Resistance and resilience have become important concepts in the evaluation of disturbance events, providing a framework that is useful in light of the expected increase in frequency and occurrences of hurricanes as a consequence of climate change. Hurricane Maria landed on Puerto Rico as a category 4 storm in September of 2017. Among the affected elements were agricultural systems, including coffee agroecosystems. Historically, coffee has been a major backbone of the island’s agricultural sector. Grown with a range of management styles, the coffee agroecosystem provides an excellent model system to study the resistance/resilience of agroecosystems faced with hurricane disturbance. Sampling 28 farms and comparing pre-hurricane data (2013) with post hurricane data we find that management style had only a small effect on either resistance or resilience, likely due to the especially strong nature of the storm. Rather, the socio-political context of individual farms seems to be a more useful predictor of resilience.
Ecological systems, as is often noted, are complex. Equally notable is the generalization that complex systems tend to be oscillatory, whether Huygens' simple patterns of pendulum entrainment or the twisted chaotic orbits of Lorenz’ convection rolls. The analytics of oscillators may thus provide insight into the structure of ecological systems. One of the most popular analytical tools for such study is the Kuramoto model of coupled oscillators. We apply this model as a stylized vision of the dynamics of a well-studied system of pests and their enemies, to ask whether its actual natural history is reflected in the dynamics of the qualitatively instantiated Kuramoto model. Emerging from the model is a series of synchrony groups generally corresponding to subnetworks of the natural system, with an overlying chimeric structure, depending on the strength of the inter-oscillator coupling. We conclude that the Kuramoto model presents a novel window through which interesting questions about the structure of ecological systems may emerge.
Ecosystem management is integral to the future of soils, yet anthropogenic drivers represent a key source of uncertainty in ecosystem models. First- and new-generation soil models formulate many soil pools using first-order decomposition, which tends to generate simpler yet numerous parameters. Systems or complexity theory, developed across various scientific and social fields, may help improve robustness of soil models, by offering consistent assumptions about system openness, potential dynamic instability and distance from commonly assumed stable equilibria, as well as new analytical tools for formulating more generalized model structures that reduce parameter space and yield a wider array of possible model outcomes, such as quickly shrinking carbon stocks with pulsing or lagged respiration. This paper builds on recent perspectives of soil modeling to ask how various soil functions can be better understood by applying a complex systems lens. We synthesized previous literature reviews with concepts from non-linear dynamical systems in theoretical ecology and soil sciences more broadly to identify areas for further study that may help improve the robustness of soil models under the uncertainty of human activities and management. Three broad dynamical concepts were highlighted: soil variable memory or state-dependence, oscillations, and tipping points or hysteresis. These themes represent less intuitive yet key dynamics that can emerge after assuming nuanced observations, such as reversibility of organo-mineral associations, dynamic aggregate- and pore hierarchies, persistent wet-dry cycles, higher-order microbial community and predator-prey interactions, cumulative legacy land use history, and social management interactions and/or cooperation. We discuss how these aspects may contribute useful analytical tools, metrics, and frameworks that help integrate the uncertainties in future soil states, ranging from micro- to regional scales, including those indirectly affected by human activities and management decisions. Overall, this study highlights the potential benefits of incorporating spatial heterogeneity and dynamic instabilities into future model representations of whole soil processes. Additionally, it advocates for transdisciplinary collaborations between natural and social scientists, extending research into anthropedology and biogeosociochemistry, to better integrate and understand longer-term anthropogenic drivers of soil processes, potentially from soil structural dynamics to microbial community and food web ecology.
The metacommunity, as it evolved from Levin's metapopulation, provides a framework to consider the spatial organization of species interactions. Arguably the most fundamental feature of metapopulations and metacommunities are that demes are connected via migration. An important result from Levin's metapopulation work-that increasing migration lowers regional extinction probability-is often incorporated into conceptions of metacommunities. We first use a toy model to show how this result from Levin's metapopulation does not necessarily hold when considering community interactions in a metacommunity context. We also report results from a metacommunity field experiment conducted with a tropical terrestrial leaf litter community and show that migration induces the extinction of predators in the metacommunity. Our result corroborates the findings of a prior metacommunity experiment in a temperate terrestrial leaf litter community. The concordance between these experiments even with vastly di↵erent communities highlights the importance of considering trophic and non-trophic community structure to understand metacommunity dynamics.
About half of all forests are tropical and secondary, making tropical forest regeneration integral to future forests. Tree stand biomass and taxonomic richness can recover in a few decades, but relative abundances may lag indefinitely. Since most forests are within a km of a habitat edge, edge effects likely affect community composition regeneration. However, most studies assess how degraded edges affect intact forests, leaving it unclear whether higher-quality edges could facilitate regeneration of nearby degraded forests. Notably, higher quality edges near intact forests could promote processes like dispersal and wood biomass accumulation that effectively accelerate succession, leading to better performance of shade-tolerant taxa compared to pioneer taxa in the early stages of forested plantation regeneration. This study addressed how wet tropical forested plantation regeneration was affected by distance to adjacent intact forest edge. It was hypothesized that old timber plantations facilitate regeneration by increasing available shade, favoring the presence and biomass of later-successional taxa, ultimately changing community composition overall. A wet neotropical timber plantation reforested after 20 years and adjacent to primary forest was censused for trees along a 300 m edge distance gradient, and analysis matched identified taxa to broad dispersal mode and wood density traits using relevant literature. As distance from primary forest edge increased, stem and wood density tended to increase significantly, with ~10% variation explained, while biomass and canopy light surprisingly tended to stay the same. Stand tree richness also tended to increase significantly, but diversity decreased steeply and non-linearly, explained in part by wood density, and taxonomic composition varied notably. Finally, tree taxa associated with both early and late successional stages decreased significantly, as well as genus Ficus, but biomass by dispersal mode did not tend to change. Overall this study supports that stand composition is less resilient and more subject to edge effects than biomass and richness, suggesting that global forests will likely be distinctly new assemblages in the future, with timber and biodiversity trade-offs occurring based on local and regional management activity.
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