Dr Nicolas Vereecken

LES ABEILLES PRENNENT LEURS QUARTIERS EN VILLE�

Jardins potagers et réserves naturelles comme relais de biodiversité urbaine?

nicolas.vereecken@ulb.ac.beChair of Agroecology, Interfaculty School of Bioengineering

Abeilles sauvages vs domestiques

Contexte

Apis mellifera

L’abeille domestique = 1 seule espèce

Photo NJ Vereecken

Déclin des pollinisateurs et approche conventionnelle pour renforcer le

service de pollinisation

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ront

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12(8

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= Cercle vicieux

La production agricole finit

par être dépendante d’une seule espèce de

pollinisateur

= Très fragile!

Projet à BruxellesAgriculture urbaine & abeilles sauvages

Projet de thèse de Celia Chaiban (promotion 2014)

4 mémorants bio-ingénieurs (promotion 2015)

Premier focus sur la structure des communautés d’abeilles sauvages dans les réserves naturelles vs. les jardins potagers collectifs en Région Bruxelles-Capitale

* structuration spatiale

* structuration fonctionnelle

* structuration phylogénétique

Collaboration avec l’IBGE, la SRABE, Le Début des Haricots

Collaboration avec l’UniLux, l’IRSNB, l’UMons

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25 sites sélectionnés 2015

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RANK SPECIES A SPECIES B SPATIO-TEMPORAL CORRELATION VALUE

1 A_barbilabris A_mitis 1.0000

2 L_pauxillum L_zonulum 1.0000

3 A_chrysoceles S_geofrellus 0.9485

4 N_lathburiana S_geofrellus 0.9485

5 A_ruficrus N_panzeri 0.9178

6 A_chrysoceles N_lathburiana 0.8991

7 A_haemorrhoa S_geofrellus 0.8440

8 A_chrysoceles A_haemorrhoa 0.8374

9 A_cineraria A_nigroaenea 0.8357

10 A_cineraria L_pallens 0.8282

Overview of the 10 most highly correlated species (Spearman's rho statistic) across months, habitats, sites and coloured pan traps

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La biodiversité est multivariée : elle va au-delà du simple comptage des

espèces présentes

Andrena floreaPhotos NJ Vereecken

Bryonia dioica

Osmia aurulenta Photo NJ Vereecken

Anthidium byssinum

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La famille des légumineuses (Fabaceae) est la première famille botanique d’importance écologique (alimentaire) pour les abeilles sauvages de Belgique

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Vereecken et al., in prep.

Espèces cleptoparasites montrant une préférence et/ou étant associés à des espèces montrant une préférence

Abeilles sauvages polylectiques mais montrant une préférence pour les plantes d’une famille ou d’un genre

Abeilles sauvages oligolectiques mais montrant une préférence pour les plantes d’une famille ou d’un genre

“Paysage alimentaire” des abeilles sauvages de Belgique

50 pages; disponible gratuitement sur www.jedonnevieamaplanete.be

50 pages; disponible gratuitement sur www.jedonnevieamaplanete.be

TRAIT CATEGORY TRAIT CODE TRAIT DESCRIPTION

Nesting strategy AerialResinNest Aerial nests built with plant resin (e.g. Anthidiellum strigatum)

Carder Larval cells built with moss, grass or plant fibres

Cleptoparasite No nest building (i.e. cleptoparasitic)

Excavator:Deadstems Nests in the ground; excavated by the nesting female

Excavator:Ground Nests in the ground; excavated by the nesting female

Renter:Existingcavitiesaboveground Renter of pre-existing nest and holes above the ground

Renter:Existingcavitiesbelowground Renter of pre-existing nest and holes below the ground

Socialparasite Parasite of primitively eusocial species (e.g. subgenus Psithyrus)

Renter:Snailshells Renter of empty snail shells

Dispersion ITD Inter-Tegular Distance = the distance between the insertion points of the wings

Social status Solitary Species nesting solitarily

Communal Species sharing a nest entrance

Solitary+Primitivelyeusocial Species with mixed social status; either solitary or primitively eusocial

