Interpreting realized pollen flow in terms of pollinator travel paths and land-use resistance in heterogeneous landscapes

Widespread ecosystem change has led to declines in species world-wide. The loss of pollinators in particular constitutes a problem for ecosystem function and crop production. Understanding how landscape change affects pollinator movement, effective pollen flow, and plant and pollinator survival is therefore a global priority. In this study we investigated patterns of effective pollen flow, using wild cherry tree (Prunus avium) progeny arrays, to address two questions in three case studies: Do land-use types present different resistances to pollinator movement? Which pollinator travel path best explains the pollination data (straight lines, weighted straight lines, least cost paths or pair-wise resistance)? Trees and progeny arrays were genotyped and effective pollen flow and pollinator movement were estimated using the spatially explicit mating model. We found that pollinators did modify their travel paths in response to land-use type and arrangement, but the travel path that best described pollinator movement and the resistance rank of the land uses depended on the type and size of land-use patches and the landscape context. We propose a novel theoretical framework rooted in behavioural ecology, the resource model, for interpreting pollinator behaviour in heterogeneous landscapes. We conclude by discussing the importance and practicality of conservation and management strategies in which native and non-native land-use types together provide functional habitat and support ecosystem services across economic landscapes.

[1]  R. Bošković,et al.  Characterisation of novel S-alleles from cherry (Prunus avium L.) , 2008, Tree Genetics & Genomes.

[2]  Yvan Richard,et al.  Cost distance modelling of landscape connectivity and gap‐crossing ability using radio‐tracking data , 2010 .

[3]  Jordi Bascompte,et al.  Spatial mating networks in insect-pollinated plants. , 2008, Ecology letters.

[4]  David R. Anderson,et al.  Model selection and multimodel inference : a practical information-theoretic approach , 2003 .

[5]  R. Macarthur,et al.  The Theory of Island Biogeography , 1969 .

[6]  M. Aizen,et al.  Pollination and other ecosystem services produced by mobile organisms: a conceptual framework for the effects of land-use change. , 2007, Ecology letters.

[7]  Atte Moilanen,et al.  METAPOPULATION DYNAMICS: EFFECTS OF HABITAT QUALITY AND LANDSCAPE STRUCTURE , 1998 .

[8]  S. Oddou-Muratorio,et al.  Estimating the variance of male fecundity from genotypes of progeny arrays: evaluation of the Bayesian forward approach , 2011 .

[9]  D. Bebber,et al.  The Circe Principle Explains How Resource-Rich Land Can Waylay Pollinators in Fragmented Landscapes , 2011, Current Biology.

[10]  M. Fortin,et al.  Use of resistance surfaces for landscape genetic studies: considerations for parameterization and analysis , 2010, Molecular ecology.

[11]  J. Ollerton,et al.  Landscape structure influences pollinator movements and directly affects plant reproductive success , 2012 .

[12]  J. Rappole,et al.  The use of movement data as an assay of habitat quality , 1995, Oecologia.

[13]  J. Biesmeijer,et al.  Global pollinator declines: trends, impacts and drivers. , 2010, Trends in ecology & evolution.

[14]  Viral B. Shah,et al.  Using circuit theory to model connectivity in ecology, evolution, and conservation. , 2008, Ecology.

[15]  R. Macarthur,et al.  On Optimal Use of a Patchy Environment , 1966, The American Naturalist.

[16]  R. Testolin,et al.  Microsatellite DNA in peach (Prunus persica L. Batsch) and its use in fingerprinting and testing the genetic origin of cultivars. , 2000, Genome.

[17]  Todd C. Esque,et al.  Making molehills out of mountains: landscape genetics of the Mojave desert tortoise , 2011, Landscape Ecology.

[18]  T. Meagher Analysis of Paternity within a Natural Population of Chamaelirium luteum. 1. Identification of Most-Likely Male Parents , 1986, The American Naturalist.

[19]  W. J. Bell Searching Behavior Patterns in Insects , 1990 .

[20]  S. Oddou-Muratorio,et al.  MICROEVOLUTION OF S‐ALLELE FREQUENCIES IN WILD CHERRY POPULATIONS: RESPECTIVE IMPACTS OF NEGATIVE FREQUENCY DEPENDENT SELECTION AND GENETIC DRIFT , 2012, Evolution; international journal of organic evolution.

[21]  J. Osborne,et al.  Pollination biology of fruit-bearing hedgerow plants and the role of flower-visiting insects in fruit-set. , 2009, Annals of botany.

