Short communication: Landlab v2.0: a software package for Earth surface dynamics

Barnhart, Katherine R.; Hutton, Eric; Tucker, G. E.; Gasparini, N. M.; Istanbulluoglu, Erkan; Hobley, Daniel E. J.; Lyons, Nathan J.; Mouchené, Margaux; Nudurupati, Sai Siddhartha; Adams, J. M.; Bandaragoda, C.

doi:10.5194/esurf-8-379-2020

Cited by 77 publications

(67 citation statements)

References 75 publications

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“…* and * for the objective function and model 802 BasicRtTh. This model was the best two-element model in the calibration effort presented by Barnhart et al (2020). (a) The sensitivity of the objective function to changing the input parameter values and (b) the sensitivity to changing initial and boundary conditions.…”

Section: Initial and Boundary Conditionsmentioning

confidence: 99%

“…Each step of model analysis was conducted within this alternative‐model framework. All of the computer programs used to implement these models numerically are available through the terrainbento python package, which was developed using the Landlab toolkit (Barnhart, Hutton, et al, ; Hobley et al, ) and is described by Barnhart, Glade, et al (). Landlab is not, itself, a model, but a python package that can be used to construct any number of models.…”

Section: Multimodel Implementationmentioning

confidence: 99%

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Inverting Topography for Landscape Evolution Model Process Representation: 1. Conceptualization and Sensitivity Analysis

et al. 2020

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Despite considerable community effort, there is no general set of equations to model long-term landscape evolution. In order to determine a suitable set of landscape evolution process laws for a site where postglacial erosion has incised valleys up to 50 m deep, we generate a set of alternative models and perform a multimodel analysis. The most basic model we consider includes stream power channel incision, uniform lithology, hillslope transport by linear diffusion, and surface-water discharge proportional to drainage area. We systematically add one, two, or three elements of complexity to this model from one of four categories: hillslope processes, channel processes, surface hydrology, and representation of geologic materials. We apply methods of formal model analysis to the 37 alternative models. The global Method of Morris sensitivity analysis method is used to identify model input parameters that most and least strongly influence model outputs. Only a few parameters are identified as important, and this finding is consistent across two alternative model outputs: one based on a collection of topographic metrics and one that uses an objective function based on a topographic difference. Parameters that control channel erosion are consistently important, while hillslope diffusivity is important for only select model outputs. Uncertainty in initial and boundary conditions is associated with low sensitivity. Sensitivity analysis provides insight to model dynamics and is a critical step in using model analysis for mechanistic hypothesis testing in landscape evolution theory.

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Section: Initial and Boundary Conditionsmentioning

confidence: 99%

Section: Multimodel Implementationmentioning

confidence: 99%

Inverting Topography for Landscape Evolution Model Process Representation: 1. Conceptualization and Sensitivity Analysis

et al. 2020

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“…The 37 models used here were developed using the Landlab Toolkit (Barnhart et al, ; Hobley et al, ) and are available in the terrainbento python package (Barnhart, Glade et al, ). It is important to note that Landlab is not, itself, a model.…”

Section: Summary Of Model Set and Implementationmentioning

confidence: 99%

Inverting Topography for Landscape Evolution Model Process Representation: 2. Calibration and Validation

et al. 2020

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We present a multimodel analysis for mechanistic hypothesis testing in landscape evolution theory. The study site is a watershed with well-constrained initial and boundary conditions in which a river network locally incised 50 m over the last 13 ka. We calibrate and validate a set of 37 landscape evolution models designed to hierarchically test elements of complexity from four categories: hillslope processes, channel processes, surface hydrology, and representation of geologic materials. Comparison of each model to a base model, which uses stream power channel incision, uniform lithology, hillslope transport by linear diffusion, and surface water discharge proportional to drainage area, serves as a formal test of which elements of complexity improve model performance. Model fit is assessed using an objective function based on a direct difference between observed and simulated modern topography. A hybrid optimization scheme identifies optimal parameters and uncertainty. Multimodel analysis determines which elements of complexity improve simulation performance. Validation tests which model improvements persist when models are applied to an independent watershed. The three most important model elements are (1) spatial variation in lithology (differentiation between shale and glacial till), (2) a fluvial erosion threshold, and (3) a nonlinear relationship between slope and hillslope sediment flux. Due to nonlinear interactions between model elements, some process representations (e.g., nonlinear hillslopes) only become important when paired with the inclusion of other processes (e.g., erosion thresholds). This emphasizes the need for caution in identifying the minimally sufficient process set. Our approach provides a general framework for hypothesis testing in landscape evolution.

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“…Speciation, when it is triggered by zone fragmentation, is carried out more rapidly as this parameter decreases. The parameter was set to the same value for all species in a trial, and it varied from 1 to 100 kyr among the trials, consistent with empirical studies on freshwater fishes (Albert and Carvalho, 2011;Tedesco et al, 2012;Albert et al, 2018) and a theoretical model arising from analyses of molecular phylogenies linking speciation to rare stochastic events that cause reproductive isolation (Venditti et al, 2010;Beaulieu and O'Meara, 2015). For example, if the zone of Figure 3.…”

Section: Perturb Phasementioning

confidence: 99%

Topographic controls on divide migration, stream capture, and diversification in riverine life

et al. 2020

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Abstract. Drainages reorganise in landscapes under diverse conditions and process dynamics that impact biotic distributions and evolution. We first investigated the relative control that Earth surface process parameters have on divide migration and stream capture in scenarios of base-level fall and heterogeneous uplift. A model built with the Landlab toolkit was run 51 200 times in sensitivity analyses that used globally observed values. Large-scale drainage reorganisation occurred only in the model runs within a limited combination of parameters and conditions. Uplift rate, rock erodibility, and the magnitude of perturbation (base-level fall or fault displacement) had the greatest influence on drainage reorganisation. The relative magnitudes of perturbation and topographic relief limited landscape susceptibility to reorganisation. Stream captures occurred more often when the channel head distance to divide was low. Stream topology set by initial conditions strongly affected capture occurrence when the imposed uplift was spatially heterogeneous. We also integrated simulations of geomorphic and biologic processes to investigate relationships among topographic relief, drainage reorganisation, and riverine species diversification in the two scenarios described above. We used a new Landlab component called SpeciesEvolver that models species at landscape scale following macroevolutionary process rules. More frequent stream capture and less frequent stream network disappearance due to divide migration increased speciation and decreased extinction, respectively, especially in the heterogeneous uplift scenario in which final species diversity was often greater than the base-level fall scenario. Under both scenarios, the landscape conditions that led to drainage reorganisation also controlled diversification. Across the model trials, the climatic or tectonic perturbation was more likely in low-relief landscapes to drive more extensive drainage reorganisation that in turn increased the diversity of riverine species lineages, especially for the species that evolved more rapidly. This model result supports recent research on natural systems that implicates drainage reorganisation as a mechanism of riverine species diversification in lowland basins. Future research applications of SpeciesEvolver software can incorporate complex climatic and tectonic forcings as they relate to macroevolution and surface processes, as well as region- and taxon-specific organisms based in rivers and those on continents at large.

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Short communication: Landlab v2.0: a software package for Earth surface dynamics

Cited by 77 publications

References 75 publications

Inverting Topography for Landscape Evolution Model Process Representation: 1. Conceptualization and Sensitivity Analysis

Inverting Topography for Landscape Evolution Model Process Representation: 1. Conceptualization and Sensitivity Analysis

Inverting Topography for Landscape Evolution Model Process Representation: 2. Calibration and Validation

Topographic controls on divide migration, stream capture, and diversification in riverine life

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