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5 results for “Stochastic environments”
Raw Data: Timing of Calanus finmarchicus diapause in stochastic environments
<p><strong>This dataset contains the raw (unprocessed) model outputs of the Individual-Based Model used to generate the research article: </strong></p> <p>Bandara, K., Varpe, Ø., Maps, F., Ji, R., Eiane, K., & Tverberg, V. (2021). Timing of Calanus finmarchicus diapause in stochastic environments. <em>Ecological Modelling</em>, <em>460</em>, 109739.</p> <p><strong>Description</strong></p> <p>ITEM DESCRIPTION<br> ----------------<br> CONTENTS : RAW DATA FILES<br> UNCOMPRESSED SIZE : 19.6 GB <br> COMPRESSION : YES<br> COMPRESSED SIZE : 3.74 GB<br> COMPRESSION FORMAT : .ZIO<br> ENCRYPTION : NO<br> ENCRYPT METHOD : N/A<br> INTERNAL FILE TYPE(S) : .CSV<br> SOURCE : PASCAL <br> ID : v3.x (2020-2022)<br> DECRYPTION PASSWD : N/A<br> DOWNLOADABLE FROM : 10.5281/zenodo.7646734</p> <p>DATA DESCRIPTION<br> ----------------<br> THIS ARCHIVE CONTAINS FIVE (05) DIRECTORIES. EACH FROM A SINGLE SIMULATION EXPERIMENT, INDICATED BY THE FILE NAMES. <br> + DeterministicSetting : SIMULATION RAN IN DETERMINISTIC MODEL ENVIRONMENT (FIG. 2A-C)<br> + STStochasticSetting : SIMULATION RAN IN SHORTER-TERM (6-H) STOCHASTIC ENVIRONMENT (FIG. 2D-F)<br> + LTStochasticSetting-TFI : SIMULATION RAN IN LONGER-TERM (INTERANNUAL) STOCHASTIC ENVIRONMENT WITH GROWTH POTENTIAL VARIABILITY ONLY (FIG. 2G)<br> + LTStochasticSetting-VPR : SIMULATION RAN IN LONGER-TERM (INTERANNUAL) STOCHASTIC ENVIRONMENT WITH GROWTH POTENTIAL + VISUAL PREDATION RISK VARIABILITY (FIG. 2G)<br> + LTStochasticSetting-NVPR : SIMULATION RAN IN LONGER-TERM (INTERANNUAL) STOCHASTIC ENVIRONMENT WITH GROWTH POTENTIAL VARIABILITY + NON-VISUAL PREDATION RISK VARIABILITY (FIG. 2G)</p> <p>KEY<br> ---<br> + AnnualLog : DOUBLE VALUES OF LOW-RESOLUTION TRACKERS <br> + DailyLog_I : INTEGER VALUES OF HIGH-RESOLUTION TRACKERS<br> + DailyLog_R : DOUBLE VALUES OF HIGH-RESOLUTION TRACKERS<br> + VerticalPosition_N : INTEGER VALUES OF POPULATION VERTICAL DISTRIBUTION (NUMBER OF INDIVIDUALS IN EACH 1M x 6H BIN)<br> + VerticalPosition_CW : DOUBLE VALUES OF AVERAGE BODYMASS VERTICAL DISTRIBUTION (AVERAGE INDIVIDUAL BODYMASS IN EACH 1M x 6H BIN) :: UNUSED IN ANALYSES<br> + VerticalPosition_SW : DOUBLE VALUES OF AVERAGE ENERGY RESERVE VERTICAL DISTRIBUTION (AVERAGE INDIVIDUAL ENERGY RESERVES [LIPIDSCAPE] IN EACH 1M x 6H BIN) :: UNUSED IN ANALYSES<br> + FoodConcentration : DOUBLE VALUES OF 1D FOOD ENVIRONMENT<br> + Irradiance : DOUBLE VALUES OF 1D SUB-SURFACE IRRADIANCE ENVIRONMENT<br> + Temperature : DOUBLE VALUES OF 1D TEMPERATURE ENVIRONMENT<br> + VisualPredationRisk : DOUBLE VALUES OF 1D UNSCALED VISUAL PREDATION ENVIRONMENT</p> <p>NOTES<br> -----<br> The above attributes (excl. AnnualLog) are recorded for 100 calendar year in the LTStochasticSetting-TFI, LTStochasticSetting-VPR & LTStochasticSetting-NVPR simulations.<br> These are named after the year number (e.g. DailyLog_I_1, DailyLog_I_2....)</p> <p>ADDITIONAL FILES<br> ----------------<br> SOME DIRECTORIES MAY CONTAIN ADDITIONAL FILES, SUCH AS THOSE USED AS PCA INPUTS. THESE ARE PROCESSED FILES.<br> AVERAGE ANNUAL ENVIRONMENTAL VARIABLES TRACED IN THE "ENV" DIRECTORY (ONLY FOR LONGER-TERM STOCHASTIC SIMULATIONS).</p> <p>FURTHER QUESTIONS?<br> ------------------<br> Direct further question, either to: info@kanchanabandara.com (personal) or kba@akvaplan.niva.no (official)</p>
Multiple-batch spawning as a bet-hedging strategy in highly stochastic environments: an exploratory analysis of Atlantic cod
