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Question 1: How is the Earth’s metabolism responding to anthropogenic global change, and
what surprises are in store?
The Earth is getting faster. Human activities, including fossil fuel combustion and
nitrogen fertilization, are warming the climate. In response to these perturbations, the Earth’s
metabolism – the basic photosynthesis, respiration, and biogeochemical cycling of the planet – is
speeding up. This increased metabolism is manifested in enhanced rates of photosynthesis
(carbon uptake from the atmosphere), enhanced rates of respiration (carbon loss from the
biosphere), and higher rates of nutrient cycling. During the Anthropocene, the increased
metabolism has allowed much of the carbon emitted to the atmosphere to disappear into the
biosphere (the “missing carbon sink”) (Schimel 2007, Normile 2009). This tells us that
photosynthesis for the world as a whole has increased, effectively slowing down climate change
by soaking up much of the extra carbon humans have put into the atmosphere. Ecological theory
suggests, and experimental results indicate, that this enhanced biospheric activity, should
eventually relax (Schimel 2007, and other references). Recent evidence from a variety of
sources suggest that the Earth’s photosynthetic metabolism may indeed be relaxing, at least for
certain regions of the planet (Canadell et al. 2007, Schimel 2007, Zhao & Running 2010). If true,
the implications of this relaxation are that climate change, which has been slowed by the
enhanced biospheric metabolism, will accelerate. The biosphere’s response to human
perturbation comprises a feedback to the climate that has been difficult to predict, can switch
from a negative to positive feedback, and limits our ability to project our future climate with
accuracy (Schimel 2007).
Understanding the Earth’s metabolism is one of the central goals of ecosystem science
and global ecology. Individually, we measure metabolism as individual biogeochemical cycles
or fluxes, but knowing how the parts fit together remains a grand challenge (Falkowski et al.
2000). We currently have tools to monitor this metabolism, ranging from satellites to flux
networks (Running et al. 1999). Yet, when we try to assess individual components (e.g.
ecosystem photosynthesis and respiration), they do not add up to the whole. From a carbon
cycle perspective, we have not been able to add up the global carbon budget; about one third of
the carbon that we put into the atmosphere has been disappearing into the biosphere (Schimel
1997, Schlesinger 1997). So while we believe we understand the basic principles and
mechanisms we have a sampling problem and a challenge integrating all the parts to match the
whole. Being able to accurately assess the pools and fluxes of the global carbon cycle has been
identified as a grand challenge needing a systems approach (Falkowski et al. 2000).
Until we can demonstrate that we can understand and measure the Earth’s changing
metabolism, we are likely to experience unpleasant surprises. We are currently faced with the
challenge of meeting the needs of a growing world population at a time when our collective
activities put at risk the sustainability of the human experience. We must balance the need for
expanding economic growth and food production against the risk of a changing climate that
threatens to undermine the sustainability of the human experience. Up until now, we have been
getting a free ride, with the biosphere soaking up much of the carbon that we put into the
atmosphere, slowing climate change, and allowing us to continue increasing the rate of resource
use. Defining safe limits to these activities is a fundamental topic that policymakers must now
address (Rockström et al. 2009). What level is “safe” is partly defined by the activity of the
biosphere. This, in turn, can inform sensible resource and climate policy that can best meet
human needs.
Question 2: How will projected patterns in global energy use over the next three decades impact
the sustainability of the world's ecosystems?
There is a strong and still-growing consensus among scientists that the Earth is currently
undergoing a period of unprecedented global warming. Researchers believe ongoing rapid
changes in Earth's climate are largely attributable to human activity, especially from the
combustion of fossil fuels and changes in land use patterns since the beginning of the industrial
revolution approximately 250 years ago (IPCC Working Group I 2007). And a recent report
raises additional concerns about the pace of climate change, suggesting that warming trends are
not only unprecedented over the past 1500 years, but, based on paleotemperature reconstructions,
unprecedented over the past 11,000+ years (Marcott et al. 2013).
The impacts of these global warming trends on regional and global ecosystems—in terms
of their composition, distribution, diversity, function, etc.—are likely to be profound. Ample
documentation already exists for rapidly shifting ranges and phenologies for a number of
biological taxa, both terrestrial and aquatic, and these are almost certainly due to climate change.
These impacts may not be due simply to global warming per se, but to linked impacts such as
changes in precipitation patterns, increases in the frequency and severity of extreme weather
events, alterations in seasonal durations and onsets, and others.
At the same time that various aspects of climate are rapidly changing, ecosystems are
confronted by rapid change due to other human activities as well, including habitat fragmentation
and degradation from human-engineered structures, and declining air and water quality due to
broadly dispersed outputs of industrial and other activities (Staudinger et al. 2012) These factors
not only potentially threaten the effectiveness of our world's ecosystems services and global
biodiversity, but also the livability of many high-density coastal communities due to rises in sealevel, or the productivity of agricultural areas that may no longer be suitable for growing the few
monoculture crops on which the bulk of human population depends for sustenance.
In light of these concerns is the further complication of the rapid economic growth
underway in several areas of the developing world, particularly China and India—where large
numbers of humans are being lifted out of subsistence existence due to growing global markets.
This rapid growth is generating a growing need for energy, and industry analysts forecast energy
demand growing by ~60% over the next three decades particularly in developing and non-OECD
nations (International Energy Agency 2012). Much of this growth in energy demand will be
satisfied by fossil fuels, exacerbating climate change at a time when developed nations are
considering how alternative energy sources can begin to replace more environmentally harmful
options. These developing nations understandably are concerned about maintaining economic
growth, and moreover, may not have the scientific nor societal imperatives to modify their
energy policies.
These facts and trends present a Grand Challenge for earth and environmental scientists,
i.e. to determine:
"How will projected patterns in global energy use over the next three decades impact the
sustainability of the world's ecosystems"?
By "sustainability" we mean maintaining the quality and quantity of various
environmental functions that provide humans with adequate food, water, shelter and reasonably
hygienic living conditions, as well as preserving the integrity of ecosystem services and
"priceless" though potentially monetizable biodiversity resources. This Grand Challenge needs
to clarify linkages between aggregate human energy consumption (i.e. "global energy use")—
including both direct (extractive activities such as deforestation through need for fuel) and
indirect (energy cost of producing some consumer item); and environmental impacts—both
direct (e.g. fracking potentially leading to fragmented and poisoned landscapes) and indirect (e.g.
decreasing farmland productivity due to changing patterns in precipitation).
