committee established in 1991 to coordinate possum research gave high priority to research aimed at biological control of possums, particularly contraceptive control. Surveys are identifying pathogens and potential vectors, and research has begun on immunology, gene transcription, potential contraceptive targets, and sociobiology. As there are more than 60 million possums in New Zealand, contraceptive vaccine delivery systems need to be cost effective, and they must be publicly acceptable. A vaccine could be included in a bait, but long-term cost-effective control will probably require a biological vector. Eventually the best control strategy will probably combine traditional control and immunocontraception

Monitoring the cost-effectiveness of aerial 1080 and ground hunting for possum control

Cataloguing-in-Publication dat

Quantifying the direct transfer costs of common brushtail possum dispersal using least-cost modelling: a combined cost-surface and accumulated-cost dispersal kernel approach.

Dispersal costs need to be quantified from empirical data and incorporated into dispersal models to improve our understanding of the dispersal process. We are interested in quantifying how landscape features affect the immediately incurred direct costs associated with the transfer of an organism from one location to another. We propose that least-cost modelling is one method that can be used to quantify direct transfer costs. By representing the landscape as a cost-surface, which describes the costs associated with traversing different landscape features, least-cost modelling is often applied to measure connectivity between locations in accumulated-cost units that are a combination of both the distance travelled and the costs traversed. However, we take an additional step by defining an accumulated-cost dispersal kernel, which describes the probability of dispersal in accumulated-cost units. This novel combination of cost-surface and accumulated-cost dispersal kernel enables the transfer stage of dispersal to incorporate the effects of landscape features by modifying the direction of dispersal based on the cost-surface and the distance of dispersal based on the accumulated-cost dispersal kernel. We apply this approach to the common brushtail possum (Trichosurus vulpecula) within the North Island of New Zealand, demonstrating how commonly collected empirical dispersal data can be used to calibrate a cost-surface and associated accumulated-cost dispersal kernel. Our results indicate that considerable improvements could be made to the modelling of the transfer stage of possum dispersal by using a cost-surface and associated accumulated-cost dispersal kernel instead of a more traditional straight-line distance based dispersal kernel. We envisage a variety of ways in which the information from this novel combination of a cost-surface and accumulated-cost dispersal kernel could be gainfully incorporated into existing dispersal models. This would enable more realistic modelling of the direct transfer costs associated with the dispersal process, without requiring existing dispersal models to be abandoned

Possum dispersal kernels based on straight-line distance and accumulated-cost.

<p>Examples of the dispersal kernel calibration from connectivity values of observed possum dispersal events for (A) the highest-ranked cost-surface landscape representation (DTR in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0088293#pone-0088293-t002" target="_blank">Table 2</a>), and (B) the uniform landscape representation (D in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0088293#pone-0088293-t002" target="_blank">Table 2</a>). A stacked histogram of the possum dispersal events categorised by sex is shown along with the fitted lognormal dispersal kernel's probability density function (PDF), and both the cumulative distribution function (CDF) and the inverted cumulative distribution function (1-CDF).</p

Dispersal events as straight-lines and least-cost paths.

<p>Examples of nine of the 65 radio-collared brushtail possum dispersal events used to calibrate the dispersal kernels. To allow for the effect of incorporating landscape features to be shown, both the straight-line distances associated with the uniform landscape representation (D, in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0088293#pone-0088293-t002" target="_blank">Table 2</a>) and the least-cost paths associated with the highest ranked cost-surface landscape representation (DTR, in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0088293#pone-0088293-t002" target="_blank">Table 2</a>) are shown. While the straight-line distances do not consider the landscape at all, the least-cost paths avoid both rivers and areas without tree and scrub cover.</p

The locations of six studies that provided empirical possum dispersal data.

<p>Dispersal of possums was measured either directly using radio-telemetry or indirectly using landscape genetics, and each study was associated with a variety of different landscape environments across the North Island of New Zealand categorised on the basis of differences in climate, landform, and soils <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0088293#pone.0088293-Leathwick1" target="_blank">[53]</a>.</p