16.1 Introduction
Mountains are the crown jewels of our natural heritage around the world and yet are
locally unique. They provide key ecosystems services particularly sensitive to
human impact. The challenge for mountain conservation is to determine ecosystem
exposure and sensitivity to environmental changes as well as their ability to adapt to
global change in the present and the future (Hansen et al. 2014; Zamora et al. 2016).
Despite uncertainties concerning the response of biophysical processes to human
impact, there is enough scientific capability to envisage the foreseeable trajectory of
major ecological processes and to manage the adaptation of ecosystems to possible
future scenarios. In this context, long-term research and monitoring are essential for
understanding the dynamics of populations, communities, and ecosystems
(Carpenter 1998; Lovett et al. 2007). One of the most prominent examples of a
long-term study is the work begun in 1958 in Mauna Loa, Hawaii, which has
demonstrated a slow but steady increase in the concentration of atmospheric carbon
dioxide (Keeling et al. 1995, 1996)—a trend that continues today and is now
investigated through a global network of stations (Battin et al. 2009). Moreover,
developing long-time data series is critical for the proper parameterization and
validation of environmental models, such as the general circulation models to
predict future climate, or related potential changes in species distribution (Burgman
et al. 1993; Canham et al. 2003; Berdanier and Clark 2016). Thus, high-quality
ecological information collected over extended periods of time can yield valuable
insights into changes in ecosystem structure, key ecological processes, and the
services provided by ecosystems (e.g. Daily 1997; Lindenmayer et al. 2012).
A full comprehension of many ecological processes requires long-term monitoring because their rate of change is very slow, and/or because extreme events that
can have substantial impacts are usually rare (Fahey et al. 2015). Many ecosystems
are likely to undergo abrupt changes due to global drivers such as climate change
(Barnosky et al. 2012). Designing and implementing large-scale ecosystem management programmes are needed to confront these problems and to provide positive
ecological and economic solutions (Pace et al. 2015). Additionally, the use of
information from long-term data series enables managers to evaluate and mitigate
threats to ecosystem function and services while operating more effectively in the
legal and political arenas. This point is important because resource managers,
policy-makers, and the general public may be unaware of these values and the
critical role of long-term ecological studies in tackling emerging problems of major
social concern (Lindenmayer et al. 2012).
16.2 Monitoring Global Change in High Mountains:
The Case of Sierra Nevada
To understand the consequences of human impact on the planet, we need systems
of reference. Mountain ecosystems may represent the best-preserved reference
systems in a given region, providing us the opportunity to compare their dynamic
386
R. Zamora et al.
Mountains are the crown jewels of our natural heritage around the world and yet are
locally unique. They provide key ecosystems services particularly sensitive to
human impact. The challenge for mountain conservation is to determine ecosystem
exposure and sensitivity to environmental changes as well as their ability to adapt to
global change in the present and the future (Hansen et al. 2014; Zamora et al. 2016).
Despite uncertainties concerning the response of biophysical processes to human
impact, there is enough scientific capability to envisage the foreseeable trajectory of
major ecological processes and to manage the adaptation of ecosystems to possible
future scenarios. In this context, long-term research and monitoring are essential for
understanding the dynamics of populations, communities, and ecosystems
(Carpenter 1998; Lovett et al. 2007). One of the most prominent examples of a
long-term study is the work begun in 1958 in Mauna Loa, Hawaii, which has
demonstrated a slow but steady increase in the concentration of atmospheric carbon
dioxide (Keeling et al. 1995, 1996)—a trend that continues today and is now
investigated through a global network of stations (Battin et al. 2009). Moreover,
developing long-time data series is critical for the proper parameterization and
validation of environmental models, such as the general circulation models to
predict future climate, or related potential changes in species distribution (Burgman
et al. 1993; Canham et al. 2003; Berdanier and Clark 2016). Thus, high-quality
ecological information collected over extended periods of time can yield valuable
insights into changes in ecosystem structure, key ecological processes, and the
services provided by ecosystems (e.g. Daily 1997; Lindenmayer et al. 2012).
A full comprehension of many ecological processes requires long-term monitoring because their rate of change is very slow, and/or because extreme events that
can have substantial impacts are usually rare (Fahey et al. 2015). Many ecosystems
are likely to undergo abrupt changes due to global drivers such as climate change
(Barnosky et al. 2012). Designing and implementing large-scale ecosystem management programmes are needed to confront these problems and to provide positive
ecological and economic solutions (Pace et al. 2015). Additionally, the use of
information from long-term data series enables managers to evaluate and mitigate
threats to ecosystem function and services while operating more effectively in the
legal and political arenas. This point is important because resource managers,
policy-makers, and the general public may be unaware of these values and the
critical role of long-term ecological studies in tackling emerging problems of major
social concern (Lindenmayer et al. 2012).
16.2 Monitoring Global Change in High Mountains:
The Case of Sierra Nevada
To understand the consequences of human impact on the planet, we need systems
of reference. Mountain ecosystems may represent the best-preserved reference
systems in a given region, providing us the opportunity to compare their dynamic
386
R. Zamora et al.