Skip to main content
Dryad logo

Unravelling processes between phenotypic plasticity and population dynamics in migratory birds

Citation

Liu, Jin et al. (2022), Unravelling processes between phenotypic plasticity and population dynamics in migratory birds, Dryad, Dataset, https://doi.org/10.5061/dryad.gxd2547p6

Abstract

Populations can rapidly respond to environmental change via adaptive phenotypic plasticity, which can also modify interactions between individuals and their environment, affecting population dynamics. Bird migration is a highly plastic resource-tracking tactic in seasonal environments. However, the link between the population dynamics of migratory birds and migration tactic plasticity is not well understood.

The quality of staging habitats affects individuals’ migration timing and energy budgets in the course of migration, and can consequently affect individuals’ breeding and overwintering performance, and impact population dynamics. Given staging habitats being lost in many parts of the world, our goal is to investigate responses of individual migration tactics and population dynamics in the face of loss of staging habitat, and to identify the key processes connecting them.

We started by constructing and analysing a general full-annual-cycle individual-based model with a stylized migratory population to generate hypotheses on how changes in the size of staging habitat might drive changes in individual stopover duration and population dynamics. Next, through the interrogation of survey data, we tested these hypotheses by analysing population trends and stopover duration of migratory waterbirds experiencing loss of staging habitat.

Our modelling exercise led to us posing the following hypotheses: the loss of staging habitat generates plasticity in migration tactics, with individuals remaining on the staging habitat for longer to obtain food due to a reduction in per capita food availability. The subsequent increasing population density on the staging habitat has knock on effects on population dynamics in the breeding and overwintering stage. Our empirical results were consistent with the modelling predictions.

Our results demonstrate how environmental change that impacts one energetically costly life history stage in migratory birds can have population dynamics impacts across the entire annual cycle via phenotypic plasticity.

Methods

IBM: The individual-based model was constructed in NetLogo

Bird survey data: Bird surveys were conducted in the wetlands in the north of Bohai Bay, located in the northwest of the Yellow Sea. The survey range is shown in Fig S3. Survey data was collected between 2004 and 2018 by using telescopes and binoculars.

Usage Notes

1. NetLogo code for the individual-based model

NetLogo code to construct the individual-based model with capital breeding tactic and income breeding tactic respectively, and to get the model outputs including: total number of individuals, daily population density at each habitat, individual time spent at each habitat, individual energy reserves when leaving each habitat and individual energy reserves at each time step. Different habitat scenarios and sensitivity analysis can be run by using the "behaviour space".

The model scenarios, the decision rules, the order of events of the model are fully described in the paper. 

Code_IBM_CapitalBreeding.nlogo

Code_IBM_IncomeBreeding.nlogo

2. Bird survey data

The dataset comes from the long-term bird survey project on the Bohai Bay, China, run by Beijing Normal University (BNU). The data provided here is a subset of the full dataset, which includes bird surveys from 2016 to 2018. If you are interested in the full dataset, please contact Zhengwang Zhang (BNU).

Key to variables:

year: is the year of the survey

month: is the month of the survey

day: is the date of the survey

julian: is the Julian date of the survey

area: is the survey site, the location of the survey site can be found in Fig.S3

species: is the common English name of the species. The "uncurlew sp.", "unduck sp.", "untern sp." are species that cannot be identified as species level, they were all treated as unidentified species in our analyses.

number: is the population size of the species at the survey site at the specific survey date

effort: is the number of observers of the survey

Survey_data_BNU.csv

figure_S3_SurveyArea.tif