4,446 research outputs found
Vernal Pool Conservation: Enhancing Existing Regulation Through the Creation of the Maine Vernal Pool Special Area Management Plan
Conservation of natural resources is challenging given the competing economic and ecological goals humans have for landscapes. Vernal pools in the northeastern US are seasonal, small wetlands that provide critical breeding habitat for amphibians and invertebrates adapted to temporary waters, and are exceptionally hard to conserve as their function is dependent on connections to other wetlands and upland forests. A team of researchers in Maine joined forces with a diverse array of governmental and private stakeholders to develop an alternative to existing top-down vernal pool regulation. Through creative adoption and revision of various resource management tools, they produced a vernal pool conservation mechanism, the Maine Vernal Pool Special Management Area Plan that meets the needs of diverse stakeholders from developers to ecologists. This voluntary mitigation tool uses fees from impacts to vernal pools in locally identified growth areas to fund conservation of “poolscapes” (pools plus appropriate adjacent habitat) in areas locally designated for rural use. In this case study, we identify six key features of this mechanism that illustrate the use of existing tools to balance growth and pool conservation. This case study will provide readers with key concepts that can be applied to any conservation problem: namely, how to work with diverse interests toward a common goal, how to evaluate and use existing policy tools in new ways, and how to approach solutions to sticky problems through a willingness to accept uncertainty and risk
Model for Dissipative Highly Nonlinear Waves in Dry Granular Systems
A model is presented for the characterization of dissipative effects on
highly nonlinear waves in one-dimensional dry granular media. The model
includes three terms: Hertzian, viscoelastic, and a term proportional to the
square of the relative velocity of particles. The model outcomes are confronted
with different experiments where the granular system is subject to several
constraints for different materials. Excellent qualitative and quantitative
agreement between theory and experiments is found.Comment: Link to the Journal: http://prl.aps.org/abstract/PRL/v104/i11/e11800
Condensation temperature of interacting Bose gases with and without disorder
The momentum-shell renormalization group (RG) is used to study the
condensation of interacting Bose gases without and with disorder. First of all,
for the homogeneous disorder-free Bose gas the interaction-induced shifts in
the critical temperature and chemical potential are determined up to second
order in the scattering length. The approach does not make use of dimensional
reduction and is thus independent of previous derivations. Secondly, the RG is
used together with the replica method to study the interacting Bose gas with
delta-correlated disorder. The flow equations are derived and found to reduce,
in the high-temperature limit, to the RG equations of the classical
Landau-Ginzburg model with random-exchange defects. The random fixed point is
used to calculate the condensation temperature under the combined influence of
particle interactions and disorder.Comment: 7 pages, 2 figure
The Ising Model for Neural Data: Model Quality and Approximate Methods for Extracting Functional Connectivity
We study pairwise Ising models for describing the statistics of multi-neuron
spike trains, using data from a simulated cortical network. We explore
efficient ways of finding the optimal couplings in these models and examine
their statistical properties. To do this, we extract the optimal couplings for
subsets of size up to 200 neurons, essentially exactly, using Boltzmann
learning. We then study the quality of several approximate methods for finding
the couplings by comparing their results with those found from Boltzmann
learning. Two of these methods- inversion of the TAP equations and an
approximation proposed by Sessak and Monasson- are remarkably accurate. Using
these approximations for larger subsets of neurons, we find that extracting
couplings using data from a subset smaller than the full network tends
systematically to overestimate their magnitude. This effect is described
qualitatively by infinite-range spin glass theory for the normal phase. We also
show that a globally-correlated input to the neurons in the network lead to a
small increase in the average coupling. However, the pair-to-pair variation of
the couplings is much larger than this and reflects intrinsic properties of the
network. Finally, we study the quality of these models by comparing their
entropies with that of the data. We find that they perform well for small
subsets of the neurons in the network, but the fit quality starts to
deteriorate as the subset size grows, signalling the need to include higher
order correlations to describe the statistics of large networks.Comment: 12 pages, 10 figure
Synchronization from Disordered Driving Forces in Arrays of Coupled Oscillators
The effects of disorder in external forces on the dynamical behavior of
coupled nonlinear oscillator networks are studied. When driven synchronously,
i.e., all driving forces have the same phase, the networks display chaotic
dynamics. We show that random phases in the driving forces result in regular,
periodic network behavior. Intermediate phase disorder can produce network
synchrony. Specifically, there is an optimal amount of phase disorder, which
can induce the highest level of synchrony. These results demonstrate that the
spatiotemporal structure of external influences can control chaos and lead to
synchronization in nonlinear systems.Comment: 4 pages, 4 figure
Competition between ferro-retrieval and anti-ferro orders in a Hopfield-like network model for plant intelligence
We introduce a simple cellular-network model to explain the capacity of the
plants as memory devices. Following earlier observations (Bose \cite{Bose} and
others), we regard the plant as a network in which each of the elements (plant
cells) are connected via negative (inhibitory) interactions. To investigate the
performance of the network, we construct a model following that of Hopfield,
whose energy function possesses both Hebbian spin glass and anti-ferromagnetic
terms. With the assistance of the replica method, we find that the memory state
of the network decreases enormously due to the effect of the anti-ferromagnetic
order induced by the inhibitory connections. We conclude that the ability of
the plant as a memory device is rather weak.Comment: To be pulished in Physica A (Proc. STATPHYS-KOLKATA V), 9 pages, 6
eps fig
Scaling of the magnetic entropy and magnetization in YbRh_2(Si_{0.95}Ge_{0.05})_2
The magnetic entropy of YbRh_2(Si_{0.95}Ge_{0.05})_2 is derived from
low-temperature ( mK) specific heat measurements. Upon field-tuning
the system to its antiferromagnetic quantum critical point unique temperature
over magnetic field scaling is observed indicating the disintegration of heavy
quasiparticles. The field dependence of the entropy equals the temperature
dependence of the dc-magnetization as expected from the Maxwell relation. This
proves that the quantum-critical fluctuations affect the thermal and magnetic
properties in a consistent way.Comment: 6 pages, 2 figures, manuscript submitted to SCES2004 conferenc
Gamete donor anonymity and limits on numbers of offspring: the views of three stakeholders
This paper discusses the attitudes of three groups of stakeholders in the world of assisted reproduction gamete donors, parents who use donated gamete, and offspring conceived with donated gametes with respect to the two issues of donor anonymity and limits on the number of offspring a single donor can produce. The data are drawn from on-line surveys which were made available between May 12, 2104 and August 15, 2014 to gamete donors, donor-conceived offspring, and parents who used donated gametes to conceive. A total of 325 donors (176 egg donors; 149 sperm donors) responded to the survey as did 2134 parents and 419 offspring. The data show that offspring are more opposed to donor anonymity than are parents and donors. Among offspring opposition to anonymity grows as they age. On the other hand, parents are most in favor of limits on numbers of offspring produced by a single donor. Parents worry about health and accidental contact between people conceived from the same donor
- …