Climate and plant community diversity in space and time.

Climate strongly shapes plant diversity over large spatial scales, with relatively warm and wet (benign, productive) regions supporting greater numbers of species. Unresolved aspects of this relationship include what causes it, whether it permeates to community diversity at smaller spatial scales, whether it is accompanied by patterns in functional and phylogenetic diversity as some hypotheses predict, and whether it is paralleled by climate-driven changes in diversity over time. Here, studies of Californian plants are reviewed and new analyses are conducted to synthesize climate-diversity relationships in space and time. Across spatial scales and organizational levels, plant diversity is maximized in more productive (wetter) climates, and these consistent spatial relationships are mirrored in losses of taxonomic, functional, and phylogenetic diversity over time during a recent climatic drying trend. These results support the tolerance and climatic niche conservatism hypotheses for climate-diversity relationships, and suggest there is some predictability to future changes in diversity in water-limited climates

Integrating species traits into species pools

Despite decades of research on the species‐pool concept and the recent explosion of interest in trait‐based frameworks in ecology and biogeography, surprisingly little is known about how spatial and temporal changes in species‐pool functional diversity (SPFD) influence biodiversity and the processes underlying community assembly. Current trait‐based frameworks focus primarily on community assembly from a static regional species pool, without considering how spatial or temporal variation in SPFD alters the relative importance of deterministic and stochastic assembly processes. Likewise, species‐pool concepts primarily focus on how the number of species in the species pool influences local biodiversity. However, species pools with similar richness can vary substantially in functional‐trait diversity, which can strongly influence community assembly and biodiversity responses to environmental change. Here, we integrate recent advances in community ecology, trait‐based ecology, and biogeography to provide a more comprehensive framework that explicitly considers how variation in SPFD, among regions and within regions through time, influences the relative importance of community assembly processes and patterns of biodiversity. First, we provide a brief overview of the primary ecological and evolutionary processes that create differences in SPFD among regions and within regions through time. We then illustrate how SPFD may influence fundamental processes of local community assembly (dispersal, ecological drift, niche selection). Higher SPFD may increase the relative importance of deterministic community assembly when greater functional diversity in the species pool increases niche selection across environmental gradients. In contrast, lower SPFD may increase the relative importance of stochastic community assembly when high functional redundancy in the species pool increases the influence of dispersal history or ecological drift. Next, we outline experimental and observational approaches for testing the influence of SPFD on assembly processes and biodiversity. Finally, we highlight applications of this framework for restoration and conservation. This species‐pool functional diversity framework has the potential to advance our understanding of how local‐ and regional‐scale processes jointly influence patterns of biodiversity across biogeographic regions, changes in biodiversity within regions over time, and restoration outcomes and conservation efforts in ecosystems altered by environmental change

When does intraspecific trait variation contribute to functional beta-diversity?

Summary Intraspecific trait variation (ITV) is hypothesized to play an important role in community assembly and the maintenance of biodiversity. However, fundamental gaps remain in our understanding of how ITV contributes to mechanisms that create spatial variation in the functional-trait composition of communities (functional Β-diversity). Importantly, ITV may influence the perceived importance of environmental filtering across spatial scales. We examined how ITV contributes to functional Β-diversity and environmental filtering in woody plant communities in a temperate forest in the Ozark ecoregion, Missouri, USA. To test the hypothesis that ITV contributes to changes in the perceived importance of environmental filtering across scales, we compared patterns of functional Β-diversity across soil-resource and topographic gradients at three spatial grains and three spatial extents. To quantify the contribution of ITV to functional Β-diversity, we compared patterns that included ITV in five traits (leaf area, specific leaf area, leaf water content, leaf toughness and chlorophyll content) to patterns based on species-mean trait values. Functional Β-diversity that included ITV increased with spatial extent and decreased with spatial grain, suggesting stronger environmental filtering within spatially extensive landscapes that contain populations locally adapted to different habitats. In contrast, functional β-diversity based on species-mean trait values increased with spatial extent but did not change with spatial grain, suggesting weaker environmental filtering among larger communities which each contain a variety of habitats and locally adapted populations. Synthesis. Although studies typically infer community assembly mechanisms from species-mean trait values, our study suggests that mean trait values may mask the strength of assembly mechanisms such as environmental filtering, especially in landscape-scale studies that encompass strong environmental gradients and locally adapted populations. Our study highlights the utility of integrating ITV into studies of functional Β-diversity to better understand the ecological conditions under which trait variation within and among species contributes most strongly to patterns of biodiversity across spatial scales

Ontogenetic trait variation influences tree community assembly across environmental gradients

