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Ungulates MOVing across heterogeneous landscapes: identifying behavioural processes linking global change to spatially- explicIT demographic performance and management
项目编号ANR-16-CE02-0010
Madame Anne Loison
项目主持机构Laboratoire d'Ecologie Alpine
开始日期2017
结束日期2021-1-01
英文摘要The responses of animal populations to global change are mediated by proximate behavioral processes that determine the energy budget and, ultimately, the demographic performance of individuals. Animal movement is currently considered as a key behavior for understanding, and so predicting, the responses of animals (such as shifts in spatial distribution) to global change. The plasticity of movement behavior within and among individuals is hence critical to the potential for both adaptive and non-adaptive responses of animal populations to environmental variability and change. Mov-It aims to be among the first empirical based studies to evaluate, at both intra- and inter-specific levels, how individual behavioral heterogeneity impacts movement energetics, habitat selection, and demographic responses to global change.
We will (1) quantify intra- and inter-specific variability in movement patterns and activity rhythms and, from this, infer energetic budgets of locomotion in relation to major drivers of global change (temperature, seasonality, landscape modification, human activities) (2) use these new insights to identify population responses to environmental drivers while accounting for individual variability, (3) parametrise spatially explicit demographic models to forecast how population dynamics and distribution should respond to environmental changes and human disturbance, accounting for individual heterogeneity, landscape constraints, and species-specific traits. To reach these goals, we will combine long term monitoring programs on spatial behavior and demography, new empirical data from cutting-edge biologgers, and demographic modeling to generate spatially-explicit demographic models for forecasting population- and species-specific responses to global change.
We will focus on large wild herbivores, considered as ecosystem engineers with marked impacts on their habitat, as a highly relevant model group to link fine-scale processes of movement with broad-scale demographic rates and patterns of distribution. We will exploit 6 unique long term monitoring studies (>20 years) of marked individuals (>1000 individuals marked with GPS so far) of 4 species (roe deer, red deer, chamois, mouflon) with contrasting behavior and life histories. We will generate a massive amount of additional, very high resolution, data from GPS monitoring combined with biologgers (200 year-individuals over the 6 sites) to infer ranging behaviors and energetic expenditure. This new generation of biologgers can record tri-axial accelerometry up to 40 times per second, but also geomagnetism, temperature, light, and pressure. They will allow us to obtain completely new insights into animal body micro-movements and behaviors (i.e. proxies of energetic expenditure that previously could only be measured in the laboratory), but also into the local environment experienced by the animal itself in a natural setting.
Through 5 linked work packages, we will explore how key dimensions of the landscape which were hitherto beyond the reach of ecological studies (thermal- and energetic-landscapes, WPs 1 & 2), shape movement behavior, time budgets, and energy balance in large herbivores. Next, we will focus on consistent inter-individual variability in movement and activity in relation to habitat heterogeneity, infrastructures (WP3), and human recreational activities (WP4). From there, we will link individual variability in movement and energetic balance to demographic performance by parameterising Integral Population Models (WP5). Mov-It will thereby provide new insights on the sensitivity of population dynamics and spatial distribution of large wild herbivores to forecast global change (both climatic and human-driven) derived from behavioral processes studied at the individual level in species with contrasting life histories, and clearly founded in the principles of evolutionary ecology.
资助机构FR-ANR
项目经费533998
项目类型(DS0101) 2016
URLhttp://www.agence-nationale-recherche.fr/en/anr-funded-project/?solr=run&tx_lwmsuivibilan_pi2%5BCODE%5D=ANR-16-CE02-0010
国家FR
语种英语
文献类型项目
条目标识符http://gcip.llas.ac.cn/handle/2XKMVOVA/69538
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Madame Anne Loison.Ungulates MOVing across heterogeneous landscapes: identifying behavioural processes linking global change to spatially- explicIT demographic performance and management.2017.
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