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Edward R. Carr, Grant Fleming, and Tshibangu Kalala

. 2002 , p. 416) note that, among the Mossi inhabitants of Bonam village in Burkina Faso, [c]ollecting water and firewood expands the boundaries of [women’s] observations to the uncultivated bush. Women note fluctuations in water levels in ponds and wells and in the production of wild fruit that they collect to cook or sell in the market. They also observe insect behavior at water sources and in rubbish heaps. For instance, bugvaré are black insects of the Orthoptera sp. that dig concave nests in

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Marianne Cohen, Josyane Ronchail, María Alonso-Roldán, Céline Morcel, Stéphane Angles, Eduardo Araque-Jimenez, and David Labat

with stakeholders and farmers led to the innovation and improvement of our scientific approach and of its results. This process required open-mindedness on the part of each researcher. b. Data 1) Climatic data The analyses of the local climate 1 and its evolution are based on local daily rainfall and temperatures from the Spanish Meteorological State Agency database [Agencia Estatal de Meteorología (AEMET)] ( Fig. 3 ; see the appendix ; Table A1 ). The description of the current climate is based

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Markus Enenkel, Daniel Osgood, Martha Anderson, Bristol Powell, Jessica McCarty, Christopher Neigh, Mark Carroll, Margaret Wooten, Greg Husak, Christopher Hain, and Molly Brown

distribution of rainfall. The rainy season is fairly homogenous ( Black et al. 2016 ) and driven primarily by the intertropical convergence zone (ITCZ) and what is known as the Zaire Air Boundary (ZAB). Fig . 4. Topography (m; based on GTOPO30) and estimated population distribution (people per grid square) at a spatial resolution of 0.000 83 decimal degrees (approximately 100 m at the equator) for (top) Senegal, (middle) Ethiopia, and (bottom) Zambia; note that the legend values are unique for each country

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Calum G. Turvey, Apurba Shee, and Ana Marr

relatively homogenous across farms in a particular heat unit isocline. Variance in weather conditions—heat and rainfall—can shift the stages across calendar date boundaries, however, rendering the ideal of specificity benign. A possible approach would be to widen the date range so that in probability the shifting patterns of weather affecting a particular stage of growth (e.g., silking in corn) would adequately be captured. From this point of view, basing WII on broader phenological stages may be a

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J. D. Tamerius, M. S. Perzanowski, L. M. Acosta, J. S. Jacobson, I. F. Goldstein, J. W. Quinn, A. G. Rundle, and J. Shaman

1. Introduction Numerous studies link weather and climate conditions to human health outcomes ( Tamerius et al. 2007 ). In many cases, however, the mechanisms responsible for the linkage between specific health outcomes, weather, and climate are not clearly understood. A more comprehensive understanding of these mechanisms is required to mitigate current environmentally mediated health risks, and predict the effects of future climate and environmental change on human welfare ( Ebi et al. 2006

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Daniel Tobin, Rama Radhakrishna, Allison Chatrchyan, and Shorna B. Allred

. Ascertaining the perceived challenges and opportunities to implementing programming is important to increase the likelihood of successfully encouraging behavior change ( Burke 2002 ). The current study addresses this need by exploring the barriers and priorities that researchers and Extension professionals at land-grant universities in the northeastern United States perceive in translating scientific information into useful programming for agricultural and natural resource audiences. While many previous

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Amy Savage, Lisa Schubert, Corey Huber, Hilary Bambrick, Nina Hall, and Bill Bellotti

of low-quality humanitarian food assistance, impaired livelihoods, volatile and rising food prices, and food system instability, among others ( Asch et al. 2018 ; Barnett 2011 ; Bell et al. 2016 ; Campbell 2015 ; Campbell and Warrick 2014 ; Savage et al. 2020a ; Taylor et al. 2016 ). These effects are likely to exacerbate the current shift away from diverse, minimally processed diets, to a lower-quality diet high in fat, sugar, and salt and increasing prevalence of diet-related NCDs such as

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Majid Shafiee-Jood, Tatyana Deryugina, and Ximing Cai

forecasts. We refer to a new evidence (i.e., forecast–observation pairs) that leads to a positive change in trust ( Δ μ τ = μ τ t + 1 − μ τ t > 0 ) as trust strengthening , whereas trust-weakening evidence leads to a negative change in trust ( Δ μ τ < 0 ). According to Eqs. (8) and (9) , the user’s trust is not only influenced by the new evidence but also depends on the user’s current trust level. In other words, as Fig. 4 illustrates, there are forecast–observation pairs that could be trust

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Joshua J. Hatzis, Jennifer Koch, and Harold E. Brooks

adoption of the EF scale in 2007, rural tornadoes may have been underrated and there may have been more violent tornadoes than the records currently indicate ( Strader et al. 2015 ). A good example of a tornado that was likely underrated was the tornado that hit El Reno, Oklahoma, on 31 May 2013. This tornado tracked over mostly rural areas and did not hit many DIs, resulting in a rating of only EF3. However, a mobile Doppler unit (RaXPol) recorded multiple wind speed measurements exceeding 100 m s −1

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Carol R. Ember, Ian Skoggard, Benjamin Felzer, Emily Pitek, and Mingkai Jiang

). The widely used Palmer drought severity index (PDSI) contains information about antecedent and current soil moisture ( Alley 1984 ) and is computed from 1901 to 2009 ( Van der Schrier et al. 2013 ). The two precipitation minus evaporation indices, which describe the deficit of soil moisture were developed by Felzer et al. (2020) from monthly temperature, precipitation, and Penman–Monteith potential evapotranspiration (PET_pm) data from 1901 to 2014. One version of the precipitation minus

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