Intraspecific trait variation is hypothesized to influence the relative importance of community assembly mechanisms. However, few studies have explicitly considered how intraspecific trait variation among ontogenetic stages influences community assembly across environmental gradients. Because the relative importance of abiotic and biotic assembly mechanisms can differ among ontogenetic stages within and across environments, ontogenetic trait variation may have an important influence on patterns of functional diversity and inferred assembly mechanisms. We tested the hypothesis that variation in functional diversity across a topo-edaphic gradient differs among ontogenetic stages and that these patterns reflect a shift in the relative importance of different assembly mechanisms. In a temperate forest in the Missouri Ozarks, USA, we compared functional diversity of leaf size and specific leaf area (SLA) of 34 woody plant species at two ontogenetic stages (adults and saplings) to test predictions about how the relative importance of abiotic and biotic filtering changes among adult and sapling communities. Local communities of adults had lower mean SLA and lower functional dispersion of SLA than expected by chance, particularly at the resource-limited end of the topo-edaphic gradient, suggesting an important role for abiotic filtering among co-occurring adults. In contrast, local communities of saplings often had higher functional dispersion of leaf size and SLA than expected by chance regardless of their location along the topo-edaphic gradient, suggesting an important role for biotic filtering among co-occurring saplings. Moreover, the overall strength of trait-environment relationships varied between saplings and adults for both leaf traits, generally resulting in stronger environmental shifts in mean trait values and trait dispersion for adults relative to saplings. Our results illustrate how community assembly mechanisms may shift in their relative importance during ontogeny, leading to variable patterns of functional diversity across environmental gradients. Moreover, our results highlight the importance of integrating ontogeny, an important axis of intraspecific trait variability, into approaches that use plant functional traits to understand community assembly and species coexistence

Active Collaborative Localization in Heterogeneous Robot Teams

Accurate and robust state estimation is critical for autonomous navigation of robot teams. This task is especially challenging for large groups of size, weight, and power (SWAP) constrained aerial robots operating in perceptually-degraded GPS-denied environments. We can, however, actively increase the amount of perceptual information available to such robots by augmenting them with a small number of more expensive, but less resource-constrained, agents. Specifically, the latter can serve as sources of perceptual information themselves. In this paper, we study the problem of optimally positioning (and potentially navigating) a small number of more capable agents to enhance the perceptual environment for their lightweight,inexpensive, teammates that only need to rely on cameras and IMUs. We propose a numerically robust, computationally efficient approach to solve this problem via nonlinear optimization. Our method outperforms the standard approach based on the greedy algorithm, while matching the accuracy of a heuristic evolutionary scheme for global optimization at a fraction of its running time. Ultimately, we validate our solution in both photorealistic simulations and real-world experiments. In these experiments, we use lidar-based autonomous ground vehicles as the more capable agents, and vision-based aerial robots as their SWAP-constrained teammates. Our method is able to reduce drift in visual-inertial odometry by as much as 90%, and it outperforms random positioning of lidar-equipped agents by a significant margin. Furthermore, our method can be generalized to different types of robot teams with heterogeneous perception capabilities. It has a wide range of applications, such as surveying and mapping challenging dynamic environments, and enabling resilience to large-scale perturbations that can be caused by earthquakes or storms.Comment: To appear in Robotics: Science and Systems (RSS) 202

What Made Me the Teacher I Am Today? A Reflection by Selected Leonore Annenberg-Woodrow Wilson Teaching Fellows

The report offers a series of short essays from 18 teachers, each reflecting on what inspired and guided them into the teaching profession. Some of the highlights include:"I've come to realize that my learning process in the classroom actually feels a whole lot like the science I practiced at the bench: engineering experimental procedures, collecting and analyzing data, and formulating questions about next steps. It turns out that my scientific worldview can really improve learning outcomes for my students," said Kristin Milks, a biology and earth science teacher in Bloomington, IN, who enrolled in a teacher preparation program shortly after completing her Ph.D. in biochemistry."What transforms someone from being a good teacher to being a great teacher is the passion to make connections with students, to constantly evaluate and adjust their practice to do what is in the students' best interest," said Catherine Ann Haney, a Virginia Spanish teacher who has recently been teaching in Santiago, Chile."Enrolling in a teacher education program, instead of starting my career as a teacher first and then obtaining my master's degree after, meant I had a cohort of other soon-to-be teachers to learn with as we persevered through a very rigorous and demanding year," said Jeremy Cress, a math teacher in Philadelphia."I realized that being a good math teacher does not mean explaining clearly, making kids like me, or making math fun. Rather, it means giving students the opportunity to solve problems by themselves from start to finish, to struggle and persevere, and to learn from each other's particular strengths," said Brittany Leknes, a math teacher from Sunnyvale, CA."Together my students and I co-create their identities, their sense of themselves, and their understanding of their place in society. Because I believe wholly in my students' own power, I teach to disrupt school cultures that suggest that students need to be anything less than their whole selves," said Kayla Vinson, who taught social students in the Harlem Children's Zone.Created in 2007, the Leonore Annenberg-Woodrow Wilson Teaching Fellowship was designed to serve as the equivalent of a national "Rhodes Scholarship" for teaching. Working with Stanford University, the University of Pennsylvania, the University of Virginia, and the University of Washington, the Woodrow Wilson Foundation provided $30,000 stipends for exceptionally able candidates to complete a yearlong master's degree program. In exchange, the teacher candidates agreed to teach for three years in high-need secondary schools across the country. The Leonore Annenberg Teaching Fellowship was funded through grants from the Annenberg Foundation and Carnegie Corporation of New York. It served as the basis for the Woodrow Wilson Foundation's successful Teaching Fellowship program, which now operates in five states (Georgia, Indiana, Michigan, New Jersey, and Ohio), operating in partnership with 28 universities. Woodrow Wilson Teaching Fellows complete a rigorous yearlong master's degree program, coupled with a robust yearlong clinical experience. Once they earn their degrees, Woodrow Wilson Teaching Fellows teach in high-need STEM classrooms, while receiving three years of coaching and mentoring

