Remote sensing and ecosystem services: Current status and future opportunities for the study of bees and pollination-related services

Current Forestry Reports

Volumn 1, Issue 4, 2015, Pages 261-274

  Galbraith, Sara M ^a,b   Vierling, L A ^a   Bosque Perez N A ^a  

^a UNIVERSITY OF IDAHO   (United States)

^b CATIE   (Costa Rica)

Author keywords

Bees; Ecosystemservices; Pollination; Remote sensing

Indexed keywords

EID: 84977596338     PISSN: None     EISSN: 21986436     Source Type: Journal    
DOI: 10.1007/s40725-015-0024-6     Document Type: Article

References (112)

1. Hansen MC, DeFries RS, Townshend JRG, Sohlberg R. Global land cover classification at 1 km spatial resolution using a classification tree approach. Int J Remote Sens. 2000;21:1331–64.
2. Kennedy RE, Cohen WB, Schroeder TA. Trajectory-based change detection for automated characterization of forest disturbance dynamics. Remote Sens Environ. 2007;110:370–86.
3. Wulder MA, Dymond CC, White JC, Leckie DG, Carroll AL. Surveying mountain pine beetle damage of forests: a review of remote sensing opportunities. For Ecol Manag. 2006;221:27–41.
4. Magney TS, Eusden SA, Eitel JUH, Logan BA, Jiang J, Vierling LA. Assessing leaf photoprotective mechanisms using terrestrial LiDAR: towards mapping canopy photosynthetic performance in three dimensions. New Phytol. 2014;201:344–56.
5. DeFries RS, Field CB, Fung I, Collatz GJ, Bounoua L. Combining satellite data and biogeochemicalmodels to estimate global effects of human-induced land cover change on carbon emissions and primary productivity. Glob Biogeochem Cycles. 1999;13:803–15.
6. Vihervaara P, Mononen L, Auvinen A-P, Virkkala R, Lü Y, Pippuri I, et al. How to integrate remotely sensed data and biodiversity for ecosystem assessments at landscape scale. Landsc Ecol. 2014;30:501–16.
7. de Araujo Barbosa CC, Atkinson PM, Dearing JA. Remote sensing of ecosystem services: a systematic review. Ecol Indic. 2015;52:430–43. Describes and quantifies the number of publications applying remote sensing to ecosystem service questions, the range of variables predicted and how they are applied.
8. Daily GC. Introduction: what are ecosystem services? In: Daily GC, editor. Nature’s Services: Societal dependence on natural ecosystems. Washington D.C: Island Press; 1997. pp. 1–11.
9. Millennium Ecosystem Assessment. Ecosystems and human wellbeing: Synthesis. Washington D.C.: Island Press; 2005. vol. 3.
10. Newton AC, Hill RA, Echeverria C, Golicher D, Rey Benayas JM, Cayuela L, et al. Remote sensing and the future of landscape ecology. Prog Phys Geogr. 2009;33:528–46.
11. Pettorelli N, Laurance WF, O’Brien TG, Wegmann M, Nagendra H, Turner W. Satellite remote sensing for applied ecologists: opportunities and challenges. J Appl Ecol. 2014;51:839–48. This review includes a discussion of established work and new avenues for interdisciplinary applications of passive and active satellite remote sensing tools to ecological studies. Includes a description of remote sensing applications for understanding organism movement and individual species detection.
12. Leyequien E, Verrelst J, Slot M, Schaepman-Strub G, Heitkönig IMA, Skidmore A. Capturing the fugitive: applying remote sensing to terrestrial animal distribution and diversity. Int J Appl Earth Obs Geoinf. 2007;9:1–20.
13. Müller J, Brandl R. Assessing biodiversity by remote sensing in mountainous terrain: the potential of LiDAR to predict forest beetle assemblages. J Appl Ecol. 2009;46:897–905.