Primitivelyeusocial Species primitively eusocial

Highlyeusocial Species highly eusocial (Apis mellifera)

Socialparasite Parasite of primitively eusocial species (e.g. subgenus Psithyrus)

Cleptoparasite Species parasitising the nests of solitary species

Pollen transport Legs&Body Species collecting pollen on their legs and on their body

Underside:Abdomen Species collecting pollen on the underside of their abdomen

Legsonly Species collecting pollen on their legs

Accidental Species collecting pollen accidentally (i.e., clepto- and social parasites)

Corbiculae Species collecting pollen in their corbiculae

Crop Species collecting pollen in their crop (Hylaeus)

Tongue length Short Short-tongued species

Long Long-tongued species

Pollen specialization Oligolectic Species with a strong preference for plants belonging to one genus or one

Polylectic Species capable of exploiting plants from several families

Seasonality Spring Species active only during spring (i.e. with a peak season before June 21)

Summer Species active only during summer (i.e. with a peak season after June 21)

Spring:Summer Species active in late spring and early summer

Year Species active all year round (e.g. bumblebees and the honey bee)

A functional approach revealscommunity responses to disturbancesDavid Mouillot1,2, Nicholas A.J. Graham2, Sebastien Villeger1,3, Norman W.H. Mason4,and David R. Bellwood2,5

1 Laboratoire ECOSYM, UMR 5119 CNRS-UM2-IRD-IFREMER, Place Euge ne Bataillon cc 93, 34095 Montpellier, France2ARC Centre of Excellence for Coral Reef Studies, James Cook University, Townsville, Qld 4811, Australia3Universite Paul Sabatier, CNRS, ENFA, UMR5174 EDB (Laboratoire Evolution et Diversite Biologique), 118 route de Narbonne,

F-31062 Toulouse, France4 Landcare Research, PO Box 40, Lincoln 7640, New Zealand5School of Marine and Tropical Biology, James Cook University, Townsville, Qld 4811, Australia

Understanding the processes shaping biological com-munities under multiple disturbances is a core challengein ecology and conservation science. Traditionally, ecol-ogists have explored linkages between the severity andtype of disturbance and the taxonomic structure ofcommunities. Recent advances in the application ofspecies traits, to assess the functional structure of com-munities, have provided an alternative approach thatresponds rapidly and consistently across taxa and eco-systems to multiple disturbances. Importantly, trait-based metrics may provide advanced warning of distur-bance to ecosystems because they do not need speciesloss to be reactive. Here, we synthesize empirical evi-dence and present a theoretical framework, based onspecies positions in a functional space, as a tool to revealthe complex nature of change in disturbed ecosystems.

Disturbance and biodiversity: why traits should matterDespite conservation efforts, biodiversity loss continuesapace at regional or global scales across a wide range ofecosystems, due to increasing intensity of disturbances(see Glossary), such as overexploitation of species [1],destruction of habitats [2], climate change [3], or invasionby alien species [4]. As a feedback, biodiversity erosion isimperiling the sustainability of ecological processes andthe provision of ecosystem services [5]. Thus, there is anurgent need to quantify and predict the effects of distur-bance on biodiversity patterns to guide conservation effortsand the management of ecological resources. Here, weconsider the term ‘disturbance’ in its widest sense asany event, natural or human-driven, that causes tempo-rary and localized shifts in species demographic rates. Weclassify disturbances in three categories as those caused by(i) direct human impacts; (ii) biotic pressure (mainly im-posed by exotic species); and (iii) environmental changes(abrupt shifts in abiotic conditions and habitat degrada-tion).

Until recently, the effect of disturbance on species di-versity was largely assumed to be unimodal, with speciesdiversity reaching its maximum at intermediate levels ofdisturbance [6]. The underlying mechanistic explanation

for this pattern is that competitive exclusion may reducespecies richness at low levels of disturbance, whereas highlevels of disturbance exclude all but the most disturbance-tolerant species. However, the unimodal model is far fromuniversal, having been falsified by observational [7],experimental [8], and theoretical studies [9]. Moreover,

Review

Glossary

Disturbance: any event, natural or human driven, that causes temporary and

localized shifts in demographic rates.

