ENVIRONMENTAL CONSEQUENCES OF LAND USE CHANGE: ACCOUNTING FOR COMPLEXITY WITH AGENT-BASED MODELS

EPA Science Inventory

The effects of people on ecosystems and the impacts of ecosystem services on human well-being are being viewed increasingly as an integrated system. Demographic and economic pressures change a variety of ecological indicators, which can then result in reduced quality of ecosystem...

An individual-based process model to simulate landscape-scale forest ecosystem dynamics

Treesearch

Rupert Seidl; Werner Rammer; Robert M. Scheller; Thomas Spies

2012-01-01

Forest ecosystem dynamics emerges from nonlinear interactions between adaptive biotic agents (i.e., individual trees) and their relationship with a spatially and temporally heterogeneous abiotic environment. Understanding and predicting the dynamics resulting from these complex interactions is crucial for the sustainable stewardship of ecosystems, particularly in the...

Biogeochemical modelling vs. tree-ring data - comparison of forest ecosystem productivity estimates

NASA Astrophysics Data System (ADS)

Zorana Ostrogović Sever, Maša; Barcza, Zoltán; Hidy, Dóra; Paladinić, Elvis; Kern, Anikó; Marjanović, Hrvoje

2017-04-01

Forest ecosystems are sensitive to environmental changes as well as human-induce disturbances, therefore process-based models with integrated management modules represent valuable tool for estimating and forecasting forest ecosystem productivity under changing conditions. Biogeochemical model Biome-BGC simulates carbon, nitrogen and water fluxes, and it is widely used for different terrestrial ecosystems. It was modified and parameterised by many researchers in the past to meet the specific local conditions. In this research, we used recently published improved version of the model Biome-BGCMuSo (BBGCMuSo), with multilayer soil module and integrated management module. The aim of our research is to validate modelling results of forest ecosystem productivity (NPP) from BBGCMuSo model with observed productivity estimated from an extensive dataset of tree-rings. The research was conducted in two distinct forest complexes of managed Pedunculate oak in SE Europe (Croatia), namely Pokupsko basin and Spačva basin. First, we parameterized BBGCMuSo model at a local level using eddy-covariance (EC) data from Jastrebarsko EC site. Parameterized model was used for the assessment of productivity on a larger scale. Results of NPP assessment with BBGCMuSo are compared with NPP estimated from tree ring data taken from trees on over 100 plots in both forest complexes. Keywords: Biome-BGCMuSo, forest productivity, model parameterization, NPP, Pedunculate oak

Simulating Carbon cycle and phenology in complex forests using a multi-layer process based ecosystem model; evaluation and use of 3D-CMCC-Forest Ecosystem Model in a deciduous and an evergreen neighboring forests, within the area of Brasschaat (Be)

NASA Astrophysics Data System (ADS)

Marconi, S.; Collalti, A.; Santini, M.; Valentini, R.

2013-12-01

3D-CMCC-Forest Ecosystem Model is a process based model formerly developed for complex forest ecosystems to estimate growth, water and carbon cycles, phenology and competition processes on a daily/monthly time scale. The Model integrates some characteristics of the functional-structural tree models with the robustness of the light use efficiency approach. It treats different heights, ages and species as discrete classes, in competition for light (vertical structure) and space (horizontal structure). The present work evaluates the results of the recently developed daily version of 3D-CMCC-FEM for two neighboring different even aged and mono specific study cases. The former is a heterogeneous Pedunculate oak forest (Quercus robur L. ), the latter a more homogeneous Scot pine forest (Pinus sylvestris L.). The multi-layer approach has been evaluated against a series of simplified versions to determine whether the improved model complexity in canopy structure definition increases its predictive ability. Results show that a more complex structure (three height layers) should be preferable to simulate heterogeneous scenarios (Pedunculate oak stand), where heights distribution within the canopy justify the distinction in dominant, dominated and sub-dominated layers. On the contrary, it seems that using a multi-layer approach for more homogeneous stands (Scot pine stand) may be disadvantageous. Forcing the structure of an homogeneous stand to a multi-layer approach may in fact increase sources of uncertainty. On the other hand forcing complex forests to a mono layer simplified model, may cause an increase in mortality and a reduction in average DBH and Height. Compared with measured CO2 flux data, model results show good ability in estimating carbon sequestration trends, on both a monthly/seasonal and daily time scales. Moreover the model simulates quite well leaf phenology and the combined effects of the two different forest stands on CO2 fluxes.

Complex Dynamics of Wetland Ecosystem with Nonlinear Harvesting: Application to Chilika Lake in Odisha, India

NASA Astrophysics Data System (ADS)

Upadhyay, Ranjit Kumar; Tiwari, S. K.; Roy, Parimita

2015-06-01

In this paper, an attempt has been made to study the spatial and temporal dynamical interactions among the species of wetland ecosystem through a mathematical model. The model represents the population dynamics of phytoplankton, zooplankton and fish species found in Chilika lake, Odisha, India. Nonlinear stability analysis of both the temporal and spatial models has been carried out. Maximum sustainable yield and optimal harvesting policy have been studied for a nonspatial model system. Numerical simulation has been performed to figure out the parameters responsible for the complex dynamics of the wetland system. Significant outcomes of our numerical findings and their interpretations from an ecological point of view are provided in this paper. Numerical simulation of spatial model exhibits some interesting and beautiful patterns. We have also pointed out the parameters that are responsible for the good health of wetland ecosystem.

The distribution of persistent organic pollutants in a trophically complex Antarctic ecosystem model

NASA Astrophysics Data System (ADS)

Bates, Michael L.; Bengtson Nash, Susan M.; Hawker, Darryl W.; Shaw, Emily C.; Cropp, Roger A.

2017-06-01

Despite Antarctica's isolation from human population centres, persistent organic pollutants (POPs) are transported there via long range atmospheric transport and subsequently cold-trapped. The challenging nature of working in the Antarctic environment greatly limits our ability to monitor POP concentrations and understand the processes that govern the distribution of POPs in Antarctic ecosystems. Here we couple a dynamic, trophically complex biological model with a fugacity model to investigate the distribution of hexachlorobenzene (HCB) in a near-shore Antarctic ecosystem. Using this model we examine the steady-state, and annual cycle of HCB concentration in the atmosphere, ocean, sediment, detritus, and 21 classes of biota that span from primary producers to apex predators. The scope and trophic resolution of our model allows us to examine POP pathways through the ecosystem. In our model the main pathway of HCB to upper trophic species is via pelagic communities, with relatively little via benthic communities. Using a dynamic ecosystem model also allows us to examine the seasonal and potential climate change induced changes in POP distribution. We show that there is a large annual cycle in concentration in the planktonic communities, which may have implications for biomagnification factors calculated from observations. We also examine the direct effects of increasing temperature on the redistribution of HCB in a changing climate and find that it is likely minor compared to other indirect effects, such as changes in atmospheric circulation, sea ice dynamics, and changes to the ecosystem itself.

Supporting Fisheries Management by Means of Complex Models: Can We Point out Isles of Robustness in a Sea of Uncertainty?

PubMed Central

Gasche, Loïc; Mahévas, Stéphanie; Marchal, Paul

2013-01-01

Ecosystems are usually complex, nonlinear and strongly influenced by poorly known environmental variables. Among these systems, marine ecosystems have high uncertainties: marine populations in general are known to exhibit large levels of natural variability and the intensity of fishing efforts can change rapidly. These uncertainties are a source of risks that threaten the sustainability of both fish populations and fishing fleets targeting them. Appropriate management measures have to be found in order to reduce these risks and decrease sensitivity to uncertainties. Methods have been developed within decision theory that aim at allowing decision making under severe uncertainty. One of these methods is the information-gap decision theory. The info-gap method has started to permeate ecological modelling, with recent applications to conservation. However, these practical applications have so far been restricted to simple models with analytical solutions. Here we implement a deterministic approach based on decision theory in a complex model of the Eastern English Channel. Using the ISIS-Fish modelling platform, we model populations of sole and plaice in this area. We test a wide range of values for ecosystem, fleet and management parameters. From these simulations, we identify management rules controlling fish harvesting that allow reaching management goals recommended by ICES (International Council for the Exploration of the Sea) working groups while providing the highest robustness to uncertainties on ecosystem parameters. PMID:24204873

Supporting fisheries management by means of complex models: can we point out isles of robustness in a sea of uncertainty?

PubMed

Gasche, Loïc; Mahévas, Stéphanie; Marchal, Paul

2013-01-01

Ecosystems are usually complex, nonlinear and strongly influenced by poorly known environmental variables. Among these systems, marine ecosystems have high uncertainties: marine populations in general are known to exhibit large levels of natural variability and the intensity of fishing efforts can change rapidly. These uncertainties are a source of risks that threaten the sustainability of both fish populations and fishing fleets targeting them. Appropriate management measures have to be found in order to reduce these risks and decrease sensitivity to uncertainties. Methods have been developed within decision theory that aim at allowing decision making under severe uncertainty. One of these methods is the information-gap decision theory. The info-gap method has started to permeate ecological modelling, with recent applications to conservation. However, these practical applications have so far been restricted to simple models with analytical solutions. Here we implement a deterministic approach based on decision theory in a complex model of the Eastern English Channel. Using the ISIS-Fish modelling platform, we model populations of sole and plaice in this area. We test a wide range of values for ecosystem, fleet and management parameters. From these simulations, we identify management rules controlling fish harvesting that allow reaching management goals recommended by ICES (International Council for the Exploration of the Sea) working groups while providing the highest robustness to uncertainties on ecosystem parameters.

Modeled interactive effects of precipitation, temperature, and [CO2] on ecosystem carbon and water dynamics in different climatic zones

Treesearch

Yiqi Luo; Dieter Gerten; Guerric Le Maire; William J. Parton; Ensheng Weng; Xuhui Zhou; Cindy Keough; Claus Beier; Philippe Ciais; Wolfgang Cramer; Jeffrey S. Dukes; Bridget Emmett; Paul J. Hanson; Alan Knapp; Sune Linder; Dan Nepstad; Lindsey. Rustad

2008-01-01

Interactive effects of multiple global change factors on ecosystem processes are complex. It is relatively expensive to explore those interactions in manipulative experiments. We conducted a modeling analysis to identify potentially important interactions and to stimulate hypothesis formulation for experimental research. Four models were used to quantify interactive...

Simulation of the effect of air pollution on forest ecosystems in a region

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tarko, A.M.; Bykadorov, A.V.; Kryuchkov, V.V.

1995-03-01

This article describes a model of air pollution effects on spruce in forests of the northern taiga regions which have been exposed to air pollution from a large metallurgical industrial complex. Both the predictions the model makes about forest ecosystem degradation zones and the limitations of the model are discussed. 5 refs., 1 fig.

An agent architecture for an integrated forest ecosystem management decision support system

Treesearch

Donald Nute; Walter D. Potter; Mayukh Dass; Astrid Glende; Frederick Maier; Hajime Uchiyama; Jin Wang; Mark Twery; Peter Knopp; Scott Thomasma; H. Michael Rauscher

2003-01-01

A wide variety of software tools are available to support decision in the management of forest ecosystems. These tools include databases, growth and yield models, wildlife models, silvicultural expert systems, financial models, geographical informations systems, and visualization tools. Typically, each of these tools has its own complex interface and data format. To...

Modeling Complex Marine Ecosystems: An Investigation of Two Teaching Approaches with Fifth Graders

ERIC Educational Resources Information Center

Papaevripidou, M.; Constantinou, C. P.; Zacharia, Z. C.

2007-01-01

This study investigated acquisition and transfer of the modeling ability of fifth graders in various domains. Teaching interventions concentrated on the topic of marine ecosystems either through a modeling-based approach or a worksheet-based approach. A quasi-experimental (pre-post comparison study) design was used. The control group (n = 17)…

A multitrophic model to quantify the effects of marine viruses on microbial food webs and ecosystem processes

PubMed Central

Weitz, Joshua S; Stock, Charles A; Wilhelm, Steven W; Bourouiba, Lydia; Coleman, Maureen L; Buchan, Alison; Follows, Michael J; Fuhrman, Jed A; Jover, Luis F; Lennon, Jay T; Middelboe, Mathias; Sonderegger, Derek L; Suttle, Curtis A; Taylor, Bradford P; Frede Thingstad, T; Wilson, William H; Eric Wommack, K

2015-01-01

Viral lysis of microbial hosts releases organic matter that can then be assimilated by nontargeted microorganisms. Quantitative estimates of virus-mediated recycling of carbon in marine waters, first established in the late 1990s, were originally extrapolated from marine host and virus densities, host carbon content and inferred viral lysis rates. Yet, these estimates did not explicitly incorporate the cascade of complex feedbacks associated with virus-mediated lysis. To evaluate the role of viruses in shaping community structure and ecosystem functioning, we extend dynamic multitrophic ecosystem models to include a virus component, specifically parameterized for processes taking place in the ocean euphotic zone. Crucially, we are able to solve this model analytically, facilitating evaluation of model behavior under many alternative parameterizations. Analyses reveal that the addition of a virus component promotes the emergence of complex communities. In addition, biomass partitioning of the emergent multitrophic community is consistent with well-established empirical norms in the surface oceans. At steady state, ecosystem fluxes can be probed to characterize the effects that viruses have when compared with putative marine surface ecosystems without viruses. The model suggests that ecosystems with viruses will have (1) increased organic matter recycling, (2) reduced transfer to higher trophic levels and (3) increased net primary productivity. These model findings support hypotheses that viruses can have significant stimulatory effects across whole-ecosystem scales. We suggest that existing efforts to predict carbon and nutrient cycling without considering virus effects are likely to miss essential features of marine food webs that regulate global biogeochemical cycles. PMID:25635642

A multitrophic model to quantify the effects of marine viruses on microbial food webs and ecosystem processes.

PubMed

Weitz, Joshua S; Stock, Charles A; Wilhelm, Steven W; Bourouiba, Lydia; Coleman, Maureen L; Buchan, Alison; Follows, Michael J; Fuhrman, Jed A; Jover, Luis F; Lennon, Jay T; Middelboe, Mathias; Sonderegger, Derek L; Suttle, Curtis A; Taylor, Bradford P; Frede Thingstad, T; Wilson, William H; Eric Wommack, K

2015-06-01

Viral lysis of microbial hosts releases organic matter that can then be assimilated by nontargeted microorganisms. Quantitative estimates of virus-mediated recycling of carbon in marine waters, first established in the late 1990s, were originally extrapolated from marine host and virus densities, host carbon content and inferred viral lysis rates. Yet, these estimates did not explicitly incorporate the cascade of complex feedbacks associated with virus-mediated lysis. To evaluate the role of viruses in shaping community structure and ecosystem functioning, we extend dynamic multitrophic ecosystem models to include a virus component, specifically parameterized for processes taking place in the ocean euphotic zone. Crucially, we are able to solve this model analytically, facilitating evaluation of model behavior under many alternative parameterizations. Analyses reveal that the addition of a virus component promotes the emergence of complex communities. In addition, biomass partitioning of the emergent multitrophic community is consistent with well-established empirical norms in the surface oceans. At steady state, ecosystem fluxes can be probed to characterize the effects that viruses have when compared with putative marine surface ecosystems without viruses. The model suggests that ecosystems with viruses will have (1) increased organic matter recycling, (2) reduced transfer to higher trophic levels and (3) increased net primary productivity. These model findings support hypotheses that viruses can have significant stimulatory effects across whole-ecosystem scales. We suggest that existing efforts to predict carbon and nutrient cycling without considering virus effects are likely to miss essential features of marine food webs that regulate global biogeochemical cycles.

From Bacteria to Whales: Using Functional Size Spectra to Model Marine Ecosystems.

PubMed

Blanchard, Julia L; Heneghan, Ryan F; Everett, Jason D; Trebilco, Rowan; Richardson, Anthony J

2017-03-01

Size-based ecosystem modeling is emerging as a powerful way to assess ecosystem-level impacts of human- and environment-driven changes from individual-level processes. These models have evolved as mechanistic explanations for observed regular patterns of abundance across the marine size spectrum hypothesized to hold from bacteria to whales. Fifty years since the first size spectrum measurements, we ask how far have we come? Although recent modeling studies capture an impressive range of sizes, complexity, and real-world applications, ecosystem coverage is still only partial. We describe how this can be overcome by unifying functional traits with size spectra (which we call functional size spectra) and highlight the key knowledge gaps that need to be filled to model ecosystems from bacteria to whales. Copyright © 2017 Elsevier Ltd. All rights reserved.

Trophic signatures of seabirds suggest shifts in oceanic ecosystems

PubMed Central

Gagne, Tyler O.; Hyrenbach, K. David; Hagemann, Molly E.; Van Houtan, Kyle S.

2018-01-01

Pelagic ecosystems are dynamic ocean regions whose immense natural capital is affected by climate change, pollution, and commercial fisheries. Trophic level–based indicators derived from fishery catch data may reveal the food web status of these systems, but the utility of these metrics has been debated because of targeting bias in fisheries catch. We analyze a unique, fishery-independent data set of North Pacific seabird tissues to inform ecosystem trends over 13 decades (1890s to 2010s). Trophic position declined broadly in five of eight species sampled, indicating a long-term shift from higher–trophic level to lower–trophic level prey. No species increased their trophic position. Given species prey preferences, Bayesian diet reconstructions suggest a shift from fishes to squids, a result consistent with both catch reports and ecosystem models. Machine learning models further reveal that trophic position trends have a complex set of drivers including climate, commercial fisheries, and ecomorphology. Our results show that multiple species of fish-consuming seabirds may track the complex changes occurring in marine ecosystems. PMID:29457134

Trophic signatures of seabirds suggest shifts in oceanic ecosystems.