14. Vierling KT, Bässler C, Brandl R, Vierling LA, Weiss I, Müller J. Spinning a laser web: predicting spider distributions using LiDAR. Ecol Appl. 2011;21:577–88.
15. Chapman JW, Drake VA, Reynolds DR. Recent insights from radar studies of insect flight. Annu Rev Entomol. 2011;56:337–56.
16. Riley JR. Remote sensing in entomology. Annu Rev Entomol. 1989;34:247–71.
17. Hay SI, Packer MJ, Rogers DJ. The impact of remote sensing on the study and control of invertebrate intermediate hosts and vectors for disease. Int J Remote Sens. 1997;18:2899–930.
18. Garcia-Ruiz F, Sankaran S, Maja JM, Lee WS, Rasmussen J, Ehsani R. Comparison of two aerial imaging platforms for identification of Huanglongbing-infected citrus trees. Comput Electron Agric. 2013;91:106–15.
19. Ollerton J, Winfree R, Tarrant S. How many flowering plants are pollinated by animals? Oikos. 2011;120:321–6.
20. Klein AM, Vaissière BE, Cane JH, Steffan-Dewenter I, Cunningham SA, Kremen C, et al. Importance of pollinators in changing landscapes for world crops. Proc R Soc Biol Sci. 2007;274:303–13.
21. Kremen C, Williams NM, Aizen MA, Gemmill-Herren B, LeBuhn G, Minckley R, et al. Pollination and other ecosystem services produced by mobile organisms: a conceptual framework for the effects of land-use change. Ecol Lett. 2007;10:299–314.
22. Brown MJF, Paxton RJ. The conservation of bees: a global perspective. Apidologie. 2009;40:410–6.
23. Potts SG, Biesmeijer JC, Kremen C, Neumann P, Schweiger O, Kunin WE. Global pollinator declines: trends, impacts and drivers. Trends Ecol Evol. 2010;25:345–53.
24. Winfree R. Global change, biodiversity, and ecosystem services: what can we learn from studies of pollination? Basic Appl Ecol. 2013;14:453–60.
25. Nagendra H. Using remote sensing to assess biodiversity. Int J Remote Sens. 2001;22:2377–400.
26. Turner W, Spector S, Gardiner N, Fladeland M, Sterling E, Steininger M. Remote sensing for biodiversity science and conservation. Trends Ecol Evol. 2003;18:306–14.
27. Gamon JA, Rahman AF, Dungan JL, Schildhauer M, Huemmrich KF. Spectral Network (SpecNet)—what is it and why do we need it? Remote Sens Environ. 2006;103:227–35.
28. Kissling DW, Pattemore DE, Hagen M. Challenges and prospects in the telemetry of insects. Biol Rev. 2014;89:511–30.
29. Wulder MA, White JC, Goward SN, Masek JG, Irons JR, Herold M, et al. Landsat continuity: issues and opportunities for land cover monitoring. Remote Sens Environ. 2008;112:955–69.
30. Roy DP, Wulder MA, Loveland TR, Woodcock CE, Allen RG, Anderson MC, et al. Landsat-8: science and product vision for terrestrial global change research. Remote Sens Environ. 2014;145:154–72.
31. Dobson CM, Ulaby FT, LeToan T, Beaudoin A, Kasischke ES, Christensen N. Dependence of radar backscatter on coniferous forest biomass. IEEE Trans Geosci Remote Sens. 1992;30:412–5.
32. Lefsky MA, Cohen WB, Parker GG, Harding DJ. Lidar remote sensing for ecosystem studies. Bioscience. 2002;52:19–30.
33. Kerr JT, Ostrovsky M. From space to species: ecological applications for remote sensing. Trends Ecol Evol. 2003;18:299–305.
34. Andrew ME, Wulder MA, Nelson TA. Potential contributions of remote sensing to ecosystem service assessments. Prog Phys Geogr. 2014;38:328–53. Description of the remote sensing products available that offer more direct estimates of ecological properties controlling ecosystem services than those currently represented in most studies. Includes a discussion of biodiversity proxies and phenology measurements useful for bee and/or pollination studies
35. Burkhard B, Kroll F, Nedkov S, Müller F. Mapping ecosystem service supply, demand and budgets. Ecol Indic. 2012;21:17–29.