<p><span><span><span><span><span><span><span><span><span><span><span>Stochastic environments shape life-history traits and can promote selection for risk-spreading strategies, such as bet-hedging. Although the strategy has often been hypothesised to exist for various species, empirical tests providing firm evidence have been rare, mainly due to the challenge in tracking fitness across generations. Here, we take a 'proof of principle' approach to explore whether the reproductive strategy of multiple-batch spawning constitutes a bet-hedging. We used Atlantic cod (<i>Gadus morhua</i>) as the study species and parameterised an eco-evolutionary model, using empirical data on size-related reproductive and survival traits. To evaluate the fitness benefits of multiple-batch spawning (within a single breeding period), the mechanistic model separately simulated multiple-batch and single-batch spawning populations under temporally varying environments. We followed the arithmetic and geometric mean fitness associated with both strategies and quantified the mean changes in fitness under several environmental stochasticity levels. We found that, by spreading the environmental risk among batches, multiple-batch spawning increases fitness under fluctuating environmental conditions. The multiple-batch spawning trait is, thus, advantageous and acts as a bet-hedging strategy when the environment is exceptionally unpredictable. Our research identifies an analytically flexible, stochastic, life-history modelling approach to explore the fitness consequences of a risk-spreading strategy and elucidates the importance of evolutionary applications to life-history diversity. </span></span></span></span></span></span></span></span></span></span></span></p>
Data and code from: Species interactions drive continuous assembly of freshwater communities in stochastic environments
<p>Understanding the factors driving the maintenance of long-term biodiversity in changing environments is essential for improving restoration and sustainability strategies in the face of global environmental change. Biodiversity is shaped by both niche and stochastic processes, however the strength of deterministic processes in unpredictable environmental regimes is highly debated. Since communities continuously change over time and space -- species persist, disappear or (re)appear -- understanding the drivers of species gains and losses from communities should inform us about whether niche or stochastic processes dominate community dynamics.<br>Applying a nonparametric causal discovery approach to a 30-year time series containing annual abundances of benthic invertebrates across 66 locations in New Zealand rivers, we found a strong \hl{negative} causal relationship between species gains and losses directly driven by predation indicating that niche processes dominate community dynamics. Despite the unpredictable nature of these system, environmental noise was only indirectly related to species gains and losses through altering life history trait distribution. Using a stochastic birth-death framework, we demonstrate that the negative relationship between species gains and losses can not emerge without strong niche processes. Our results showed that even in systems that are dominated by unpredictable environmental variability, species interactions drive continuous community assembly. </p>
Multiple-batch spawning as a bet-hedging strategy in highly stochastic environments: an exploratory analysis of Atlantic cod
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Data from: A stochastic vision based model inspired by the collective behaviour of zebrafish in heterogeneous environments
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