452
further details on other ecosystem functions can be obtained in Pettorelli et al.
(2017). The narrative below focuses on satellite RS measurements because they are
widely accessible and offer a relatively inexpensive and verifiable means of deriving
data with complete spatial coverage in a consistent manner over large areas with
(near) appropriate temporal resolutions, thus offering great potential for tracking
change in ecosystem functions (Cabello et al. 2012; Nagendra et al. 2013). However,
these satellite measurements can (and should) be integrated with a host of other data
sources that are remotely acquired; these are also discussed where appropriate.
17.2.1 Pollination
The transport of pollen between plants is crucial for reproduction. Different pollination types exist with varying distributions in space and time. The ecosystem function of pollination is under varying threats especially with declines in abundance
and the loss of the organisms providing the service (e.g., bees) (Vanbergen et al.
2013; IPBES 2016). Thus, up-to-date information on pollination is extremely
important.
Two distinct RS approaches can be used to study this function: (i) direct RS of
different pollination types and (ii) remotely sensed indicators of pollination (i.e.,
vegetation phenology or biomass as an indicator). The former is challenging because
many pollination traits cannot be directly measured with RS sensors due to the signal contribution of some pollination traits (nectar content, flower structure, etc.)
being too low relative to other surface components. Alternatively, Feilhauer et al.
(2016) posited that different pollination types might be inferred from leaf and canopy optical traits (leaf area index, leaf tilt angle, mean canopy height, cover, specific
leaf area, leaf dry matter content, leaf dry mass; see also Olinger 2011), allowing for
an indirect classification of plant pollination types. Using data acquired by an airborne hyperspectral sensor, pollination types were related to canopy reflectance in a
way that allows their discrimination, opening the potential to expand this approach
to other ecosystems and different phenological stages. Such an approach should
benefit from upcoming satellite missions equipped with hyperspectral sensors, for
example, the German EnMAP and the Chinese GF-5 Hyperspectral Imager
(Fig. 17.1). Further, pollination traits such as floral display size may have too little
of a signal to be discernible from other surface components with RS, although several studies have been able to detect flowers with hyperspectral airborne sensors
and use the information to, for example, detect invasive species (see Bolch et al.,
Chap. 12, in this book).
Plant phenology is another ecosystem function directly linked to pollination,
since any change in the phenological cycle may affect interactions such as
competition between plant species and mutualism with pollinators (Buitenwerf
et al. 2015). Any direct alteration in functional or taxonomic plant diversity as a
result of change in vegetation phenology is further compounded by both short- and
long-term climatic changes. RS has demonstrated capacity for measuring and
F. Schrodt et al.
further details on other ecosystem functions can be obtained in Pettorelli et al.
(2017). The narrative below focuses on satellite RS measurements because they are
widely accessible and offer a relatively inexpensive and verifiable means of deriving
data with complete spatial coverage in a consistent manner over large areas with
(near) appropriate temporal resolutions, thus offering great potential for tracking
change in ecosystem functions (Cabello et al. 2012; Nagendra et al. 2013). However,
these satellite measurements can (and should) be integrated with a host of other data
sources that are remotely acquired; these are also discussed where appropriate.
17.2.1 Pollination
The transport of pollen between plants is crucial for reproduction. Different pollination types exist with varying distributions in space and time. The ecosystem function of pollination is under varying threats especially with declines in abundance
and the loss of the organisms providing the service (e.g., bees) (Vanbergen et al.
2013; IPBES 2016). Thus, up-to-date information on pollination is extremely
important.
Two distinct RS approaches can be used to study this function: (i) direct RS of
different pollination types and (ii) remotely sensed indicators of pollination (i.e.,
vegetation phenology or biomass as an indicator). The former is challenging because
many pollination traits cannot be directly measured with RS sensors due to the signal contribution of some pollination traits (nectar content, flower structure, etc.)
being too low relative to other surface components. Alternatively, Feilhauer et al.
(2016) posited that different pollination types might be inferred from leaf and canopy optical traits (leaf area index, leaf tilt angle, mean canopy height, cover, specific
leaf area, leaf dry matter content, leaf dry mass; see also Olinger 2011), allowing for
an indirect classification of plant pollination types. Using data acquired by an airborne hyperspectral sensor, pollination types were related to canopy reflectance in a
way that allows their discrimination, opening the potential to expand this approach
to other ecosystems and different phenological stages. Such an approach should
benefit from upcoming satellite missions equipped with hyperspectral sensors, for
example, the German EnMAP and the Chinese GF-5 Hyperspectral Imager
(Fig. 17.1). Further, pollination traits such as floral display size may have too little
of a signal to be discernible from other surface components with RS, although several studies have been able to detect flowers with hyperspectral airborne sensors
and use the information to, for example, detect invasive species (see Bolch et al.,
Chap. 12, in this book).
Plant phenology is another ecosystem function directly linked to pollination,
since any change in the phenological cycle may affect interactions such as
competition between plant species and mutualism with pollinators (Buitenwerf
et al. 2015). Any direct alteration in functional or taxonomic plant diversity as a
result of change in vegetation phenology is further compounded by both short- and
long-term climatic changes. RS has demonstrated capacity for measuring and
F. Schrodt et al.