36. Biesmeijer JC, Roberts SPM, Reemer M, Ohlemüller R, Edwards M, Peeters T, et al. Parallel declines in pollinators and insectpollinated plants in Britain and the Netherlands. Science. 2006;313:351–4.
37. Fontaine C, Dajoz I, Meriguet J, Loreau M. Functional diversity of plant-pollinator interaction webs enhances the persistence of plant communities. PLoS Biol. 2006;4:129–35.
38. Hoehn P, Tscharntke T, Tylianakis JM, Steffan-Dewenter I. Functional group diversity of bee pollinators increases crop yield. Proc R Soc B. 2008;275:2283–91.
39. Martins KT, Gonzalez A, Lechowicz MJ. Pollination services are mediated by bee functional diversity and landscape context. Agric Ecosyst Environ. 2015;200:12–20.
40. Lonsdorf E, Kremen C, Ricketts T, Winfree R, Williams N, Greenleaf S. Modelling pollination services across agricultural landscapes. Ann Bot. 2009;103:1589–600.
41. Luck GW, Daily GC, Ehrlich PR. Population diversity and ecosystem services. Trends Ecol. Evol. 2003;18:331–6.
42. Mori AS, Furukawa T, Sasaki T. Response diversity determines the resilience of ecosystems to environmental change. Biol Rev. 2013;88:349–64.
43. Kremen C, Williams NM, Bugg RL, Fay JP, Thorp RW. The area requirements of an ecosystem service: crop pollination by native bee communities in California. Ecol Lett. 2004;7:1109–19.
44. Ricketts TH, Regetz J, Steffan-Dewenter I, Cunningham SA, Kremen C, Bogdanski A, et al. Landscape effects on crop pollination services: are there general patterns? Ecol Lett. 2008;11: 499–515.
45. Garibaldi LA, Steffan-Dewenter I, Kremen C, Morales JM, Bommarco R, Cunningham SA, et al. Stability of pollination services decreases with isolation from natural areas despite honey bee visits. Ecol Lett. 2011;14:1062–72.
46. Rader R, Bartomeus I, Tylianakis JM, Laliberté E. The winners and losers of land use intensification: pollinator community disassembly is non-random and alters functional diversity. Divers Distrib. 2014;20:908–17.
47. Davis ES, Murray TE, Fitzpatrick N, Brown MJF, Paxton RJ. Landscape effects on extremely fragmented populations of a rare solitary bee, Colletes floralis. Mol Ecol. 2010;19:4922–35.
48. Ripperger SP, Tschapka M, Kalko EKV, Rodriguez-Herrera B, Mayer F. Life in a mosaic landscape: anthropogenic habitat fragmentation affects genetic population structure in a frugivorous bat species. Conserv Genet. 2013;14:925–34.
49. Zulian G, Maes J, Paracchini ML. Linking land cover data and crop yields for mapping and assessment of pollination services in Europe. Land. 2013;2:472–92.
50. Hooper DU, Chapin FSI, Ewel JJ, Hector A, Inchausti P, Lavorel S, et al. Effects of biodiversity on ecosystem functioning: a consensus of current knowledge. Ecol Monogr. 2011;75:3–35.
51. Tscharntke T, Sekercioglu CH, Dietsch TV, Sodhi NS, Hoehn P, Tylianakis JM. Landscape constraints on functional diversity of birds and insects in tropical agroecosystems. Ecology. 2008;89: 944–51.
52. Blitzer EJ, Dormann CF, Holzschuh A, Klein AM, Rand TA, Tscharntke T. Spillover of functionally important organisms between managed and natural habitats. Agric Ecosyst Environ. 2012;146:34–43. Review of studies done on five functionally important trophic groups that analyze movement across habitats, particularly between agricultural and natural systems. Highlights the need for more studies on the movement from agricultural towards natural systems, such as forests.
53. Morgan JL, Gergel SE, Coops NC. Aerial photography: a rapidly evolving tool for ecological management. Bioscience. 2010;60: 47–59.
