461
of deforestation and was also produced using the Landsat archive (Hansen et al.
2013), which have been used to track deforestation dynamics and development
frontiers (Potapov et al. 2017). These data sets are now freely available for initiatives such as the Global Forest Watch (https://www.globalforestwatch.org/), in
which the dynamics of deforestation can be monitored within and outside protected
areas. These initiatives are fundamental to downscale global biodiversity goals to
local scale action (Geijzendorffer et al. 2018). The quality of the forest classification
in the Hansen et al. (2013) product is, however, limiting. In this data set, any pixel
with >25% tree cover is considered a forest, and there is no distinction between
naturally occurring forests and planted forests (e.g., eucalyptus or oil palm plantations) or forests planted for REDD+ programs. While these readily available products are fundamental to monitoring protected areas, they still rely on careful
interpretation of their results on the ground. Asner and Tupayachi (2017) showed
the extent of mining in the Amazon, and within this system, road development has
long been shown to lead to deforestation and land cover changes within and outside
protected areas. For example, Gude et al. (2007) showed how land use change
around Yellowstone National Park could increase the risk to biodiversity inside the
park. Svancara et al. (2009) showed areas surrounding US national parks are more
protected and natural than areas farther away but had higher human population density and subsequently higher conversion risk for the parks’ ecosystems and natural
processes.
Such changes in land cover might result in changes in habitat availability and
quality both outside and within protected areas. For example, Taubert et al. (2018)
showed global patterns of tropical forest fragmentation follow a power-law distribution, which suggests that tropical forest fragmentation is close to a critical point.
Santos et al. (2017) showed how the extent of habitat for small mammals in Yosemite
National Park has changed in the last 100 years and that these habitat changes might
in some cases counteract negative effects of climate change on species persistence.
Platforms such as the Global Forest Watch (mentioned above) and the Global
Surface Water Explorer from the EU Joint Research Centre show ways by which
this integration may be achieved. Novel satellite configurations also show unexpected potential to monitor ecosystems and their responses to disturbance, providing potential new avenues for further integration at conservation-relevant scales.
17.3.5 Challenges
Two main challenges are more immediate in the conservation applications of
RS. The first is that it is important to move beyond considering biodiversity as only
number of species, and novel approaches looking at the four dimensions of biodiversity (genetic, species, function, and ecosystem structure) are necessary. Jetz et al.
(2016) provide a framework for such an approach, and several chapters in this book
(see Record et al., Chap. 10, in this book) already show the state of the art of the RS
potential in these areas.
17 Integrating Biodiversity, Remote Sensing, and Auxiliary Information for the Study…
of deforestation and was also produced using the Landsat archive (Hansen et al.
2013), which have been used to track deforestation dynamics and development
frontiers (Potapov et al. 2017). These data sets are now freely available for initiatives such as the Global Forest Watch (https://www.globalforestwatch.org/), in
which the dynamics of deforestation can be monitored within and outside protected
areas. These initiatives are fundamental to downscale global biodiversity goals to
local scale action (Geijzendorffer et al. 2018). The quality of the forest classification
in the Hansen et al. (2013) product is, however, limiting. In this data set, any pixel
with >25% tree cover is considered a forest, and there is no distinction between
naturally occurring forests and planted forests (e.g., eucalyptus or oil palm plantations) or forests planted for REDD+ programs. While these readily available products are fundamental to monitoring protected areas, they still rely on careful
interpretation of their results on the ground. Asner and Tupayachi (2017) showed
the extent of mining in the Amazon, and within this system, road development has
long been shown to lead to deforestation and land cover changes within and outside
protected areas. For example, Gude et al. (2007) showed how land use change
around Yellowstone National Park could increase the risk to biodiversity inside the
park. Svancara et al. (2009) showed areas surrounding US national parks are more
protected and natural than areas farther away but had higher human population density and subsequently higher conversion risk for the parks’ ecosystems and natural
processes.
Such changes in land cover might result in changes in habitat availability and
quality both outside and within protected areas. For example, Taubert et al. (2018)
showed global patterns of tropical forest fragmentation follow a power-law distribution, which suggests that tropical forest fragmentation is close to a critical point.
Santos et al. (2017) showed how the extent of habitat for small mammals in Yosemite
National Park has changed in the last 100 years and that these habitat changes might
in some cases counteract negative effects of climate change on species persistence.
Platforms such as the Global Forest Watch (mentioned above) and the Global
Surface Water Explorer from the EU Joint Research Centre show ways by which
this integration may be achieved. Novel satellite configurations also show unexpected potential to monitor ecosystems and their responses to disturbance, providing potential new avenues for further integration at conservation-relevant scales.
17.3.5 Challenges
Two main challenges are more immediate in the conservation applications of
RS. The first is that it is important to move beyond considering biodiversity as only
number of species, and novel approaches looking at the four dimensions of biodiversity (genetic, species, function, and ecosystem structure) are necessary. Jetz et al.
(2016) provide a framework for such an approach, and several chapters in this book
(see Record et al., Chap. 10, in this book) already show the state of the art of the RS
potential in these areas.
17 Integrating Biodiversity, Remote Sensing, and Auxiliary Information for the Study…