Aside from the challenging nature of the scientific foci of this question, this Grand
Challenge will require advancing a number of technology tools and frameworks in order to make
these analyses timely, accurate, efficient, and reproducible. Data sources will range from
industry estimates of energy consumption and anticipated demands, national energy policy plans
and their timelines; to various land-use coverages for focal biomes such as forests, grasslands,
and agricultural lands; and integrated with the best resolution climatic forecast data from credible
sources.
Question 3: What are the safe limits or critical thresholds for atmospheric pollutants within
and among ecosystems?
To many, atmospheric pollutants are a largely invisible problem. Perhaps one of the most
widely discussed atmospheric pollutants is CO2. However, numerous other pollutants enter the
atmosphere either directly (nitrogen) or become pollutants via chemical transformation (ozone).
In many cases emissions of these pollutants, such as reactive forms of nitrogen (N), remain
relatively unregulated. Since the invention of the Haber-Bosch process anthropogenic sources of
N-fixation now exceed that of global ecosystems. That is, in the last 60 years we have more than
doubled the amount of biologically available N on the planet. Significant sources of N pollution
include agriculture and internal combustion engines. The N that enters the atmosphere is
dispersed regionally by wind currents and is deposited in “down-stream” ecosystems in both wet
(precipitation) and dry (dust) forms. Atmospheric N deposition from air pollution has significant
consequences for biodiversity, ecosystem services, water quality and human health.
Although sources of N to the atmosphere are reasonably well understood, transport
models, measurements of deposition and studies of N fertilization on ecosystems vary in spatial
and temporal extent, and data quality. We have abundant empirical data on the effects of high
levels of N addition in some ecosystems, particularly grasslands, but we lack that information for
many other terrestrial and aquatic systems. To address this environmental grand challenge and
advance the state-of-the-science we need to combine, integrate and improve (1) models of
atmospheric N deposition, (2) ecosystem process models, (3) existing empirical data on
deposition rates, (4) data from fertilization experiments, and (5) data from new coordinated
cross-site experiments to determine if critical thresholds exist for N deposition that lead to loss of
ecosystem services, and how those thresholds differ among ecosystems. Addressing this
environmental grand challenge question will greatly advance our understanding of the global
nitrogen cycle while furthering our knowledge of how nitrogen fertilization impacts ecosystem
structure and function with the potential to impact human health.
Nitrate nitrogen is a regulated pollutant in drinking water. Currently we rely on
infrastructure (e.g., drinking water and waste water treatment plants) more so than ecosystem
services to mitigate the impacts of nitrogen pollutants despite, for example, the well-documented
role of wetlands in processing aquatic nitrogen pollution. Nevertheless, many components of the
N cycle (among others) remain poorly understood, such as terrestrial-aquatic coupling, yet with a
more detailed knowledge of processes and responses to N availability we can deliberately
enhance ecosystem services at costs that are far lower than construction and maintenance of hard
infrastructure. Moreover, much that we learn from a deeper understanding of the N cycle will aid
in focusing attention on other pollutants, such as phosphorus, which can also have significant
impacts on terrestrial and aquatic ecosystems.
Bobbink, R. et al. 2010. Global assessment of nitrogen deposition effects on terrestrial plant
diversity: a synthesis. Ecol Appl 20: 30-59.
Cuelemans, T. et al. 2012. Plant species loss from European semi-natural grasslands following
nutrient enrichment – is it nitrogen or is it phosphorus. Global Ecol Biogeog 22: 73-82.
Holtgrieve, G.W. et al. 2011. A coherent signature of anthropogenic nitrogen deposition to
remote watersheds of the northern hemisphere. Science 334: 1545-1548.
Pardo, L.H. et al. 2012. Effects of nitrogen deposition and empirical nitrogen critical loads for
ecoregions of the United States. Ecological Applications 21: 3049-3082.
Phoenix, G.K. et al. 2012. Impacts of atmospheric nitrogen deposition: response of multiple plant
and soil parameters across contrasting ecosystems in long-term field experiments. Global Change
Biology 18: 1197-1215.
Vitousek, P.M. et al. 1997. Human alteration of the global nitrogen cycle: sources and
consequences. Ecol Appl 7: 737-750.
Question 4: How will coupled human and biophysical systems shape and be shaped by water
availability?
The water cycle is an integral component of the climate system, intersects all major
biogeochemical cycles, and provisions freshwater resources that are essential to human society
and most terrestrial ecosystems. Physical and biological drivers of the water cycle are varied,
including planetary energy balance, internal climate system variability, soil and aquifer
properties, plant water use, and direct human intervention. Cycling of water also involves
processes acting across an enormous range of temporal and spatial scales, from water’s
molecular role as the electron donor in photosynthesis to global-scale transport by atmospheric
and ocean circulation. This incredible complexity makes the water cycle a highly non-linear
system, and our current ability to make precise predictions of water cycle response to
perturbations at local, regional and global scales is limited. For example, intercomparison of
climate and land surface models indicates widespread disagreement in not only the magnitude
but also the sign of future regional precipitation changes associated with future climate warming
(IPCC Working Group I 2007) and recent evapotranspiration changes due to simple land-cover
shifts (Pitman et al. 2009). The timing, amount, and form of water availability also constrain and
shape human- and eco-systems, with potential feedbacks on water cycling. For example local
water scarcity necessitates widespread water diversion for crop irrigation in California’s Central
Valley, which may alter summer monsoons in Arizona (Lo & Famiglietti 2013), and interactions
between atmospheric CO2 levels and water availability will drive future changes in plant water
use that influence river runoff and continental evapotranspiration (Betts et al. 2007). Developing
a predictive understanding of the water cycle and its 2-way interaction with human and
biophysical systems will require the tight integration of data, theories, and algorithms from a
large number of disparate domains, including climate science, hydrology, hydroecology, remote
sensing, agricultural science, civil and environmental engineering, water management and
planning and economics.
