Ecology in a (rapidly) changing world
I study how animals perceive and adjust to their environment,
and why this matters for populations and ecosystems.
My model of choice: large herbivores. Because you can (relatively) easily monitor their behaviour in natura, and they have important ecosystem effects. Some have high societal and economical values, so my research sometimes matter beyond basic science.
We (as humans) are making the world's climate different. How this affects organisms in the hottest applied ecological question. I do my share to bring an answer to it.
Research outputs
the most interesting ones, in no specific order!
Memory-driven movements explain home-range formation, reduce competition, and underlie migration strategies
Most animals use a limited space compared to what is available to them, i.e. they have well-defined home-ranges. What mechanism leads to such pattern is unknown, although it is hypothesized that memory does play a role. We have recently shown that the use of spatial memory leads to more efficient foraging than other forms of movements and that home-ranges naturally emerge from such memory-driven movements (Riotte-Lambert et al. 2015 Am. Nat.). We have further shown that animals with spatial memory reduce competition pressure by segregating themselves (Riotte-Lambert et al. 2015 Am. Nat.), and that these memory-driven movements could have important implications for the study of density dependence and population regulation (Riotte-Lambert et al. 2017 Proc. Roy. Soc. Lond. B.).
Another widely-observed movement pattern that is believed to be largely influenced by spatial memory is migration. We have recently described a long (up to 250 km), trans-boundary (between Zimbabwe and Botswana) migration of African elephants (Tshipa et al. 2017 Biol. Cons.) driven by the availability of surface-water, and are investigating the role memory plays in this migration, in the face of unpredictable climate variability.
Finally, we are currently studying to what extent memory-use, which can lead to predictability in movement, matters in the predator-prey space race (Patin et al. preprint on bioRxiv).
Spatial predator avoidance is pervasive and occurs at multiple scales
Animals must go where their food is, but need to compromise with the risk of being predated upon when foraging means being in an unsafe place. This is well known, but surprisingly we don't understand so well the contribution of spatial avoidance vs. other strategies (like vigilance), and most importantly at what scale does this avoidance occur. We are studying this theoretically (Patin et al. 2019 Am. Nat.), but also empirically in various systems. For instance, we have shown that plains zebras move quickly away from lions when they encounter them (Courbin et al. 2016 Oikos), but most importantly move away from waterholes at night, to reduce the ‘chance’ of encounter, and come back to the same areas the next day (Courbin et al. 2019 J. Anim. Ecol.). This diel migration (similar to the famous diel vertical migration of aquatic animals) decrease risk by more than 60% in the dry season! (to the best of my knowledge this is the first quantification of the impact of such diel migration, correct me if I am wrong). Although I do work a lot with African ungulates, I do also conduct studies on temperate ungulates (e.g. roe deer: Padié et al. 2015 Oikos) including investigating the persistence of anti-predator behaviours in absence of predators (in black-tailed deer: Chamaillé-Jammes et al. 2014 Oecologia, Le Saout et al. 2015 Ethology). I even have studied rabbits ;-) (Blanchard et al. 2018 BMC Ecology). Check out the publication list!
Overall, I am interested to understand the extent of all the non-lethal effects, still poorly quantified (Say-Sallaz et al. 2019 Biol. Cons.), that predators exert on their prey.
Human activities reshape animal movements
I am curious to understand to what extent people’s presence and human activities modifies movement strategies of animals. This can be done through large-scale global collaborative analyses, such as in Tucker et al. 2018 Science where we showed that animals move less where human footprint is high. I am however more interested in getting into the details of why this happens, and thus address the issue of human influence on animal movements in many systems. For instance, in areas where people, cattle and wildlife such as elephants and buffalo co-exist (Valls-Fox et al. 2018 Anim. Cons.). Elephant’s response differ widely to the one of buffalo, the former living with people by fine-scale adjustments while the latter is ‘pushed away’ from areas used by people. In France, we have shown that roe deer avoidance of risky areas occur both at the habitat scale and within-habitats, but not at larger scale (Padié et al. 2015 Oikos). We have also showed experimentally that roe deer reactive response is more associated with the proximity of the threat that the nature of it (Padié et al. 2015 Eur. J. Wildl. Res.). Currently, I am fascinated by how wild boars use the landscape, and the strategies they develop to navigate rural- to peri-urban gradients (ongoing studies).
