Habitat size influences community stability

Ecosystem-size relationships of river populations and communities

Knowledge of ecosystem-size influences on river populations and communities is integral to the balancing of human and environmental needs for water. The multiple dimensions of dendritic river networks complicate understanding of ecosystem-size influences, but could be resolved by the development of scaling relationships. We highlight the importance of physical constraints limiting predator body sizes, movements, and population sizes in small rivers, and where river contraction limits space or creates stressful conditions affecting community stability and food webs. Investigations of the scaling and contingency of these processes will be insightful because of the underlying generality and scale independence of such relationships. Doing so will also pinpoint damaging water-management practices and identify which aspects of river size can be most usefully manipulated in river restoration.

Perturbation responses in co-evolved model meta-communities

A spatially explicit eco-evolutionary model assembles simulated meta-communities which are subjected to species and community perturbation experiments to determine factors affecting the stability of the global ecosystem. Spatial structure and resource variety increase the persistence of the ensembles against the removal of an individual species, yet they remain vulnerable to re-invasion by an existing member of the meta-community if it is introduced to all patches with minimal population. Optimal reserve placement strategies are identified for maximally preserving global biodiversity from the effects of sequences of patch disruption, and targeted reserve placement that shields the most or the rarest biodiversity is usually effective. However, if disturbed populations are permitted to re-settle in neighboring patches, then reserves should also be situated remotely to isolate their residents from invasion.

Spatial and Ecological Scaling of Stability in Spatial Community Networks

There are many scales at which to quantify stability in spatial and ecological networks. Local-scale analyses focus on specific nodes of the spatial network, while regional-scale analyses consider the whole network. Similarly, species- and community-level analyses either account for single species or for the whole community. Furthermore, stability itself can be defined in multiple ways, including resistance (the inverse of the relative displacement caused by a perturbation), initial resilience (the rate of return after a perturbation), and invariability (the inverse of the relative amplitude of the population fluctuations). Here, we analyze the scale-dependence of these stability properties. More specifically, we ask how spatial scale (local vs. regional) and ecological scale (species vs. community) influence these stability properties. We find that regional initial resilience is the weighted arithmetic mean of the local initial resiliences. The regional resistance is the harmonic mean of local resistances, which makes regional resistance particularly vulnerable to nodes with low stability, unlike regional initial resilience. Analogous results hold for the relationship between community- and species-level initial resilience and resistance. Both resistance and initial resilience are “scale-free” properties: regional and community values are simply the biomass-weighted means of the local and species values, respectively. Thus, one can easily estimate both stability metrics of whole networks from partial sampling. In contrast, invariability generally is greater at the regional and community-level than at the local and species-level, respectively. Hence, estimating the invariability of spatial or ecological networks from measurements at the local or species level is more complicated, requiring an unbiased estimate of the network (i.e., region or community) size. In conclusion, we find that scaling of stability depends on the metric considered, and we present a reliable framework to estimate these metrics.

Food web rewiring drives long-term compositional differences and late-disturbance interactions at the community level

Multiple anthropogenic disturbances affect the structure and functioning of communities. Recent evidence highlighted that, after pulse disturbance, the functioning a community performs may be recovered fast due to functional redundancy, whereas community multivariate composition needs a longer time. Yet, the mechanisms that drive the different community recovery times have not been quantified empirically. We use quantitative food-web analysis to assess the influence of species interactions on community recovery. We found species-interactions strength to be the main mechanism driving differences between structural and functional recovery. Additionally, we show that interactions between multiple disturbances appear in the long term only when both species-interaction strength and food-web architecture change significantly.

Ecological communities are constantly exposed to multiple natural and anthropogenic disturbances. Multivariate composition (if recovered) has been found to need significantly more time to be regained after pulsed disturbance compared to univariate diversity metrics and functional endpoints. However, the mechanisms driving the different recovery times of communities to single and multiple disturbances remain unexplored. Here, we apply quantitative ecological network analyses to try to elucidate the mechanisms driving long-term community-composition dissimilarity and late-stage disturbance interactions at the community level. For this, we evaluate the effects of two pesticides, nutrient enrichment, and their interactions in outdoor mesocosms containing a complex freshwater community. We found changes in interactions strength to be strongly related to compositional changes and identified postdisturbance interaction-strength rewiring to be responsible for most of the observed compositional changes. Additionally, we found pesticide interactions to be significant in the long term only when both interaction strength and food-web architecture are reshaped by the disturbances. We suggest that quantitative network analysis has the potential to unveil ecological processes that prevent long-term community recovery.