A comprehensive, predictive understanding of the water cycling and its 2-way interaction
with human and biophysical systems will support a vast portfolio of research in related scientific
domains. With this information researchers will be able to more accurately predict changes in
global and regional climate change, ecosystem structure, and geomorphic and biogeochemical
processes. This information would also advance our retrospective understating of events in Earth
history such as major biogeochemical perturbations, evolutionary transitions, and collapse of
ancient human societies. The strategies and transdisciplinary collaborative infrastructure
developed in pursuit of predictive understanding of water availability and its connectivity to
human and biophysical systems would benefit efforts to develop understanding of other major
Earth cycles and systems.
Water availability already constrains human development in many regions on Earth
(Vörösmarty et al. 2010), and sustaining and improving human well-being will require
continued access to water. Prediction of the amount, form and timing of water availability in the
environment is necessary to inform development of built infrastructure and management
practices that ensure stable supplies of water for human use, sustain availability of water
resources that support critical ecosystem services, and protect human and biophysical systems
from hydrological extremes.
Question 5: What is the mean and uncertainty for global extinction of species critical to
ecosystem services, and what drives shifts in these means and uncertainties under
expected/possible future anthropogenic habitat and climate change?
Increasing rates of land-use change and climate change will place tremendous pressure on
continually shifting ecosystems to provide critical resources to meet basic human needs (e.g.,
water, food, shelter). These critical resources or ecosystem services are highly dependent on
species present in ecosystems and their population levels (Costanza et al. 1997). Thus, the
production of services in the future will depend on how well we can project population decline
and loss of species critical to services. Documenting species presence/absence in many
ecosystems is a current challenge (Joos et al. 2001, Team et al. 2008); projections will therefore
require a major scaling up of research. It will additionally require embracing and understanding
uncertainty in our ability to project population levels. Such uncertainty is driven by error in
measurements, in future scenarios of anthropogenic habitat and climate change and in a number
of unknown drivers that control population abundance and variance (Bakker et al. 2009, Cressie
et al. 2009). Addressing this need requires answering the questions: What is the mean and its
uncertainty for global decline of species critical to ecosystem services and what drives shifts in
these means and uncertainties under possible future anthropogenic habitat and climate change?
Understanding and projecting species' population levels is a fundamental question in
ecology, and its relevance to other disciplines has been highlighted by recent, dramatic nonstationary shifts in habitat and climate. Scientific questions in many disciplines would thus be
informed by robust understanding of the drivers of population decline. In particular, nearly every
study in ecology is linked to an understanding or projection of species' abundance, from
estimating ecosystem-scale carbon sequestration to network theory, to examining shifts in plant
pollinator networks. Focus, however, has generally been strongly on mean population size and,
often, on an assumption of underlying stationary processes. Thus addressing the above questions
will require transforming ecological science into a discipline with a greater emphasis on research
that at once examines drivers of the mean abundance and its variance, and how those drivers
themselves will shift in the future. Integrating research on shifting drivers will require
collaboration with a number of other disciplines, including those projecting anthropogenic
climate change and land-use change. Prioritizing species for research will require strong
integration with research on which species drive ecosystem services and which services will be
most strongly connected to basic human needs under future scenarios.
Question 6: How can we better forecast ecosystem responses, feedbacks, and services, for a
rapidly emerging new state of the Earth system, one with no analogy or baseline in societal
and scientific experience?
In a changing world, skillful forecasting is an essential tool for informed decision-making.
Improving the predictive skill of ecosystem models, which are used to forecast the behavior of
complex and highly interlinked socio-ecological systems in a changing world, is arguably the
central challenge facing our discipline (Clark et al. 2001). Because the world of the 21st century
is likely to be very different from the recent past, models based solely on empirical calibration
against recent observations face a problem of extrapolation and are likely to have low predictive
skill under the no-analog environments of the future (Williams & Jackson 2007, Williams et al.
2012). Hence, such models must be based whenever possible on mechanistic representation of
ecological processes rather than empirical calibration (Kearney & Porter 2009, Buckley et al.
2012) and capable of simulating feedbacks within and between ecological subsystems, across
spatial and temporal scales, and within coupled human-ecological systems. Moreover, the
development and parameterization of these models must be constrained by all relevant
observations, including contemporary observational arrays, experimental data, and geohistorical
data. We must accelerate the cycle of model development and improvement and data-model
fusion such that every new observation collected is quickly used to assess and refine the
parameterization of models.
Transform. There is no shortage of already existing models and data; the challenge instead is to
better interlink existing models to each other and better fuse models with data. An instructive
analogy comes from the development of earth system models, which began in the 1970’s as
models of atmospheric dynamics, then broadened to include dynamic ocean models, dynamic
vegetation models, and now include fully coupled carbon cycle and climate models. One
opportunity now is to better modularize and nest existing process models within each other (e.g.
nesting landscape-scale models of fire dynamics within global-scale models of forest dynamics)
or to interlink models representing different components of ecosystems increasing their joint
power and interoperability (e.g. integrating models of lake and stream food webs with landscapeto watershed-scale models of water and nutrient transport). Such model linking must be done
thoughtfully, to ensure that gained model realism is not swamped by cascading uncertainty. A
second major opportunity is to take advantage of advances in data assimilation (Fig. 1) (Zobitz et
al. 2011, Hartig et al. 2012), a powerful set of approaches for iteratively using new observations
to constrain model parameterization and state variable estimation. In a data assimilation
framework, every new observation collected is an immediate test of a hypothesis encoded by a
computational model, and can be immediately applied to refine the model. A challenge and
opportunity here is data heterogeneity – relevant data can derive from contemporary observations
(needed to constrain the initial system state, essential for predicting future responses to climate),
experimental systems (needed to constrain key parameters under tightly managed experimental
conditions), and geohistorical systems (needed to constrain the evolution of dynamic systems
over time and slow-acting processes such as forest growth and species range shifts).
This overarching framing is intentionally broad, and could apply to virtually any
ecosystem. Here we outline a couple of case studies:
Terrestrial Ecosystem Modeling and Data-Model Fusion. Terrestrial ecosystem modeling is a
well-developed field, and encompasses a broad range of models, ranging in spatial grain from
spatially explicit models of individual trees within a single forest stand to dynamic global
vegetation models representing cohorts of plant functional types, many different types of
ecological processes, and codebase complexity ranging up to hundreds of thousands of lines
(Dietz & Latimer 2012). Global terrestrial ecosystem models are used to forecast the responses
of the terrestrial biosphere to 21st century climate change, but their predictions differ widely, e.g.
whether the biosphere will be a net source or sink of carbon to the atmosphere over this century
(Friedlingstein et al. 2006).