Soil Microbial Networks Shift Across a High-Elevation Successional Gradient.

While it is well established that microbial composition and diversity shift along environmental gradients, how interactions among microbes change is poorly understood. Here, we tested how community structure and species interactions among diverse groups of soil microbes (bacteria, fungi, non-fungal eukaryotes) change across a fundamental ecological gradient, succession. Our study system is a high-elevation alpine ecosystem that exhibits variability in successional stage due to topography and harsh environmental conditions. We used hierarchical Bayesian joint distribution modeling to remove the influence of environmental covariates on species distributions and generated interaction networks using the residual species-to-species variance-covariance matrix. We hypothesized that as ecological succession proceeds, diversity will increase, species composition will change, and soil microbial networks will become more complex. As expected, we found that diversity of most taxonomic groups increased over succession, and species composition changed considerably. Interestingly, and contrary to our hypothesis, interaction networks became less complex over succession (fewer interactions per taxon). Interactions between photosynthetic microbes and any other organism became less frequent over the gradient, whereas interactions between plants or soil microfauna and any other organism were more abundant in late succession. Results demonstrate that patterns in diversity and composition do not necessarily relate to patterns in network complexity and suggest that network analyses provide new insight into the ecology of highly diverse, microscopic communities

Robust Localization of Aerial Vehicles via Active Control of Identical Ground Vehicles

This paper addresses the problem of active collaborative localization in heterogeneous robot teams with unknown data association. It involves positioning a small number of identical unmanned ground vehicles (UGVs) at desired positions so that an unmanned aerial vehicle (UAV) can, through unlabelled measurements of UGVs, uniquely determine its global pose. We model the problem as a sequential two player game, in which the first player positions the UGVs and the second identifies the two distinct hypothetical poses of the UAV at which the sets of measurements to the UGVs differ by as little as possible. We solve the underlying problem from the vantage point of the first player for a subclass of measurement models using a mixture of local optimization and exhaustive search procedures. Real-world experiments with a team of UAV and UGVs show that our method can achieve centimeter-level global localization accuracy. We also show that our method consistently outperforms random positioning of UGVs by a large margin, with as much as a 90% reduction in position and angular estimation error. Our method can tolerate a significant amount of random as well as non-stochastic measurement noise. This indicates its potential for reliable state estimation on board size, weight, and power (SWaP) constrained UAVs. This work enables robust localization in perceptually-challenged GPS-denied environments, thus paving the road for large-scale multi-robot navigation and mapping.Comment: To appear in IROS 202

Wave-induced loss of ultra-relativistic electrons in the Van Allen radiation belts.

The dipole configuration of the Earth's magnetic field allows for the trapping of highly energetic particles, which form the radiation belts. Although significant advances have been made in understanding the acceleration mechanisms in the radiation belts, the loss processes remain poorly understood. Unique observations on 17 January 2013 provide detailed information throughout the belts on the energy spectrum and pitch angle (angle between the velocity of a particle and the magnetic field) distribution of electrons up to ultra-relativistic energies. Here we show that although relativistic electrons are enhanced, ultra-relativistic electrons become depleted and distributions of particles show very clear telltale signatures of electromagnetic ion cyclotron wave-induced loss. Comparisons between observations and modelling of the evolution of the electron flux and pitch angle show that electromagnetic ion cyclotron waves provide the dominant loss mechanism at ultra-relativistic energies and produce a profound dropout of the ultra-relativistic radiation belt fluxes