PubMed

Gagne, Tyler O; Hyrenbach, K David; Hagemann, Molly E; Van Houtan, Kyle S

2018-02-01

Pelagic ecosystems are dynamic ocean regions whose immense natural capital is affected by climate change, pollution, and commercial fisheries. Trophic level-based indicators derived from fishery catch data may reveal the food web status of these systems, but the utility of these metrics has been debated because of targeting bias in fisheries catch. We analyze a unique, fishery-independent data set of North Pacific seabird tissues to inform ecosystem trends over 13 decades (1890s to 2010s). Trophic position declined broadly in five of eight species sampled, indicating a long-term shift from higher-trophic level to lower-trophic level prey. No species increased their trophic position. Given species prey preferences, Bayesian diet reconstructions suggest a shift from fishes to squids, a result consistent with both catch reports and ecosystem models. Machine learning models further reveal that trophic position trends have a complex set of drivers including climate, commercial fisheries, and ecomorphology. Our results show that multiple species of fish-consuming seabirds may track the complex changes occurring in marine ecosystems.

Sharing the floodplain: Mediated modeling for environmental management

USGS Publications Warehouse

Metcalf, S.S.; Wheeler, E.; BenDor, T.K.; Lubinski, S.J.; Hannon, B.M.

2010-01-01

Complex ecosystems, such as the Upper Mississippi River (UMR), present major management challenges. Such systems often provide a range of ecosystem services that are differentially valued by stakeholders representing distinct interests (e.g., agriculture, conservation, navigation) or institutions (e.g., federal and state agencies). When no single entity has the knowledge or authority to resolve conflicts over shared resource use, stakeholders may struggle to jointly understand the scope of the problem and to reach reasonable compromises. This paper explores mediated modeling as a group consensus building process for understanding relationships between ecological, economic and cultural well-being in the UMR floodplain. We describe a workshop structure used to engage UMR stakeholders that may be extended to resource use conflicts in other complex ecosystems. We provide recommendations for improving on these participatory methods in structuring future efforts. In conclusion, we suggest that tools which facilitate collaborative learning, such as mediated modeling, need to be incorporated at an institutional level as a vital element of integrated ecosystem management. ?? 2008 Elsevier Ltd.

Error quantification of a high-resolution coupled hydrodynamic-ecosystem coastal-ocean model: Part 2. Chlorophyll-a, nutrients and SPM

NASA Astrophysics Data System (ADS)

Allen, J. Icarus; Holt, Jason T.; Blackford, Jerry; Proctor, Roger

2007-12-01

Marine systems models are becoming increasingly complex and sophisticated, but far too little attention has been paid to model errors and the extent to which model outputs actually relate to ecosystem processes. Here we describe the application of summary error statistics to a complex 3D model (POLCOMS-ERSEM) run for the period 1988-1989 in the southern North Sea utilising information from the North Sea Project, which collected a wealth of observational data. We demonstrate that to understand model data misfit and the mechanisms creating errors, we need to use a hierarchy of techniques, including simple correlations, model bias, model efficiency, binary discriminator analysis and the distribution of model errors to assess model errors spatially and temporally. We also demonstrate that a linear cost function is an inappropriate measure of misfit. This analysis indicates that the model has some skill for all variables analysed. A summary plot of model performance indicates that model performance deteriorates as we move through the ecosystem from the physics, to the nutrients and plankton.

Emergence of a complex and stable network in a model ecosystem with extinction and mutation.

PubMed

Tokita, Kei; Yasutomi, Ayumu

2003-03-01

We propose a minimal model of the dynamics of diversity-replicator equations with extinction, invasion and mutation. We numerically study the behavior of this simple model and show that it displays completely different behavior from the conventional replicator equation and the generalized Lotka-Volterra equation. We reach several significant conclusions as follows: (1) a complex ecosystem can emerge when mutants with respect to species-specific interaction are introduced; (2) such an ecosystem possesses strong resistance to invasion; (3) a typical fixation process of mutants is realized through the rapid growth of a group of mutualistic mutants with higher fitness than majority species; (4) a hierarchical taxonomic structure (like family-genus-species) emerges; and (5) the relative abundance of species exhibits a typical pattern widely observed in nature. Several implications of these results are discussed in connection with the relationship of the present model to the generalized Lotka-Volterra equation.

Modeling dynamic interactions and coherence between marine zooplankton and fishes linked to environmental variability

NASA Astrophysics Data System (ADS)

Liu, Hui; Fogarty, Michael J.; Hare, Jonathan A.; Hsieh, Chih-hao; Glaser, Sarah M.; Ye, Hao; Deyle, Ethan; Sugihara, George

2014-03-01

The dynamics of marine fishes are closely related to lower trophic levels and the environment. Quantitatively understanding ecosystem dynamics linking environmental variability and prey resources to exploited fishes is crucial for ecosystem-based management of marine living resources. However, standard statistical models typically grounded in the concept of linear system may fail to capture the complexity of ecological processes. We have attempted to model ecosystem dynamics using a flexible, nonparametric class of nonlinear forecasting models. We analyzed annual time series of four environmental indices, 22 marine copepod taxa, and four ecologically and commercially important fish species during 1977 to 2009 on Georges Bank, a highly productive and intensively studied area of the northeast U.S. continental shelf ecosystem. We examined the underlying dynamic features of environmental indices and copepods, quantified the dynamic interactions and coherence with fishes, and explored the potential control mechanisms of ecosystem dynamics from a nonlinear perspective. We found: (1) the dynamics of marine copepods and environmental indices exhibiting clear nonlinearity; (2) little evidence of complex dynamics across taxonomic levels of copepods; (3) strong dynamic interactions and coherence between copepods and fishes; and (4) the bottom-up forcing of fishes and top-down control of copepods coexisting as target trophic levels vary. These findings highlight the nonlinear interactions among ecosystem components and the importance of marine zooplankton to fish populations which point to two forcing mechanisms likely interactively regulating the ecosystem dynamics on Georges Bank under a changing environment.

Multi-Agent-Based Simulation of a Complex Ecosystem of Mental Health Care.

PubMed

Kalton, Alan; Falconer, Erin; Docherty, John; Alevras, Dimitris; Brann, David; Johnson, Kyle

2016-02-01

This paper discusses the creation of an Agent-Based Simulation that modeled the introduction of care coordination capabilities into a complex system of care for patients with Serious and Persistent Mental Illness. The model describes the engagement between patients and the medical, social and criminal justice services they interact with in a complex ecosystem of care. We outline the challenges involved in developing the model, including process mapping and the collection and synthesis of data to support parametric estimates, and describe the controls built into the model to support analysis of potential changes to the system. We also describe the approach taken to calibrate the model to an observable level of system performance. Preliminary results from application of the simulation are provided to demonstrate how it can provide insights into potential improvements deriving from introduction of care coordination technology.

CHEMICAL PROCESSES AND MODELING IN ECOSYSTEMS

EPA Science Inventory

Trends in regulatory strategies require EPA to understand better chemical behavior in natural and impacted ecosystems and in biological systems to carry out the increasingly complex array of exposure and risk assessments needed to develop scientifically defensible regulations (GP...

Mechanisms controlling primary and new production in a global ecosystem model - Part I: Validation of the biological simulation

NASA Astrophysics Data System (ADS)

Popova, E. E.; Coward, A. C.; Nurser, G. A.; de Cuevas, B.; Fasham, M. J. R.; Anderson, T. R.

2006-12-01

A global general circulation model coupled to a simple six-compartment ecosystem model is used to study the extent to which global variability in primary and export production can be realistically predicted on the basis of advanced parameterizations of upper mixed layer physics, without recourse to introducing extra complexity in model biology. The "K profile parameterization" (KPP) scheme employed, combined with 6-hourly external forcing, is able to capture short-term periodic and episodic events such as diurnal cycling and storm-induced deepening. The model realistically reproduces various features of global ecosystem dynamics that have been problematic in previous global modelling studies, using a single generic parameter set. The realistic simulation of deep convection in the North Atlantic, and lack of it in the North Pacific and Southern Oceans, leads to good predictions of chlorophyll and primary production in these contrasting areas. Realistic levels of primary production are predicted in the oligotrophic gyres due to high frequency external forcing of the upper mixed layer (accompanying paper Popova et al., 2006) and novel parameterizations of zooplankton excretion. Good agreement is shown between model and observations at various JGOFS time series sites: BATS, KERFIX, Papa and HOT. One exception is the northern North Atlantic where lower grazing rates are needed, perhaps related to the dominance of mesozooplankton there. The model is therefore not globally robust in the sense that additional parameterizations are needed to realistically simulate ecosystem dynamics in the North Atlantic. Nevertheless, the work emphasises the need to pay particular attention to the parameterization of mixed layer physics in global ocean ecosystem modelling as a prerequisite to increasing the complexity of ecosystem models.

Describing Ecosystem Complexity through Integrated Catchment Modeling

NASA Astrophysics Data System (ADS)

Shope, C. L.; Tenhunen, J. D.; Peiffer, S.

2011-12-01

Land use and climate change have been implicated in reduced ecosystem services (ie: high quality water yield, biodiversity, and agricultural yield. The prediction of ecosystem services expected under future land use decisions and changing climate conditions has become increasingly important. Complex policy and management decisions require the integration of physical, economic, and social data over several scales to assess effects on water resources and ecology. Field-based meteorology, hydrology, soil physics, plant production, solute and sediment transport, economic, and social behavior data were measured in a South Korean catchment. A variety of models are being used to simulate plot and field scale experiments within the catchment. Results from each of the local-scale models provide identification of sensitive, local-scale parameters which are then used as inputs into a large-scale watershed model. We used the spatially distributed SWAT model to synthesize the experimental field data throughout the catchment. The approach of our study was that the range in local-scale model parameter results can be used to define the sensitivity and uncertainty in the large-scale watershed model. Further, this example shows how research can be structured for scientific results describing complex ecosystems and landscapes where cross-disciplinary linkages benefit the end result. The field-based and modeling framework described is being used to develop scenarios to examine spatial and temporal changes in land use practices and climatic effects on water quantity, water quality, and sediment transport. Development of accurate modeling scenarios requires understanding the social relationship between individual and policy driven land management practices and the value of sustainable resources to all shareholders.

Carbon cycling at the tipping point: Does ecosystem structure predict resistance to disturbance?

NASA Astrophysics Data System (ADS)

Gough, C. M.; Bond-Lamberty, B. P.; Stuart-Haentjens, E.; Atkins, J.; Haber, L.; Fahey, R. T.

2017-12-01

Ecosystems worldwide are subjected to disturbances that reshape their physical and biological structure and modify biogeochemical processes, including carbon storage and cycling rates. Disturbances, including those from insect pests, pathogens, and extreme weather, span a continuum of severity and, accordingly, may have different effects on carbon cycling processes. Some ecosystems resist biogeochemical changes following disturbance, until a critical threshold of severity is exceeded. The ecosystem properties underlying such functional resistance, and signifying when a tipping point will occur, however, are almost entirely unknown. Here, we present observational and experimental results from forests in the Great Lakes region, showing ecosystem structure is closely coupled with carbon cycling responses to disturbance, with shifts in structure predicting thresholds of and, in some cases, increases in carbon storage. We find, among forests in the region, that carbon storage regularly exhibits a non-linear threshold response to increasing disturbance levels, but the severity at which a threshold is reached varies among disturbed forests. More biologically and structurally complex forest ecosystems sometimes exhibit greater functional resistance than simpler forests, and consequently may have a higher disturbance severity threshold. Counter to model predictions but consistent with some theoretical frameworks, empirical data show moderate levels of disturbance may increase ecosystem complexity to a point, thereby increasing rates of carbon storage. Disturbances that increase complexity therefore may stimulate carbon storage, while severe disturbances at or beyond thresholds may simplify structure, leading to carbon storage declines. We conclude that ecosystem structural attributes are closely coupled with biogeochemical thresholds across disturbance severity gradients, suggesting that improved predictions of disturbance-related changes in the carbon cycle require better representation of ecosystem structure in models.

Complex terrain influences ecosystem carbon responses to temperature and precipitation

NASA Astrophysics Data System (ADS)

Reyes, W. M.; Epstein, H. E.; Li, X.; McGlynn, B. L.; Riveros-Iregui, D. A.; Emanuel, R. E.

2017-08-01

Terrestrial ecosystem responses to temperature and precipitation have major implications for the global carbon cycle. Case studies demonstrate that complex terrain, which accounts for more than 50% of Earth's land surface, can affect ecological processes associated with land-atmosphere carbon fluxes. However, no studies have addressed the role of complex terrain in mediating ecophysiological responses of land-atmosphere carbon fluxes to climate variables. We synthesized data from AmeriFlux towers and found that for sites in complex terrain, responses of ecosystem CO2 fluxes to temperature and precipitation are organized according to terrain slope and drainage area, variables associated with water and energy availability. Specifically, we found that for tower sites in complex terrain, mean topographic slope and drainage area surrounding the tower explained between 51% and 78% of site-to-site variation in the response of CO2 fluxes to temperature and precipitation depending on the time scale. We found no such organization among sites in flat terrain, even though their flux responses exhibited similar ranges. These results challenge prevailing conceptual framework in terrestrial ecosystem modeling that assumes that CO2 fluxes derive from vertical soil-plant-climate interactions. We conclude that the terrain in which ecosystems are situated can also have important influences on CO2 responses to temperature and precipitation. This work has implications for about 14% of the total land area of the conterminous U.S. This area is considered topographically complex and contributes to approximately 15% of gross ecosystem carbon production in the conterminous U.S.

Linking Local Scale Ecosystem Science to Regional Scale Management

NASA Astrophysics Data System (ADS)

Shope, C. L.; Tenhunen, J.; Peiffer, S.

2012-04-01

Ecosystem management with respect to sufficient water yield, a quality water supply, habitat and biodiversity conservation, and climate change effects requires substantial observational data at a range of scales. Complex interactions of local physical processes oftentimes vary over space and time, particularly in locations with extreme meteorological conditions. Modifications to local conditions (ie: agricultural land use changes, nutrient additions, landscape management, water usage) can further affect regional ecosystem services. The international, inter-disciplinary TERRECO research group is intensively investigating a variety of local processes, parameters, and conditions to link complex physical, economic, and social interactions at the regional scale. Field-based meteorology, hydrology, soil physics, plant production, solute and sediment transport, economic, and social behavior data were measured in a South Korean catchment. The data are used to parameterize suite of models describing local to landscape level water, sediment, nutrient, and monetary relationships. We focus on using the agricultural and hydrological SWAT model to synthesize the experimental field data and local-scale models throughout the catchment. The approach of our study was to describe local scientific processes, link potential interrelationships between different processes, and predict environmentally efficient management efforts. The Haean catchment case study shows how research can be structured to provide cross-disciplinary scientific linkages describing complex ecosystems and landscapes that can be used for regional management evaluations and predictions.

Prairie wetland complexes as landscape functional units in a changing climate

USGS Publications Warehouse

Johnson, W. Carter; Werner, Brett; Guntenspergen, Glenn R.; Voldseth, Richard A.; Millett, Bruce; Naugle, David E.; Tulbure, Mirela; Carroll, Rosemary W.H.; Tracy, John; Olawsky, Craig

2010-01-01

The wetland complex is the functional ecological unit of the prairie pothole region (PPR) of central North America. Diverse complexes of wetlands contribute high spatial and temporal environmental heterogeneity, productivity, and biodiversity to these glaciated prairie landscapes. Climatewarming simulations using the new model WETLANDSCAPE (WLS) project major reductions in water volume, shortening of hydroperiods, and less-dynamic vegetation for prairie wetland complexes. The WLS model portrays the future PPR as a much less resilient ecosystem: The western PPR will be too dry and the eastern PPR will have too few functional wetlands and nesting habitat to support historic levels of waterfowl and other wetland-dependent species. Maintaining ecosystem goods and services at current levels in a warmer climate will be a major challenge for the conservation community.

Understanding variation in ecosystem pulse responses to wetting: Benefits of data-model coupling

NASA Astrophysics Data System (ADS)

Jenerette, D.

2011-12-01

Metabolic pulses of activity are a common ecological response to intermittently available resources and in water-limited ecosystems these pulses often occur in response to wetting. Net ecosystem CO2 exchange (NEE) in response to episodic wetting events is hypothesized to have a complex trajectory reflecting the distinct responses, or "pulses", of respiration and photosynthesis. To help direct research activities a physiological-based model of whole ecosystem metabolic activity up- and down-regulation was developed to investigate ecosystem energy balance and gas exchange pulse responses following precipitation events. This model was to investigate pulse dynamics from a local network of sites in southern Arizona, a global network of eddy-covariance ecosystem monitoring sites, laboratory incubation studies, and field manipulations. Pulse responses were found to be ubiquitous across ecosystem types. These pulses had a highly variable influence on NEE following wetting, ranging from large net sinks to sources of CO2 to the atmosphere. Much of the variability in pulse responses of NEE could be described through a coupled up- and down-regulation pulse response model. Respiration pulses were hypothesized to occur through a reduction in whole ecosystem activation energy; this model was both useful and corroborated through laboratory incubation studies of soil respiration. Using the Fluxnet eddy-covariance measurement database event specific responses were combined with the pulse model into an event specific twenty-five day net flux calculation. Across all events observed a general net accumulation of CO2 following a precipitation event, with the largest net uptake within deciduous broadleaf forests and smallest within grasslands. NEE pulses favored greater uptake when pre-event ecosystem respiration rates and total precipitation were higher. While the latter was expected, the former adds to previous theory by suggesting a larger net uptake of CO2 when pre-event metabolic activity is higher. Scenario analyses of precipitation regimes suggested increased uptake with increasing total precipitation while more complex NEE responses to increasing number of events and interval between events. Pulse dynamics provides a general framework for understanding ecosystem responses to intermittent wetting projected to occur more frequently in future climates. Pulse dynamics also provides an opportunity to evaluate processes spanning cellular upregulation to global change.