Several opportunities exist for improving terrestrial ecosystem models, including the
incorporation of new processes (e.g. not all TEMs include the effects of nitrogen limitation on
carbon uptake XXREF) and the assimilation of new kinds of data. There has already been
success in assimilating the data available from flux towers on sub-daily to annual variations in
NEE and using this as a constraint on ecosystem models paramerization and state variable
estimation DAVE FOX XXREF. A new opportunity now is to assimilate longer-term data on
forest growth, tree population dynamics, and fire regime, represented in high-resolution
geohistorical archives (e.g. tree-rings, witness trees, fossil pollen data, and paleofire data) using
this to constrain longer-term processes in terrestrial ecosystem models (PalEON working group
in prep.).
Future work – land use, … high-resolution data, …
Benefits to society. We rely on ecosystems for the most fundamental of services – food, water,
energy, timber, carbon storage, etc. – we must make informed decisions about how best to
steward those resources (Chapin et al. 2011). Doing so in a way that maximally leverages our
collective scientific knowledge and expertise requires a) computational models well-grounded in
ecological mechanism and theory and b) the fusion of these models with diverse data streams
derived from observational, experimental, and geohistorical sources.
FIGURE 1
Figure 1: Data assimilation as an approach for fusing observational data with process-based
models of the earth system. From Hartig et al. 2012.
Question 7: What are the controls, impacts, and societal responses to atmosphere–land–
water transfer of pollutants, and how will they change under multiple, global -change
stressors?
Increased mobilization and cycling of pollutant materials within ecosystems change the
nature of biogeochemical cycles and exert negative impacts on receiving systems. For example,
increased fertilizer applications in the US after WWII produced large increases in crop yields but,
through leaching and transport of excess N and P to coastal waters, caused eutrophication and
dead zones (Carpenter et al. 1998, Rabalais et al. 2002). Inputs to the atmosphere of N, P, and S
associated with industrial and transportation sectors have caused acid rain, N saturation of forests,
and eutrophication of inland water bodies (various). Novel organic pollutants including personal
care products (PCPs) have dramatically increased in aquatic systems downstream from
wastewater treatment outfalls (Rosi-Marshall and Royer 2012), with as-yet unexplored
consequences for aquatic ecosystem processes, aquatic life, and water security.
Recent research suggests that the two major controls on riverine nutrient transport are
input rates and water discharge (Howarth et al. 2012, Raymond et al. 2012, Sobota et al. 2013),
underscoring the need for interdisciplinary understanding of 1) how human behaviors, decisions,
and land use have and will influence inputs—i.e., sociology/geography/political science
integrating with ecology/biogeochemistry; and 2) how change in hydrology and hydrological
modifications made by people have and will influence transport—i.e., hydrology/engineering
integrating with ecology/biogeochemistry. Similarly, integration of atmospheric sciences, social
sciences, and ecology is required to understand atmosphere–land transfers of materials.
Movement of materials across landscapes among atmospheric, land, and water
compartments is therefore controlled by a suite of physical, ecological, and societal processes,
but the relative importance of these controls is not well understood for diverse contextual settings
(e.g., climatic zones, different land uses, economic settings). Impacts may be similarly contextdependent, as are societal responses (including regulatory, management, and other policy actions
at multiple institutional levels, as well as individual attitudes and behaviors). Finally, the
temporal context is important: the environment is changing rapidly in multiple ways, especially
via anthropogenic forcing (Steffan 2010), giving rise to new constellations of hydrologic regimes,
land cover and use, hydrologic modifications and design, and ever greater mobilization of novel
pollutants (e.g., nanomaterials). The interaction of these multiple global-change stressors is
poorly known, may be additive, synergistic, or antagonistic, and may trigger the crossing of
thresholds and shifts to alternative stable (and perhaps undesirable) states.
This grand challenge question can be transformative because it can provide a synthesis of a
plethora of data that currently go underused, using a comparative, cross-system, or multiple-scale
approach to develop models from core existing knowledge. Data are not uniformly available
globally, but are perhaps more available than many variables because hydrologic, census, and
nutrient monitoring is frequently done. Through comparison of multiple regions at a single
(large) scale or a single large region/continent at multiple scales, a better understanding of
controls can be derived. Answering the question will require integration of several disciplinary
perspectives, and it will look to the future under different types of global environmental change
that we know are happening now and will increase in the future. Furthermore, it has the potential
to result in a paradigm shift by simultaneously evaluating multiple stressors usually considered
in isolation.
Massive changes in nutrients and other materials mobilized by human activity since the preindustrial age have strong impacts. The US Clean Water Act has had a major effect on water
quality but nonpoint-source pollution remains a problem (Carpenter et al. 1998), and emerging
pollutants do not fit well into existing regulatory frameworks (Fawell and Ong 2012); in many
developing countries water-quality problems are severe enough to create serious public health
risks. Not only fundamental understanding of controls and impacts, but greater knowledge of
what drives societal responses and which of these are effective will benefit future planning for
managing waste products of human activity, and potentially toward deriving solutions that can
use excesses in one region to ameliorate shortages in another (example: P sustainability; Childers
et al. 2011).
Question 8: How can cities be redesigned based upon principles of environmental quality,
social equity, and economic feasibility, and the best available science, so that they can
persist into the future?
The proportion of the global human population living in cities and the areal extent of cities both
are expanding. We expect nearly two thirds of the world population to be urbanized by 2050, up
from ~ half today (UNPD 2006). Both the physical extent of cities and their dependence upon
non-urban ecosystems for consumptive goods and waste processing are expanding more rapidly
than their populations, meaning that the draw of cities on the life-support systems of Earth is
increasing. However, a global population (expected to reach 10 billion) that was entirely
urbanized would have a lesser impact on these life-support systems than the same population
spread evenly across the Earth, all else equal, because of economies of scale afforded by cities
(Betancourt et al. 2007). On the other hand, concentration of the human population into cities
may increase vulnerability to environmental variability and extreme events.