54. Asner G, Archer S, Hughes RF, Ansley RJ, Wessman CA. Net changes in regional woody vegetation cover and carbon storage in Texas drylands, 1937–1999. Glob Chang Biol. 2003;9:316–35.
55. Strand EK, Vierling LA, Smith AMS, Bunting SC. Net changes in aboveground woody carbon stock in western juniper woodlands, 1946–1998. J Geophys Res. 2008;113:1–13.
56. Thomilnson JR. Land-use dynamics in a post-agricultural Puerto Rican landscape (1936–1988). Biotropica. 1996;28:525–36.
57. Robinson L, Newell JP, Marzluff JM. Twenty-five years of sprawl in the Seattle region: growth management responses and implications for conservation. Landsc Urban Plan. 2005;71:51–72.
58. Steffan-Dewenter I, Munzenberg CB, Thies C, Tscharntke T. Scale-dependent effects of landscape context on three pollinator guilds. Ecology. 2002;83:1421–32.
59. Brosi BJ, Daily GC, Shih TM, Oviedo F, Durán G. The effects of forest fragmentation on bee communities in tropical countryside. J Appl Ecol. 2007;45:773–83.
60. Strand EK, Smith AMS, Bunting SC, Vierling LA, Hann DB, Gessler PE. Wavelet estimation of plant spatial patterns in multitemporal aerial photography. Int J Remote Sens. 2006;27: 2049–54.
61. Asner GP, Martin RE, Ford AJ, Metcalfe DJ, Liddell MJ. Leaf chemical and spectral diversity in Australian tropical forests. Ecol Appl. 2009;19:236–53.
62. Young KE, Abbott LB, Caldwell CA, Schrader TS. Estimating suitable environments for invasive plant species across large landscapes: a remote sensing strategy using Landsat 7 ETM +. Int J Biodivers Conserv. 2013;5:122–34.
63. Williams NM, Cariveau D, Winfree R, Kremen C. Bees in disturbed habitats use, but do not prefer, alien plants. Basic Appl Ecol. 2011;12:332–41.
64. Stout JC, Morales CL. Ecological impacts of invasive alien species on bees. Apidologie. 2009;40:388–409.
65. Lack D, Varley GC. Detection of birds by radar. Nature. 1945;156: 446.
66. ONeal ME, Landis DA, Rothwell E. Tracking insects with harmonic radar: a case study. Am Entomol. 2004;50:212–8.
67. Osborne JL, Clark SJ, Morris RJ, Williams IH, Riley JR, Smith AD, et al. A landscape-scale study of bumble bee foraging range and constancy using harmonic radar. J Appl Ecol. 1999;36:519–33.
68. Hagen M, Wikelski M, Kissling WD. Space use of bumblebees (Bombus spp.) revealed by radio-tracking. PLoS One. 2011;6:1–10.
69. Wikelski M, Moxley J, Eaton-Mordas A, López-Uribe MM, Holland R, Moskowitz D, et al. Large-range movements of neotropical orchid bees observed via radio telemetry. PLoS One. 2010;5:5–10.
70. Shaw J, Seldomridge N, Dunkle D, Nugent P, Spangler L, Bromenshenk J, et al. Polarization lidar measurements of honey bees in flight for locating land mines. Opt Express. 2005;13: 5853–63.
71. Hoffman DS, Nehrir AR, Repasky KS, Shaw JA, Carlsten JL. Range-resolved optical detection of honeybees by use of wingbeat modulation of scattered light for locating land mines. Appl Opt. 2007;46:3007–12.
72. Azmy SN, Sah SAM, Shafie NJ, Ariffin A, Majid Z, Ismail MNA, et al. Counting in the dark: non-intrusive laser scanning for population counting and identifying roosting bats. Sci Rep. 2012;2:1–4.
73. Yang X, Schaaf C, Strahler A, Kunz T, Fuller N, Betke M, et al. Study of bat flight behavior by combining thermal image analysis with a LiDAR forest reconstruction. Can J Remote Sens. 2013;39.
74. Hillebrand H, Matthiessen B. Biodiversity in a complex world: consolidation and progress in functional biodiversity research. Ecol Lett. 2009;12:1405–19.
75. Folke C, Carpenter S, Walker B, Scheffer M, Elmqvist T, Gunderson L, et al. Regime shifts, resilience, and biodiversity in ecosystem management. Annu Rev Ecol Evol Syst. 2004;35:557–81.