[22]  Chris J. Johnson,et al.  Maintaining or restoring connectivity of modified landscapes: evaluating the least-cost path model with multiple sources of ecological information , 2010, Landscape Ecology.

[23]  L. Fahrig,et al.  How should we measure landscape connectivity? , 2000, Landscape Ecology.

[24]  Veronica A. J. Doerr,et al.  Connectivity, dispersal behaviour and conservation under climate change: A response to Hodgson et al. , 2011 .

[25]  J. Guitian,et al.  Pollen transfer and diurnal versus nocturnal pollination in Lonicera etrusca , 1993 .

[26]  B. Degen,et al.  Mating patterns and pollen dispersal in four contrasting wild cherry populations (Prunus avium L.) , 2011, European Journal of Forest Research.

[27]  R. Dyer,et al.  Pollination graphs: quantifying pollen pool covariance networks and the influence of intervening landscape on genetic connectivity in the North American understory tree, Cornus florida L. , 2011, Landscape Ecology.

[28]  K. Russell EUFORGEN Technical Guidelines for genetic conservation and use for wild cherry (Prunus avium) , 2003 .

[29]  J. Cottrell,et al.  Contemporary pollen flow, characterization of the maternal ecological neighbourhood and mating patterns in wild cherry (Prunus avium L.) , 2009, Heredity.

[30]  Wilfried Thuiller,et al.  Environmental and human factors influencing rare plant local occurrence, extinction and persistence: a 115‐year study in the Mediterranean region , 2005 .

[31]  L. Harder,et al.  Variation in Pollination: Causes and Consequences for Plant Reproduction , 2009, The American Naturalist.

[32]  N. Frascaria-Lacoste,et al.  Heterozygote excess in a self‐incompatible and partially clonal forest tree species —Prunus avium L. , 2006, Molecular ecology.

[33]  K. Tobutt,et al.  Allele-specific PCR detection of sweet cherry self-incompatibility (S) alleles S1 to S16 using consensus and allele-specific primers , 2003, Theoretical and Applied Genetics.

[34]  Clayton M. Hodges,et al.  Pollinator flight directionality and the assessment of pollen returns , 1981, Oecologia.

[35]  R. Moritz,et al.  Foraging distance in Bombus terrestris L. (Hymenoptera: Apidae) , 2008, Apidologie.

[36]  A. Dornhaus,et al.  Predation risk makes bees reject rewarding flowers and reduce foraging activity , 2011, Behavioral Ecology and Sociobiology.

[37]  A. Iezzoni,et al.  Polymorphic DNA Markers in Black Cherry (Prunus serotina) Are Identified Using Sequences from Sweet Cherry, Peach, and Sour Cherry , 2000 .

[38]  J. Vandermeer,et al.  Metapopulation Dynamics and the Quality of the Matrix , 2001, The American Naturalist.

[39]  J. Cane The potential consequences of pollinator declines on the conservation of biodiversity and stability of food crop yields , 1997 .

[40]  E. Jules,et al.  A broader ecological context to habitat fragmentation: Why matrix habitat is more important than we thought , 2003 .

[41]  J. Koricheva,et al.  A Meta-Analysis of Predation Risk Effects on Pollinator Behaviour , 2011, PloS one.

[42]  Kevin McGarigal,et al.  Estimating landscape resistance to movement: a review , 2012, Landscape Ecology.

[43]  Nicolas Ray,et al.  pathmatrix: a geographical information system tool to compute effective distances among samples , 2005 .

[44]  T. Ricketts The Matrix Matters: Effective Isolation in Fragmented Landscapes , 2001, The American Naturalist.

[45]  J. Thomson,et al.  Efficient harvesting of renewing resources , 2005 .

[46]  S. Rands,et al.  Field Margins, Foraging Distances and Their Impacts on Nesting Pollinator Success , 2011, PloS one.

[47]  W. Jordan,et al.  Molecular and spatial analyses reveal links between colony-specific foraging distance and landscape-level resource availability in two bumblebee species , 2012 .

[48]  R. Testolin,et al.  AC/GT and AG/CT microsatellite repeats in peach [Prunus persica (L) Batsch]: isolation, characterisation and cross-species amplification in Prunus , 1999, Theoretical and Applied Genetics.

[49]  G. King,et al.  Development of a second generation linkage map for almond using RAPD and SSR markers. , 2000, Genome.

[50]  Leslie Ries,et al.  Ecological Responses to Habitat Edges: Mechanisms, Models, and Variability Explained , 2004 .