Cities were awful places in the early years of the Industrial Revolution, but redesign of
cities, regulation to improve living conditions, and separation of industry from residences has
improved their ‘livability’ for our species. Unfortunately, these improvements have been uneven
across the globe, and the current trajectory of human development may be improving the
situation for some cities/nations at the expense of others. For example, expansion of textile
industries south of the US-Mexico border has increased economic opportunities greatly for US
companies and slightly for Mexican border towns, but at the expense of their local environmental
quality. Rapid economic development in China has taken place at the expense of water and air
quality in some of its major cities (Beijing).
The question remains of whether we are using the best available knowledge, considering
all aspects of the sustainability equation (i.e., ecology, economy, and equity), to design cities of
today and of the future to ensure that they can persist as good places for human habitation while
reducing their impact on the ecosystems on which all life depends and ensuring fairness and a
chance at economic opportunity at local, national, and global scales. The concept of redesign, as
opposed to design, assumes that we will come to terms with the need to make adjustments to our
cities (i.e., adaptation and resilience planning) in the face of extant and looming threats of air and
water pollution, sanitation, food security, challenges of delivery of an adequate and safe water
supply, sea-level rise, increased frequency of severe storms and other extreme events, and excess
heat.
How will the answer transform the state-of-the-science?
How will the answer benefit society? To my mind, this is THE challenge of the 21st century,
given the demographic changes that have resulted in the rise of cities over the course of the 20th
century, and our future depends upon it. Urban systems lie at the core of many global
environmental challenges and it is likely that the answers to these challenges will be found in
cities (Grimm et al. 2008). The transformative nature of this challenge lies in its promise to
balance considerations of environment, social fairness, and economics rather than just the last—
to restore to prominence the ideas of natural, human, and economic capital. This will require
transformational integration of the social, economic, physical, and natural sciences and
engineering.
Question 9: How do spatial and temporal patterns of microclimates affect plant species
resistance and resilience to regional and range-wide climate change?
Plant species distributions are changing in response to ongoing climate change, and
scientists are rapidly accumulating data documenting those changes, forecasting future
distributions and extinction risks, and evaluating implications for society in terms of timber and
forage species, wildlife habitat, and other ecosystem services. Coarse climate models are
inadequate for this task (Franklin et al. 2013). Plants live in microclimates at spatial scales of
meters to centimeters, so to understand how climate change will alter distribution and abundance
of a species we must model climate at those local-to-micro scales (Dobrowski et al. 2010). We
also need to understand what aspects of microclimate are most important in regulating rates of
seed germination, establishment, growth and reproduction. Next we must be able to connect
these processes at the scale of individual plants to plant population dynamics across the
landscape and ultimately to species range dynamics, accounting for genetic variation in plantclimate responses (Sork et al. 2010). If we can downscale climate to microclimate, and then
upscale from individual plants to metapopulation dynamics, we will have a much firmer basis for
interpreting past changes in plant distributions and forecasting future distributions under modern
climate change. Addressing this challenge requires close collaboration among climate modelers,
plant ecologists, population geneticists, landscape ecologists and biogeographers. It also requires
overcoming both conceptual and technical challenges in considering the coupled climate-plant
system at multiple scales, accounting for other sources of environmental variation, and modeling
organizational hierarchies from individuals to multiple populations.
Connecting microclimate to macroecology is more than an academic exercise.
Forecasting species distributions under climate change is important to conservation planning,
extinction risk assessment for rare and endangered species, and adaptive management of
economically important plant species for food, timber, forage, wildlife habitat, carbon storage
and other services (Dawson et al. 201).
Question 10: How is the complexity of interactions at multiple scales between different
trophic levels and abiotic factors influencing ecosystem response to global climate change?
Ecosystems are composed of complex communities of organisms and abiotic factors that
interact at different temporal and spatial levels and respond and adapt to changing environmental
conditions. Interactions occur and can be measured at different levels from molecular signaling
(i.e. transcriptomics, proteomics, metabolomics) to larger scale processes in the environment (i.e.
predation, competition, etc). Interactions are also regulated and influenced by dynamic abiotic
factors, as well as space and time, and happen across and between many trophic levels. A small
change in these dynamic systems can create cascade effects that are difficult to model and
predict and limit our possibilities of predicting the impact of global climate change in short or
long-term scenarios (Ellis et al. 2010).
Clear understanding of the complexity of these networks will allow us to establish more
comprehensive models on how ecosystems respond to global change. It will require proper
documentation of biological diversity, especially for groups that control fundamental processes
such as decomposition and nutrient cycling (e.g., bacteria and fungi) (Blackwell 2011) and it will
facilitate our ability to determine core and functional groups and their roles in ecosystem
processes that are fundamental for stability and adaptation to changing conditions. For example,
the true impact of an emergent pathogen or an invasive species in an ecosystem could be
determined more accurately if we have a better understanding of how the network and the
different scenarios will determine ecosystem response to a particular invasive organism or the
loss of a particular species (Blehert et al. 2009).
Understanding this level of complexity will require and will bring together a inter- and
multi-disciplinary group of scientists that could take advantage of new devices to monitor
environmental changes but also the new technologies to accurately measure how organisms
respond at the molecular level (-omics) and how this translates in adaptation and interactions
with other organisms in the environment (Sauer et al. 2007).
Our capacity to determine and predict ecosystem response to climate change has a direct
impact on political decisions, funding priorities, conservation strategies, agricultural planning
and health and food security. For example, the availability of resources and response of
agricultural systems are all subject to our capacity to find the major players or factors that will
reduce the impact of climate change in specific areas. The establishment of system networks will
help us determine species that are a higher risk in fragile environments and will also facilitate the
definition of priorities for conservation efforts.
Question 11:What are the bioservices of organisms that contribute to human well-being?
Where and when in the history of life did they arise? How valuable are they in economic
terms?
Biological organisms that comprise the diversity of life on Earth provide services that
sustain human life and contribute to our well-being (Millennium Ecosystem Assessment 2005).
