Evolution of predator dispersal in relation to spatio-temporal prey dynamics : how not to get stuck in the wrong place!

Peer reviewedPublisher PD

Can forest management based on natural disturbances maintain ecological resilience?

Given the increasingly global stresses on forests, many ecologists argue that managers must maintain ecological resilience: the capacity of ecosystems to absorb disturbances without undergoing fundamental change. In this review we ask: Can the emerging paradigm of natural-disturbance-based management (NDBM) maintain ecological resilience in managed forests? Applying resilience theory requires careful articulation of the ecosystem state under consideration, the disturbances and stresses that affect the persistence of possible alternative states, and the spatial and temporal scales of management relevance. Implementing NDBM while maintaining resilience means recognizing that (i) biodiversity is important for long-term ecosystem persistence, (ii) natural disturbances play a critical role as a generator of structural and compositional heterogeneity at multiple scales, and (iii) traditional management tends to produce forests more homogeneous than those disturbed naturally and increases the likelihood of unexpected catastrophic change by constraining variation of key environmental processes. NDBM may maintain resilience if silvicultural strategies retain the structures and processes that perpetuate desired states while reducing those that enhance resilience of undesirable states. Such strategies require an understanding of harvesting impacts on slow ecosystem processes, such as seed-bank or nutrient dynamics, which in the long term can lead to ecological surprises by altering the forest's capacity to reorganize after disturbance

Markovian Dynamics on Complex Reaction Networks

Complex networks, comprised of individual elements that interact with each other through reaction channels, are ubiquitous across many scientific and engineering disciplines. Examples include biochemical, pharmacokinetic, epidemiological, ecological, social, neural, and multi-agent networks. A common approach to modeling such networks is by a master equation that governs the dynamic evolution of the joint probability mass function of the underling population process and naturally leads to Markovian dynamics for such process. Due however to the nonlinear nature of most reactions, the computation and analysis of the resulting stochastic population dynamics is a difficult task. This review article provides a coherent and comprehensive coverage of recently developed approaches and methods to tackle this problem. After reviewing a general framework for modeling Markovian reaction networks and giving specific examples, the authors present numerical and computational techniques capable of evaluating or approximating the solution of the master equation, discuss a recently developed approach for studying the stationary behavior of Markovian reaction networks using a potential energy landscape perspective, and provide an introduction to the emerging theory of thermodynamic analysis of such networks. Three representative problems of opinion formation, transcription regulation, and neural network dynamics are used as illustrative examples.Comment: 52 pages, 11 figures, for freely available MATLAB software, see http://www.cis.jhu.edu/~goutsias/CSS%20lab/software.htm

Improved upper limb function in non-ambulant children with SMA type 2 and 3 during nusinersen treatment: a prospective 3-years SMArtCARE registry study

Background The development and approval of disease modifying treatments have dramatically changed disease progression in patients with spinal muscular atrophy (SMA). Nusinersen was approved in Europe in 2017 for the treatment of SMA patients irrespective of age and disease severity. Most data on therapeutic efficacy are available for the infantile-onset SMA. For patients with SMA type 2 and type 3, there is still a lack of sufficient evidence and long-term experience for nusinersen treatment. Here, we report data from the SMArtCARE registry of non-ambulant children with SMA type 2 and typen 3 under nusinersen treatment with a follow-up period of up to 38 months. Methods SMArtCARE is a disease-specific registry with data on patients with SMA irrespective of age, treatment regime or disease severity. Data are collected during routine patient visits as real-world outcome data. This analysis included all non-ambulant patients with SMA type 2 or 3 below 18 years of age before initiation of treatment. Primary outcomes were changes in motor function evaluated with the Hammersmith Functional Motor Scale Expanded (HFMSE) and the Revised Upper Limb Module (RULM). Results Data from 256 non-ambulant, pediatric patients with SMA were included in the data analysis. Improvements in motor function were more prominent in upper limb: 32.4% of patients experienced clinically meaningful improvements in RULM and 24.6% in HFMSE. 8.6% of patients gained a new motor milestone, whereas no motor milestones were lost. Only 4.3% of patients showed a clinically meaningful worsening in HFMSE and 1.2% in RULM score. Conclusion Our results demonstrate clinically meaningful improvements or stabilization of disease progression in non-ambulant, pediatric patients with SMA under nusinersen treatment. Changes were most evident in upper limb function and were observed continuously over the follow-up period. Our data confirm clinical trial data, while providing longer follow-up, an increased number of treated patients, and a wider range of age and disease severity

Species persistence in landscapes with spatial variation in habitat quality: a pair approximation model

Habitat degradation has become a major threat to species persistence. Although several models have explicitly integrated habitat quality into metapopulation dynamics, we still lack knowledge of the spatial variability of species persistence which may result from the clustering of habitat patches of differing quality. Here we construct both pair approximation (PA) and cellular automaton (CA) models for species persistence in homogeneous versus heterogeneous landscapes. Heterogeneous landscapes are generated by varying the orthogonal-neighbour correlation between two different-quality habitats. In our simulations, the PA model exhibits similar population dynamics to the CA model, though it overestimates species persistence due to the doublet approximation neglecting correlation beyond nearest neighbours. Generally, landscape heterogeneity enhances species persistence relative to landscape homogeneity, especially with enlarging habitat-quality difference. This indicates that models based on homogeneous landscapes may overestimate species extinction rate. In heterogeneous landscapes, habitat clumping does not influence global dispersers because of random establishment, although it does promote the persistence of local dispersers, especially under severe habitat degradation. However, habitat configurational fragmentation improves the persistence of global dispersers that are highly sensitive to local crowding, probably by reducing density dependence, but this positive fragmentation effect on local dispersers is overshadowed by the stronger negative border effect on impeding local extension. Furthermore, increasing density dependence promotes the extinction risk of local dispersers, while global dispersers are not influenced. For conservation and habitat management, our results suggest that minimising random anthropogenic disturbance should take priority over increasing the connectivity of good-quality habitat, as random habitat degradation poses a more serious threat to species persistence than clustered habitat degradation. Owing to species' diverse responses to habitat configurational fragmentation, landscapes with different properties may accommodate different species. (C) 2013 Elsevier Ltd. All rights reserved

Dispersal strategies, few dominating or many coexisting: the effect of environmental spatial structure and multiple sources of mortality.

Interspecific competition, life history traits, environmental heterogeneity and spatial structure as well as disturbance are known to impact the successful dispersal strategies in metacommunities. However, studies on the direction of impact of those factors on dispersal have yielded contradictory results and often considered only few competing dispersal strategies at the same time. We used a unifying modeling approach to contrast the combined effects of species traits (adult survival, specialization), environmental heterogeneity and structure (spatial autocorrelation, habitat availability) and disturbance on the selected, maintained and coexisting dispersal strategies in heterogeneous metacommunities. Using a negative exponential dispersal kernel, we allowed for variation of both species dispersal distance and dispersal rate. We showed that strong disturbance promotes species with high dispersal abilities, while low local adult survival and habitat availability select against them. Spatial autocorrelation favors species with higher dispersal ability when adult survival and disturbance rate are low, and selects against them in the opposite situation. Interestingly, several dispersal strategies coexist when disturbance and adult survival act in opposition, as for example when strong disturbance regime favors species with high dispersal abilities while low adult survival selects species with low dispersal. Our results unify apparently contradictory previous results and demonstrate that spatial structure, disturbance and adult survival determine the success and diversity of coexisting dispersal strategies in competing metacommunities