TY - JOUR A1 - Radchuk, Viktoriia A1 - Oppel, Steffen A1 - Groeneveld, Juergen A1 - Grimm, Volker A1 - Schtickzelle, Nicolas T1 - Simple or complex: Relative impact of data availability and model purpose on the choice of model types for population viability analyses JF - Ecological modelling : international journal on ecological modelling and engineering and systems ecolog N2 - Population viability analysis (PVA) models are used to estimate population extinction risk under different scenarios. Both simple and complex PVA models are developed and have their specific pros and cons; the question therefore arises whether we always use the most appropriate model type. Generally, the specific purpose of a model and the availability of data are listed as determining the choice of model type, but this has not been formally tested yet. We quantified the relative importance of model purpose and nine metrics of data availability and resolution for the choice of a PVA model type, while controlling for effects of the different life histories of the modelled species. We evaluated 37 model pairs: each consisting of a generally simpler, population-based model (PBM) and a more complex, individual-based model (IBM) developed for the same species. The choice of model type was primarily affected by the availability and resolution of demographic, dispersal and spatial data. Low-resolution data resulted in the development of less complex models. Model purpose did not affect the choice of the model type. We confirm the general assumption that poor data availability is the main reason for the wide use of simpler models, which may have limited predictive power for population responses to changing environmental conditions. Conservation biology is a crisis discipline where researchers learned to work with the data at hand. However, for threatened and poorly-known species, there is no short-cut when developing either a PBM or an IBM: investments to collect appropriately detailed data are required to ensure PVA models can assess extinction risk under complex environmental conditions. (C) 2015 Elsevier B.V. All rights reserved. KW - Model complexity KW - Individual-based model KW - Population-based model KW - Matrix model KW - Structured population model KW - Stage-based model Y1 - 2016 U6 - https://doi.org/10.1016/j.ecolmodel.2015.11.022 SN - 0304-3800 SN - 1872-7026 VL - 323 SP - 87 EP - 95 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Leins, Johannes A. A1 - Banitz, Thomas A1 - Grimm, Volker A1 - Drechsler, Martin T1 - High-resolution PVA along large environmental gradients to model the combined effects of climate change and land use timing BT - lessons from the large marsh grasshopper JF - Ecological modelling : international journal on ecological modelling and systems ecology N2 - Both climate change and land use regimes affect the viability of populations, but they are often studied separately. Moreover, population viability analyses (PVAs) often ignore the effects of large environmental gradients and use temporal resolutions that are too coarse to take into account that different stages of a population's life cycle may be affected differently by climate change. Here, we present the High-resolution Large Environmental Gradient (HiLEG) model and apply it in a PVA with daily resolution based on daily climate projections for Northwest Germany. We used the large marsh grasshopper (LMG) as the target species and investigated (1) the effects of climate change on the viability and spatial distribution of the species, (2) the influence of the timing of grassland mowing on the species and (3) the interaction between the effects of climate change and grassland mowing. The stageand cohort-based model was run for the spatially differentiated environmental conditions temperature and soil moisture across the whole study region. We implemented three climate change scenarios and analyzed the population dynamics for four consecutive 20-year periods. Climate change alone would lead to an expansion of the regions suitable for the LMG, as warming accelerates development and due to reduced drought stress. However, in combination with land use, the timing of mowing was crucial, as this disturbance causes a high mortality rate in the aboveground life stages. Assuming the same date of mowing throughout the region, the impact on viability varied greatly between regions due to the different climate conditions. The regional negative effects of the mowing date can be divided into five phases: (1) In early spring, the populations were largely unaffected in all the regions; (2) between late spring and early summer, they were severely affected only in warm regions; (3) in summer, all the populations were severely affected so that they could hardly survive; (4) between late summer and early autumn, they were severely affected in cold regions; and (5) in autumn, the populations were equally affected across all regions. The duration and start of each phase differed slightly depending on the climate change scenario and simulation period, but overall, they showed the same pattern. Our model can be used to identify regions of concern and devise management recommendations. The model can be adapted to the life cycle of different target species, climate projections and disturbance regimes. We show with our adaption of the HiLEG model that high-resolution PVAs and applications on large environmental gradients can be reconciled to develop conservation strategies capable of dealing with multiple stressors. KW - Climate change KW - Land use KW - Population viability analysis KW - Stage-based model KW - High resolution KW - Environmental gradients Y1 - 2020 U6 - https://doi.org/10.1016/j.ecolmodel.2020.109355 SN - 0304-3800 SN - 1872-7026 VL - 440 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Radchuk, Viktoriia A1 - Johst, Karin A1 - Groeneveld, Jürgen A1 - Turlure, Camille A1 - Grimm, Volker A1 - Schtickzelle, Nicolas T1 - Appropriate resolution in time and model structure for population viability analysis: Insights from a butterfly metapopulation JF - : an international journal N2 - The importance of a careful choice of the appropriate scale for studying ecological phenomena has been stressed repeatedly. However, issues of spatial scale in metapopulation dynamics received much more attention compared to temporal scale. Moreover, multiple calls were made to carefully choose the appropriate model structure for Population Viability Analysis (PVA). We assessed the effect of using coarser resolution in time and model structure on population dynamics. For this purpose, we compared outcomes of two PVA models differing in their time step: daily individual-based model (dIBM) and yearly stage-based model (ySBM), loaded with empirical data on a well-known metapopulation of the butterfly Boloria eunomia. Both models included the same environmental drivers of population dynamics that were previously identified as being the most important for this species. Under temperature change scenarios, both models yielded the same qualitative scenario ranking, but they quite substantially differed quantitatively with dIBM being more pessimistic in absolute viability measures. We showed that these differences stemmed from inter-individual heterogeneity in dIBM allowing for phenological shifts of individual appearance. We conclude that a finer temporal resolution and an individual-based model structure allow capturing the essential mechanisms necessary to go beyond mere PVA scenario ranking. We encourage researchers to carefully chose the temporal resolution and structure of their model aiming at (1) depicting the processes important for (meta)population dynamics of the species and (2) implementing the environmental change scenarios expected for their study system in the future, using the temporal resolution at which such changes are predicted to operate. KW - Temporal grain KW - Model complexity KW - Model comparison KW - Population dynamics KW - Individual-based model KW - Stage-based model Y1 - 2014 U6 - https://doi.org/10.1016/j.biocon.2013.12.004 SN - 0006-3207 SN - 1873-2917 VL - 169 SP - 345 EP - 354 PB - Elsevier CY - Oxford ER -