We are increasingly recognizing the benefits of biodiversity to humans (Isbell et al. 2011,
Cardinale et al. 2012), yet huge gaps remain in identifying the functions of organisms upon
which humans depend. We have an even poorer understanding of how those bioservices are
distributed across the “tree of life” and of their contributions to humans in economic terms
(Kareiva et al. 2011). In the face of altered climate and human dominion of Planet Earth, a grand
challenge for the 21st century is to take stock of the function, value and origins of the organisms
that are integral to the sustenance of our life-support systems. Addressing this problem requires
integration across multiple domains of biology and applied economics, developing process-based
models linking organismal functions to bioservices and ultimately to economic value, and
bridging data sources, databases, software tools and cyberinfrastructure from natural history
museums, molecular systematics, functional ecology, ecosystem ecology, and environmental
economics.
How will the answer transform the state of the science? Biodiversity research has often
proceeded by counting the number of species in a system rather than considering the functions of
those organisms or their historical context. Yet, consistently we find that integrating information
about the phylogenetic history of organisms and their function provides more explanatory power
in ecosystem function and service provision than numbers of species (Cadotte et al. 2008,
Cavender-Bares et al. 2009). Currently, scientists are limited by disciplinary boundaries, skill
sets and software tools associated with those boundaries in accessing critical information about
the evolutionary context and timescale in which critical bioservices arose and their economic
valuation. Were existing tools for biodiversity research across disciplines seamlessly integrated,
such barriers would be diminished, allowing a more realistic and truly transformative picture to
emerge of the nature and value of the Earth’s biodiversity.
How will the answer benefit society? Management of our biodiversity capital is, in part, an
accounting problem. How can we wisely manage biodiversity if we don’t know what we have
and how individual organisms contribute to our life support systems? The tree of life provides a
convenient framework on which to map the bioservices of organisms. More importantly, it tells
the story of the history of life on Earth, provides insight into the conditions critical to the origins
and maintenance of bioservices, and reveals much about the redundancy and potential
substitutability of bioservices. By addressing this grand challenge problem, we will build the
capacity to take stock of the bioservices of life on Earth, recognize the evolutionary context in
which these services arose and identify “hot spots” of bioservices. In turn, an integrated picture
of these bioservices can emerge, be visualized readily by school children and brought into
national and global accounting frameworks to manage for a sustainable future.
Question 12: What will be the impact on services provided by the earth system based on
policy decisions made today?
Anthropogenic activities have influenced the chemical composition of the atmosphere, which has
long-term consequences for the services provided by the earth system. Examples of long-term
consequences include the increase in global air temperature, changes in precipitation patterns,
and ocean acidification (Christensen et al. 2007, Le Quere et al. 2007). Therefore policy
decisions that influence human activities have had and will have long-term impacts in the
services provided by the earth system (Christensen et al. 2007, Kurz et al. 2008). Therefore, it is
important to understand the biophysical controls of the earth system to forecast how human
activities may influence it under different scenarios.
To address this question there is a need to include information and tools from different
disciplines including sociology, economics, mathematics, physics, biology, and chemistry.
Furthermore, earth system-scale problems move beyond political boundaries and require a
coordinated and integrated effort among disciplines and countries. This information will provide
scenarios, with their proper uncertainty boundaries, based on different policy decisions that
influence human activities and the services provided by the earth system. This grand challenge is
already being pursued by different efforts (e.g., IPCC). This effort is influencing how data is
being processed, shared/analyzed, and is helping to identify knowledge gaps from measurements
to theories and methodologies. By answering this question the scientific community is forced to
think on the next-generation of experiments and model simulations under a data-model fusion
approach across multiple spatial and temporal scales.
Policy decisions that influence human activities have had long-term impacts in the services
provided by the earth system. Examples are changes in air temperature and precipitation that
have direct impact on human societies and will threaten food security across nations (Lobell et al.
2008). The answer to this question has economic, political, moral, and ethical implications that
will need to be discussed based on the outcome (Boykoff 2008, Rübbelke 2011). Ideally,
society could be empowered by providing likely outcomes to make informed policy decisions
with the understanding that these choices will have long-term consequences for the earth system.
Question 13: How does the understanding of flow of material and organisms across scale
and systems allow us to predict responses to disturbances?
The Earth is a dynamic system largely reflected by the flow of organisms (biotic fluxes) and
material (abiotic fluxes) in both air and water. Human activities have altered in many ways the
physical-biological interactions that drive fluxes of nutrients and the dispersion and migration of
organisms within ecosystems; they have also introduced pollutants and invasive species in
terrestrial and marine ecosystems alike. In addition, increasing perturbations in the global climate
manifested in ocean acidification, increased temperature and frequency of extreme events, are
affecting the physical-biological interactions and altering the dispersion, fate, and fluxes of
organisms (i.e., larvae, seeds) and material or pollutants (i.e., CDOM, oil, plastic) across multiple
scales and systems, ultimately affecting globally the resilience of present-time ecosystems and
the distribution and characteristics of our natural resources (Thomas et al. 2004). To date, mixing
and flux exchanges across scales and systems are not well resolved in coupled models, and their
mechanisms are not well understood.
Technological advances in tracking individual organisms, remote sensing capabilities, and
observational and sensing systems in terrestrial, atmospheric and oceanic systems, represent an
opportunity to gather a critical mass of information that will feed models with realistic initial
boundary conditions and track more accurately fluxes across the Earth system. Ultimately, the
ability to integrate shovel-ready information will foster the development, application, and
adaption of numerical methods for the simulation of flows. Novel data assimilation schemes,
uncertainties quantification methods, parallel computing, and visualization software will be
required to achieve a mechanistic understanding of underlying processes driving fluxes across
scales (Paris et al. 2013). From there, virtual disturbance of initial condition will lead to
anticipate and potentially reveal means to change the response and behavior of the system to
further disturbances.
Addressing one of the biggest challenges in environmental sciences by integrating Earth system
different components will allow the prediction of a wide range of atmospheric, oceanic, and
terrestrial phenomena (e.g., climate and weather extremes, coastal renewable energy, marine
ecosystems, runoffs from land-use) and enable scientific discoveries. The long-term benefit will
be to improve management and the sustainability of our resources.
Question 14: What is the past, present, and future state of flux of all water everywhere?
Given that water is required for life, all ecological and human science is based on either
explicit or implicit assumptions about its presence or absence. Because of this, hydrologists have
proposed a number of so-called hydrologic science “grand challenges” related to, for example,
prediction in ungauged basins (Sivapalan 2003), global terrestrial water monitoring (Wood, et al.