Monitoring and modeling for investigating driver/pressure-state/impact relationships in coastal ecosystems: Examples from the Lagoon of Venice

NASA Astrophysics Data System (ADS)

Pastres, Roberto; Solidoro, Cosimo

2012-01-01

In this paper, we show how the integration of monitoring data and mathematical model can generate valuable information by using a few examples taken from a well studied but complex ecosystem, namely the Lagoon of Venice. We will focus on three key issues, which are of concern also for many other coastal ecosystems, namely: (1) Nitrogen and Phosphorus annual budgets; (2) estimation of Net Ecosystem Metabolism and early warnings for anoxic events; (3) assessment of ecosystem status. The results highlight the importance of framing monitoring activities within the "DPSIR" conceptual model, thus going far beyond the monitoring of major biogeochemical variables and including: (1) the estimation of the fluxes of the main constituents at the boundaries; (2) the use of appropriate mathematical models. These tools can provide quantitative links among Pressures and State/Impacts, thus enabling decision makers and stakeholders to evaluate the effects of alternative management scenarios.

Do microbial processes regulate the stability of a coral atoll's enclosed pelagic ecosystem?

EPA Science Inventory

Complex marine ecosystems contain multiple feedback cycles that can cause unexpected responses to perturbations. To better predict these responses, complicated models are increasingly being developed to enable the study of feedback cycles. However, the sparseness of ecological da...

A practical approach for comparing management strategies in complex forest ecosystems using meta-modelling toolkits

Treesearch

Andrew Fall; B. Sturtevant; M.-J. Fortin; M. Papaik; F. Doyon; D. Morgan; K. Berninger; C. Messier

2010-01-01

The complexity and multi-scaled nature of forests poses significant challenges to understanding and management. Models can provide useful insights into process and their interactions, and implications of alternative management options. Most models, particularly scientific models, focus on a relatively small set of processes and are designed to operate within a...

Analyzing urban ecosystem variation in the City of Dongguan: A stepwise cluster modeling approach.

PubMed

Sun, J; Li, Y P; Gao, P P; Suo, C; Xia, B C

2018-06-13

In this study, a stepwise cluster modeling approach (SCMA) is developed for analyzing urban ecosystem variation via Normalized Difference Vegetation Index (NDVI). NDVI is an indicator of vegetation growth and coverage and useful in reflecting urban ecosystem. SCMA is established on a cluster tree that can characterize the complex relationship between independent and dependent variables. SCMA is applied to the City of Dongguan for simulating the urban NDVI and identifying associated drivers of human activity, topography and meteorology without specific functions. Results show that SCMA performances better than conventional statistical methods, illustrating the ability of SCMA in capturing the complex and nonlinear features of urban ecosystem. Results disclose that human activities play negative effects on NDVI due to the destruction of green space for pursuing more space for buildings. NDVI reduces gradually from the south part to the north part of Dongguan due to increased gross domestic product and population density, indicating that the ecosystem in Dongguan is better in the south part. NDVI in the northeast part (dominated by agriculture) is sensitive to the growth of economy and population. More attention should be paid to this part for sustainable development, such as increasing afforestation, planting grass and constructing parks. Precipitation has a positive effect on NDVI due to the promotion of soil moisture that is beneficial to plants' growth. Awareness of these complexities is helpful for sustainable development of urban ecosystem. Copyright © 2018 Elsevier Inc. All rights reserved.

Structure, Behavior, Function as a Framework For Teaching and Learning about Complexity In Ecosystems: Lessons from Middle School Classrooms (Invited)

NASA Astrophysics Data System (ADS)

Hmelo-Silver, C.; Gray, S.; Jordan, R.

2010-12-01

Complex systems surround us, and as Sabelli (2006) has argued, understanding complex systems is a critical component of science literacy. Understanding natural and designed systems are also prominent in the new draft science standards (NRC, 2010) and therefore of growing importance in the science classroom. Our work has focused on promoting an understanding of one complex natural system, aquatic ecosystems, which given current events, is fast becoming a requisite for informed decision-making as citizens (Jordan et al. 2008). Learners have difficulty understanding many concepts related to complex natural systems (e.g., Hmelo-Silver, Marathe, & Liu, 2007; Jordan, Gray, Liu, Demeter, & Hmelo-Silver, 2009). Studies of how students think about complex ecological systems (e.g; Hmelo-Silver, Marathe, & Liu, 2007; Hogan, 2000, Hogan & Fisherkeller, 1996: Covitt & Gunkel, 2008) have revealed difficulties in thinking beyond linear flow, single causality, and visible structure. Helping students to learn about ecosystems is a complex task that requires providing opportunities for students to not only engage directly with ecosystems but also with resources that provide relevant background knowledge and opportunities for learners to make their thinking visible. Both tasks can be difficult given the large spatial and temporal scales on which ecosystems operate. Additionally, visible components interact with often invisible components which can obscure ecosystem processes for students. Working in the context of aquatic ecosystems, we sought to provide learners with representations and simulations that make salient the relationship between system components. In particular, we provided learners with opportunities to experience both the micro-level and macro-level phenomena that are key to understanding ecosystems (Hmelo-Silver, Liu, Gray, & Jordan, submitted; Liu & Hmelo-Silver, 2008; Jacobson & Wilensky, 2006). To accomplish this, we needed to help learners make connections across the levels of ecosystems. A big part of this is making phenomena accessible to their experience. We accomplished through the use of physical models and computers simulations at different scale. In an effort to promote a coherent understanding in our learners, we sought to develop tools that can provide dynamic feedback that will enable them to modify, enrich, and repair their mental models as needed (e.g., Roschelle, 1996). Additionally, we also wanted to develop a conceptual representation that can be used across multiple ecosystems to prepare students to learn about new systems in the future (Bransford & Schwartz, 1999). Our approach to this has been to use the structure-behavior-function (SBF) conceptual representation (Liu & Hmelo-Silver, 2009; Vattam et al., in press). Often, learning life science is about learning the names of structures. One of our design principles is to ensure instruction emphasizes the behaviors (or mechanisms) of systems as well as the functions (the system outputs) in addition to the structures. We have used simulations to help make behaviors and functions visible and a modeling tool that supports students in thinking about the SBF conceptual representation. In this presentation, we will report on the results of classroom interventions and the lessons learned.

Ecosystem function in complex mountain terrain: Combining models and long-term observations to advance process-based understanding

NASA Astrophysics Data System (ADS)

Wieder, William R.; Knowles, John F.; Blanken, Peter D.; Swenson, Sean C.; Suding, Katharine N.

2017-04-01

Abiotic factors structure plant community composition and ecosystem function across many different spatial scales. Often, such variation is considered at regional or global scales, but here we ask whether ecosystem-scale simulations can be used to better understand landscape-level variation that might be particularly important in complex terrain, such as high-elevation mountains. We performed ecosystem-scale simulations by using the Community Land Model (CLM) version 4.5 to better understand how the increased length of growing seasons may impact carbon, water, and energy fluxes in an alpine tundra landscape. The model was forced with meteorological data and validated with observations from the Niwot Ridge Long Term Ecological Research Program site. Our results demonstrate that CLM is capable of reproducing the observed carbon, water, and energy fluxes for discrete vegetation patches across this heterogeneous ecosystem. We subsequently accelerated snowmelt and increased spring and summer air temperatures in order to simulate potential effects of climate change in this region. We found that vegetation communities that were characterized by different snow accumulation dynamics showed divergent biogeochemical responses to a longer growing season. Contrary to expectations, wet meadow ecosystems showed the strongest decreases in plant productivity under extended summer scenarios because of disruptions in hydrologic connectivity. These findings illustrate how Earth system models such as CLM can be used to generate testable hypotheses about the shifting nature of energy, water, and nutrient limitations across space and through time in heterogeneous landscapes; these hypotheses may ultimately guide further experimental work and model development.

Competition favors elk over beaver in a riparian willow ecosystem

USGS Publications Warehouse

Baker, B.W.; Peinetti, H.R.; Coughenour, M.C.; Johnson, T.L.

2012-01-01

Beaver (Castor spp.) conservation requires an understanding of their complex interactions with competing herbivores. Simulation modeling offers a controlled environment to examine long-term dynamics in ecosystems driven by uncontrollable variables. We used a new version of the SAVANNA ecosystem model to investigate beaver (C. Canadensis) and elk (Cervus elapses) competition for willow (Salix spp.). We initialized the model with field data from Rocky Mountain National Park, Colorado, USA, to simulate a 4-ha riparian ecosystem containing beaver, elk, and willow. We found beaver persisted indefinitely when elk density was or = 30 elk km_2. The loss of tall willow preceded rapid beaver declines, thus willow condition may predict beaver population trajectory in natural environments. Beaver were able to persist with slightly higher elk densities if beaver alternated their use of foraging sites in a rest-rotation pattern rather than maintained continuous use. Thus, we found asymmetrical competition for willow strongly favored elk over beaver in a simulated montane ecosystem. Finally, we discuss application of the SAVANNA model and mechanisms of competition relative to beaver persistence as metapopulations, ecological resistance and alternative state models, and ecosystem regulation.

Conceptual ecological models to guide integrated landscape monitoring of the Great Basin

USGS Publications Warehouse

Miller, D.M.; Finn, S.P.; Woodward, Andrea; Torregrosa, Alicia; Miller, M.E.; Bedford, D.R.; Brasher, A.M.

2010-01-01

The Great Basin Integrated Landscape Monitoring Pilot Project was developed in response to the need for a monitoring and predictive capability that addresses changes in broad landscapes and waterscapes. Human communities and needs are nested within landscapes formed by interactions among the hydrosphere, geosphere, and biosphere. Understanding the complex processes that shape landscapes and deriving ways to manage them sustainably while meeting human needs require sophisticated modeling and monitoring. This document summarizes current understanding of ecosystem structure and function for many of the ecosystems within the Great Basin using conceptual models. The conceptual ecosystem models identify key ecological components and processes, identify external drivers, develop a hierarchical set of models that address both site and landscape attributes, inform regional monitoring strategy, and identify critical gaps in our knowledge of ecosystem function. The report also illustrates an approach for temporal and spatial scaling from site-specific models to landscape models and for understanding cumulative effects. Eventually, conceptual models can provide a structure for designing monitoring programs, interpreting monitoring and other data, and assessing the accuracy of our understanding of ecosystem functions and processes.

Comparison of Commercial Structure-From Photogrammety Software Used for Underwater Three-Dimensional Modeling of Coral Reef Environments

NASA Astrophysics Data System (ADS)

Burns, J. H. R.; Delparte, D.

2017-02-01

Structural complexity in ecosystems creates an assortment of microhabitat types and has been shown to support greater diversity and abundance of associated organisms. The 3D structure of an environment also directly affects important ecological parameters such as habitat provisioning and light availability and can therefore strongly influence ecosystem function. Coral reefs are architecturally complex 3D habitats, whose structure is intrinsically linked to the ecosystem biodiversity, productivity, and function. The field of coral ecology has, however, been primarily limited to using 2-dimensional (2D) planar survey techniques for studying the physical structure of reefs. This conventional approach fails to capture or quantify the intricate structural complexity of corals that influences habitat facilitation and biodiversity. A 3-dimensional (3D) approach can obtain accurate measurements of architectural complexity, topography, rugosity, volume, and other structural characteristics that affect biodiversity and abundance of reef organisms. Structurefrom- Motion (SfM) photogrammetry is an emerging computer vision technology that provides a simple and cost-effective method for 3D reconstruction of natural environments. SfM has been used in several studies to investigate the relationship between habitat complexity and ecological processes in coral reef ecosystems. This study compared two commercial SfM software packages, Agisoft Photoscan Pro and Pix4Dmapper Pro 3.1, in order to assess the cpaability and spatial accuracy of these programs for conducting 3D modeling of coral reef habitats at three spatial scales.

Discontinuity in the responses of ecosystem processes and multifunctionality to altered soil community composition.

PubMed

Bradford, Mark A; Wood, Stephen A; Bardgett, Richard D; Black, Helaina I J; Bonkowski, Michael; Eggers, Till; Grayston, Susan J; Kandeler, Ellen; Manning, Peter; Setälä, Heikki; Jones, T Hefin

2014-10-07

Ecosystem management policies increasingly emphasize provision of multiple, as opposed to single, ecosystem services. Management for such "multifunctionality" has stimulated research into the role that biodiversity plays in providing desired rates of multiple ecosystem processes. Positive effects of biodiversity on indices of multifunctionality are consistently found, primarily because species that are redundant for one ecosystem process under a given set of environmental conditions play a distinct role under different conditions or in the provision of another ecosystem process. Here we show that the positive effects of diversity (specifically community composition) on multifunctionality indices can also arise from a statistical fallacy analogous to Simpson's paradox (where aggregating data obscures causal relationships). We manipulated soil faunal community composition in combination with nitrogen fertilization of model grassland ecosystems and repeatedly measured five ecosystem processes related to plant productivity, carbon storage, and nutrient turnover. We calculated three common multifunctionality indices based on these processes and found that the functional complexity of the soil communities had a consistent positive effect on the indices. However, only two of the five ecosystem processes also responded positively to increasing complexity, whereas the other three responded neutrally or negatively. Furthermore, none of the individual processes responded to both the complexity and the nitrogen manipulations in a manner consistent with the indices. Our data show that multifunctionality indices can obscure relationships that exist between communities and key ecosystem processes, leading us to question their use in advancing theoretical understanding--and in management decisions--about how biodiversity is related to the provision of multiple ecosystem services.

Discontinuity in the responses of ecosystem processes and multifunctionality to altered soil community composition

PubMed Central

Bradford, Mark A.; Wood, Stephen A.; Bardgett, Richard D.; Black, Helaina I. J.; Bonkowski, Michael; Eggers, Till; Grayston, Susan J.; Kandeler, Ellen; Manning, Peter; Setälä, Heikki; Jones, T. Hefin

2014-01-01

Ecosystem management policies increasingly emphasize provision of multiple, as opposed to single, ecosystem services. Management for such “multifunctionality” has stimulated research into the role that biodiversity plays in providing desired rates of multiple ecosystem processes. Positive effects of biodiversity on indices of multifunctionality are consistently found, primarily because species that are redundant for one ecosystem process under a given set of environmental conditions play a distinct role under different conditions or in the provision of another ecosystem process. Here we show that the positive effects of diversity (specifically community composition) on multifunctionality indices can also arise from a statistical fallacy analogous to Simpson’s paradox (where aggregating data obscures causal relationships). We manipulated soil faunal community composition in combination with nitrogen fertilization of model grassland ecosystems and repeatedly measured five ecosystem processes related to plant productivity, carbon storage, and nutrient turnover. We calculated three common multifunctionality indices based on these processes and found that the functional complexity of the soil communities had a consistent positive effect on the indices. However, only two of the five ecosystem processes also responded positively to increasing complexity, whereas the other three responded neutrally or negatively. Furthermore, none of the individual processes responded to both the complexity and the nitrogen manipulations in a manner consistent with the indices. Our data show that multifunctionality indices can obscure relationships that exist between communities and key ecosystem processes, leading us to question their use in advancing theoretical understanding—and in management decisions—about how biodiversity is related to the provision of multiple ecosystem services. PMID:25246582

Integrating structure-from-motion photogrammetry with geospatial software as a novel technique for quantifying 3D ecological characteristics of coral reefs

PubMed Central

Delparte, D; Gates, RD; Takabayashi, M

2015-01-01

The structural complexity of coral reefs plays a major role in the biodiversity, productivity, and overall functionality of reef ecosystems. Conventional metrics with 2-dimensional properties are inadequate for characterization of reef structural complexity. A 3-dimensional (3D) approach can better quantify topography, rugosity and other structural characteristics that play an important role in the ecology of coral reef communities. Structure-from-Motion (SfM) is an emerging low-cost photogrammetric method for high-resolution 3D topographic reconstruction. This study utilized SfM 3D reconstruction software tools to create textured mesh models of a reef at French Frigate Shoals, an atoll in the Northwestern Hawaiian Islands. The reconstructed orthophoto and digital elevation model were then integrated with geospatial software in order to quantify metrics pertaining to 3D complexity. The resulting data provided high-resolution physical properties of coral colonies that were then combined with live cover to accurately characterize the reef as a living structure. The 3D reconstruction of reef structure and complexity can be integrated with other physiological and ecological parameters in future research to develop reliable ecosystem models and improve capacity to monitor changes in the health and function of coral reef ecosystems. PMID:26207190

Ecosystem Model Skill Assessment. Yes We Can!

PubMed Central

Olsen, Erik; Fay, Gavin; Gaichas, Sarah; Gamble, Robert; Lucey, Sean; Link, Jason S.

2016-01-01

Need to Assess the Skill of Ecosystem Models Accelerated changes to global ecosystems call for holistic and integrated analyses of past, present and future states under various pressures to adequately understand current and projected future system states. Ecosystem models can inform management of human activities in a complex and changing environment, but are these models reliable? Ensuring that models are reliable for addressing management questions requires evaluating their skill in representing real-world processes and dynamics. Skill has been evaluated for just a limited set of some biophysical models. A range of skill assessment methods have been reviewed but skill assessment of full marine ecosystem models has not yet been attempted. Northeast US Atlantis Marine Ecosystem Model We assessed the skill of the Northeast U.S. (NEUS) Atlantis marine ecosystem model by comparing 10-year model forecasts with observed data. Model forecast performance was compared to that obtained from a 40-year hindcast. Multiple metrics (average absolute error, root mean squared error, modeling efficiency, and Spearman rank correlation), and a suite of time-series (species biomass, fisheries landings, and ecosystem indicators) were used to adequately measure model skill. Overall, the NEUS model performed above average and thus better than expected for the key species that had been the focus of the model tuning. Model forecast skill was comparable to the hindcast skill, showing that model performance does not degenerate in a 10-year forecast mode, an important characteristic for an end-to-end ecosystem model to be useful for strategic management purposes. Skill Assessment Is Both Possible and Advisable We identify best-practice approaches for end-to-end ecosystem model skill assessment that would improve both operational use of other ecosystem models and future model development. We show that it is possible to not only assess the skill of a complicated marine ecosystem model, but that it is necessary do so to instill confidence in model results and encourage their use for strategic management. Our methods are applicable to any type of predictive model, and should be considered for use in fields outside ecology (e.g. economics, climate change, and risk assessment). PMID:26731540

Ecosystem Model Skill Assessment. Yes We Can!

