Elisha Hendel, Harel Bacher, Adi Oksenberg, Harkamal Walia, Nimrod Schwartz, and Zvi Peleg. 2021. “Deciphering the genetic basis of wheat seminal root anatomy uncovers ancestral axial conductance alleles.” Plant, Cell & EnvironmentPlant, Cell & EnvironmentPlant Cell Environ, n/a, n/a. Publisher's Version Abstract
ABSTRACT Root axial conductance which describes the ability of water to move through the xylem, contributes to the rate of water uptake from the soil throughout the whole plant lifecycle. Under the rainfed wheat agro-system, grain-filling is typically occurring during declining water availability (i.e. terminal drought). Therefore, preserving soil water moisture during grain filling could serve as a key adaptive trait. We hypothesized that lower wheat root axial conductance can promote higher yields under terminal drought. A segregating population derived from a cross between durum wheat and its direct progenitor wild emmer wheat was used to underpin the genetic basis of seminal root architectural and functional traits. We detected 75 QTL associated with seminal roots morphological, anatomical, and physiological traits, with several hotspots harboring co-localized QTL. We further validated the axial conductance and central metaxylem QTL using wild introgression lines. Field-based characterization of genotypes with contrasting axial conductance suggested the contribution of low axial conductance as a mechanism for water conservation during grain filling and consequent increase in grain size and yield. Our findings underscore the potential of harnessing wild alleles to reshape the wheat root system architecture and associated hydraulic properties for greater adaptability under changing climate. This article is protected by copyright. All rights reserved.
Shilo Shiff, David Helman, and Itamar M Lensky. 2021. “Worldwide continuous gap-filled MODIS land surface temperature dataset.” Scientific Data, 8, 1, Pp. 74 - 74. Publisher's Version Abstract
Satellite land surface temperature (LST) is vital for climatological and environmental studies. However, LST datasets are not continuous in time and space mainly due to cloud cover. Here we combine LST with Climate Forecast System Version 2 (CFSv2) modeled temperatures to derive a continuous gap filled global LST dataset at a spatial resolution of 1 km. Temporal Fourier analysis is used to derive the seasonality (climatology) on a pixel-by-pixel basis, for LST and CFSv2 temperatures. Gaps are filled by adding the CFSv2 temperature anomaly to climatological LST. The accuracy is evaluated in nine regions across the globe using cloud-free LST (mean values: R2 = 0.93, Root Mean Square Error (RMSE) = 2.7 °C, Mean Absolute Error (MAE) = 2.1 °C). The provided dataset contains day, night, and daily mean LST for the Eastern Mediterranean. We provide a Google Earth Engine code and a web app that generates gap filled LST in any part of the world, alongside a pixel-based evaluation of the data in terms of MAE, RMSE and Pearson’s r.
Adam Lampert and Andrew M. Liebhold. 2021. “Combining multiple tactics over time for cost-effective eradication of invading insect populations.” Ecology Letters, 24, 2, Pp. 279 - 287. Publisher's Version Abstract
Abstract Because of the profound ecological and economic impacts of many non-native insect species, early detection and eradication of newly founded, isolated populations is a high priority for preventing damages. Though successful eradication is often challenging, the effectiveness of several treatment methods/tactics is enhanced by the existence of Allee dynamics in target populations. Historically, successful eradication has often relied on the application of two or more tactics. Here, we examine how to combine three treatment tactics in the most cost-effective manner, either simultaneously or sequentially in a multiple-annum process. We show that each tactic is most efficient across a specific range of population densities. Furthermore, we show that certain tactics inhibit the efficiency of other tactics and should therefore not be used simultaneously; but since each tactic is effective at specific densities, different combinations of tactics should be applied sequentially through time when a multiple-annum eradication programme is needed.
Yael Arien, Arnon Dag, Shiran Yona, Zipora Tietel, Taly Lapidot Cohen, and Sharoni Shafir. 2020. “Effect of diet lipids and omega-6:3 ratio on honey bee brood development, adult survival and body composition,” 124, Pp. 104074. Publisher's Version Abstract
Lipids have a key role in a variety of physiological functions in insects including energy, reproduction, growth and development. Whereas most of the required fatty acids can be synthesized endogenously, omega-3 and omega-6 polyunsaturated fatty acids (PUFA) are essential fatty acids that must be acquired through nutrition. Honey bees (Apis mellifera) obtain lipids from pollen, but different pollens vary in nutritional composition, including of PUFAs. Low floral diversity and abundance may expose bees to nutritional stress. We tested the effect of total lipids concentration and their omega-6:3 ratio on aspects of honey bee physiology: brood development, adult longevity and body fatty acids composition. All three parameters were affected by dietary lipid concentration and omega-6:3 ratio. Higher lipid concentration in diet increased brood production, and high omega-6:3 ratio increased mortality rate and decreased brood rearing. Fatty acid analysis of the bees showed that the amount of lipids and the omega-6:3 ratio in their body generally reflected the composition of the diet on which they fed. Consistent with previous findings of the importance of a balanced omega-6:3 ratio diet for learning performance, we found that such a balanced PUFA diet, with above threshold total lipid composition, is also necessary for maintaining proper colony development.
A major challenge in ecosystem management is to promote cooperation among the multiple agents that manage the ecosystem. In particular, sharing information among the agents is often essential for reaching a desirable collective treatment. However, it is unclear how the sharing of information affects the incentives of selfish agents to cooperate and contribute to the common environmental project. Here, we consider a harmful species population that migrates across lands and causes damages to multiple agents, each of which aims to minimize her/his own costs due to both treatment and damages over time. We use game-theoretical models and compare the resulting collective treatment in three scenarios that differ in the information that agents have about (1) the true contribution of their neighbors to the treatment and (2) the true damages inflicted on their neighbors by the harmful species. We demonstrate that sharing such social information may incentivize the agents to free ride on their neighbors’ contributions, thereby reducing the efficiency of the collective treatment. This implies that monitoring and sharing information may have negative consequences, and the extent to which information should be shared in joint projects necessitates a careful examination.
Harmful species are becoming increasingly prevalent due to trade globalization and climate change. A major question is how international cooperation and coordination can help to mitigate the spread of harmful species. In this study, we show that a single country may be able to abate the harmful species population effectively. However, when the countries need to control the harmful species at a low density for prolonged periods, a joint effort results in maintaining the harmful species at a lower density. In particular, controlling the harmful species in certain hot spot locations is often the key to preventing global spreads of harmful species, which implies that international cooperation is necessary for achieving effective treatment.The management of harmful species, including invasive species, pests, parasites, and diseases, is a major global challenge. Harmful species cause severe damage to ecosystems, biodiversity, agriculture, and human health. In particular, managing harmful species often requires cooperation among multiple agents, such as landowners, agencies, and countries. Each agent may have incentives to contribute less to the treatment, leaving more work for other agents, which may result in inefficient treatment. A central question is, therefore, how should a policymaker allocate treatment duties among the agents? Specifically, should the agents work together in the same area, or should each agent work only in a smaller area designated just for her/him? We consider a dynamic game-theoretic model, where a Nash equilibrium corresponds to a possible set of contributions that the agents could adopt over time. In turn, the allocation by the policymaker determines which of the Nash equilibria could be adopted, which allows us to compare the outcome of various allocations. Our results show that fewer agents can abate the harmful species population faster, but more agents can better control the population to keep its density lower. We prove this result in a general theorem and demonstrate it numerically for two case studies. Therefore, following an outbreak, the better policy would be to split and assign one or a few agents to treat the species in a given location, but if controlling the harmful species population at some low density is needed, the agents should work together in all of the locations.