2011), large scale recharge mapping (Entekhabi 2007), and defining mass flux and energy
balance (Zoback 2001). It could be argued that each of these challenges is a sub component of a
single overarching grand challenge in hydrology: “What is the past, present, and future state of
flux of all water everywhere?”
Developing the ability to answer this question – even if only at a cursory level – would
foster inconceivable transformative scientific discoveries in all fields of earth and life science.
For example, paleontologists could tie fossil discoveries more accurately with hydro-climate
regimes; stream ecologists could more accurately make predictions about biotic
presence/absence of species at any location on earth and at any time in history; water resources
scientists could make use of forecasts to estimate impacts of anticipated changes in water supply
due to climate variability; sociologists and political scientists could more accurately make
predictions about global societal evolution and political change using water and water related
variables; and estimates of recent past, present, and future water flux could drive regional and
national economic models.
Ultimately the ability to synthesize all current and historical observation databases,
records, satellite images, inverse models, and historical predictions together with massive
forward modeling simulations of coupled climate and surface water systems on a global scale
would be required to meet this grand challenge. The question is extreme in its scope and scale,
but the societal benefits would be extreme as well. Accurate estimates of precipitation,
infiltration, evaporation, and flow in ungauged basins will improve crop management, water
supply planning, urban development, climate change impacts mitigation, and flood disaster
preparation and management.
To paraphrase Sivapalan (2003), the hydrologic flux grand challenge “forces us to deal
with questions that are at once, deep, grand, and practical” requiring both major breakthroughs in
fundamental science while addressing urgent practical problems of immediate benefit to society.
Question 15: Society and wildlife depend on vascular plants, so how do various factors
influence soil nutrient/water availability and biotic uptake of these under future global
changes and across spatial and temporal scales?
Plants are of critical concern for human and wildlife well-being. Whereas we understand
many of the separate pieces of how abiotic factors (e.g., precipitation and temperature regimes,
soil chemical and physical characteristics, atmospheric deposition) interact with biotic factors
(e.g., lichens, mosses, bacteria, fungi, microfauna, macrofauna, plant exudates) to transform
nutrients into plant-available forms, especially in agricultural settings, we lack a comprehensive
and integrated understanding of this process so we can’t model. We still have large data gaps that
need to be filled, such as how the quantity of one nutrient influences the availability of other
nutrients for given species, or how understudied taxa contribute to basic ecosystem processes,
especially in natural settings, and new tools to fill many of these gaps. Feedback loops operating
among the above components are poorly understood and small changes in these dynamics can
reverberate through the systems, creating effects that are difficult to model, limiting our ability to
predict short and long-term impacts. As many of these abiotic and biotic factors will change with
different land uses and future climate, we need this basic information to forecast how nutrient
transformations, and thus nutrient availability, will respond. We also have a limited
understanding of how plants and soil biota access nutrients and water in many ecosystems,
especially the role and interaction of non-mycorrhizal fungi, bacteria, and other under-studied
soil organisms. For example, studies of a few mycorrhizal fungal taxa have shown them essential
to uptake of nitrogen, phosphorus and water for many plant species. However, we know almost
nothing about the role played by the other estimated 1-5 million fungal taxa (Bass and Richards
2011) despite new data showing other groups can be vital (Collins et al. 2008). The response of
nutrient transformations and biotic uptake to different drivers will likely vary in time (e.g.,
ranging from short- to long-term responses to drivers) and space (e.g., ranging from micro-site
[~1cm] to a global scale) even under similar conditions, as legacy effects may influence
outcomes. Soil-plant interactions and feedbacks are complex and incorporating space and time
changes will make them even more so. Thus, to answer the questions posed, we require new
tools and a multi- and trans-disciplinary teams (e.g., plant physiological ecologists, soil scientists,
biogeochemists, soil ecologists) to fill data gaps and then apply a data-model fusion approach
that improves model structure with the end result of results presented in a visually unique way
and predictive models that can be empirically tested.
Limited funding and attention to soil processes in natural ecosystems has seriously hindered our
understanding of controls and drivers of soil systems. Worse, we have very little concept of how
the various processes interact and the feedback loops that exist in these systems. The ability to
integrate these different aspects will truly transform this science and enable us to move forward
past the one to five species mesocosms.
Vascular plants provide food and habitat for both humans and wildlife. Factors controlling the
amount of plant-available water and nutrients in soils, and uptake of water and nutrients, thus
controls plant nutritional quality and biomass. This, in turn, affects the nutritional benefit to
plant consumers, including humans and wildlife. As changes in land use and climate are
expected to affect soil and plant processes, understanding controls on soil fertility and biotic
uptake of water and nutrients is needed to plan for the changing future.
Question 16: How can the negative impacts on ecosystems and the services they provide be
minimized given growth in the global trade of natural resource commodities like food and
biofuels?
As we move further into the 21st century the world is increasingly interconnected in ways
that were unimaginable even a decade ago. Globalization describes the increasing interactions
among cultures, economies, and societies that are driven by factors such as the international trade
of natural resource commodities like food and biofuels. As global trade has accelerated, so too
has recognition that negative environmental externalities that are damaging the environment in
ways that may compromise the provision of ecosystem services at local and global scales.
Production of food or biofuels may be occurring at rates that are no longer sustainable at the
local scale and/or may produce unintended consequences for local ecosystems and quality of life
for the people that depend on those ecosystems. However, understanding how to minimize the
negative effects of global trading of such commodities requires consideration of meso and global
scale economic and environmental drivers and feedbacks. In short, the local implications of
producing those resources and the global implications of distributing them across vast distances
must both be considered (Wiesmeth 2012).
The challenge scientifically is to quantify the food/biofuel production and associated
impacts to the local environment (including and feedbacks from global effects), the costs and
environmental consequences of transporting the food, and influence of these on local ecosystem
services. This will require a dramatic increase in access to geospatially explicit data that are
currently highly distributed and vary dramatically in their quality (e.g., export data, rates of
food/biofuel production, rates of land use change locally, ecosystem services lost/gained locally).