Fourth-corner analysis: a method that quantifies the correlations between

species traits and abiotic variables in a fourth matrix using three input matrices

(R, abiotic variables; L, species presences and/or absences or abundances; and

Q, species traits).

Functional dissimilarity: the dissimilarity in the functional space occupied by

two communities.

Functional divergence: the proportion of total abundance supported by species

with the most extreme trait values within a community.

Functional diversity: the distribution of species and their abundances in the

functional space of a given community.

Functional evenness: the regularity of the distribution and relative abundance

of species in functional space for a given community.

Functional identity: the mean value of functional traits, weighted by

abundance, across all species present in a given community.

Functional originality: the isolation of a species in the functional space

occupied by a given community.

Functional richness: the volume of multidimensional space occupied by all

species in a community within functional space.

Functional space: a multidimensional space where the axes are functional

traits along which species are placed according to their functional trait values.

Functional specialization: the mean distance of a species from the rest of the

species pool in functional space.

Functional trait: any trait directly influencing organismal performance.

Linear trait-environment method (LTE): a method that linearly relates species

traits to abiotic variables using species abundances across environments.

Maximum Entropy model (MaxEnt): a predictive model assuming that the

relative abundance of a given species in a given environment is a function of its

trait values.

Monotonic relation: a relation is monotonic if a response or dependent

variable consistently increases (or decreases) or stays the same with every

increase in an associated predictive or independent variable.

Performance filter: the process by which local abiotic variables determine the

performance of a given trait, defined as its fitness, in a given environment.

RLQ analysis: a three-table (R, abiotic variables; L, species abundances; Q,

species traits) ordination method testing the relations between species traits

and abiotic variables.

Trait filtering: the process by which abiotic variables determine whether a

species has the requisite traits to colonize, establish, and persist in a given

environment.

Trait: any morphological, physiological, or phenological feature usually

measurable at the individual level.

Unimodal relation: a relation is unimodal if a response or dependent variable has

a single mode (or peak) along the axis of the predictive or independent variable.Corresponding author: Mouillot, D. (david.mouillot@univ-montp2.fr).

0169-5347/$ – see front matter � 2012 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.tree.2012.10.004 Trends in Ecology & Evolution, March 2013, Vol. 28, No. 3 167

L ETTERThe multidimensionality of the niche reveals functional diversity

changes in benthic marine biotas across geological time

Sebastien Villeger,1,2,3*

Philip M. Novack-Gottshall4 and

David Mouillot1,5

AbstractDespite growing attention on the influence of functional diversity changes on ecosystem functioning, a

palaeoecological perspective on the long-term dynamic of functional diversity, including mass extinction crises,

is still lacking. Here, using a novel multidimensional functional framework and comprehensive null-models, we

compare the functional structure of Cambrian, Silurian and modern benthic marine biotas. We demonstrate

that, after controlling for increases in taxonomic diversity, functional richness increased incrementally between

each time interval with benthic taxa filling progressively more functional space, combined with a significant

functional dissimilarity between periods. The modern benthic biota functionally overlaps with fossil biotas but

some modern taxa, especially large predators, have new trait combinations that may allow more functions to be

performed. From a methodological perspective, these results illustrate the benefits of using multidimensional

instead of lower dimensional functional frameworks when studying changes in functional diversity over space

and time.

KeywordsBenthic invertebrates, corals, functional dissimilarity, functional richness, functional traits, Palaeozoic fossils.

Ecology Letters (2011) 14: 561–568

INTRODUCTION

All ecosystems on Earth are currently affected by human activities

(Vitousek et al. 1997) and one of the major components of this global

change is the accelerated loss of biodiversity (Vitousek et al. 1997).