76. Rocchini D, Balkenhol N, Carter GA, Foody GM, Gillespie TW, He KS, et al. Remotely sensed spectral heterogeneity as a proxy of species diversity: recent advances and open challenges. Ecol Inform. 2010;5:318–29.
77. Vierling KT, Vierling LA, Gould WA, Martinuzzi S, Clawges RM. Lidar: shedding new light on habitat characterization and modeling. Front Ecol Environ. 2008;6:90–8.
78. Bergen KM, Goetz SJ, Dubayah RO, Henebry GM, Hunsaker CT, Imhoff ML, et al. Remote sensing of vegetation 3-D structure for biodiversity and habitat: review and implications for lidar and radar spaceborne missions. J Geophys Res. 2009;114:1–13.
79. Oldeland J, Wesuls D, Rocchini D, Schmidt M, Jürgens N. Does using species abundance data improve estimates of species diversity from remotely sensed spectral heterogeneity? Ecol Indic. 2010;10:390–6.
80. Work T, St Onge B, Jacobs J. Response of female beetles to LIDAR derived topographic variables in eastern boreal mixedwood forests (Coleoptera, Carabidae). Zookeys. 2011;147: 623.
81. Bradbury RB, Hill RA, Mason DC, Hinsley SA, Wilson JD, Balzter H, et al. Modelling relationships between birds and vegetation structure using airborne LiDAR data: a review with case studies from agricultural and woodland environments. Ibis. 2005;147:443–52.
82. Hill RA, Hinsley SA, Gaveau DLA, Bellamy PE. Predicting habitat quality for great tits (Parusmajor) with airborne laser scanning data. Int J Remote Sens. 2004;25:4851–5.
83. Bradley BA, Olsson AD, Wang O, Dickson BG, Pelech L, Sesnie SE, et al. Species detection vs. habitat suitability: are we biasing habitat suitability models with remotely sensed data? EcolModel. 2012;244:57–64.
84. Dohzono I, Yokoyama J. Impacts of alien bees on native plantpollinator relationships: a review with special emphasis on plant reproduction. Appl Entomol Zool. 2010;45:37–47.
85. Jarnevich CS, Esaias WE, Ma PLA, Jeffery T, Nickeson JE, Stohlgren TJ, et al. Regional distribution models with lack of proximate predictors: Africanized honeybees expanding north. Divers Distrib. 2014;20:193–201.
86. Running SW, Nemani RR, Heinsch FA, Zhao M, Reeves M, Hashimoto H. A continuous satellite-derived measure of global terrestrial primary production. Bioscience. 2004;547:60.
87. Levanoni O, Levin N, Pe’er G, Turbé A, Kark S. Can we predict butterfly diversity along an elevation gradient from space? Ecography. 2011;34:372–83.
88. Nightingale JM, Esaias WE, Wolfe RE, Nickeson JE, Ma PLA. Assessing honey bee equilibrium range and forage supply using satellite-derived phenology. Geosci Remote Sens Symp. 2008;3: 763–6.
89. Sánchez-Azofeifa A, Rivard B, Wright J, Feng J-L, Li P, Chong MM, et al. Estimation of the distribution of Tabebuia guayacan (Bignoniaceae) using high-resolution remote sensing imagery. Sensors. 2011;11:3831–51.
90. Archer CR, Pirk CWW, Carvalheiro LG, Nicolson SW. Economic and ecological implications of geographic bias in pollinator ecology in the light of pollinator declines. Oikos. 2014;123:401–7.
91. Müller J, Bae S, Röder J, Chao A, Didham RK. Airborne LiDAR reveals context dependence in the effects of canopy architecture on arthropod diversity. For Ecol Manag. 2014;312:129–37. Links information collected at landscape and local scales with forest beetle assemblages. LiDAR-derived variables had high predictive power for beetles sampled, including mean body size and species composition. Shows potential for using LiDAR to understand arthropod distributions in complex forested habitat.
