Simplicity versus complexity

Simplified Marsh Response Model (SMRM): A Methodological Approach to Quantify the Evolution of Salt Marshes in a Sea-Level Rise Context

Salt marshes are highly valued coastal environments for different services: coastline protection, biodiversity, and blue carbon. They are vulnerable to climate changes, particularly to sea-level rise. For this reason, it is essential to project the evolution of marsh areas until the end of the century. This work presents a reduced complexity model to quantify salt marshes’ evolution in a sea-level rise (SLR) context through combining field and remote sensing data: SMRM (Simplified Marsh Response Model). SMRM is a two-dimensional rule-based model that requires four parameters: a digital terrain model (DTM), local tidal levels, a sea-level rise projection, and accretion rates. A MATLAB script completes the process, and the output is a GeoTIFF file. Two test areas were selected in Tróia sandspit (Setúbal, Portugal). Additionally, a sensitivity analysis for each parameter’s influence and a comparison with SLAMM (another rule-based model) were undertaken. The sensitivity analysis indicates that SLR is the most relevant parameter, followed by accretion rates. The comparison of SMRM with SLAMM shows quite similar results for both models. This new model application indicates that the studied salt marshes could be resilient to conservative sea-level rise scenarios but not to more severe sea-level rise projections.

Eco-epidemiological scaling of Leptospirosis: Vulnerability mapping and early warning forecasts

Infectious disease epidemics are plaguing the world and a lot of research is focused on the development of models to reproduce disease dynamics for eco-environmental and biological investigation, and disease management. Leptospirosis is an example of a neglected zoonosis strongly mediated by ecohydrological dynamics with emerging endemic and epidemic patterns worldwide in both animal and human populations. By accounting for large heterogeneities of affected areas we show how exponential endemics and scale-free epidemics are largely predictable and linked to common socio-environmental features via scaling laws with different exponents that inform about vulnerability factors. This led to the development of a novel pattern-oriented integrated model that can be used as an early-warning signal (EWS) tool for endemic-epidemic regime classification, risk determinant attribution, and near real-time forecast of outbreaks. Forecasts are grounded on expected outbreak recurrence time dependent on exceedance probabilities and statistical EWS that sense outbreak onset. A stochastic spatially-explicit model is shown to comprehensively predict outbreak dynamics (early sensing, timing, magnitude, decay, and eco-environmental determinants) and derive a spreading factor characterizing endemics and epidemics, where average over maximum rainfall is the critical factor characterizing disease transitions. Dynamically, case cross-correlation considering neighboring communities senses 2-weeks in advance outbreaks. Eco-environmental scaling relationships highlight how predicted host suitability and topographic index can be used as epidemiological footprints to effectively distinguish and control Leptospirosis regimes and areas dependent on hydro-climatological dynamics as the main trigger. The spatio-temporal scale-invariance of epidemics - underpinning persistent criticality and neutrality or independence among areas - is emphasized by the high accuracy in reproducing sequence and magnitude of cases via reliable surveillance. Further investigations of robustness and universality of eco-environmental determinants are required; nonetheless a comprehensive and computationally simple EWS method for the full characterization of Leptospirosis is provided. The tool is extendable to other climate-sensitive zoonoses to define vulnerability factors and predict outbreaks useful for optimal disease risk prevention and control.

A Participatory Approach for Balancing Accuracy and Complexity in Modeling Resilience and Robustness

Robustness and resilience are widely used in the biological sciences and related disciplines to describe how systems respond to change. Robustness is the ability to tolerate change without adapting or moving to another state. Resilience refers to the ability for a system to sustain a perturbation and maintain critical functions. Robustness and resilience transcend levels of biological organization, though they do not scale directly across levels. We live in an era of novel stressors and unprecedented change, including climate change, emerging environmental contaminants, and changes to earth's biogeochemical and hydrological cycles. We envision a common framework for developing models to predict the robustness and resilience of biological functions associated with complex systems that can transcend disciplinary boundaries. Conceptual and quantitative models of robustness and resilience must consider cross-scale interactions of potentially infinite complexity, but it is impossible to capture everything within a single model. Here, we discuss the need to balance accuracy and complexity when designing models, data collection, and downstream analyses to study robustness and resilience. We also consider the difficulties in defining the spatiotemporal domain when studying robustness and resilience as an emergent property of a complex system. We suggest a framework for implementing transdisciplinary research on robustness and resilience of biological systems that draws on participatory stakeholder engagement methods from the fields of conservation and natural resources management. Further, we suggest that a common, simplified model development framework for describing complex biological systems will provide new, broadly relevant educational tools. Efficient interdisciplinary collaboration to accurately develop a model of robustness and resilience would enable rapid, context-specific assessment of complex biological systems with benefits for a broad range of societally relevant problems.