PubMed

Olsen, Erik; Fay, Gavin; Gaichas, Sarah; Gamble, Robert; Lucey, Sean; Link, Jason S

2016-01-01

Accelerated changes to global ecosystems call for holistic and integrated analyses of past, present and future states under various pressures to adequately understand current and projected future system states. Ecosystem models can inform management of human activities in a complex and changing environment, but are these models reliable? Ensuring that models are reliable for addressing management questions requires evaluating their skill in representing real-world processes and dynamics. Skill has been evaluated for just a limited set of some biophysical models. A range of skill assessment methods have been reviewed but skill assessment of full marine ecosystem models has not yet been attempted. We assessed the skill of the Northeast U.S. (NEUS) Atlantis marine ecosystem model by comparing 10-year model forecasts with observed data. Model forecast performance was compared to that obtained from a 40-year hindcast. Multiple metrics (average absolute error, root mean squared error, modeling efficiency, and Spearman rank correlation), and a suite of time-series (species biomass, fisheries landings, and ecosystem indicators) were used to adequately measure model skill. Overall, the NEUS model performed above average and thus better than expected for the key species that had been the focus of the model tuning. Model forecast skill was comparable to the hindcast skill, showing that model performance does not degenerate in a 10-year forecast mode, an important characteristic for an end-to-end ecosystem model to be useful for strategic management purposes. We identify best-practice approaches for end-to-end ecosystem model skill assessment that would improve both operational use of other ecosystem models and future model development. We show that it is possible to not only assess the skill of a complicated marine ecosystem model, but that it is necessary do so to instill confidence in model results and encourage their use for strategic management. Our methods are applicable to any type of predictive model, and should be considered for use in fields outside ecology (e.g. economics, climate change, and risk assessment).

COMPLEX INTERACTIONS BETWEEN AUTOTROPHS IN SHALLOW MARINE AND FRESHWATER ECOSYSTEMS: IMPLICATIONS FOR COMMUNITY RESPONSES TO NUTRIENT STRESS. (U915532)

EPA Science Inventory

The relative biomass of autotrophs (vascular plants, macroalgae, microphytobenthos, phytoplankton) in shallow aquatic ecosystems is thought to be controlled by nutrient inputs and underwater irradiance. Widely accepted conceptual models indicate that this is the case both in m...

Measuring and Modeling the U.S. Regulatory Ecosystem

NASA Astrophysics Data System (ADS)

Bommarito, Michael J., II; Katz, Daniel Martin

2017-09-01

Over the last 23 years, the U.S. Securities and Exchange Commission has required over 34,000 companies to file over 165,000 annual reports. These reports, the so-called "Form 10-Ks," contain a characterization of a company's financial performance and its risks, including the regulatory environment in which a company operates. In this paper, we analyze over 4.5 million references to U.S. Federal Acts and Agencies contained within these reports to measure the regulatory ecosystem, in which companies are organisms inhabiting a regulatory environment. While individuals across the political, economic, and academic world frequently refer to trends in this regulatory ecosystem, far less attention has been paid to supporting such claims with large-scale, longitudinal data. In this paper, in addition to positing a model of regulatory ecosystems, we document an increase in the regulatory energy per filing, i.e., a warming "temperature." We also find that the diversity of the regulatory ecosystem has been increasing over the past two decades. These findings support the claim that regulatory activity and complexity are increasing, and this framework contributes an important step towards improving academic and policy discussions around legal complexity and regulation.

Inferring Aggregated Functional Traits from Metagenomic Data Using Constrained Non-negative Matrix Factorization: Application to Fiber Degradation in the Human Gut Microbiota.

PubMed

Raguideau, Sébastien; Plancade, Sandra; Pons, Nicolas; Leclerc, Marion; Laroche, Béatrice

2016-12-01

Whole Genome Shotgun (WGS) metagenomics is increasingly used to study the structure and functions of complex microbial ecosystems, both from the taxonomic and functional point of view. Gene inventories of otherwise uncultured microbial communities make the direct functional profiling of microbial communities possible. The concept of community aggregated trait has been adapted from environmental and plant functional ecology to the framework of microbial ecology. Community aggregated traits are quantified from WGS data by computing the abundance of relevant marker genes. They can be used to study key processes at the ecosystem level and correlate environmental factors and ecosystem functions. In this paper we propose a novel model based approach to infer combinations of aggregated traits characterizing specific ecosystemic metabolic processes. We formulate a model of these Combined Aggregated Functional Traits (CAFTs) accounting for a hierarchical structure of genes, which are associated on microbial genomes, further linked at the ecosystem level by complex co-occurrences or interactions. The model is completed with constraints specifically designed to exploit available genomic information, in order to favor biologically relevant CAFTs. The CAFTs structure, as well as their intensity in the ecosystem, is obtained by solving a constrained Non-negative Matrix Factorization (NMF) problem. We developed a multicriteria selection procedure for the number of CAFTs. We illustrated our method on the modelling of ecosystemic functional traits of fiber degradation by the human gut microbiota. We used 1408 samples of gene abundances from several high-throughput sequencing projects and found that four CAFTs only were needed to represent the fiber degradation potential. This data reduction highlighted biologically consistent functional patterns while providing a high quality preservation of the original data. Our method is generic and can be applied to other metabolic processes in the gut or in other ecosystems.

Quantifying Florida Bay habitat suitability for fishes and invertebrates under climate change scenarios.

PubMed

Kearney, Kelly A; Butler, Mark; Glazer, Robert; Kelble, Christopher R; Serafy, Joseph E; Stabenau, Erik

2015-04-01

The Florida Bay ecosystem supports a number of economically important ecosystem services, including several recreational fisheries, which may be affected by changing salinity and temperature due to climate change. In this paper, we use a combination of physical models and habitat suitability index models to quantify the effects of potential climate change scenarios on a variety of juvenile fish and lobster species in Florida Bay. The climate scenarios include alterations in sea level, evaporation and precipitation rates, coastal runoff, and water temperature. We find that the changes in habitat suitability vary in both magnitude and direction across the scenarios and species, but are on average small. Only one of the seven species we investigate (Lagodon rhomboides, i.e., pinfish) sees a sizable decrease in optimal habitat under any of the scenarios. This suggests that the estuarine fauna of Florida Bay may not be as vulnerable to climate change as other components of the ecosystem, such as those in the marine/terrestrial ecotone. However, these models are relatively simplistic, looking only at single species effects of physical drivers without considering the many interspecific interactions that may play a key role in the adjustment of the ecosystem as a whole. More complex models that capture the mechanistic links between physics and biology, as well as the complex dynamics of the estuarine food web, may be necessary to further understand the potential effects of climate change on the Florida Bay ecosystem.

Quantifying Florida Bay Habitat Suitability for Fishes and Invertebrates Under Climate Change Scenarios

NASA Astrophysics Data System (ADS)

Kearney, Kelly A.; Butler, Mark; Glazer, Robert; Kelble, Christopher R.; Serafy, Joseph E.; Stabenau, Erik

2015-04-01

The Florida Bay ecosystem supports a number of economically important ecosystem services, including several recreational fisheries, which may be affected by changing salinity and temperature due to climate change. In this paper, we use a combination of physical models and habitat suitability index models to quantify the effects of potential climate change scenarios on a variety of juvenile fish and lobster species in Florida Bay. The climate scenarios include alterations in sea level, evaporation and precipitation rates, coastal runoff, and water temperature. We find that the changes in habitat suitability vary in both magnitude and direction across the scenarios and species, but are on average small. Only one of the seven species we investigate ( Lagodon rhomboides, i.e., pinfish) sees a sizable decrease in optimal habitat under any of the scenarios. This suggests that the estuarine fauna of Florida Bay may not be as vulnerable to climate change as other components of the ecosystem, such as those in the marine/terrestrial ecotone. However, these models are relatively simplistic, looking only at single species effects of physical drivers without considering the many interspecific interactions that may play a key role in the adjustment of the ecosystem as a whole. More complex models that capture the mechanistic links between physics and biology, as well as the complex dynamics of the estuarine food web, may be necessary to further understand the potential effects of climate change on the Florida Bay ecosystem.

Global Patterns in Ecological Indicators of Marine Food Webs: A Modelling Approach

PubMed Central

Heymans, Johanna Jacomina; Coll, Marta; Libralato, Simone; Morissette, Lyne; Christensen, Villy

2014-01-01

Background Ecological attributes estimated from food web models have the potential to be indicators of good environmental status given their capabilities to describe redundancy, food web changes, and sensitivity to fishing. They can be used as a baseline to show how they might be modified in the future with human impacts such as climate change, acidification, eutrophication, or overfishing. Methodology In this study ecological network analysis indicators of 105 marine food web models were tested for variation with traits such as ecosystem type, latitude, ocean basin, depth, size, time period, and exploitation state, whilst also considering structural properties of the models such as number of linkages, number of living functional groups or total number of functional groups as covariate factors. Principal findings Eight indicators were robust to model construction: relative ascendency; relative overhead; redundancy; total systems throughput (TST); primary production/TST; consumption/TST; export/TST; and total biomass of the community. Large-scale differences were seen in the ecosystems of the Atlantic and Pacific Oceans, with the Western Atlantic being more complex with an increased ability to mitigate impacts, while the Eastern Atlantic showed lower internal complexity. In addition, the Eastern Pacific was less organised than the Eastern Atlantic although both of these systems had increased primary production as eastern boundary current systems. Differences by ecosystem type highlighted coral reefs as having the largest energy flow and total biomass per unit of surface, while lagoons, estuaries, and bays had lower transfer efficiencies and higher recycling. These differences prevailed over time, although some traits changed with fishing intensity. Keystone groups were mainly higher trophic level species with mostly top-down effects, while structural/dominant groups were mainly lower trophic level groups (benthic primary producers such as seagrass and macroalgae, and invertebrates). Keystone groups were prevalent in estuarine or small/shallow systems, and in systems with reduced fishing pressure. Changes to the abundance of key functional groups might have significant implications for the functioning of ecosystems and should be avoided through management. Conclusion/significance Our results provide additional understanding of patterns of structural and functional indicators in different ecosystems. Ecosystem traits such as type, size, depth, and location need to be accounted for when setting reference levels as these affect absolute values of ecological indicators. Therefore, establishing absolute reference values for ecosystem indicators may not be suitable to the ecosystem-based, precautionary approach. Reference levels for ecosystem indicators should be developed for individual ecosystems or ecosystems with the same typologies (similar location, ecosystem type, etc.) and not benchmarked against all other ecosystems. PMID:24763610

Global patterns in ecological indicators of marine food webs: a modelling approach.

PubMed

Heymans, Johanna Jacomina; Coll, Marta; Libralato, Simone; Morissette, Lyne; Christensen, Villy

2014-01-01

Ecological attributes estimated from food web models have the potential to be indicators of good environmental status given their capabilities to describe redundancy, food web changes, and sensitivity to fishing. They can be used as a baseline to show how they might be modified in the future with human impacts such as climate change, acidification, eutrophication, or overfishing. In this study ecological network analysis indicators of 105 marine food web models were tested for variation with traits such as ecosystem type, latitude, ocean basin, depth, size, time period, and exploitation state, whilst also considering structural properties of the models such as number of linkages, number of living functional groups or total number of functional groups as covariate factors. Eight indicators were robust to model construction: relative ascendency; relative overhead; redundancy; total systems throughput (TST); primary production/TST; consumption/TST; export/TST; and total biomass of the community. Large-scale differences were seen in the ecosystems of the Atlantic and Pacific Oceans, with the Western Atlantic being more complex with an increased ability to mitigate impacts, while the Eastern Atlantic showed lower internal complexity. In addition, the Eastern Pacific was less organised than the Eastern Atlantic although both of these systems had increased primary production as eastern boundary current systems. Differences by ecosystem type highlighted coral reefs as having the largest energy flow and total biomass per unit of surface, while lagoons, estuaries, and bays had lower transfer efficiencies and higher recycling. These differences prevailed over time, although some traits changed with fishing intensity. Keystone groups were mainly higher trophic level species with mostly top-down effects, while structural/dominant groups were mainly lower trophic level groups (benthic primary producers such as seagrass and macroalgae, and invertebrates). Keystone groups were prevalent in estuarine or small/shallow systems, and in systems with reduced fishing pressure. Changes to the abundance of key functional groups might have significant implications for the functioning of ecosystems and should be avoided through management. Our results provide additional understanding of patterns of structural and functional indicators in different ecosystems. Ecosystem traits such as type, size, depth, and location need to be accounted for when setting reference levels as these affect absolute values of ecological indicators. Therefore, establishing absolute reference values for ecosystem indicators may not be suitable to the ecosystem-based, precautionary approach. Reference levels for ecosystem indicators should be developed for individual ecosystems or ecosystems with the same typologies (similar location, ecosystem type, etc.) and not benchmarked against all other ecosystems.

Complex climatic and CO2 controls on net primary productivity of temperate dryland ecosystems over central Asia during 1980-2014

NASA Astrophysics Data System (ADS)

Zhang, Chi; Ren, Wei

2017-09-01

Central Asia covers a large land area of 5 × 106 km2 and has unique temperate dryland ecosystems, with over 80% of the world's temperate deserts, which has been experiencing dramatic warming and drought in the recent decades. How the temperate dryland responds to complex climate change, however, is still far from clear. This study quantitatively investigates terrestrial net primary productivity (NPP) in responses to temperature, precipitation, and atmospheric CO2 during 1980-2014, by using the Arid Ecosystem Model, which can realistically predict ecosystems' responses to changes in climate and atmospheric CO2 according to model evaluation against 28 field experiments/observations. The simulation results show that unlike other middle-/high-latitude regions, NPP in central Asia declined by 10% (0.12 × 1015 g C) since the 1980s in response to a warmer and drier climate. The dryland's response to warming was weak, while its cropland was sensitive to the CO2 fertilization effect (CFE). However, the CFE was inhibited by the long-term drought from 1998 to 2008 and the positive effect of warming on photosynthesis was largely offset by the enhanced water deficit. The complex interactive effects among climate drivers, unique responses from diverse ecosystem types, and intensive and heterogeneous climatic changes led to highly complex NPP changing patterns in central Asia, of which 69% was dominated by precipitation variation and 20% and 9% was dominated by CO2 and temperature, respectively. The Turgay Plateau in northern Kazakhstan and southern Xinjiang in China are hot spots of NPP degradation in response to climate change during the past three decades and in the future.

Testing paradigms of ecosystem change under climate warming in Antarctica.

PubMed

Melbourne-Thomas, Jessica; Constable, Andrew; Wotherspoon, Simon; Raymond, Ben

2013-01-01

Antarctic marine ecosystems have undergone significant changes as a result of human activities in the past and are now responding in varied and often complicated ways to climate change impacts. Recent years have seen the emergence of large-scale mechanistic explanations-or "paradigms of change"-that attempt to synthesize our understanding of past and current changes. In many cases, these paradigms are based on observations that are spatially and temporally patchy. The West Antarctic Peninsula (WAP), one of Earth's most rapidly changing regions, has been an area of particular research focus. A recently proposed mechanistic explanation for observed changes in the WAP region relates changes in penguin populations to variability in krill biomass and regional warming. While this scheme is attractive for its simplicity and chronology, it may not account for complex spatio-temporal processes that drive ecosystem dynamics in the region. It might also be difficult to apply to other Antarctic regions that are experiencing some, though not all, of the changes documented for the WAP. We use qualitative network models of differing levels of complexity to test paradigms of change for the WAP ecosystem. Importantly, our approach captures the emergent effects of feedback processes in complex ecological networks and provides a means to identify and incorporate uncertain linkages between network elements. Our findings highlight key areas of uncertainty in the drivers of documented trends, and suggest that a greater level of model complexity is needed in devising explanations for ecosystem change in the Southern Ocean. We suggest that our network approach to evaluating a recent and widely cited paradigm of change for the Antarctic region could be broadly applied in hypothesis testing for other regions and research fields.

Testing Paradigms of Ecosystem Change under Climate Warming in Antarctica

PubMed Central

Melbourne-Thomas, Jessica; Constable, Andrew; Wotherspoon, Simon; Raymond, Ben

2013-01-01

Antarctic marine ecosystems have undergone significant changes as a result of human activities in the past and are now responding in varied and often complicated ways to climate change impacts. Recent years have seen the emergence of large-scale mechanistic explanations–or “paradigms of change”–that attempt to synthesize our understanding of past and current changes. In many cases, these paradigms are based on observations that are spatially and temporally patchy. The West Antarctic Peninsula (WAP), one of Earth’s most rapidly changing regions, has been an area of particular research focus. A recently proposed mechanistic explanation for observed changes in the WAP region relates changes in penguin populations to variability in krill biomass and regional warming. While this scheme is attractive for its simplicity and chronology, it may not account for complex spatio-temporal processes that drive ecosystem dynamics in the region. It might also be difficult to apply to other Antarctic regions that are experiencing some, though not all, of the changes documented for the WAP. We use qualitative network models of differing levels of complexity to test paradigms of change for the WAP ecosystem. Importantly, our approach captures the emergent effects of feedback processes in complex ecological networks and provides a means to identify and incorporate uncertain linkages between network elements. Our findings highlight key areas of uncertainty in the drivers of documented trends, and suggest that a greater level of model complexity is needed in devising explanations for ecosystem change in the Southern Ocean. We suggest that our network approach to evaluating a recent and widely cited paradigm of change for the Antarctic region could be broadly applied in hypothesis testing for other regions and research fields. PMID:23405116

Meta-ecosystem dynamics and functioning on finite spatial networks

PubMed Central

Marleau, Justin N.; Guichard, Frédéric; Loreau, Michel

2014-01-01

The addition of spatial structure to ecological concepts and theories has spurred integration between sub-disciplines within ecology, including community and ecosystem ecology. However, the complexity of spatial models limits their implementation to idealized, regular landscapes. We present a model meta-ecosystem with finite and irregular spatial structure consisting of local nutrient–autotrophs–herbivores ecosystems connected through spatial flows of materials and organisms. We study the effect of spatial flows on stability and ecosystem functions, and provide simple metrics of connectivity that can predict these effects. Our results show that high rates of nutrient and herbivore movement can destabilize local ecosystem dynamics, leading to spatially heterogeneous equilibria or oscillations across the meta-ecosystem, with generally increased meta-ecosystem primary and secondary production. However, the onset and the spatial scale of these emergent dynamics depend heavily on the spatial structure of the meta-ecosystem and on the relative movement rate of the autotrophs. We show how this strong dependence on finite spatial structure eludes commonly used metrics of connectivity, but can be predicted by the eigenvalues and eigenvectors of the connectivity matrix that describe the spatial structure and scale. Our study indicates the need to consider finite-size ecosystems in meta-ecosystem theory. PMID:24403323

Linking big models to big data: efficient ecosystem model calibration through Bayesian model emulation

NASA Astrophysics Data System (ADS)

Fer, I.; Kelly, R.; Andrews, T.; Dietze, M.; Richardson, A. D.

