Your E-mail
Remember me
 Forgotten password
SCALETOOL IntroductionDriversBiodiversityPolicies and managementConnectivity and protected areas

Dynamic modelling of range expansion with RangeShifter: impacts of land cover and species traits

Risto K. Heikkinen, Greta Bocedi, Mikko Kuussaari, Janne Heliölä, Niko Leikola, Juha Pöyry and Justin M.J. Travis

Dynamic range expansion models provide promising tools for nature conservation and management planning. In particular, they can be employed to develop spatially more realistic regional assessments of species' responses to global changes and their capacities for persisting in habitat networks under changing climate. RangeShifter, a platform for dynamic modelling of ecological and evolutionary dynamics (Bocedi et al. 2014) recently developed with support from the SCALES-project, is a novel example of such tools. RangeShifter is able to integrate complex population dynamics and dispersal behaviour. It provides functionality for a wide variety of modelling applications ranging from applied conservation biological questions, such as investigating real-life species' range dynamics, to theoretical studies of species' eco-evolutionary dynamics and responses to different environmental pressures.

This case study provides a practical application of RangeShifter and illustrates its usefulness to assess species' range expansion potential in a fragmented network of suitable habitats (for an extended treatment of the study see Heikkinen et al. 2014). Two sources of uncertainty in dynamic models were specially addressed: the impacts of land cover data selection and species parameterisation on model outputs. Known occurrence records for the two grassland butterfly species, Meadow Brown (Maniola jurtina; a grassland specialist in Finland) and Queen of Spain Fritillary (Issoria lathonia; a grassland generalist in Finland) from the years 1991-2000 were used as starting points to perform 50-year period range expansion simulations for the species (Fig. 1). Simulations were run using a grid system showing the amount of suitable grassland habitat in several millions of 200-m grid cells covering southern Finland (Fig. 1).

Figure 1. Known occurrence areas (10-km grid cells) for (A) Meadow Brown (Maniola jurtina) and (B) Queen of Spain Fritillary (Issoria lathonia) in Finland in 1991-2000, shown with red dots (source NAFI database; Saarinen et al. 2002; Pöyry et al. 2009). Area where the range expansion simulations were performed is indicated with orange. Modified from: doi:10.1371/journal.pone.0108436.g001. Copyright of the species photographs: (A) Maniola jurtina: Albert Vliegenthart; (B) Issoria lathonia: Martin Wiemers.

The RangeShifter results show that the spatial projections of species' range expansion depend much on the choice between using CORINE land cover data vs. using qualitatively more detailed (but spatially more sparse) grassland data from three alternative national databases, especially in the case of Maniola jurtina (Fig. 2). Varying the four life-history traits studied (extent and probability of long-distance dispersal events, population growth rate and carrying capacity) may also cause notable differences in the forecasts of range expansion dynamics , with carrying capacity and length of long-distance movements showing the strongest effect (selected results for Issoria lathonia shown in Fig. 3). The results of this case study highlight the sensitivity of dynamic species population models to the selection of the model parameters and land cover data, and illustrate the need for conducting careful evaluations before applying the models to nature conservation questions.

Figure 2. Maps showing the simulated range expansion of Maniola jurtina in SW Finland. Probability of a 200-m grid cell to be occupied is depicted with a colour ramp from red (high prob.) to orange (intermediate prob.) and yellow (low prob.), with areas in dark blue having a probability of zero. Light blue squares indicate 10-km grid cells where the simulations were seeded. Simulations were done using and (A) CORINE land cover data and (B) combined data on grasslands included in the Finnish Agri-environmental scheme and the National survey of valuable traditional rural biotopes. Source: doi:10.1371/journal.pone.0108436.g005

Figure 3. The projected total number of 200-m cells occupied by Issoria lathonia individuals (A), and maximal range shift of the butterfly (B) at the end of a 50 year dynamic simulation period. Simulations including 100 replicate runs were conducted using summed cover of CORINE classes 'Pastures' and 'Natural grassland', 'Land principally occupied by agriculture, with significant areas of natural vegetation', 'Abandoned arable land' and field margins. Species parameterisation settings: BASE = the default model parameterisation (mean distance of long-distance dispersal events, DL = 3000 m; probability of short-distance events, DP = 0.90; population growth rate, GR = 2.0; carrying capacity, K = 250). Alternative values: DL1 = 1500 m, DL2 = 5000 m; DP1 = 0.80, DP2 = 0.95; GR1 = 1.5, GR2 = 2.5; K1 = 200, K2 = 300. Modified from: doi:10.1371/journal.pone.0108436.g006.


Bocedi G, Palmer, SCF, Pe'er G, Heikkinen RK, Matsinos Y, Watts K, Travis JMJ (2014) RangeShifter: a platform for modeling spatial eco-evolutionary dynamics and species' responses to environmental changes. Methods in Ecology and Evolution 5: 388-396.

Heikkinen RK, Bocedi G, Kuussaari M, Heliölä J, Leikola N, Pöyry J, Travis JMJ (2014) Impacts of land cover data selection and trait parameterisation on dynamic species range expansion modelling. PLoS ONE 9(9): e108436. doi:10.1371/journal.pone.0108436.

Pöyry J, Luoto M, Heikkinen RK, Kuussaari M, Saarinen K (2009) Species traits explain recent range shifts of Finnish butterflies. Global Change Biology 15 (723-743).

Saarinen K, Lahti T, Marttila O (2002) Population trends of Finnish butterflies (Lepidoptera: Hesperioidea, Papilionoidea) in 1991-2000. Biodivers Conserv 12:2147-2159.

Copyright and disclaimer: SCALES and SCALETOOL

CONDITIONS OF USE: We explicitly encourage the use of SCALETOOL. SCALETOOL is freely available for non-commercial use provided you acknowledge SCALES as source. For more extensive access to databases (e.g. for statistical analyses or if you want to contribute data), tools, or background material, please contact the SCALES coordinator (send us email).


© 2010 - 2018 SCALES. All rights reserved.