Modularity buffers the spread of spatial perturbations in macroalgal networks

Theory predicts that spatial modular networks contain the propagation of local disturbances, but field experimental tests of this hypothesis are lacking. We combined a field experiment with a metacommunity model to assess the role of modularity in buffering the spatial spread of algal turfs in three replicated canopy-dominated macroalgal networks. Experimental networks included three modules where plots with intact canopy cover (nodes) were connected through canopy-thinned corridors. The local perturbation consisted of removal of the canopy and understory species from four nodes within a single module to enable the establishment of algal turfs, which could then spread vegetatively to other untouched nodes through the canopy-thinned links. Results show that algal turfs invade mainly untouched nodes in the perturbed module, in agreement with the hypothesis that modularity can effectively constrain the spread of a spatial perturbation. The metacommunity model supports the empirical findings, illustrating greater resistance to perturbations of modular than random macroalgal canopy networks and making alternative explanations for the observed results unlikely. Evidence that the buffering effect of modularity can operate in natural environmental conditions has important implications for designing more robust networks of protected areas and less-fragile human-dominated fragmented landscapes.

Resource Flow Network Structure Drives Metaecosystem Function

AbstractNonliving resources frequently flow across ecosystem boundaries, which can yield networks of spatially coupled ecosystems. Yet the significance of resource flows for ecosystem function has predominantly been understood by studying two or a few coupled ecosystems, overlooking the broader resource flow network and its spatial structure. Here, we investigate how the spatial structure of larger resource flow networks influences ecosystem function at metaecosystem scales by analyzing metaecosystem models with homogeneously versus heterogeneously distributed resource flow networks but otherwise identical characteristics. We show that metaecosystem function can differ strongly between metaecosystems with contrasting resource flow networks. Differences in function generally arise through the scaling up of nonlinear local processes interacting with spatial variation in local dynamics, the latter of which is influenced by network structure. However, we find that neither network structure guarantees the greatest metaecosystem function. Rather, biotic (organism traits) and abiotic (resource flow rates) properties interact with network structure to determine which yields greater metaecosystem function. Our findings suggest that the spatial structure of resource flow networks coupling ecosystems can be a driver of ecosystem function at landscape scales. Furthermore, our study demonstrates how modifications to the structural, biotic, or abiotic properties of metaecosystem networks can have nontrivial large-scale effects on ecosystem function.

Spatial correlation reverses the compound effect of multiple stressors on rocky shore biofilm

Understanding how multifactorial fluctuating environments affect species and communities remains one of the major challenges in ecology. The spatial configuration of the environment is known to generate complex patterns of correlation among multiple stressors. However, to what extent the spatial correlation between simultaneously fluctuating variables affects ecological assemblages in real-world conditions remains poorly understood. Here, we use field experiments and simulations to assess the influence of spatial correlation of two relevant climate variables - warming and sediment deposition following heavy precipitation - on the biomass and photosynthetic activity of rocky intertidal biofilm. First, we used a response-surface design experiment to establish the relation between biofilm, warming, and sediment deposition in the field. Second, we used the response surface to generate predictions of biofilm performance under different scenarios of warming and sediment correlation. Finally, we tested the predicted outcomes by manipulating the degree of correlation between the two climate variables in a second field experiment. Simulations stemming from the experimentally derived response surface showed how the degree and direction (positive or negative) of spatial correlation between warming and sediment deposition ultimately determined the nonlinear response of biofilm biomass (but not photosynthetic activity) to fluctuating levels of the two climate variables. Experimental results corroborated these predictions, probing the buffering effect of negative spatial correlation against extreme levels of warming and sediment deposition. Together, these results indicate that consideration of nonlinear response functions and local-scale patterns of correlation between climate drivers can improve our understanding and ability to predict ecological responses to multiple processes in heterogeneous environments.