2016-12-01

Our ability to forecast ecosystems is limited by how well we parameterize ecosystem models. Direct measurements for all model parameters are not always possible and inverse estimation of these parameters through Bayesian methods is computationally costly. A solution to computational challenges of Bayesian calibration is to approximate the posterior probability surface using a Gaussian Process that emulates the complex process-based model. Here we report the integration of this method within an ecoinformatics toolbox, Predictive Ecosystem Analyzer (PEcAn), and its application with two ecosystem models: SIPNET and ED2.1. SIPNET is a simple model, allowing application of MCMC methods both to the model itself and to its emulator. We used both approaches to assimilate flux (CO2 and latent heat), soil respiration, and soil carbon data from Bartlett Experimental Forest. This comparison showed that emulator is reliable in terms of convergence to the posterior distribution. A 10000-iteration MCMC analysis with SIPNET itself required more than two orders of magnitude greater computation time than an MCMC run of same length with its emulator. This difference would be greater for a more computationally demanding model. Validation of the emulator-calibrated SIPNET against both the assimilated data and out-of-sample data showed improved fit and reduced uncertainty around model predictions. We next applied the validated emulator method to the ED2, whose complexity precludes standard Bayesian data assimilation. We used the ED2 emulator to assimilate demographic data from a network of inventory plots. For validation of the calibrated ED2, we compared the model to results from Empirical Succession Mapping (ESM), a novel synthesis of successional patterns in Forest Inventory and Analysis data. Our results revealed that while the pre-assimilation ED2 formulation cannot capture the emergent demographic patterns from ESM analysis, constrained model parameters controlling demographic processes increased their agreement considerably.

Toward New Data and Information Management Solutions for Data-Intensive Ecological Research

ERIC Educational Resources Information Center

Laney, Christine Marie

2013-01-01

Ecosystem health is deteriorating in many parts of the world due to direct and indirect anthropogenic pressures. Generating accurate, useful, and impactful models of past, current, and future states of ecosystem structure and function is a complex endeavor that often requires vast amounts of data from multiple sources and knowledge from…

Amazon forest structure generates diurnal and seasonal variability in light utilization

Treesearch

Douglas C. Morton; Jeremy Rubio; Bruce D. Cook; Jean-Philippe Gastellu-Etchegorry; Marcos Longo; Hyeungu Choi; Maria Hunter; Michael Keller

2016-01-01

The complex three-dimensional (3-D) structure of tropical forests generates a diversity of light environments for canopy and understory trees. Understanding diurnal and seasonal changes in light availability is critical for interpreting measurements of net ecosystem exchange and improving ecosystem models. Here, we used the Discrete Anisotropic Radiative Transfer (DART...

Progress and challenges in coupled hydrodynamic-ecological estuarine modeling.

PubMed

Ganju, Neil K; Brush, Mark J; Rashleigh, Brenda; Aretxabaleta, Alfredo L; Del Barrio, Pilar; Grear, Jason S; Harris, Lora A; Lake, Samuel J; McCardell, Grant; O'Donnell, James; Ralston, David K; Signell, Richard P; Testa, Jeremy M; Vaudrey, Jamie M P

2016-03-01

Numerical modeling has emerged over the last several decades as a widely accepted tool for investigations in environmental sciences. In estuarine research, hydrodynamic and ecological models have moved along parallel tracks with regard to complexity, refinement, computational power, and incorporation of uncertainty. Coupled hydrodynamic-ecological models have been used to assess ecosystem processes and interactions, simulate future scenarios, and evaluate remedial actions in response to eutrophication, habitat loss, and freshwater diversion. The need to couple hydrodynamic and ecological models to address research and management questions is clear, because dynamic feedbacks between biotic and physical processes are critical interactions within ecosystems. In this review we present historical and modern perspectives on estuarine hydrodynamic and ecological modeling, consider model limitations, and address aspects of model linkage, skill assessment, and complexity. We discuss the balance between spatial and temporal resolution and present examples using different spatiotemporal scales. Finally, we recommend future lines of inquiry, approaches to balance complexity and uncertainty, and model transparency and utility. It is idealistic to think we can pursue a "theory of everything" for estuarine models, but recent advances suggest that models for both scientific investigations and management applications will continue to improve in terms of realism, precision, and accuracy.

Progress and challenges in coupled hydrodynamic-ecological estuarine modeling

USGS Publications Warehouse

Ganju, Neil K.; Brush, Mark J.; Rashleigh, Brenda; Aretxabaleta, Alfredo L.; del Barrio, Pilar; Grear, Jason S.; Harris, Lora A.; Lake, Samuel J.; McCardell, Grant; O'Donnell, James; Ralston, David K.; Signell, Richard P.; Testa, Jeremy; Vaudrey, Jamie M. P.

2016-01-01

Numerical modeling has emerged over the last several decades as a widely accepted tool for investigations in environmental sciences. In estuarine research, hydrodynamic and ecological models have moved along parallel tracks with regard to complexity, refinement, computational power, and incorporation of uncertainty. Coupled hydrodynamic-ecological models have been used to assess ecosystem processes and interactions, simulate future scenarios, and evaluate remedial actions in response to eutrophication, habitat loss, and freshwater diversion. The need to couple hydrodynamic and ecological models to address research and management questions is clear because dynamic feedbacks between biotic and physical processes are critical interactions within ecosystems. In this review, we present historical and modern perspectives on estuarine hydrodynamic and ecological modeling, consider model limitations, and address aspects of model linkage, skill assessment, and complexity. We discuss the balance between spatial and temporal resolution and present examples using different spatiotemporal scales. Finally, we recommend future lines of inquiry, approaches to balance complexity and uncertainty, and model transparency and utility. It is idealistic to think we can pursue a “theory of everything” for estuarine models, but recent advances suggest that models for both scientific investigations and management applications will continue to improve in terms of realism, precision, and accuracy.

Progress and challenges in coupled hydrodynamic-ecological estuarine modeling

PubMed Central

Ganju, Neil K.; Brush, Mark J.; Rashleigh, Brenda; Aretxabaleta, Alfredo L.; del Barrio, Pilar; Grear, Jason S.; Harris, Lora A.; Lake, Samuel J.; McCardell, Grant; O’Donnell, James; Ralston, David K.; Signell, Richard P.; Testa, Jeremy M.; Vaudrey, Jamie M.P.

2016-01-01

Numerical modeling has emerged over the last several decades as a widely accepted tool for investigations in environmental sciences. In estuarine research, hydrodynamic and ecological models have moved along parallel tracks with regard to complexity, refinement, computational power, and incorporation of uncertainty. Coupled hydrodynamic-ecological models have been used to assess ecosystem processes and interactions, simulate future scenarios, and evaluate remedial actions in response to eutrophication, habitat loss, and freshwater diversion. The need to couple hydrodynamic and ecological models to address research and management questions is clear, because dynamic feedbacks between biotic and physical processes are critical interactions within ecosystems. In this review we present historical and modern perspectives on estuarine hydrodynamic and ecological modeling, consider model limitations, and address aspects of model linkage, skill assessment, and complexity. We discuss the balance between spatial and temporal resolution and present examples using different spatiotemporal scales. Finally, we recommend future lines of inquiry, approaches to balance complexity and uncertainty, and model transparency and utility. It is idealistic to think we can pursue a “theory of everything” for estuarine models, but recent advances suggest that models for both scientific investigations and management applications will continue to improve in terms of realism, precision, and accuracy. PMID:27721675

Environmental metabarcoding reveals heterogeneous drivers of microbial eukaryote diversity in contrasting estuarine ecosystems

PubMed Central

Lallias, Delphine; Hiddink, Jan G; Fonseca, Vera G; Gaspar, John M; Sung, Way; Neill, Simon P; Barnes, Natalie; Ferrero, Tim; Hall, Neil; Lambshead, P John D; Packer, Margaret; Thomas, W Kelley; Creer, Simon

2015-01-01

Assessing how natural environmental drivers affect biodiversity underpins our understanding of the relationships between complex biotic and ecological factors in natural ecosystems. Of all ecosystems, anthropogenically important estuaries represent a ‘melting pot' of environmental stressors, typified by extreme salinity variations and associated biological complexity. Although existing models attempt to predict macroorganismal diversity over estuarine salinity gradients, attempts to model microbial biodiversity are limited for eukaryotes. Although diatoms commonly feature as bioindicator species, additional microbial eukaryotes represent a huge resource for assessing ecosystem health. Of these, meiofaunal communities may represent the optimal compromise between functional diversity that can be assessed using morphology and phenotype–environment interactions as compared with smaller life fractions. Here, using 454 Roche sequencing of the 18S nSSU barcode we investigate which of the local natural drivers are most strongly associated with microbial metazoan and sampled protist diversity across the full salinity gradient of the estuarine ecosystem. In order to investigate potential variation at the ecosystem scale, we compare two geographically proximate estuaries (Thames and Mersey, UK) with contrasting histories of anthropogenic stress. The data show that although community turnover is likely to be predictable, taxa are likely to respond to different environmental drivers and, in particular, hydrodynamics, salinity range and granulometry, according to varied life-history characteristics. At the ecosystem level, communities exhibited patterns of estuary-specific similarity within different salinity range habitats, highlighting the environmental sequencing biomonitoring potential of meiofauna, dispersal effects or both. PMID:25423027

Parameter optimization, sensitivity, and uncertainty analysis of an ecosystem model at a forest flux tower site in the United States

USGS Publications Warehouse

Wu, Yiping; Liu, Shuguang; Huang, Zhihong; Yan, Wende

2014-01-01

Ecosystem models are useful tools for understanding ecological processes and for sustainable management of resources. In biogeochemical field, numerical models have been widely used for investigating carbon dynamics under global changes from site to regional and global scales. However, it is still challenging to optimize parameters and estimate parameterization uncertainty for complex process-based models such as the Erosion Deposition Carbon Model (EDCM), a modified version of CENTURY, that consider carbon, water, and nutrient cycles of ecosystems. This study was designed to conduct the parameter identifiability, optimization, sensitivity, and uncertainty analysis of EDCM using our developed EDCM-Auto, which incorporated a comprehensive R package—Flexible Modeling Framework (FME) and the Shuffled Complex Evolution (SCE) algorithm. Using a forest flux tower site as a case study, we implemented a comprehensive modeling analysis involving nine parameters and four target variables (carbon and water fluxes) with their corresponding measurements based on the eddy covariance technique. The local sensitivity analysis shows that the plant production-related parameters (e.g., PPDF1 and PRDX) are most sensitive to the model cost function. Both SCE and FME are comparable and performed well in deriving the optimal parameter set with satisfactory simulations of target variables. Global sensitivity and uncertainty analysis indicate that the parameter uncertainty and the resulting output uncertainty can be quantified, and that the magnitude of parameter-uncertainty effects depends on variables and seasons. This study also demonstrates that using the cutting-edge R functions such as FME can be feasible and attractive for conducting comprehensive parameter analysis for ecosystem modeling.

Stabilization of Large Generalized Lotka-Volterra Foodwebs By Evolutionary Feedback

NASA Astrophysics Data System (ADS)

Ackland, G. J.; Gallagher, I. D.

2004-10-01

Conventional ecological models show that complexity destabilizes foodwebs, suggesting that foodwebs should have neither large numbers of species nor a large number of interactions. However, in nature the opposite appears to be the case. Here we show that if the interactions between species are allowed to evolve within a generalized Lotka-Volterra model such stabilizing feedbacks and weak interactions emerge automatically. Moreover, we show that trophic levels also emerge spontaneously from the evolutionary approach, and the efficiency of the unperturbed ecosystem increases with time. The key to stability in large foodwebs appears to arise not from complexity perse but from evolution at the level of the ecosystem which favors stabilizing (negative) feedbacks.

Stabilization of large generalized Lotka-Volterra foodwebs by evolutionary feedback.

PubMed

Ackland, G J; Gallagher, I D

2004-10-08

Conventional ecological models show that complexity destabilizes foodwebs, suggesting that foodwebs should have neither large numbers of species nor a large number of interactions. However, in nature the opposite appears to be the case. Here we show that if the interactions between species are allowed to evolve within a generalized Lotka-Volterra model such stabilizing feedbacks and weak interactions emerge automatically. Moreover, we show that trophic levels also emerge spontaneously from the evolutionary approach, and the efficiency of the unperturbed ecosystem increases with time. The key to stability in large foodwebs appears to arise not from complexity per se but from evolution at the level of the ecosystem which favors stabilizing (negative) feedbacks.

Panarchy: Theory and Application

EPA Science Inventory

The concept of panarchy was introduced by Gunderson et al. (1995) and refined by Gunderson and Holling (2002) as a heuristic model to help explain complex changes in ecosystem processes and structures within and across scales of organization. The concept takes a complex systems a...

Identity effects dominate the impacts of multiple species extinctions on the functioning of complex food webs.

PubMed

Harvey, Eric; Séguin, Annie; Nozais, Christian; Archambault, Philippe; Gravel, Dominique

2013-01-01

Understanding the impacts of species extinctions on the functioning of food webs is a challenging task because of the complexity of ecological interactions. We report the impacts of experimental species extinctions on the functioning of two food webs of freshwater and marine systems. We used a linear model to partition the variance among the multiple components of the diversity effect (linear group richness, nonlinear group richness, and identity). The identity of each functional group was the best explaining variable of ecosystem functioning for both systems. We assessed the contribution of each functional group in multifunctional space and found that, although the effect of functional group varied across ecosystem functions, some functional groups shared common effects on functions. This study is the first experimental demonstration that functional identity dominates the effects of extinctions on ecosystem functioning, suggesting that generalizations are possible despite the inherent complexity of interactions.

Flux frequency analysis of seasonally dry ecosystem fluxes in two unique biomes of Sonora Mexico

NASA Astrophysics Data System (ADS)

Verduzco, V. S.; Yepez, E. A.; Robles-Morua, A.; Garatuza, J.; Rodriguez, J. C.; Watts, C.

2013-05-01

Complex dynamics from the interactions of ecosystems processes makes difficult to model the behavior of ecosystems fluxes of carbon and water in response to the variation of environmental and biological drivers. Although process oriented ecosystem models are critical tools for studying land-atmosphere fluxes, its validity depends on the appropriate parameterization of equations describing temporal and spatial changes of model state variables and their interactions. This constraint often leads to discrepancies between model simulations and observed data that reduce models reliability especially in arid and semiarid ecosystems. In the semiarid north western Mexico, ecosystem processes are fundamentally controlled by the seasonality of water and the intermittence of rain pulses which are conditions that require calibration of specific fitting functions to describe the response of ecosystem variables (i.e. NEE, GPP, ET, respiration) to these wetting and drying periods. The goal is to find functions that describe the magnitude of ecosystem fluxes during individual rain pulses and the seasonality of the ecosystem. Relaying on five years of eddy covariance flux data of a tropical dry forest and a subtropical shrubland we present a flux frequency analysis that describe the variation of net ecosystem exchange (NEE) of CO2 to highlight the relevance of pulse driven dynamics controlling this flux. Preliminary results of flux frequency analysis of NEE indicate that these ecosystems are strongly controlled by the frequency distribution of rain. Also, the output of fitting functions for NEE, GPP, ET and respiration using semi-empirical functions applied at specific rain pulses compared with season-long statistically generated simulations do not agree. Seasonality and the intrinsic nature of individual pulses have different effects on ecosystem flux responses. This suggests that relationships between the nature of seasonality and individual pulses can help improve the parameterization of process oriented ecosystem models.

Integrating research on ecohydrology and land use change with land use management

NASA Astrophysics Data System (ADS)

Bass, Brad; Byers, Ralph E.; Lister, Nina-Marie

1998-10-01

One objective of the International Geosphere-Biosphere Programme is to provide a scientific basis for sustainable development policies. Land use change and ecohydrology are important components of this scientific basis, but predicting change is difficult because of the scale and complexity of the interactions between non-linear ecohydrological and socio-economic processes at different spatial and temporal scales. A systems framework, the Ecosystem Approach, has been developed to conceptualize these interactions for the purpose of providing information for sustainable development policy. The Ecosystem Approach combines the dynamics of the Holling figure-eight model - a conceptual model of dynamics that stresses discontinuous change and destruction as an internal property of the system - and the properties of self-organizing systems with the socio political aspects of decision making.The Ecosystem Approach highlights the problems of managing change in complex systems when that change may involve unpredictable shifts to a different attractor. Although there are methods available to detect the occurrence of such shifts, both detection and modelling are complicated by the presence of semi-stable attractors. When a model or an ecosystem is on a semi-stable attractor, it may appear to remain stable for an extended period prior to changing as a consequence of inherent instabilities. When the shift to a new attractor occurs, it is quite sudden and unpredictable. A technical discussion on prediction under conditions of semi-stability and chaos is included because it enhances our understanding of the role of surprise in ecosystems, as well as the utility of simulation models.The principles of the Ecosystem Approach are derived from the theoretical discussion and an example of a land use policy in the Huron Natural Area in south-western Ontario. These principles provide a clear role for scientific research, and particularly simulation modelling, within the larger context of policy and land use management.