Although biodiversity is a multifaceted concept that ranges from

genetic diversity inside a population to the variety of landscapes in

ecosystems, most studies have focused only on species richness

(Purvis & Hector 2000). Besides its intrinsic value, biodiversity

provides essential ecosystem services to human populations through

genetic resources, food production and nutrient-cycle regulation

(Costanza et al. 1997). In this context, there is a growing consensus

that the functional diversity of communities (i.e. diversity of species

traits, Petchey & Gaston 2006) is more informative than taxonomic

richness per se in explaining the structure and function of ecological

communities (McGill et al. 2006; Mokany et al. 2008). For instance,

within marine communities, there is evidence that functional diversity

of benthic communities drives important ecosystem processes (Solan

et al. 2004).

Like taxonomic diversity, functional diversity can be measured

within local communities (i.e. alpha-diversity) or among communities

(i.e. beta-diversity). The former component quantifies the functional

richness of the traits present in the community whereas the latter

corresponds to the dissimilarity of functional composition between

two or more communities. Several studies have focused on temporal

dynamics of functional richness for several taxa (Flynn et al. 2009;

Villeger et al. 2010) but there is to date no study assessing functional

dissimilarity trends because of a lack of a practical framework.

Therefore, in the global change context, it is urgent to develop a

general framework that allows assessing how changes in taxonomic

diversity affect functional diversity, for both its alpha and beta

components (Devictor et al. 2010).

Marine ecosystems, which are among the world�s most productive

and diverse (Costanza et al. 1997) and are facing unprecedented levels

of human pressure today (Halpern et al. 2008), have been subject to

both fundamental evolutionary diversifications as well as dramatic

extinction crises (Erwin 2008). Such events modified – sometimes

irreversibly – the biota, environments, and geochemical fluxes in

marine ecosystems (Alroy 2010). For instance, the Late Cretaceous

mass extinction (Schulte et al. 2010), which caused the demise of more

than 60% of all animal taxa, altered biogeochemical processes for

millions of years afterwards (D�Hondt 2005) and its biogeographic

impact persists today in the marine biota (Krug et al. 2009). Much of

our knowledge of such transitions is based on the well-preserved

marine invertebrate fossil record (Foote & Sepkoski 1999), and

especially that from the benthic shelf habitat (Alroy et al. 2008). There

has been substantial progress in understanding how biological traits

of marine organisms contributed to these evolutionary transitions.

For example, victims of the Late Permian mass extinction were

disproportionately immobile and physiologically �unbuffered� (Bam-

bach et al. 2002), whereas no such selectivity existed during the Late-

Cretaceous mass extinction (Jablonski & Raup 1995), at least among

benthic invertebrates (Friedman 2009). Such approaches have been

generalized to focus on multiple traits simultaneously across entire

1Laboratoire ECOSYM, UMR 5119 CNRS-UM2-IRD-IFREMER, Place Eugene

Bataillon, 34095 Montpellier, France2CNRS, UPS, ENFA, UMR5174 EDB (Laboratoire Evolution et Diversite

Biologique), 118 route de Narbonne, F-31062 Toulouse, France3Universite de Toulouse, UMR5174 EDB, F-31062 Toulouse, France

4Department of Biological Science, Benedictine University, Lisle, IL 60532, USA5ARC Centre of Excellence for Coral Reef Studies, James Cook University,

Townsville, Qld 4811, Australia

*Correspondence: E-mail: villeger@cict.fr

Ecology Letters, (2011) 14: 561–568 doi: 10.1111/j.1461-0248.2011.01618.x

� 2011 Blackwell Publishing Ltd/CNRS

Villéger et al. (2011) Mouillot et al. (2013)

Vereecken & Dufrêne (in prep.)

