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1. Plasticity’s role in adaptive evolution depends on environmental change components

   https://doi.org/10.1016/j.tree.2022.08.008  

   Vinton, Anna C.; Gascoigne, Samuel J.L.; Sepil, Irem; Salguero-Gómez, Roberto (December 2022, Trends in Ecology & Evolution)

   Dr Andrea E. A. Stephens (Ed.)

   To forecast extinction risks of natural populations under climate change and direct human impacts, an integrative understanding of both phenotypic plasticity and adaptive evolution is essential. To date, the evidence for whether, when, and how much plasticity facilitates adaptive responses in changing environments is contradictory. We argue that explicitly considering three key environmental change components – rate of change, variance, and temporal autocorrelation – affords a unifying framework of the impact of plasticity on adaptive evolution. These environmental components each distinctively effect evolutionary and ecological processes underpinning population viability. Using this framework, we develop expectations regarding the interplay between plasticity and adaptive evolution in natural populations. This framework has the potential to improve predictions of population viability in a changing world. 

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2. Examining plant physiological responses to climate change through an evolutionary lens

   https://doi.org/10.​1104/​pp.​16.​00793  

   Becklin, Katie M.; Anderson, Jill T.; Gerhart, Laci M.; Wadgymar, Susana M.; Wessinger, Carolyn A.; Ward, Joy K. (October 2016, Plant Physiology)

   Since the Industrial Revolution began approximately 200 years ago, global atmospheric carbon dioxide concentration ([CO2]) has increased from 270 to 401 µL L−1, and average global temperatures have risen by 0.85°C, with the most pronounced effects occurring near the poles (IPCC, 2013). In addition, the last 30 years were the warmest decades in 1,400 years (PAGES 2k Consortium, 2013). By the end of this century, [CO2] is expected to reach at least 700 µL L−1, and global temperatures are projected to rise by 4°C or more based on greenhouse gas scenarios (IPCC, 2013). Precipitation regimes also are expected to shift on a regional scale as the hydrologic cycle intensifies, resulting in greater extremes in dry versus wet conditions (Medvigy and Beaulieu, 2012). Such changes already are having profound impacts on the physiological functioning of plants that scale up to influence interactions between plants and other organisms and ecosystems as a whole (Fig. 1). Shifts in climate also may alter selective pressures on plants and, therefore, have the potential to influence evolutionary processes. In some cases, evolutionary responses can occur as rapidly as only a few generations (Ward et al., 2000; Franks et al., 2007; Lau and Lennon, 2012), but there is still much to learn in this area, as pointed out by Franks et al. (2014). Such responses have the potential to alter ecological processes, including species interactions, via ecoevolutionary feedbacks (Shefferson and Salguero-Gómez, 2015). In this review, we discuss microevolutionary and macroevolutionary processes that can shape plant responses to climate change as well as direct physiological responses to climate change during the recent geologic past as recorded in the fossil record. We also present work that documents how plant physiological and evolutionary responses influence interactions with other organisms as an example of how climate change effects on plants can scale to influence higher order processes within ecosystems. Thus, this review combines findings in plant physiological ecology and evolutionary biology for a comprehensive view of plant responses to climate change, both past and present. 

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3. Impacts of Limited Model Resolution on the Representation of Mountain Wave and Secondary Gravity Wave Dynamics in Local and Global Models. 1: Mountain Waves in the Stratosphere and Mesosphere

   https://doi.org/10.1029/2021JD035990  

   Fritts, David C.; Lund, Adam C.; Lund, Thomas S.; Yudin, Valery (May 2022, Journal of Geophysical Research: Atmospheres)