The future of insular beaches: Insights from a past-to-future sediment budget approach

Sustainable management of insular beaches, that are critical to tourism-based economies, depends on sound understanding of coastal evolution drivers. However, interconnections among geological, oceanographical, biological and human key-drivers of coastal change, operating at relevant spatial and temporal scales, remains poorly understood. This work aims at understanding and quantifying the main drivers of insular beaches evolution using a past-to-future sediment budget approach, and to address future coastal impacts raised by anthropogenic interventions and climate change. This approach was developed in Porto Santo's beach from the early 20th century to the middle 21st century. Results show that anthropic activities undertaken during the late 20th century perturbed the existing long-term (natural) coastal stability. They caused significant reduction of the main sediment source (river sediment yield) and increased sediment sinks (e.g. sediment extraction from beach, harbour sedimentation). Altogether, this resulted in the onset of an erosive trend that persists until present. Projecting patterns of coastal change into the forthcoming decades strongly depends on sediment management strategies. We show that the adoption of a neutral strategy (i.e. compensating for anthropogenic-induced losses with beach nourishment) will not be enough to cease beach erosion, given the negative impacts related to acceleration of future sea level rise. Still, maintenance of the socioeconomic values of Porto Santo's beach can be achieved by triggering positive anthropic influences on its sediment budget. The past-to-future sediment budget approach proposed herein provided a unified perspective on the evolution of the main drivers of coastal change and simultaneously offers foundations for adaptations strategies aiming at increasing sustainability of insular beaches.

Heavy Minerals for Junior Woodchucks

In the last two centuries, since the dawn of modern geology, heavy minerals have been used to investigate sediment provenance and for many other scientific or practical applications. Not always, however, with the correct approach. Difficulties are diverse, not just technical and related to the identification of tiny grains, but also procedural and conceptual. Even the definition of “heavy minerals” is elusive, and possibly impossible. Sampling is critical. In many environments (e.g., beaches), both absolute and relative heavy mineral abundances invariably increase or decrease locally to different degrees owing to hydraulic-sorting processes, so that samples close to "neutral composition" are hard to obtain. Several widely shared opinions are misleading. Choosing a narrow size-window for analysis leads to increased bias, not to increased accuracy or precision. Only point-counting provides real volume percentages, whereas grain-counting distorts results in favor of smaller minerals. This paper also briefly reviews the heavy mineral associations typically found in diverse plate-tectonic settings. A mineralogical assemblage, however, only reproduces the mineralogy of source rocks, which does not correlate univocally with the geodynamic setting in which those source rocks were formed and assembled. Moreover, it is affected by environmental bias, and by diagenetic bias on top in the case of ancient sandstones. One fruitful way to extract information on both provenance and sedimentological processes is to look for anomalies in mineralogical–textural relationships (e.g., denser minerals bigger than lower-density minerals; harder minerals better rounded than softer minerals; less durable minerals increasing with stratal age and stratigraphic depth). To minimize mistakes, it is necessary to invariably combine heavy mineral investigations with the petrographic analysis of bulk sand. Analysis of thin sections allows us to see also those source rocks that do not shed significant amounts of heavy minerals, such as limestone or granite, and helps us to assess heavy mineral concentration, the “outer” message carrying the key to decipher the “inner message” contained in the heavy mineral suite. The task becomes thorny indeed when dealing with samples with strong diagenetic overprint, which is, unfortunately, the case of most ancient sandstones. Diagenesis is the Moloch that devours all grains that are not chemically resistant, leaving a meager residue difficult or even impossible to interpret when diagenetic effects accumulate through multiple sedimentary cycles. We have conceived this friendly little handbook to help the student facing these problems, hoping that it may serve the purpose.

Naïve Simplicity: The Overlooked Piece of the Complexity-Simplicity Paradigm

Concepts of simplicity and complexity in modeling have been explored in papers, editorials, and talks. The concept is not well understood because there are at least two flavors of simplicity. Modelers envision simplicity (i.e., elegant simplicity) as the sought-after goal in modeling, but naïve simplicity, which is the focus of this paper, is commonly unrecognized and dangerous. The problem is that naïve or simple ideas are often mistaken for settled science and come with the prospect of being more wrong than right. The concept of the so-called simplicity cycle, in relation to classical problems of carbon-14 age and salinity in closed-basin lakes, is used to illustrate these points. The emerging problems of water-mosquitoes-diseases show the value of mapping new problems to the simplicity cycle. Researchers can "know what they do not know" and avoid the dangers of naïve simplicity.

Biomechanics of plant anchorage at early development stage

We propose a minimal model for the response of seedlings to pullout constraints. Central to our approach is the idea of capturing not only average mechanical properties but also the stochastic component of the uprooting process. Our model accounts on one hand for the tensile elastic response of root fibres and on the other hand for the friction between root fibres and the soil matrix. We present for validation a dataset of 98 uprooting experiments using Avena sativa L. seedlings (common oat), growing in non-cohesive sediment under controlled conditions. We show that even if the architecture of the roots used in the experiments and, as a consequence, the components of our model are very basic, the uprooting curve (stress vs. strain) presents a complex response, with sudden jumps followed by partial elastic recovery. Depending on the maturity of the root system, we identify a crossover in the response of the seedling to the constraint. While for younger seedlings the anchorage rapidly fails after the peak force has been reached, more mature root systems recover from partial failures. Finally, we discuss the importance of the characteristics of the uprooting curve (maximal uprooting force and total uprooting work) regarding the ability of seedlings to withstand environmental constraints in terms of duration or intensity.

Width of laminar laboratory rivers

A viscous fluid flowing over plastic grains spontaneously generates single-thread channels. With time, these laminar analogues of alluvial rivers reach a reproducible steady state, showing a well-defined width and cross section. In the absence of sediment transport, their shape conforms with the threshold hypothesis which states that, at equilibrium, the combined effects of gravity and flow-induced stress maintain the bed surface at the threshold of motion. This theory explains how the channel selects its size and slope for a given discharge. In this light, laboratory rivers illustrate the similarity between the avalanche angle of granular materials and Shields's criterion for sediment transport.