Diversity of Molluscan Assemblage in Relation to Biotic and Abiotic Variables in Brown Algal Forests

Canopy-forming macroalgae, mainly those belonging to the order Fucales, form the so-called brown algal forests, which are among the most productive assemblages in shallow coastal zones. Their vertical, branching canopies increase nearshore primary production, provide nursery areas for juvenile fish, and sustain understory assemblages of smaller algae and both sessile and vagile fauna. The majority of benthic invertebrates inhabiting these forests have larval stages that spend some time floating freely or swimming in the plankton. Therefore, canopy-forming macroalgae play an important role as species collectors related to larval supply and hydrodynamic processes. During the past several decades, brown algal forests have significantly reduced their extension and coverage in the Mediterranean basin, due to multiple interacting natural and anthropogenic pressures, with negative consequences also for the related fauna. The aim of this research was to examine how differences in macrophyte abundance and structure, as well as environmental variables, affect the associated molluscan communities in the shallow northern Adriatic Sea. Sampling sites with well-developed vegetation cover dominated by different canopy-forming species were selected in the shallow infralittoral belt of the northern Adriatic Sea in the spring–summer period of the years 2019 and 2020. Our results confirm the importance of algal forests for molluscan assemblage, with a total of 68 taxa of molluscs found associated with macrophytes. Gastropods showed the highest richness and abundance, followed by bivalves. Mollusc richness and diversity (in terms of biotic indices) were not related with the degree of development of canopy-forming species (in terms of total cover and total volume), nor with the ecological status of benthic macroalgae at different depths. On the contrary, the variability in molluscan taxa abundances was explained by some environmental variables, such as temperature, pH, light, and nitrates concentration.

First Restoration Experiment for Gongolaria barbata in Slovenian Coastal Waters. What Can Go Wrong?

The global decline of brown algal forests along rocky coasts is causing an exceptional biodiversity loss. Regardless of conservation efforts, different techniques have been developed for large-scale restoration strategies in the Mediterranean Sea. In this study we tested ex situ pilot restoration of Gongolaria barbata (=Treptacantha barbata) for the first time in Slovenian coastal waters. Healthy apical fronds of the species were collected and the development of recruits on clay tiles was followed under laboratory conditions for 20 days. Despite the experimental difficulties experienced, especially due to the lack of antibiotics to prevent the growth of the biofilm, G. barbata recruits were outplanted in the sea on two concrete plates with 48 tiles each, protected by purpose-built cages to avoid grazing by herbivorous fish. The high survival rate of juveniles after four months in the field (89% of the tiles on the plate that was constantly protected) suggests that outplanting G. barbata is an operable approach for restoration efforts in the northern Adriatic Sea. Our first experiment in Slovenian coastal waters provides new information for the optimization of the best practices during the laboratory cultivation and addresses the early steps of restoration and introduction of young thalli in the natural environment.

Heterogeneity of ecological patterns, processes, and funding of marine manipulative field experiments conducted in Southeastern Pacific coastal ecosystems

Ecological manipulative experiments conducted in marine coastal ecosystems have substantially improved ecological theory during the last decades and have provided useful knowledge for the management and conservation of coastal ecosystems. Although different studies report global trends in ecological patterns worldwide, Southeastern Pacific coastal ecosystems have been poorly considered. Given that the SE Pacific coast encompasses diverse coastal ecosystems, consideration of studies conducted along this range can shed light on the heterogeneity of processes regulating coastal communities. We reviewed the biotic interactions and habitat type considered, as well as the complexity in terms of spatial and temporal extent of manipulative field experimental studies conducted along the SE Pacific coast from 0°S to 56°S (Ecuador to Chile). We test the effect of funding reported by different studies as a main factor limiting experimental complexity. From field ecological studies published from 1970 to 2016, we found that 81 studies were truly manipulative, in which one or multiple factors were "manipulated." Around 77% of these studies were located between 21°S and 40°S, and conducted in intertidal rocky habitats. An increase in experimental studies was observed between 2010 and 2015, especially focused on herbivore-alga interactions, although we found that both the temporal extent and spatial extent of these studies have shown a decrease in recent decades. Funding grant amount reported had a positive effect on elapsed time of field experiments, but no effect was observed on spatial extent or in the biotic interactions considered. Elapsed time of experiments was different among the main biotic interactions considered, that is, herbivory, predation, and competition. We suggest that to further progress in applied ecological knowledge, it will be necessary to consider pollution and urbanization processes explicitly using a field experimental framework. This information could improve our understanding of how ecosystems present along the SE Pacific coast respond to climate change and increased levels of human interventions.