92. Pakeman RJ, Stockan J. Using plant functional traits as a link between land use and bee foraging abundance. Acta Oecol. 2013;50:32–9.
93. Greenleaf SS, Williams NM, Winfree R, Kremen C. Bee foraging ranges and their relationship to body size. Oecologia. 2007;153: 589–96.
94. Freitas BM, Imperatriz-Fonseca VL, Medina LM, Kleinert AMP, Galetto L, Nates-Parra G, et al. Diversity, threats and conservation of native bees in the Neotropics. Apidologie. 2009;40:332–46.
95. Garibaldi LA, Steffan-Dewenter I, Winfree R, Aizen MA, Bommarco R, Cunningham SA, et al. Wild pollinators enhance fruit set of crops regardless of honey bee abundance. Science. 2013;339:1608–11.
96. Rosenzweig ML. Species diversity in space and time. Cambridge: Cambridge University Press; 1995.
97. Sun G, Ranson KJ, Kimes DS, Blair JB, Kovaks KV. Forest vertical structure from GLAS: an evaluation using LVIS and SRTM data. Remote Sens Environ. 2008;112:107–17.
98. Frund J, Dormann CF, Holzschuh AH, Tscharntke T. Bee diversity effects on pollination depend on functional complementarity and niche shifts. Ecology. 2013;94:2042–54.
99. Lehnert LW, Bässler C, Brandl R, Burton PJ, Müller J. Conservation value of forests attacked by bark beetles: highest number of indicator species is found in early successional stages. J Nat Conserv. 2013;21:97–104.
100. Eltz T, Brühl CA. Determinants of stingless bee nest density in lowland dipterocarp forests of Sabah, Malaysia. Popul Ecol. 2002;131:27–34.
101. Martinuzzi S, Vierling LA, Gould WA, Falkowski MJ, Evans JS, Hudak AT, et al. Mapping snags and understory shrubs for a LiDAR-based assessment of wildlife habitat suitability. Remote Sens Environ. 2009;113:2533–46.
102. Bawa KS, Bullock SH, Perry DR, Coville RE, Grayum, MH. Reproductive biology of tropical lowland rainforest trees. II. Pollination systems. Am J Bot. 1985;72:346–56.
103. Homolová L, Malenovský Z, Clevers JGPW, García-Santos G, Schaepman ME. Review of optical-based remote sensing for plant trait mapping. Ecol Complex. 2013;15:1–16.
104. Garrity SR, Vierling LA, Bickford K. Asimple filtered photodiode instrument for continuous measurement of narrowband NDVI and PRI over vegetated canopies. Agric For Meteorol. 2010;150:489–96.
105. 2 uptake. Glob Chang Biol. 2014;21: 2394–409.
106. Eitel JUH, Vierling LA, Long DS. Simultaneous measurements of plant structure and chlorophyll content in broadleaf saplings with a terrestrial laser scanner. Remote Sens Environ. 2010;114:2229–37.
107. Eitel JUH, Magney TS, Vierling LA, Huggins D, Brown T. Lidar remote sensing advances quantification of wheat biomass and nitrogen status during the critical early growing season. Field Crop Res. 2014;159:21–32.
108. Gaulton R, Danson FM, Ramirez FA, Gunawan O. The potential of dual-wavelength laser scanning for estimating vegetation moisture content. Remote Sens Environ. 2013;132:32–9.
109. Wong CYS, Gamon JA. Three causes of variation in the photochemical reflectance index (PRI) in evergreen conifers. 2015;206:187–95.
110. Furfaro R, Ganapol BD, Johnson LF, Herwitz SR. Neural network algorithm for coffee ripeness evaluation using airborne images. Appl Eng Agric. 2007;23:379–87.
111. Suetsugu K, Hayamizu M. Moth floral visitors of the three rewarding Platanthera orchids revealed by interval photography with a digital camera. J Nat Hist. 2014;48:1103–9.
112. Eitel JUH, Vierling LA, Magney TS. A lightweight, low cost autonomously operating terrestrial laser scanner for quantifying and monitoring ecosystem structural dynamics. Agric For Meteorol. 2013;180:86–96.