A comparative assessment of tools for ecosystem services quantification and valuation

USGS Publications Warehouse

Bagstad, Kenneth J.; Semmens, Darius; Waage, Sissel; Winthrop, Robert

2013-01-01

To enter widespread use, ecosystem service assessments need to be quantifiable, replicable, credible, flexible, and affordable. With recent growth in the field of ecosystem services, a variety of decision-support tools has emerged to support more systematic ecosystem services assessment. Despite the growing complexity of the tool landscape, thorough reviews of tools for identifying, assessing, modeling and in some cases monetarily valuing ecosystem services have generally been lacking. In this study, we describe 17 ecosystem services tools and rate their performance against eight evaluative criteria that gauge their readiness for widespread application in public- and private-sector decision making. We describe each of the tools′ intended uses, services modeled, analytical approaches, data requirements, and outputs, as well time requirements to run seven tools in a first comparative concurrent application of multiple tools to a common location – the San Pedro River watershed in southeast Arizona, USA, and northern Sonora, Mexico. Based on this work, we offer conclusions about these tools′ current ‘readiness’ for widespread application within both public- and private-sector decision making processes. Finally, we describe potential pathways forward to reduce the resource requirements for running ecosystem services models, which are essential to facilitate their more widespread use in environmental decision making.

Modeling wildfire regimes in forest landscapes: abstracting a complex reality

Treesearch

Donald McKenzie; Ajith H. Perera

2015-01-01

Fire is a natural disturbance that is nearly ubiquitous in terrestrial ecosystems. The capacity to burn exists virtually wherever vegetation grows. In some forested landscapes, fi re is a principal driver of rapid ecosystem change, resetting succession ( McKenzie et al. 1996a ) and changing wildlife habitat (Cushman et al. 2011 ), hydrology ( Feikema et al. 2013 ),...

The Role of Model Complexity in Determining Patterns of Chlorophyll Variability in the Coastal Northwest North Atlantic

NASA Astrophysics Data System (ADS)

Kuhn, A. M.; Fennel, K.; Bianucci, L.

2016-02-01

A key feature of the North Atlantic Ocean's biological dynamics is the annual phytoplankton spring bloom. In the region comprising the continental shelf and adjacent deep ocean of the northwest North Atlantic, we identified two patterns of bloom development: 1) locations with cold temperatures and deep winter mixed layers, where the spring bloom peaks around April and the annual chlorophyll cycle has a large amplitude, and 2) locations with warmer temperatures and shallow winter mixed layers, where the spring bloom peaks earlier in the year, sometimes indiscernible from the fall bloom. These patterns result from a combination of limiting environmental factors and interactions among planktonic groups with different optimal requirements. Simple models that represent the ecosystem with a single phytoplankton (P) and a single zooplankton (Z) group are challenged to reproduce these ecological interactions. Here we investigate the effect that added complexity has on determining spatio-temporal chlorophyll. We compare two ecosystem models, one that contains one P and one Z group, and one with two P and three Z groups. We consider three types of changes in complexity: 1) added dependencies among variables (e.g., temperature dependent rates), 2) modified structural pathways, and 3) added pathways. Subsets of the most sensitive parameters are optimized in each model to replicate observations in the region. For computational efficiency, the parameter optimization is performed using 1D surrogates of a 3D model. We evaluate how model complexity affects model skill, and whether the optimized parameter sets found for each model modify the interpretation of ecosystem functioning. Spatial differences in the parameter sets that best represent different areas hint at the existence of different ecological communities or at physical-biological interactions that are not represented in the simplest model. Our methodology emphasizes the combined use of observations, 1D models to help identifying patterns, and 3D models able to simulate the environment modre realistically, as a means to acquire predictive understanding of the ocean's ecology.

Driving terrestrial ecosystem models from space

NASA Technical Reports Server (NTRS)

Waring, R. H.

1993-01-01

Regional air pollution, land-use conversion, and projected climate change all affect ecosystem processes at large scales. Changes in vegetation cover and growth dynamics can impact the functioning of ecosystems, carbon fluxes, and climate. As a result, there is a need to assess and monitor vegetation structure and function comprehensively at regional to global scales. To provide a test of our present understanding of how ecosystems operate at large scales we can compare model predictions of CO2, O2, and methane exchange with the atmosphere against regional measurements of interannual variation in the atmospheric concentration of these gases. Recent advances in remote sensing of the Earth's surface are beginning to provide methods for estimating important ecosystem variables at large scales. Ecologists attempting to generalize across landscapes have made extensive use of models and remote sensing technology. The success of such ventures is dependent on merging insights and expertise from two distinct fields. Ecologists must provide the understanding of how well models emulate important biological variables and their interactions; experts in remote sensing must provide the biophysical interpretation of complex optical reflectance and radar backscatter data.

Implications of tristability in pattern-forming ecosystems

NASA Astrophysics Data System (ADS)

Zelnik, Yuval R.; Gandhi, Punit; Knobloch, Edgar; Meron, Ehud

2018-03-01

Many ecosystems show both self-organized spatial patterns and multistability of possible states. The combination of these two phenomena in different forms has a significant impact on the behavior of ecosystems in changing environments. One notable case is connected to tristability of two distinct uniform states together with patterned states, which has recently been found in model studies of dryland ecosystems. Using a simple model, we determine the extent of tristability in parameter space, explore its effects on the system dynamics, and consider its implications for state transitions or regime shifts. We analyze the bifurcation structure of model solutions that describe uniform states, periodic patterns, and hybrid states between the former two. We map out the parameter space where these states exist, and note how the different states interact with each other. We further focus on two special implications with ecological significance, breakdown of the snaking range and complex fronts. We find that the organization of the hybrid states within a homoclinic snaking structure breaks down as it meets a Maxwell point where simple fronts are stationary. We also discover a new series of complex fronts between the uniform states, each with its own velocity. We conclude with a brief discussion of the significance of these findings for the dynamics of regime shifts and their potential control.

How models can support ecosystem-based management of coral reefs

NASA Astrophysics Data System (ADS)

Weijerman, Mariska; Fulton, Elizabeth A.; Janssen, Annette B. G.; Kuiper, Jan J.; Leemans, Rik; Robson, Barbara J.; van de Leemput, Ingrid A.; Mooij, Wolf M.

2015-11-01

Despite the importance of coral reef ecosystems to the social and economic welfare of coastal communities, the condition of these marine ecosystems have generally degraded over the past decades. With an increased knowledge of coral reef ecosystem processes and a rise in computer power, dynamic models are useful tools in assessing the synergistic effects of local and global stressors on ecosystem functions. We review representative approaches for dynamically modeling coral reef ecosystems and categorize them as minimal, intermediate and complex models. The categorization was based on the leading principle for model development and their level of realism and process detail. This review aims to improve the knowledge of concurrent approaches in coral reef ecosystem modeling and highlights the importance of choosing an appropriate approach based on the type of question(s) to be answered. We contend that minimal and intermediate models are generally valuable tools to assess the response of key states to main stressors and, hence, contribute to understanding ecological surprises. As has been shown in freshwater resources management, insight into these conceptual relations profoundly influences how natural resource managers perceive their systems and how they manage ecosystem recovery. We argue that adaptive resource management requires integrated thinking and decision support, which demands a diversity of modeling approaches. Integration can be achieved through complimentary use of models or through integrated models that systemically combine all relevant aspects in one model. Such whole-of-system models can be useful tools for quantitatively evaluating scenarios. These models allow an assessment of the interactive effects of multiple stressors on various, potentially conflicting, management objectives. All models simplify reality and, as such, have their weaknesses. While minimal models lack multidimensionality, system models are likely difficult to interpret as they require many efforts to decipher the numerous interactions and feedback loops. Given the breadth of questions to be tackled when dealing with coral reefs, the best practice approach uses multiple model types and thus benefits from the strength of different models types.

Same pattern, different mechanism: Locking onto the role of key species in seafloor ecosystem process

PubMed Central

Woodin, Sarah Ann; Volkenborn, Nils; Pilditch, Conrad A.; Lohrer, Andrew M.; Wethey, David S.; Hewitt, Judi E.; Thrush, Simon F.

2016-01-01

Seafloor biodiversity is a key mediator of ecosystem functioning, but its role is often excluded from global budgets or simplified to black boxes in models. New techniques allow quantification of the behavior of animals living below the sediment surface and assessment of the ecosystem consequences of complex interactions, yielding a better understanding of the role of seafloor animals in affecting key processes like primary productivity. Combining predictions based on natural history, behavior of key benthic species and environmental context allow assessment of differences in functioning and process, even when the measured ecosystem property in different systems is similar. Data from three sedimentary systems in New Zealand illustrate this. Analysis of the behaviors of the infaunal ecosystem engineers in each system revealed three very different mechanisms driving ecosystem function: density and excretion, sediment turnover and surface rugosity, and hydraulic activities and porewater bioadvection. Integrative metrics of ecosystem function in some cases differentiate among the systems (gross primary production) and in others do not (photosynthetic efficiency). Analyses based on behaviors and activities revealed important ecosystem functional differences and can dramatically improve our ability to model the impact of stressors on ecosystem and global processes. PMID:27230562

Same pattern, different mechanism: Locking onto the role of key species in seafloor ecosystem process.

PubMed

Woodin, Sarah Ann; Volkenborn, Nils; Pilditch, Conrad A; Lohrer, Andrew M; Wethey, David S; Hewitt, Judi E; Thrush, Simon F

2016-05-27

Seafloor biodiversity is a key mediator of ecosystem functioning, but its role is often excluded from global budgets or simplified to black boxes in models. New techniques allow quantification of the behavior of animals living below the sediment surface and assessment of the ecosystem consequences of complex interactions, yielding a better understanding of the role of seafloor animals in affecting key processes like primary productivity. Combining predictions based on natural history, behavior of key benthic species and environmental context allow assessment of differences in functioning and process, even when the measured ecosystem property in different systems is similar. Data from three sedimentary systems in New Zealand illustrate this. Analysis of the behaviors of the infaunal ecosystem engineers in each system revealed three very different mechanisms driving ecosystem function: density and excretion, sediment turnover and surface rugosity, and hydraulic activities and porewater bioadvection. Integrative metrics of ecosystem function in some cases differentiate among the systems (gross primary production) and in others do not (photosynthetic efficiency). Analyses based on behaviors and activities revealed important ecosystem functional differences and can dramatically improve our ability to model the impact of stressors on ecosystem and global processes.

Pattern-oriented modeling of agent-based complex systems: Lessons from ecology

USGS Publications Warehouse

Grimm, Volker; Revilla, Eloy; Berger, Uta; Jeltsch, Florian; Mooij, Wolf M.; Railsback, Steven F.; Thulke, Hans-Hermann; Weiner, Jacob; Wiegand, Thorsten; DeAngelis, Donald L.

2005-01-01

Agent-based complex systems are dynamic networks of many interacting agents; examples include ecosystems, financial markets, and cities. The search for general principles underlying the internal organization of such systems often uses bottom-up simulation models such as cellular automata and agent-based models. No general framework for designing, testing, and analyzing bottom-up models has yet been established, but recent advances in ecological modeling have come together in a general strategy we call pattern-oriented modeling. This strategy provides a unifying framework for decoding the internal organization of agent-based complex systems and may lead toward unifying algorithmic theories of the relation between adaptive behavior and system complexity.

Pattern-Oriented Modeling of Agent-Based Complex Systems: Lessons from Ecology

NASA Astrophysics Data System (ADS)

Grimm, Volker; Revilla, Eloy; Berger, Uta; Jeltsch, Florian; Mooij, Wolf M.; Railsback, Steven F.; Thulke, Hans-Hermann; Weiner, Jacob; Wiegand, Thorsten; DeAngelis, Donald L.

2005-11-01

Agent-based complex systems are dynamic networks of many interacting agents; examples include ecosystems, financial markets, and cities. The search for general principles underlying the internal organization of such systems often uses bottom-up simulation models such as cellular automata and agent-based models. No general framework for designing, testing, and analyzing bottom-up models has yet been established, but recent advances in ecological modeling have come together in a general strategy we call pattern-oriented modeling. This strategy provides a unifying framework for decoding the internal organization of agent-based complex systems and may lead toward unifying algorithmic theories of the relation between adaptive behavior and system complexity.

An original model of the northern Gulf of Mexico using Ecopath with Ecosim and its implications for the effects of fishing on ecosystem structure and maturity

NASA Astrophysics Data System (ADS)

Geers, T. M.; Pikitch, E. K.; Frisk, M. G.

2016-07-01

The Gulf of Mexico (GoM) is a valuable ecosystem both socially and economically, and fisheries contribute substantially to this value. Gulf menhaden, Brevoortia patronus, support the largest fishery in the Gulf (by weight) and provide forage for marine mammals, seabirds and commercially and recreationally important fish species. Understanding the complex interactions among multiple fisheries and myriad unfished species requires tools different from those used in traditional single-species management. One such tool, Ecopath with Ecosim (EwE) is increasingly being used to construct food web models of aquatic ecosystems and to evaluate fisheries management options within a broader, ecosystem context. Here, an EwE model was developed to examine the impact of Gulf fisheries on ecosystem structure and maturity. This model builds on previously published EwE models of the GoM, and is tailored to the range and habitat of Gulf menhaden. The model presented here consists of 47 functional groups, including 4 seabird groups, 1 marine mammal group, 3 elasmobranch groups, 26 bony fish groups, 9 invertebrate groups, 3 primary producer groups and 1 detritus group. A number of different management scenarios for Gulf fisheries were modeled and the results were evaluated in terms of impacts on ecosystem maturity and development. The results of the model simulations indicated that the northern Gulf of Mexico is in an immature state (sensuOdum, 1969). Management scenarios that increased fishing pressure over time consistently resulted in a decrease in the maturity indices. In particular, we found that Gulf menhaden, as a key forage fish in the ecosystem, plays a substantial role in the structure and functioning of the ecosystem.

Engineering Ecosystems and Synthetic Ecologies#

PubMed Central

Mee, Michael T; Wang, Harris H

2012-01-01

Microbial ecosystems play an important role in nature. Engineering these systems for industrial, medical, or biotechnological purposes are important pursuits for synthetic biologists and biological engineers moving forward. Here, we provide a review of recent progress in engineering natural and synthetic microbial ecosystems. We highlight important forward engineering design principles, theoretical and quantitative models, new experimental and manipulation tools, and possible applications of microbial ecosystem engineering. We argue that simply engineering individual microbes will lead to fragile homogenous populations that are difficult to sustain, especially in highly heterogeneous and unpredictable environments. Instead, engineered microbial ecosystems are likely to be more robust and able to achieve complex tasks at the spatial and temporal resolution needed for truly programmable biology. PMID:22722235

Quantifying uncertainty in high-resolution coupled hydrodynamic-ecosystem models

NASA Astrophysics Data System (ADS)

Allen, J. I.; Somerfield, P. J.; Gilbert, F. J.

2007-01-01

Marine ecosystem models are becoming increasingly complex and sophisticated, and are being used to estimate the effects of future changes in the earth system with a view to informing important policy decisions. Despite their potential importance, far too little attention has been, and is generally, paid to model errors and the extent to which model outputs actually relate to real-world processes. With the increasing complexity of the models themselves comes an increasing complexity among model results. If we are to develop useful modelling tools for the marine environment we need to be able to understand and quantify the uncertainties inherent in the simulations. Analysing errors within highly multivariate model outputs, and relating them to even more complex and multivariate observational data, are not trivial tasks. Here we describe the application of a series of techniques, including a 2-stage self-organising map (SOM), non-parametric multivariate analysis, and error statistics, to a complex spatio-temporal model run for the period 1988-1989 in the Southern North Sea, coinciding with the North Sea Project which collected a wealth of observational data. We use model output, large spatio-temporally resolved data sets and a combination of methodologies (SOM, MDS, uncertainty metrics) to simplify the problem and to provide tractable information on model performance. The use of a SOM as a clustering tool allows us to simplify the dimensions of the problem while the use of MDS on independent data grouped according to the SOM classification allows us to validate the SOM. The combination of classification and uncertainty metrics allows us to pinpoint the variables and associated processes which require attention in each region. We recommend the use of this combination of techniques for simplifying complex comparisons of model outputs with real data, and analysis of error distributions.

Studies on Interpretive Structural Model for Forest Ecosystem Management Decision-Making

NASA Astrophysics Data System (ADS)

Liu, Suqing; Gao, Xiumei; Zen, Qunying; Zhou, Yuanman; Huang, Yuequn; Han, Weidong; Li, Linfeng; Li, Jiping; Pu, Yingshan

Characterized by their openness, complexity and large scale, forest ecosystems interweave themselves with social system, economic system and other natural ecosystems, thus complicating both their researches and management decision-making. According to the theories of sustainable development, hierarchy-competence levels, cybernetics and feedback, 25 factors have been chosen from human society, economy and nature that affect forest ecosystem management so that they are systematically analyzed via developing an interpretive structural model (ISM) to reveal their relationships and positions in the forest ecosystem management. The ISM consists of 7 layers with the 3 objectives for ecosystem management being the top layer (the seventh layer). The ratio between agricultural production value and industrial production value as the bases of management decision-making in forest ecosystems becomes the first layer at the bottom because it has great impacts on the values of society and the development trends of forestry, while the factors of climatic environments, intensive management extent, management measures, input-output ratio as well as landscape and productivity are arranged from the second to sixth layers respectively.

Self-organized instability in complex ecosystems.

