Effects of plant invasions on ecosystem processes: Linking above- and below-ground resource-use strategies of native and invasive species in Eastern U.S. forests

Despite the increasing number of non-native invasive species worldwide and their potential impacts on ecosystems, the mechanisms that invaders alter ecosystem nutrient processes remain elusive. Invaders are often more productive than native species which suggests invaders may have different above- and below-ground resource-use strategies that can profoundly alter ecosystem processes. Here I investigated above- and below-ground plant traits and soil properties associated with resource-use strategies and soil nitrogen (N) dynamics for multiple native and non-native forest understory species in the Eastern U.S. to better understand invader impacts on ecosystem processes. In the first study, performed in a common garden, I examined the linkage between above- and below-ground resource-use strategies for native and invasive species that allow invaders to be more productive than co-occurring natives. Results showed that, despite invaders losing a significant amount of N from litter, they had greater root production and specific root length associated with a greater soil nutrient uptake capacity than natives. In the second study, I examined whether the different tissue traits are associated with litter decomposition rate and if invaders can increase nutrient cycling through faster litter decomposition than natives. Results revealed no differences in leaf and root decomposition rates between native and non-native forest understory woody species, suggesting that litter decomposition rate is not a process that invasive species affect with regard to soil nutrient processes in the Eastern U.S. forests. Finally, I investigated invader impacts on soil N processes in a monoculture experiment. After two growing seasons, invaders had greater above- and below-ground productivity. Invaders facilitated N cycling via greater litter N input into the soil that increased soil N availability, and had greater fine root production and SRL that increased plant N uptake. Although the greater aboveground production of invaders reduced soil temperature and moisture, which can reduce soil microbial activity, the stimulatory effects of a greater flow of litter N to the soil appeared to overwhelm any negative effects that invaders had on the soil microclimate. Taken together, my results suggest that invaders have different above-and below-ground resource-use strategies and invaders\u27 greater productivity is one of the major drivers that can significantly change ecosystem processes

Bio-Inspired Adaptive Cooperative Control of Heterogeneous Robotic Networks

We introduce a new adaptive cooperative control strategy for robotic networks comprised of heterogeneous members. The proposed feedback synchronization exploits an active parameter adaptation strategy as opposed to adaptive parameter estimation of adaptive control theory. Multiple heterogeneous robots or vehicles can coordinate their motions by parameter adaptation analogous to bio-genetic mutation and adaptation. In contrast with fixed gains used by consensus theory, both the tracking control and diffusive coupling gains are automatically computed based on the adaptation law, the synchronization errors, and the tracking errors of heterogeneous robots. The optimality of the proposed adaptive cooperative control is studied via inverse optimal control theory. The proposed adaptive cooperative control can be applied to any network structure. The stability proof, by using a relatively new nonlinear stability tool, contraction theory, shows globally asymptotically synchronized motion of a heterogeneous robotic network. This adaptive cooperative control can be widely applied to cooperative control of unmanned aerial vehicles (UAVs), formation flying spacecraft, and multi-robot systems. Results of the simulation show the effectiveness of the proposed adaptive cooperative control laws especially for a network comprised of heterogeneous members

Exponential Stability Region Estimates for the State-Dependent Riccati Equation Controllers

We investigate the nonlinear exponential stability of the State-Dependent Riccati Equation (SDRE)-based control. The SDRE technique is a nonlinear control method, which has emerged since the mid 1990's and has been applied to a wide range of nonlinear control problems. Despite the systematic method of SDRE, it is difficult to prove stability because the general analytic solution to the SDRE is not known. Some notable prior work has shown local asymptotic stability of SDRE by using numerical and analytical methods. In this paper, we introduce a new strategy, based on contraction analysis, to estimate the exponential stability region for SDRE controlled systems. Examples demonstrate the superiority of the proposed method

Cooperative Control with Adaptive Graph Laplacians for Spacecraft Formation Flying

This paper investigates exact nonlinear dynamics and cooperative control for spacecraft formation flying with Earth oblateness (J2 perturbation) and atmospheric drag effects. The nonlinear dynamics for chief and deputy motions are derived by using Gauss' variational equation and the Euler-Lagrangian formulation, respectively. The proposed cooperative control employs adaptive time-varying Laplacian gains. The tracking and diffusive coupling gains are adapted by the synchronization/tracking errors and distance-based connectivity, thereby defining a time-varying network topology. Moreover, the proposed method relaxes the network structure requirement and permits an unbalanced graph. Nonlinear stability is proven by contraction analysis and incremental input-to-state stability. Numerical examples show the effectiveness of the proposed method