1.5 1.0 0.5 0.0

2012

CCR

CSC

CMH

JUL

CSP

PPJC

CSA

PDC

JLM

CNDF

JM

JVN

PCB

JLR

JD

JPSF

JPS

JSD

JML

PPASF

Tanglegram of Quebec

0.0 0.5 1.0 1.5

2013

CCR

CSA

JPSF

CNDF

JPS

JD

PCB

JLM

JM

JLR

JML

JVN

JSD

CMH

CSP

PDC

JUL

CSC

PPASF

PPJC

INDICES MONTRÉAL QUÉBEC

Cophenetic Correlation Coefficient (-1 < 0 < 1) 0.778 0.072

Entanglement (0 < 1) 0.199 0.422

Baker’s gamma index (-1 < 0 < 1) 0.715 0.025

2.0 1.5 1.0 0.5 0.0

2012

CHD

PBL

PPPM

PIB

PPPH

CL

CP

CLV

CSG

JAN

JL

CSL

CC

JH

CBS

CV

PV

JS

JPM

JRE

JR

JP

JSM

Tanglegram of Montreal

0.0 0.5 1.0 1.5 2.0

2013

CHD

CSG

PIB

PPPH

PBL

PPPM

JAN

JL

JPM

CL

JR

JS

CP

JH

CLV

PV

CC

CSL

CV

CBS

JRE

JP

JSM

La composition des communautés est plus variable à Québec qu’à Montréal

Les communautés des parcs montréalais sont distincts des autres sites étudiés

Urbanisation => atoll de communautés peu variables et très structurées?

Montréal Québec

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174 espèces 50% des espèces de la Province de Québec

146 espèces

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Etienne NORMANDIN, Candidat Maîtrise

Espèces exotiques/indicatrices?

Paramètres paysagers?

Structure spatiale de l’activité apicole

Densité des ruches/compétition?

Abeilles sauvages vs domestiques

Compétition?

Les populations de deux espèces ayant des exigences écologiques identiques, c'est-à-dire exploitant une ressource limitante unique, ne peuvent coexister indéfiniment dans un milieu stable et homogène, la plus compétitive des deux espèces finissant à plus ou moins long terme par éliminer l'autre.

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Principe de GAUSE (1934) en écologie des communautés

(2003)(2004)

Principes de base : �

1. Les ressources florales ne sont JAMAIS illimitées localement, et on observe un recouvrement des ressources utilisées par

les abeilles sauvages et domestiques��

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2. Chaque ruche d’A. mellifera contient jusqu’à 30.000 individus actifs en permanence qui doivent accumuler des grandes quantités de nectar et surtout de pollen pour assurer le développement de la colonie��

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3. Aucune goutte de nectar, aucun grain de pollen ne peut être récolté 2x

En règle générale, les petits bourdons veillent au maintien de la colonie, alors que les plus gros récoltent du pollen et du nectar en dehors de la colonie.

Les petits bourdons ne quittent la colonie pour récolter à leur tour que lorsque les ressources deviennent moins importantes dans l’environnement

Bombus terrestris

Bombus lucorum

Bombus pascuorum

Bombus lapidarius

Goulson & Sparrow (2009) J. Insect Conserv. 13: 177-181

Photo NJ Vereecken Photo NJ Vereecken

Photo NJ VereeckenPhoto NJ Vereecken

Interactions interspécifiques et compétition

Interactions interspécifiques et compétition

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Apis mellifera

Abeilles sauvages

Photo NJ Vereecken

Photo NJ Vereecken

L’introduction de ruches modifie la fréquence de visite des fleurs par les abeilles sauvages - changement de comportement/choix floraux

Hylaeus (Macrohylaeus) alcyoneus Apis melliferaPhoto NJ Vereecken

Photo HB Jacobi

Interactions interspécifiques et compétition

Roubik & Villanueva-Guttiérez (2009) Biol. J. Linn. Soc. 98: 152-160

L’introduction de colonies d’Apis mellifera africanisées modifie les ressources alimentaires exploitées par les abeilles sauvages comme les Centris (72 spp.) et les mégachiles (28 spp.)

Le maintien des populations d’abeilles sauvages dépend donc de leur capacité à exploiter des ressources alimentaires alternatives lorsque la compétition locale avec Apis mellifera augmente de façon significative

In The Conservation of Bees, Metheson et al. (eds.), Linnean Society Symposium Series 18 (1996)

Développer une approche plus écologique de l’activité apicole

Considérer les “coûts” de l’apiculture intensive en terme de biodiversité, et pas uniquement la valeur économique des produits

dérivés de la ruche

Eviter d’introduire des ruches à proximité des réserves naturelles

et autres sites à haute valeur biologique

d’après Paini (2004)

Merci pour votre attention

Photo NJ Vereecken

nicolas.vereecken@ulb.ac.be