Experimental evidence of spatial signatures of approaching regime shifts in macroalgal canopies

Developing early warning signals to predict regime shifts in ecosystems is a central issue in current ecological research. While there are many studies addressing temporal early warning indicators, research into spatial indicators is far behind, with field experiments even more rare. Here, we tested the performance of spatial early warning signals in an intertidal macroalgal system, where removal of algal canopies pushed the system toward a tipping point (corresponding to approximately 75% of canopy loss), marking the transition between a canopy- to a turf-dominated state. We performed a two-year experiment where spatial early warning indicators were assessed in transects where the canopy was differentially removed (from 0 to 100%). Unlike Moran correlation coefficient at lag-1, spatial variance, skewness, and spatial spectra at low frequency increased along the gradient of canopy degradation and dropped, or did not show any further increase beyond the transition point from a canopy- to a turf-dominated state (100% canopy removal). Our study provides direct evidence of the suitability of spatial early warning signals to anticipate regime shifts in natural ecosystems, emphasizing the importance of field experiments as a powerful tool to establish causal relationships between environmental stressors and early warning indicators.

Migrate or evolve: options for plant pathogens under climate change

Findings on climate change influence on plant pathogens are often inconsistent and context dependent. Knowledge of pathogens affecting agricultural crops and natural plant communities remains fragmented along disciplinary lines. By broadening the perspective beyond agriculture, this review integrates cross-disciplinary knowledge to show that at scales relevant to climate change, accelerated evolution and changing geographic distribution will be the main implications for pathogens. New races may evolve rapidly under elevated temperature and CO2 , as evolutionary forces act on massive pathogen populations boosted by a combination of increased fecundity and infection cycles under favourable microclimate within enlarged canopy. Changing geographic distribution will bring together diverse lineages/genotypes that do not share common ecological niche, potentially increasing pathogen diversity. However, the uncertainty of model predictions and a lack of synthesis of fragmented knowledge remain as major deficiencies in knowledge. The review contends that the failure to consider scale and human intervention through new technology are major sources of uncertainty. Recognizing that improved biophysical models alone will not reduce uncertainty, it proposes a generic framework to increase focus and outlines ways to integrate biophysical elements and technology change with human intervention scenarios to minimize uncertainty. To synthesize knowledge of pathogen biology and life history, the review borrows the concept of 'fitness' from population biology as a comprehensive measure of pathogen strengths and vulnerabilities, and explores the implications of pathogen mode of nutrition to fitness and its interactions with plants suffering chronic abiotic stress under climate change. Current and future disease management options can then be judged for their ability to impair pathogenic and saprophytic fitness. The review pinpoints improving confidence in model prediction by minimizing uncertainty, developing management strategies to reduce overall pathogen fitness, and finding new sources of data to trawl for climate signatures on pathogens as important challenges for future research.

Scaling Up in Ecology: Mechanistic Approaches

Ecologists have long grappled with the problem of scaling up from tractable, small-scale observations and experiments to the prediction of large-scale patterns. Although there are multiple approaches to this formidable task, there is a common underpinning in the formulation, testing, and use of mechanistic response functions to describe how phenomena interact across scales. Here, we review the principles of response functions to illustrate how they provide a means to guide research, extrapolate beyond measured data, and simplify our conceptual grasp of reality. We illustrate these principles with examples of mechanistic approaches ranging from explorations of the ecological niche, random walks, and macrophysiology to theories dealing with scale transition, self-organization, and the prediction of extremes.

Integrating mechanistic organism–environment interactions into the basic theory of community and evolutionary ecology

This paper presents an overview of how mechanistic knowledge of organism–environment interactions, including biomechanical interactions of heat, mass and momentum transfer, can be integrated into basic theoretical population biology through mechanistic functional responses that quantitatively describe how organisms respond to their physical environment. Integrating such functional responses into simple community and microevolutionary models allows scaling up of the organism-level understanding from biomechanics both ecologically and temporally. For community models, Holling-type functional responses for predator–prey interactions provide a classic example of the functional response affecting qualitative model dynamics, and recent efforts are expanding analogous models to incorporate environmental influences such as temperature. For evolutionary models, mechanistic functional responses dependent on the environment can serve as fitness functions in both quantitative genetic and game theoretic frameworks, especially those concerning function-valued traits. I present a novel comparison of a mechanistic fitness function based on thermal performance curves to a commonly used generic fitness function, which quantitatively differ in their predictions for response to environmental change. A variety of examples illustrate how mechanistic functional responses enhance model connections to biologically relevant traits and processes as well as environmental conditions and therefore have the potential to link theoretical and empirical studies. Sensitivity analysis of such models can provide biologically relevant insight into which parameters and processes are important to community and evolutionary responses to environmental change such as climate change, which can inform conservation management aimed at protecting response capacity. Overall, the distillation of detailed knowledge or organism–environment interactions into mechanistic functional responses in simple population biology models provides a framework for integrating biomechanics and ecology that allows both tractability and generality.