PubMed

Solé, Ricard V; Alonso, David; McKane, Alan

2002-05-29

Why are some ecosystems so rich, yet contain so many rare species? High species diversity, together with rarity, is a general trend in neotropical forests and coral reefs. However, the origin of such diversity and the consequences of food web complexity in both species abundances and temporal fluctuations are not well understood. Several regularities are observed in complex, multispecies ecosystems that suggest that these ecologies might be organized close to points of instability. We explore, in greater depth, a recent stochastic model of population dynamics that is shown to reproduce: (i) the scaling law linking species number and connectivity; (ii) the observed distributions of species abundance reported from field studies (showing long tails and thus a predominance of rare species); (iii) the complex fluctuations displayed by natural communities (including chaotic dynamics); and (iv) the species-area relations displayed by rainforest plots. It is conjectured that the conflict between the natural tendency towards higher diversity due to immigration, and the ecosystem level constraints derived from an increasing number of links, leaves the system poised at a critical boundary separating stable from unstable communities, where large fluctuations are expected to occur. We suggest that the patterns displayed by species-rich communities, including rarity, would result from such a spontaneous tendency towards instability.

Pajarito Aerosol Couplings to Ecosystems (PACE) Field Campaign Report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dubey, M

Laboratory (LANL) worked on the Pajarito Aerosol Couplings to Ecosystems (PACE) intensive operational period (IOP). PACE’s primary goal was to demonstrate routine Mobile Aerosol Observing System (MAOS) field operations and improve instrumental and operational performance. LANL operated the instruments efficiently and effectively with remote guidance by the instrument mentors. This was the first time a complex suite of instruments had been operated under the ARM model and it proved to be a very successful and cost-effective model to build upon.

Combined global change effects on ecosystem processes in nine U.S

Treesearch

Melannie D. Hartman; Jill S. Baron; Holly A. Ewing; Kathleen C. Weathers; Chelcy Miniat

2014-01-01

Concurrent changes in climate, atmospheric nitrogen (N) deposition, and increasing levels of atmospheric carbon dioxide (CO2) affect ecosystems in complex ways. The DayCent-Chem model was used to investigate the combined effects of these human-caused drivers of change over the period 1980–2075 at seven forested montane and two alpine watersheds...

A protocol for the intercomparison of marine fishery and ecosystem models: Fish-MIP v1.0

NASA Astrophysics Data System (ADS)

Tittensor, Derek P.; Eddy, Tyler D.; Lotze, Heike K.; Galbraith, Eric D.; Cheung, William; Barange, Manuel; Blanchard, Julia L.; Bopp, Laurent; Bryndum-Buchholz, Andrea; Büchner, Matthias; Bulman, Catherine; Carozza, David A.; Christensen, Villy; Coll, Marta; Dunne, John P.; Fernandes, Jose A.; Fulton, Elizabeth A.; Hobday, Alistair J.; Huber, Veronika; Jennings, Simon; Jones, Miranda; Lehodey, Patrick; Link, Jason S.; Mackinson, Steve; Maury, Olivier; Niiranen, Susa; Oliveros-Ramos, Ricardo; Roy, Tilla; Schewe, Jacob; Shin, Yunne-Jai; Silva, Tiago; Stock, Charles A.; Steenbeek, Jeroen; Underwood, Philip J.; Volkholz, Jan; Watson, James R.; Walker, Nicola D.

2018-04-01

Model intercomparison studies in the climate and Earth sciences communities have been crucial to building credibility and coherence for future projections. They have quantified variability among models, spurred model development, contrasted within- and among-model uncertainty, assessed model fits to historical data, and provided ensemble projections of future change under specified scenarios. Given the speed and magnitude of anthropogenic change in the marine environment and the consequent effects on food security, biodiversity, marine industries, and society, the time is ripe for similar comparisons among models of fisheries and marine ecosystems. Here, we describe the Fisheries and Marine Ecosystem Model Intercomparison Project protocol version 1.0 (Fish-MIP v1.0), part of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP), which is a cross-sectoral network of climate impact modellers. Given the complexity of the marine ecosystem, this class of models has substantial heterogeneity of purpose, scope, theoretical underpinning, processes considered, parameterizations, resolution (grain size), and spatial extent. This heterogeneity reflects the lack of a unified understanding of the marine ecosystem and implies that the assemblage of all models is more likely to include a greater number of relevant processes than any single model. The current Fish-MIP protocol is designed to allow these heterogeneous models to be forced with common Earth System Model (ESM) Coupled Model Intercomparison Project Phase 5 (CMIP5) outputs under prescribed scenarios for historic (from the 1950s) and future (to 2100) time periods; it will be adapted to CMIP phase 6 (CMIP6) in future iterations. It also describes a standardized set of outputs for each participating Fish-MIP model to produce. This enables the broad characterization of differences between and uncertainties within models and projections when assessing climate and fisheries impacts on marine ecosystems and the services they provide. The systematic generation, collation, and comparison of results from Fish-MIP will inform an understanding of the range of plausible changes in marine ecosystems and improve our capacity to define and convey the strengths and weaknesses of model-based advice on future states of marine ecosystems and fisheries. Ultimately, Fish-MIP represents a step towards bringing together the marine ecosystem modelling community to produce consistent ensemble medium- and long-term projections of marine ecosystems.

Urban watershed modeling in Seattle, Washington using VELMA – a spatially explicit ecohydrological watershed model

EPA Science Inventory

Urban watersheds are notoriously difficult to model due to their complex, small-scale combinations of landscape and land use characteristics including impervious surfaces that ultimately affect the hydrologic system. We utilized EPA’s Visualizing Ecosystem Land Management A...

PICUS v1.6 - enhancing the water cycle within a hybrid ecosystem model to assess the provision of drinking water in a changing climate

NASA Astrophysics Data System (ADS)

Schimmel, A.; Rammer, W.; Lexer, M. J.

2012-04-01

The PICUS model is a hybrid ecosystem model which is based on a 3D patch model and a physiological stand level production model. The model includes, among others, a submodel of bark beetle disturbances in Norway spruce and a management module allowing any silvicultural treatment to be mimicked realistically. It has been tested intensively for its ability to realistically reproduce tree growth and stand dynamics in complex structured mixed and mono-species temperate forest ecosystems. In several applications the models capacity to generate relevant forest related attributes which were subsequently fed into indicator systems to assess sustainable forest management under current and future climatic conditions has been proven. However, the relatively coarse monthly temporal resolution of the driving climate data as well as the process resolution of the major water relations within the simulated ecosystem hampered the inclusion of more detailed physiologically based assessments of drought conditions and water provisioning ecosystem services. In this contribution we present the improved model version PICUS v1.6 focusing on the newly implemented logic for the water cycle calculations. Transpiration, evaporation from leave surfaces and the forest floor, snow cover and snow melt as well as soil water dynamics in several soil horizons are covered. In enhancing the model overarching goal was to retain the large-scale applicability by keeping the input requirements to a minimum while improving the physiological foundation of water related ecosystem processes. The new model version is tested against empirical time series data. Future model applications are outlined.

Variational methods to estimate terrestrial ecosystem model parameters

NASA Astrophysics Data System (ADS)

Delahaies, Sylvain; Roulstone, Ian

2016-04-01

Carbon is at the basis of the chemistry of life. Its ubiquity in the Earth system is the result of complex recycling processes. Present in the atmosphere in the form of carbon dioxide it is adsorbed by marine and terrestrial ecosystems and stored within living biomass and decaying organic matter. Then soil chemistry and a non negligible amount of time transform the dead matter into fossil fuels. Throughout this cycle, carbon dioxide is released in the atmosphere through respiration and combustion of fossils fuels. Model-data fusion techniques allow us to combine our understanding of these complex processes with an ever-growing amount of observational data to help improving models and predictions. The data assimilation linked ecosystem carbon (DALEC) model is a simple box model simulating the carbon budget allocation for terrestrial ecosystems. Over the last decade several studies have demonstrated the relative merit of various inverse modelling strategies (MCMC, ENKF, 4DVAR) to estimate model parameters and initial carbon stocks for DALEC and to quantify the uncertainty in the predictions. Despite its simplicity, DALEC represents the basic processes at the heart of more sophisticated models of the carbon cycle. Using adjoint based methods we study inverse problems for DALEC with various data streams (8 days MODIS LAI, monthly MODIS LAI, NEE). The framework of constraint optimization allows us to incorporate ecological common sense into the variational framework. We use resolution matrices to study the nature of the inverse problems and to obtain data importance and information content for the different type of data. We study how varying the time step affect the solutions, and we show how "spin up" naturally improves the conditioning of the inverse problems.

Divergent predictions of carbon storage between two global land models: attribution of the causes through traceability analysis

NASA Astrophysics Data System (ADS)

Rafique, Rashid; Xia, Jianyang; Hararuk, Oleksandra; Asrar, Ghassem R.; Leng, Guoyong; Wang, Yingping; Luo, Yiqi

2016-07-01

Representations of the terrestrial carbon cycle in land models are becoming increasingly complex. It is crucial to develop approaches for critical assessment of the complex model properties in order to understand key factors contributing to models' performance. In this study, we applied a traceability analysis which decomposes carbon cycle models into traceable components, for two global land models (CABLE and CLM-CASA') to diagnose the causes of their differences in simulating ecosystem carbon storage capacity. Driven with similar forcing data, CLM-CASA' predicted ˜ 31 % larger carbon storage capacity than CABLE. Since ecosystem carbon storage capacity is a product of net primary productivity (NPP) and ecosystem residence time (τE), the predicted difference in the storage capacity between the two models results from differences in either NPP or τE or both. Our analysis showed that CLM-CASA' simulated 37 % higher NPP than CABLE. On the other hand, τE, which was a function of the baseline carbon residence time (τ'E) and environmental effect on carbon residence time, was on average 11 years longer in CABLE than CLM-CASA'. This difference in τE was mainly caused by longer τ'E of woody biomass (23 vs. 14 years in CLM-CASA'), and higher proportion of NPP allocated to woody biomass (23 vs. 16 %). Differences in environmental effects on carbon residence times had smaller influences on differences in ecosystem carbon storage capacities compared to differences in NPP and τ'E. Overall, the traceability analysis showed that the major causes of different carbon storage estimations were found to be parameters setting related to carbon input and baseline carbon residence times between two models.

Divergent predictions of carbon storage between two global land models: Attribution of the causes through traceability analysis

DOE PAGES

Rafique, Rashid; Xia, Jianyang; Hararuk, Oleksandra; ...

2016-07-29

Representations of the terrestrial carbon cycle in land models are becoming increasingly complex. It is crucial to develop approaches for critical assessment of the complex model properties in order to understand key factors contributing to models' performance. In this study, we applied a traceability analysis which decomposes carbon cycle models into traceable components, for two global land models (CABLE and CLM-CASA') to diagnose the causes of their differences in simulating ecosystem carbon storage capacity. Driven with similar forcing data, CLM-CASA' predicted – 31 % larger carbon storage capacity than CABLE. Since ecosystem carbon storage capacity is a product of net primary productivitymore » (NPP) and ecosystem residence time ( τ E), the predicted difference in the storage capacity between the two models results from differences in either NPP or τ E or both. Our analysis showed that CLM-CASA'simulated 37 % higher NPP than CABLE. On the other hand, τ E, which was a function of the baseline carbon residence time ( τ' E) and environmental effect on carbon residence time, was on average 11 years longer in CABLE than CLM-CASA'. This difference in τ E was mainly caused by longer τ' E of woody biomass (23 vs. 14 years in CLM-CASA'), and higher proportion of NPP allocated to woody biomass (23 vs. 16 %). Differences in environmental effects on carbon residence times had smaller influences on differences in ecosystem carbon storage capacities compared to differences in NPP and τ' E. Altogether, the traceability analysis showed that the major causes of different carbon storage estimations were found to be parameters setting related to carbon input and baseline carbon residence times between two models.« less

Divergent predictions of carbon storage between two global land models: Attribution of the causes through traceability analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rafique, Rashid; Xia, Jianyang; Hararuk, Oleksandra

Representations of the terrestrial carbon cycle in land models are becoming increasingly complex. It is crucial to develop approaches for critical assessment of the complex model properties in order to understand key factors contributing to models' performance. In this study, we applied a traceability analysis which decomposes carbon cycle models into traceable components, for two global land models (CABLE and CLM-CASA') to diagnose the causes of their differences in simulating ecosystem carbon storage capacity. Driven with similar forcing data, CLM-CASA' predicted – 31 % larger carbon storage capacity than CABLE. Since ecosystem carbon storage capacity is a product of net primary productivitymore » (NPP) and ecosystem residence time ( τ E), the predicted difference in the storage capacity between the two models results from differences in either NPP or τ E or both. Our analysis showed that CLM-CASA'simulated 37 % higher NPP than CABLE. On the other hand, τ E, which was a function of the baseline carbon residence time ( τ' E) and environmental effect on carbon residence time, was on average 11 years longer in CABLE than CLM-CASA'. This difference in τ E was mainly caused by longer τ' E of woody biomass (23 vs. 14 years in CLM-CASA'), and higher proportion of NPP allocated to woody biomass (23 vs. 16 %). Differences in environmental effects on carbon residence times had smaller influences on differences in ecosystem carbon storage capacities compared to differences in NPP and τ' E. Altogether, the traceability analysis showed that the major causes of different carbon storage estimations were found to be parameters setting related to carbon input and baseline carbon residence times between two models.« less

Conceptualizing and Communicating River Restoration

NASA Astrophysics Data System (ADS)

Jacobosn, R. B.

2007-12-01

River restoration increasingly involves collaboration with stakeholders having diverse values and varying technical understanding. In cases where river restoration proceeds through collaborative processes, scientists are required to communicate complex understanding about riverine ecosystem processes to broad audiences. Of particular importance is communication of uncertainties in predictions of ecosystem responses to restoration actions, and how those uncertainties affect monitoring and evaluation strategies. I present a relatively simple conceptual model of how riverine ecosystems operate. The model, which has been used to conceptualize and communicate various river-restoration and management processes in the Lower Missouri River, emphasizes a) the interdependencies of driving regimes (for example, flow, sediment, and water quality), b) the filtering effect of management history, c) the typical hierarchical nature of information about how ecosystems operate, and d) how scientific understanding interacts with decision making. I provide an example of how the conceptual model has been used to illustrate the effects of extensive channel re-engineering of the Lower Missouri River which is intended to mitigate the effects of channelization and flow regulation on aquatic and flood-plain ecosystems. The conceptual model illustrates the logic for prioritizing investments in monitoring and evaluation, interactions among ecosystem components, tradeoffs between ecological and social-commercial benefits, and the feedback loop necessary for successful adaptive management.

Qualitative modelling for the Caeté Mangrove Estuary (North Brazil): a preliminary approach to an integrated eco-social analysis

NASA Astrophysics Data System (ADS)

Ortiz, Marco; Wolff, Matthias

2004-10-01

The sustainability of different integrated management regimes for the mangrove ecosystem of the Caeté Estuary (North Brazil) were assessed using a holistic theoretical framework. As a way to demonstrate that the behaviour and trajectory of complex whole systems are not epiphenomenal to the properties of the small parts, a set of conceptual models from more reductionistic to more holistic were enunciated. These models integrate the scientific information published until present for this mangrove ecosystem. The sustainability of different management scenarios (forestry and fishery) was assessed. Since the exploitation of mangrove trees is not allowed according Brazilian laws, the forestry was only included for simulation purposes. The model simulations revealed that sustainability predictions of reductionistic models should not be extrapolated into holistic approaches. Forestry and fishery activities seem to be sustainable only if they are self-damped. The exploitation of the two mangrove species Rhizophora mangle and Avicenia germinans does not appear to be sustainable, thus a rotation harvest is recommended. A similar conclusion holds for the exploitation of invertebrate species. Our results suggest that more studies should be focused on the estimation of maximum sustainable yield based on a multispecies approach. Any reference to holistic sustainability based on reductionistic approaches may distort our understanding of the natural complex ecosystems.

Bayesian calibration of terrestrial ecosystem models: a study of advanced Markov chain Monte Carlo methods

NASA Astrophysics Data System (ADS)

Lu, Dan; Ricciuto, Daniel; Walker, Anthony; Safta, Cosmin; Munger, William

2017-09-01

Calibration of terrestrial ecosystem models is important but challenging. Bayesian inference implemented by Markov chain Monte Carlo (MCMC) sampling provides a comprehensive framework to estimate model parameters and associated uncertainties using their posterior distributions. The effectiveness and efficiency of the method strongly depend on the MCMC algorithm used. In this work, a differential evolution adaptive Metropolis (DREAM) algorithm is used to estimate posterior distributions of 21 parameters for the data assimilation linked ecosystem carbon (DALEC) model using 14 years of daily net ecosystem exchange data collected at the Harvard Forest Environmental Measurement Site eddy-flux tower. The calibration of DREAM results in a better model fit and predictive performance compared to the popular adaptive Metropolis (AM) scheme. Moreover, DREAM indicates that two parameters controlling autumn phenology have multiple modes in their posterior distributions while AM only identifies one mode. The application suggests that DREAM is very suitable to calibrate complex terrestrial ecosystem models, where the uncertain parameter size is usually large and existence of local optima is always a concern. In addition, this effort justifies the assumptions of the error model used in Bayesian calibration according to the residual analysis. The result indicates that a heteroscedastic, correlated, Gaussian error model is appropriate for the problem, and the consequent constructed likelihood function can alleviate the underestimation of parameter uncertainty that is usually caused by using uncorrelated error models.

Divergent patterns of experimental and model derived variables of tundra ecosystem carbon exchange in response to arctic warming

NASA Astrophysics Data System (ADS)

Schaedel, C.; Koven, C.; Celis, G.; Hutchings, J.; Lawrence, D. M.; Mauritz, M.; Pegoraro, E.; Salmon, V. G.; Taylor, M.; Wieder, W. R.; Schuur, E.