It will also require new models that can serve as local to global ‘accounting systems” for
assessment of environmental and economic impacts. These models must also be suitable for
relevant and credible exploration of scenarios in which various policies are developed for
minimizing environmental damage while maximizing human well-being.
It will be transformative scientifically because: 1) it will provide a wealth of data
(environmental, social, economic, etc.) that can be used to address many other important
questions; 2) it will require the development of models that couple local to regional to global
environmental and social processes – such a model structure will certainly inform other
modeling developments; 3) it will require development of novel ways to combine data across
different scales and potentially integrate qualitative information with highly quantitative data
(e.g., flux rates of emissions) – and all of this must be geospatially dynamic.
This will benefit society because it will provide information and tools to empower
countries and local communities to develop environmentally and socially sustainable path.
Starting on refs:
Wiesmeth, H. 2012. The international dimension of the environment. Environmental Economics.
Pp 27-42 in Theory and Policy in Equilibrium. Springer-Verlag.
Question 17: What are the major quantifiable feedback loops among human water use,
landscape change, and global water cycles that drive availability of water from local to
global scales?
Human societies have been constructed around historical clusters of natural resources,
such as access to fisheries, rich soils for agriculture, travel routes for trade, and freshwater. These
patterns of human activity have largely been established without regard to sustainability (e.g.
water in Las Vegas; Deacon et al. 2007) or future change (e.g. subsidence in New Orleans;
Dixon et al. 2006). Numerous research efforts have galvanized around assessing anthropogenic
impacts on these resources and predicting future shortfalls, but none have comprehensively
considered the feedbacks and interactions among large-scale natural processes that drive
resource availability and the local and regional activities that humans undertake. For example, in
many if not most cases, global atmospheric movement is treated as a water delivery system
forced by large-scale processes, and not as a process that is affected by local or regional
decisions about water and land use. However, studies increasingly demonstrate the potential for
human alterations of land cover and water use (e.g. irrigation) to change regional heat and water
fluxes with large-scale consequences (Boucher et al. 2004, Pielke 2005). These fluxes are large
enough to not only redistribute water but also to alter regional rates of warming and the
movement of major atmospheric systems (Feddema et al. 2005). The global importance of local
and regional decisions is further emphasized by evidence that land use change has driven up to
50% of the observed increase in river discharge that moves water from states available for
human consumption into the sea where it is no longer readily made potable, and further alters
coastal systems and circulation patterns (Piao et al. 2007).
Humans are highly adaptable and creative under duress, and we should consider it
inevitable that humans will continue to alter land and water use as climate changes. Humans will
respond to altered water availability and quality at both very local scales, such as water treatment
that locally increases potable water supply, as well as large scales such as irrigation and crop
modifications, or moving away from areas that have become deserts. Thus these links between
relative small-scale human actions and large-scale climate systems must be considered as a
system of feedback loops. And not only are we connected from the land to the atmosphere, but
these atmospheric processes critically connect ecosystems around the globe such that our human
societies and their water dynamics are not independent of each other.
State of the science. First, standard global change models do not yet fully integrate land use and
land cover change as a driver, although multiple studies point to its influence. This area of
exploration is particularly interesting because it is a force that can be under direct human control.
Second, the role of inland waters in climate models is still poorly parameterized (Mackay et al.
2009). Third, the dynamic nature of human response and climate system response, and the
connectedness from human action on one side of the globe to the other presents limitless
opportunities for new discovery.
This topic integrally spans disciplines. In the human dimension, decision-making occurs
at institutional levels that consider a suite of evidence and pressures, and also at the level of
individuals making decisions based largely on their perceptions of risk. In the physical domains,
the feedbacks occurring between atmosphere, land and water are novel but approachable. And
the biological domains can provide understanding of the biotic pathways through which water
availability and quality are transformed.
Society. The importance of water availability and scarcity cannot be overemphasized, lying at the
root of not only difficult socioeconomic decisions, but also war. Currently the global
hydrological cycle is changing rapidly but our understanding of this coupled human-natural
system is not dynamically integrated from humans to atmosphere.
Question 18: How will coastal human and ecological communities adapt at local scales to
global climate changes?
This Grand Challenge would be focused on understanding how coastal human and
ecological communities adapt at local scales to global climate changes. The problem is partly
one of scale (Levin 1992) and partly one of integrating across systems and processes that are
typically seen as separate. Climate change is driven at a global scale, but affects individual
organisms and people through local changes in temperature, acidification, ocean currents, and
other aspects of the environment that may be mediated by topography and mesoscale processes
(Harley et al. 2006). Local changes in climate affect organismal physiology, interactions among
individuals and species, and movement of individuals across the seascape. These local processes
become apparent at regional scales as changes in the location and abundance of species (Pinsky
et al. 2013). Fishermen and other ocean users experience these changes as local changes in the
availability of particular organisms and may choose to respond by changing the location,
intensity, or targets of their activities, potentially magnifying the impacts of climate change. How
individual people make choices, exchange information with others, develop social norms, and
decide to maintain or continue their behavior may determine whether the ecosystem ultimately
collapses to a simpler, less productive state and whether humans can continue to derive abundant
goods and services from the ocean.
The current state of the science is one of scattered data, experiments, hypotheses and
projections that span the range of temporal and spatial scales and that rarely interacts between
natural and social science. Ecological data and observations of rapid change apparently mediated
by changing climate are abundant and beginning to be made available online (e.g., Ocean
Biogeographic Information System [OBIS]), while massive and largely untapped data on human
behavior have been collected as part of fisheries management efforts. High and largely
unexplained variability among species and locations has made interpreting scattered data
challenging, and we have little understanding for interactions between ecological and coastal
human communities. Answering this Grand Challenge would create a new, integrative
understanding of ecology across the spatial scales relevant to society but built on the mechanistic
and local understanding of experiments, quadrats, and interviews. It would move our
understanding of climate change from a vague and uncertain future to a quantitative science with
clear implications for human society. Finally, it would provide a concrete “model system” for the
emerging field of sustainability science.
The science would directly inform fisheries management, which traditionally ignores
climate impacts, as well as management of protected species, marine spatial planning, economic
development in coastal communities, and investments within industry. The science would
provide the knowledge to sustain our coastal communities through a period of rapid change and
support the large fraction of the Earth’s population that relies on protein and other goods and
services from the ocean.
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