These issues fit in my broader interest for understanding how people and ungulate (and their predators sometimes) interact (Kuijper et al. 2016 Proc. Roy. Soc. Lond. B, Martin et al. 2020 Biol. Rev.).
Methods and tools for movement ecology
I am always keen to think about, develop and try new approaches, always led by the eagerness to learn new things. So over the years, for instance, we have developed new statistical approaches to study recursion patterns in movement data (Riotte-Lambert et al. 2017 Behav. Ecol.), and to segment trajectories to detect behavioural modes or identify home-range shifts (Patin et al. 2020 J. Anim. Ecol., R package segclust2d).
I have a particular interest in the study of habitat selection, so here again I am always willing to try new methods (Michelot et al. 2019 Biometrics) and I have recently revisited the classical interpretation of resource selection functions (Chamaillé-Jammes preprint on bioRxiv).
Also, with my colleague L. Latorre, professor of electronical engineering, we have recently developed a new tool - the audiologger - that we use to record the sounds heard and made by the animal. Audio data, combined or not with GPS and accelerometer data, allow a much better inference of the behaviour of the animal (Wijers et al. 2019 Front. Ecol. Evol.), and of its response to environmental stimuli. This is ongoing, stay tuned for amazing data!
The CNRS LTSER Hwange National Park (Zimbabwe): insights on the role of surface-water in the ecology of savanna ungulates.
I've been working in Hwange NP (filled polygon in the map), one of the largest African's protected area, during my PhD (started in 2002), and ever since. Among other things, I've revealed that in this park climate change is occurring with drought becoming more severe (Chamaillé-Jammes et al. 2007 J. Arid Environm.). I've also clarified the drivers of vegetation spatial patterns (rainfall, waterholes: Chamaillé-Jammes et al. 2006 Int. J. Remote Sens., Chamaillé-Jammes et al. 2009 Ecography) and questioned the role of artificial water provision on the ecology of the park (Chamaillé-Jammes et al. 2007 Austral Ecol.). Finally, I have studied the long-term dynamics of the large herbivore community in the park (Valeix et al. 2008 Anim. Cons., Chamaillé-Jammes et al. 2016 PloS One).
I have had, and still have, a special interest in understanding how availability of surface-water affects the distribution and population dynamics of elephants, in Hwange and elsewhere. See the following papers: Chamaillé-Jammes et al. 2007 J. Appl. Ecol. and Chamaillé-Jammes et al. 2008 J. Anim. Ecol. for some population-level studies, and Chamaillé-Jammes et al. 2013 PloS One, Tshipa et al. 2017 Biol. Cons. and Valls-Fox et al. 2018 Landscape Ecol. for some individual-level studies.
Oh, and with others, this research has led Hwange NP to become a Long-Term Socio-Ecological Research (LTSER)(in French, "Zone Atelier") site of my institution, the CNRS (website). I currently am the deputy director of this program.
Plant architecture is a key trait driving plant-herbivore interactions
This is a bit of a side project for me, but I love it. By browsing plants, herbivores modify the growth and architecture of woody plants, changing their allometry (Moncrieff et al. 2011 Ecology). I believe that understanding plant architectural response to browsing is key to understand the tree-browser interaction. In savannas, we have worked to reveal the plant development rules leading to 'cages' and, using a suite of tree species, how these rules may be aggregated in an index that predict well the herbivore intake rate (Charles-Dominique et al. 2017 Funct. Ecol.). We are now extending current 3D architectural models of tree growth to simulate browsing, plant response and its effect on plant resource acquisition. But it all started with some drawings (this one is by C. Edelin. He says it's easy... and yes there is a tree that looks exactly like this!).
Contact
Email:
simon.chamaille@cefe.cnrs.fr
Phone:
(+33)0467613218
Postal:
CEFE-CNRS,
1919 route de Mende,
34293 Montpellier Cedex 5,
France