   Abstract Long‐term efforts have sought to extend global model resolution to smaller scales enabling more accurate descriptions of gravity wave (GW) sources and responses, given their major roles in coupling and variability throughout the atmosphere. Such studies reveal significant improvements accompanying increasing resolution, but no guidance on what is sufficient to approximate reality. We take the opposite approach, using a finite‐volume model solving the Navier‐Stokes equations exactly. The reference simulation addresses mountain wave (MW) generation and responses over the Southern Andes described using isotropic 500 m, central resolution by Fritts et al. (2021),https://doi.org/10.1175/JAS-D-20-0207.1and Lund et al. (2020),https://doi.org/10.1175/JAS-D-19-0356.1. Reductions of horizontal resolution to 1 and 2 km result in (a) systematic increases in initial MW breaking altitudes, (b) weaker, larger‐scale generation of secondary GWs and acoustic waves accompanying these dynamics, and (c) significantly weaker and less extended responses in the mesosphere in latitude and longitude. Horizontal resolution of 4 km largely suppresses instabilities, but allows weak, sustained mean‐flow interactions. Responses for 8 km resolution are very weak and fail to capture any aspects of the high‐resolution responses. The chosen mean winds allow efficient MW penetration into the mesosphere and lower thermosphere, hence only exhibit strong pseudo‐momentum deposition and mean wind decelerations at higher altitudes. A companion paper by Fritts et al. (2022),https://doi.org/10.1029/2021JD036035explores the impacts of decreasing resolution on responses in the thermosphere. 

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4. TrkB Activation during a Critical Period Mimics the Protective Effects of Early Visual Experience on Perception and the Stability of Receptive Fields in Adult Superior Colliculus

   https://doi.org/10.1523/JNEUROSCI.2598-18.2019  

   Mudd, David B.; Balmer, Timothy S.; Kim, So Yeon; Machhour, Noura; Pallas, Sarah L. (June 2019, The Journal of Neuroscience)

   na (Ed.)

   During a critical period in development, spontaneous and evoked retinal activity shape visual pathways in an adaptive fashion. Interestingly, spontaneous activity is sufficient for spatial refinement of visual receptive fields (RFs) in superior colliculus (SC) and visual cortex (V1), but early visual experience is necessary to maintain inhibitory synapses and stabilize RFs in adulthood (Carrasco et al., 2005, 2011; Carrasco and Pallas, 2006; Balmer and Pallas, 2015a). In V1, BDNF and its high-affinity receptor TrkB are important for development of visual acuity, inhibition, and regulation of the critical period for ocular dominance plasticity (Hanover et al., 1999; Huang et al., 1999; Gianfranceschi et al., 2003). To examine the generality of this signaling pathway for visual system plasticity, the present study examined the role of TrkB signaling during the critical period for RF refinement in SC. Activating TrkB receptors during the critical period (P33–P40) in dark reared subjects produced normally refined RFs, and blocking TrkB receptors in light-exposed animals resulted in enlarged adult RFs like those in dark reared animals. We also report here that deprivation- or TrkB blockade-induced RF enlargement in adulthood impaired fear responses to looming overhead stimuli and negatively impacted visual acuity. Thus, early TrkB activation is both necessary and sufficient to maintain visual RF refinement, robust looming responses, and visual acuity in adulthood. These findings suggest a common signaling pathway exists for the maturation of inhibition between V1 and SC. 

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5. Rapid assimilation and analysis of a suit of remote sensing data for predicting extreme events and their impact on ecological-human systems

   https://doi.org/doi.org/10.2172/1769770  

   N. Falco1, B. J. (January 2021, AI4ESP White Papers)

   null (Ed.)

   The science needed to understand and mitigate the impacts of global change on the biosphere will require both unprecedented access to diverse biological and environmental data across space, time, and scales and the synthesis and development of predictive theory (Dietze et al., 2018, Bush et al., 2017, Hampton et al., 2013). In this white paper, we argue that while environmental data from RS have been accumulating at a rapid pace, their broad scope generates major challenges for finding effective ways to discover, access, integrate, curate, and analyze the range and volume of relevant information. Second, to generalize and improve forecasts, there is an urgent need to harness big data and data synthesis with the vision and foresight of analytical and quantitative theory. We identify the key ML/AI capabilities to further enhance the predictability of ecosystem models: (1) enhanced connectivity from RS to model parameterization, (2) theory/model-informed RS-based estimation. Enhanced connectivity from RS to model parameterization. RS data together with data 

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