Bio-Inspired Adaptive Cooperative Control of Heterogeneous Robotic Networks

We introduce a new adaptive cooperative control strategy for robotic networks comprised of heterogeneous members. The proposed feedback synchronization exploits an active parameter adaptation strategy as opposed to adaptive parameter estimation of adaptive control theory. Multiple heterogeneous robots or vehicles can coordinate their motions by parameter adaptation analogous to bio-genetic mutation and adaptation. In contrast with fixed gains used by consensus theory, both the tracking control and diffusive coupling gains are automatically computed based on the adaptation law, the synchronization errors, and the tracking errors of heterogeneous robots. The optimality of the proposed adaptive cooperative control is studied via inverse optimal control theory. The proposed adaptive cooperative control can be applied to any network structure. The stability proof, by using a relatively new nonlinear stability tool, contraction theory, shows globally asymptotically synchronized motion of a heterogeneous robotic network. This adaptive cooperative control can be widely applied to cooperative control of unmanned aerial vehicles (UAVs), formation flying spacecraft, and multi-robot systems. Results of the simulation show the effectiveness of the proposed adaptive cooperative control laws especially for a network comprised of heterogeneous members

Exponential Stability Region Estimates for the State-Dependent Riccati Equation Controllers

We investigate the nonlinear exponential stability of the State-Dependent Riccati Equation (SDRE)-based control. The SDRE technique is a nonlinear control method, which has emerged since the mid 1990's and has been applied to a wide range of nonlinear control problems. Despite the systematic method of SDRE, it is difficult to prove stability because the general analytic solution to the SDRE is not known. Some notable prior work has shown local asymptotic stability of SDRE by using numerical and analytical methods. In this paper, we introduce a new strategy, based on contraction analysis, to estimate the exponential stability region for SDRE controlled systems. Examples demonstrate the superiority of the proposed method

Cooperative Control with Adaptive Graph Laplacians for Spacecraft Formation Flying

This paper investigates exact nonlinear dynamics and cooperative control for spacecraft formation flying with Earth oblateness (J2 perturbation) and atmospheric drag effects. The nonlinear dynamics for chief and deputy motions are derived by using Gauss' variational equation and the Euler-Lagrangian formulation, respectively. The proposed cooperative control employs adaptive time-varying Laplacian gains. The tracking and diffusive coupling gains are adapted by the synchronization/tracking errors and distance-based connectivity, thereby defining a time-varying network topology. Moreover, the proposed method relaxes the network structure requirement and permits an unbalanced graph. Nonlinear stability is proven by contraction analysis and incremental input-to-state stability. Numerical examples show the effectiveness of the proposed method

Shifts in dominant tree mycorrhizal associations in response to anthropogenic impacts

Plant-fungal symbioses play critical roles in vegetation dynamics and nutrient cycling, modulating the impacts of global changes on ecosystem functioning. Here, we used forest inventory data consisting of more than 3 million trees to develop a spatially resolved “mycorrhizal tree map” of the contiguous United States. We show that abundances of the two dominant mycorrhizal tree groups—arbuscular mycorrhizal (AM) and ectomycorrhizal trees—are associated primarily with climate. Further, we show that anthropogenic influences, primarily nitrogen (N) deposition and fire suppression, in concert with climate change, have increased AM tree dominance during the past three decades in the eastern United States. Given that most AM-dominated forests in this region are underlain by soils with high N availability, our results suggest that the increasing abundance of AM trees has the potential to induce nutrient acceleration, with critical consequences for forest productivity, ecosystem carbon and nutrient retention, and feedbacks to climate change

Phase Synchronization Control of Robotic Networks on Periodic Ellipses with Adaptive Network Topologies

This paper presents a novel formation control method for a large number of robots or vehicles described by Euler-Lagrange (EL) systems moving in elliptical orbits. A new coordinate transformation method for phase synchronization of networked EL systems in elliptical trajectories is introduced to define desired formation patterns. The proposed phase synchronization controller synchronizes the motions of agents, thereby yielding a smaller synchronization error than an uncoupled control law in the presence of bounded disturbances. A complex time-varying and switching network topology, constructed by the adaptive graph Laplacian matrix, relaxes the standard requirement of consensus stability, even permitting stabilization on an arbitrary unbalanced graph. The proofs of stability are constructed by robust contraction analysis, a relatively new nonlinear stability tool. An example of reconfiguring swarms of spacecraft in Low Earth Orbit shows the effectiveness of the proposed phase synchronization controller for a large number of complex EL systems moving in elliptical orbits