2017-12-01

Warming over the Arctic in the last decades has been twice as high as for the rest of the globe and has exposed large amounts of organic carbon to microbial decomposition in permafrost ecosystems. Continued warming and associated changes in soil moisture conditions not only lead to enhanced microbial decomposition from permafrost soil but also enhanced plant carbon uptake. Both processes impact the overall contribution of permafrost carbon dynamics to the global carbon cycle, yet field and modeling studies show large uncertainties in regard to both uptake and release mechanisms. Here, we compare variables associated with ecosystem carbon exchange (GPP: gross primary production; Reco: ecosystem respiration; and NEE: net ecosystem exchange) from eight years of experimental soil warming in moist acidic tundra with the same variables derived from an experimental model (Community Land Model version 4.5: CLM4.5) that simulates the same degree of arctic warming. While soil temperatures and thaw depths exhibited comparable increases with warming between field and model variables, carbon exchange related parameters showed divergent patterns. In the field non-linear responses to experimentally induced permafrost thaw were observed in GPP, Reco, and NEE. Indirect effects of continued soil warming and thaw created changes in soil moisture conditions causing ground surface subsidence and suppressing ecosystem carbon exchange over time. In contrast, the model predicted linear increases in GPP, Reco, and NEE with every year of warming turning the ecosystem into a net annual carbon sink. The field experiment revealed the importance of hydrology in carbon flux responses to permafrost thaw, a complexity that the model may fail to predict. Further parameterization of variables that drive GPP, Reco, and NEE in the model will help to inform and refine future model development.

Modelling Pseudocalanus elongatus stage-structured population dynamics embedded in a water column ecosystem model for the northern North Sea

NASA Astrophysics Data System (ADS)

Moll, Andreas; Stegert, Christoph

2007-01-01

This paper outlines an approach to couple a structured zooplankton population model with state variables for eggs, nauplii, two copepodites stages and adults adapted to Pseudocalanus elongatus into the complex marine ecosystem model ECOHAM2 with 13 state variables resolving the carbon and nitrogen cycle. Different temperature and food scenarios derived from laboratory culture studies were examined to improve the process parameterisation for copepod stage dependent development processes. To study annual cycles under realistic weather and hydrographic conditions, the coupled ecosystem-zooplankton model is applied to a water column in the northern North Sea. The main ecosystem state variables were validated against observed monthly mean values. Then vertical profiles of selected state variables were compared to the physical forcing to study differences between zooplankton as one biomass state variable or partitioned into five population state variables. Simulated generation times are more affected by temperature than food conditions except during the spring phytoplankton bloom. Up to six generations within the annual cycle can be discerned in the simulation.

Linking Belowground Plant Traits With Ecosystem Processes: A Multi-Biome Perspective

NASA Astrophysics Data System (ADS)

Iversen, C. M.; Norby, R. J.; Childs, J.; McCormack, M. L.; Walker, A. P.; Hanson, P. J.; Warren, J.; Sloan, V. L.; Sullivan, P. F.; Wullschleger, S.; Powell, A. S.

2015-12-01

Fine plant roots are short-lived, narrow-diameter roots that play an important role in ecosystem carbon, water, and nutrient cycling in biomes ranging from the tundra to the tropics. Root ecologists make measurements at a millimeter scale to answer a question with global implications: In response to a changing climate, how do fine roots modulate the exchange of carbon between soils and the atmosphere and how will this response affect our future climate? In a Free-Air CO2 Enrichment experiment in Oak Ridge, TN, elevated [CO2] caused fine roots to dive deeper into the soil profile in search of limiting nitrogen, which led to increased soil C storage in deep soils. In contrast, the fine roots of trees and shrubs in an ombrotrophic bog are constrained to nutrient-poor, oxic soils above the average summer water table depth, though this may change with warmer, drier conditions. Tundra plant species are similarly constrained to surface organic soils by permafrost or waterlogged soils, but have many adaptations that alter ecosystem C fluxes, including aerenchyma that oxygenate the rhizosphere but also allow direct methane flux to the atmosphere. FRED, a global root trait database, will allow terrestrial biosphere models to represent the complexity of root traits across the globe, informing both model representation of ecosystem C and nutrient fluxes, but also the gaps where measurements are needed on plant-soil interactions (for example, in the tropical biome). While the complexity of mm-scale measurements may never have a place in large-scale global models, close collaboration between empiricists and modelers can help to guide the scaling of important, yet small-scale, processes to quantify their important roles in larger-scale ecosystem fluxes.

Comparative analysis of marine ecosystems: workshop on predator-prey interactions.

PubMed

Bailey, Kevin M; Ciannelli, Lorenzo; Hunsicker, Mary; Rindorf, Anna; Neuenfeldt, Stefan; Möllmann, Christian; Guichard, Frederic; Huse, Geir

2010-10-23

Climate and human influences on marine ecosystems are largely manifested by changes in predator-prey interactions. It follows that ecosystem-based management of the world's oceans requires a better understanding of food web relationships. An international workshop on predator-prey interactions in marine ecosystems was held at the Oregon State University, Corvallis, OR, USA on 16-18 March 2010. The meeting brought together scientists from diverse fields of expertise including theoretical ecology, animal behaviour, fish and seabird ecology, statistics, fisheries science and ecosystem modelling. The goals of the workshop were to critically examine the methods of scaling-up predator-prey interactions from local observations to systems, the role of shifting ecological processes with scale changes, and the complexity and organizational structure in trophic interactions.

A modelling methodology to assess the effect of insect pest control on agro-ecosystems.

PubMed

Wan, Nian-Feng; Ji, Xiang-Yun; Jiang, Jie-Xian; Li, Bo

2015-04-23

The extensive use of chemical pesticides for pest management in agricultural systems can entail risks to the complex ecosystems consisting of economic, ecological and social subsystems. To analyze the negative and positive effects of external or internal disturbances on complex ecosystems, we proposed an ecological two-sidedness approach which has been applied to the design of pest-controlling strategies for pesticide pollution management. However, catastrophe theory has not been initially applied to this approach. Thus, we used an approach of integrating ecological two-sidedness with a multi-criterion evaluation method of catastrophe theory to analyze the complexity of agro-ecosystems disturbed by the insecticides and screen out the best insect pest-controlling strategy in cabbage production. The results showed that the order of the values of evaluation index (RCC/CP) for three strategies in cabbage production was "applying frequency vibration lamps and environment-friendly insecticides 8 times" (0.80) < "applying trap devices and environment-friendly insecticides 9 times" (0.83) < "applying common insecticides 14 times" (1.08). The treatment "applying frequency vibration lamps and environment-friendly insecticides 8 times" was considered as the best insect pest-controlling strategy in cabbage production in Shanghai, China.

A modelling methodology to assess the effect of insect pest control on agro-ecosystems

PubMed Central

Wan, Nian-Feng; Ji, Xiang-Yun; Jiang, Jie-Xian; Li, Bo

2015-01-01

The extensive use of chemical pesticides for pest management in agricultural systems can entail risks to the complex ecosystems consisting of economic, ecological and social subsystems. To analyze the negative and positive effects of external or internal disturbances on complex ecosystems, we proposed an ecological two-sidedness approach which has been applied to the design of pest-controlling strategies for pesticide pollution management. However, catastrophe theory has not been initially applied to this approach. Thus, we used an approach of integrating ecological two-sidedness with a multi-criterion evaluation method of catastrophe theory to analyze the complexity of agro-ecosystems disturbed by the insecticides and screen out the best insect pest-controlling strategy in cabbage production. The results showed that the order of the values of evaluation index (RCC/CP) for three strategies in cabbage production was “applying frequency vibration lamps and environment-friendly insecticides 8 times” (0.80) < “applying trap devices and environment-friendly insecticides 9 times” (0.83) < “applying common insecticides 14 times” (1.08). The treatment “applying frequency vibration lamps and environment-friendly insecticides 8 times” was considered as the best insect pest-controlling strategy in cabbage production in Shanghai, China. PMID:25906199

BASIN-SCALE ASSESSMENTS FOR SUSTAINABLE ECOSYSTEMS (BASE)

EPA Science Inventory

The need for multi-media, multi-stressor, and multi-response models for ecological assessment is widely acknowledged. Assessments at this level of complexity have not been conducted, and therefore pilot assessments are required to identify the critical concepts, models, data, and...

Reducing the uncertainty in the projection of the terrestrial carbon cycle by fusing models with remote sensing data

NASA Astrophysics Data System (ADS)

Serbin, S.; Shiklomanov, A. N.; Viskari, T.; Desai, A. R.; Townsend, P. A.; Dietze, M.

2015-12-01

Modeling global change requires accurate representation of terrestrial carbon (C), energy and water fluxes. In particular, capturing the properties of vegetation canopies that describe the radiation regime are a key focus for global change research because the properties related to radiation utilization and penetration within plant canopies provide an important constraint on terrestrial ecosystem productivity, as well as the fluxes of water and energy from vegetation to the atmosphere. As such, optical remote sensing observations present an important, and as yet relatively untapped, source of observations that can be used to inform modeling activities. In particular, high-spectral resolution optical data at the leaf and canopy scales offers the potential for an important and direct data constraint on the parameterization and structure of the radiative transfer model (RTM) scheme within ecosystem models across diverse vegetation types, disturbance and management histories. In this presentation we highlight ongoing work to integrate optical remote sensing observations, specifically leaf and imaging spectroscopy (IS) data across a range of forest ecosystems, into complex ecosystem process models within an efficient computational assimilation framework as a means to improve the description of canopy optical properties, vegetation composition, and modeled radiation balance. Our work leverages the Predictive Ecosystem Analyzer (PEcAn; http://www.pecanproject.org/) ecoinformatics toolbox together with a RTM module designed for efficient assimilation of leaf and IS observations to inform vegetation optical properties as well as associated plant traits. Ultimately, an improved understanding of the radiation balance of ecosystems will provide a better constraint on model projections of energy balance, vegetation composition, and carbon pools and fluxes thus allowing for a better diagnosis of the vulnerability of terrestrial ecosystems in response to global change.

Gross primary production dynamics assessment of a mediterranean holm oak forest by remote sensing time series analysis

NASA Astrophysics Data System (ADS)

Cicuéndez, Víctor; Huesca, Margarita; Rodriguez-Rastrero, Manuel; Litago, Javier; Recuero, Laura; Merino de Miguel, Silvia; Palacios Orueta, Alicia

2014-05-01

Agroforestry ecosystems have a significant social, economic and environmental impact on the development of many regions of the world. In the Iberian Peninsula the agroforestry oak forest called "Dehesa" or "Montado" is considered as the extreme case of transformation of a Mediterranean forest by the management of human to provide a wide range of natural resources. The high variability of the Mediterranean climate and the different extensive management practices which human realized on the Dehesa result in a high spatial and temporal dynamics of the ecosystem. This leads to a complex pattern in CO2 exchange between the atmosphere and the ecosystem, i.e. in ecosystem's production. Thus, it is essential to assess Dehesa's carbon cycle to reach maximum economic benefits ensuring environmental sustainability. In this sense, the availability of high frequency Remote Sensing (RS) time series allows the assessment of ecosystem evolution at different temporal and spatial scales. Extensive research has been conducted to estimate production from RS data in different ecosystems. However, there are few studies on the Dehesa type ecosystems, probably due to their complexity in terms of spatial arrangement and temporal dynamics. In this study our overall objective is to assess the Gross Primary Production (GPP) dynamics of a Dehesa ecosystem situated in Central Spain by analyzing time series (2004-2008) of two models: (1) GPP provided by Remote Sensing Images of sensor MODIS (MOD17A2 product) and (2) GPP estimated by the implementation of a Site Specific Light Use Efficiency model based as MODIS model on Monteith equation (1972), but taking into account local ecological and meteorological parameters. Both models have been compared with the Production provided by an Eddy Covariance (EC) flux Tower that is located in our study area. In addition, dynamic relationships between models of GPP with Precipitation and Soil Water Content have been investigated by means of cross-correlations and Granger causality tests. Results have indicated that both models of GPP have shown a typical dynamic of the Dehesa in a Mediterranean climate in which there are primarily two layers, the arboreal and the herbaceous strata. However, MODIS underestimates the production of the Dehesa while our Site specific model has given more similar values and dynamics to those from the EC tower. Additionally, the analysis of the dynamic relationships has corroborated the strong dynamic link between GPP and available water for plant growth. In conclusion, we have managed to avoid the main sources of underestimation that has MODIS model with the implementation of a Site specific model. Thus, it seems that the different ecological and meteorological parameters used in MODIS model are the principally responsible for this underestimation. Finally, the Granger causality tests indicate that the prediction of GPP can improve if Precipitation or Soil Water is included in the models. References Monteith, J.L., 1972. Solar Radiation and Productivity in Tropical Ecosystems. J. Appl. Ecol. 9, 747-766.

Testing a land model in ecosystem functional space via a comparison of observed and modeled ecosystem flux responses to precipitation regimes and associated stresses in a Central U.S. forest: Test Model in Ecosystem Functional Space

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gu, Lianhong; Pallardy, Stephen G.; Yang, Bai

Testing complex land surface models has often proceeded by asking the question: does the model prediction agree with the observation? This approach has yet led to high-performance terrestrial models that meet the challenges of climate and ecological studies. Here we test the Community Land Model (CLM) by asking the question: does the model behave like an ecosystem? We pursue its answer by testing CLM in the ecosystem functional space (EFS) at the Missouri Ozark AmeriFlux (MOFLUX) forest site in the Central U.S., focusing on carbon and water flux responses to precipitation regimes and associated stresses. In the observed EFS, precipitationmore » regimes and associated water and heat stresses controlled seasonal and interannual variations of net ecosystem exchange (NEE) of CO 2 and evapotranspiration in this deciduous forest ecosystem. Such controls were exerted more strongly by precipitation variability than by the total precipitation amount per se. A few simply constructed climate variability indices captured these controls, suggesting a high degree of potential predictability. While the interannual fluctuation in NEE was large, a net carbon sink was maintained even during an extreme drought year. Although CLM predicted seasonal and interanual variations in evapotranspiration reasonably well, its predictions of net carbon uptake were too small across the observed range of climate variability. Also, the model systematically underestimated the sensitivities of NEE and evapotranspiration to climate variability and overestimated the coupling strength between carbon and water fluxes. Its suspected that the modeled and observed trajectories of ecosystem fluxes did not overlap in the EFS and the model did not behave like the ecosystem it attempted to simulate. A definitive conclusion will require comprehensive parameter and structural sensitivity tests in a rigorous mathematical framework. We also suggest that future model improvements should focus on better representation and parameterization of process responses to environmental stresses and on more complete and robust representations of carbon-specific processes so that adequate responses to climate variability and a proper degree of coupling between carbon and water exchanges are captured.« less

Testing a land model in ecosystem functional space via a comparison of observed and modeled ecosystem flux responses to precipitation regimes and associated stresses in a Central U.S. forest: Test Model in Ecosystem Functional Space

DOE PAGES

Gu, Lianhong; Pallardy, Stephen G.; Yang, Bai; ...

2016-07-14

Testing complex land surface models has often proceeded by asking the question: does the model prediction agree with the observation? This approach has yet led to high-performance terrestrial models that meet the challenges of climate and ecological studies. Here we test the Community Land Model (CLM) by asking the question: does the model behave like an ecosystem? We pursue its answer by testing CLM in the ecosystem functional space (EFS) at the Missouri Ozark AmeriFlux (MOFLUX) forest site in the Central U.S., focusing on carbon and water flux responses to precipitation regimes and associated stresses. In the observed EFS, precipitationmore » regimes and associated water and heat stresses controlled seasonal and interannual variations of net ecosystem exchange (NEE) of CO 2 and evapotranspiration in this deciduous forest ecosystem. Such controls were exerted more strongly by precipitation variability than by the total precipitation amount per se. A few simply constructed climate variability indices captured these controls, suggesting a high degree of potential predictability. While the interannual fluctuation in NEE was large, a net carbon sink was maintained even during an extreme drought year. Although CLM predicted seasonal and interanual variations in evapotranspiration reasonably well, its predictions of net carbon uptake were too small across the observed range of climate variability. Also, the model systematically underestimated the sensitivities of NEE and evapotranspiration to climate variability and overestimated the coupling strength between carbon and water fluxes. Its suspected that the modeled and observed trajectories of ecosystem fluxes did not overlap in the EFS and the model did not behave like the ecosystem it attempted to simulate. A definitive conclusion will require comprehensive parameter and structural sensitivity tests in a rigorous mathematical framework. We also suggest that future model improvements should focus on better representation and parameterization of process responses to environmental stresses and on more complete and robust representations of carbon-specific processes so that adequate responses to climate variability and a proper degree of coupling between carbon and water exchanges are captured.« less

Managing for resilience: an information theory-based ...

EPA Pesticide Factsheets

Ecosystems are complex and multivariate; hence, methods to assess the dynamics of ecosystems should have the capacity to evaluate multiple indicators simultaneously. Most research on identifying leading indicators of regime shifts has focused on univariate methods and simple models which have limited utility when evaluating real ecosystems, particularly because drivers are often unknown. We discuss some common univariate and multivariate approaches for detecting critical transitions in ecosystems and demonstrate their capabilities via case studies. Synthesis and applications. We illustrate the utility of an information theory-based index for assessing ecosystem dynamics. Trends in this index also provide a sentinel of both abrupt and gradual transitions in ecosystems. In response to the need to identify leading indicators of regime shifts in ecosystems, our research compares traditional indicators and Fisher information, an information theory based method, by examining four case study systems. Results demonstrate the utility of methods and offers great promise for quantifying and managing for resilience.

Functional groups of ecosystem engineers: a proposed classification with comments on current issues.

PubMed

Berke, Sarah K

2010-08-01

Ecologists have long known that certain organisms fundamentally modify, create, or define habitats by altering the habitat's physical properties. In the past 15 years, these processes have been formally defined as "ecosystem engineering", reflecting a growing consensus that environmental structuring by organisms represents a fundamental class of ecological interactions occurring in most, if not all, ecosystems. Yet, the precise definition and scope of ecosystem engineering remains debated, as one should expect given the complexity, enormity, and variability of ecological systems. Here I briefly comment on a few specific current points of contention in the ecosystem engineering concept. I then suggest that ecosystem engineering can be profitably subdivided into four narrower functional categories reflecting four broad mechanisms by which ecosystem engineering occurs: structural engineers, bioturbators, chemical engineers, and light engineers. Finally, I suggest some conceptual model frameworks that could apply broadly within these functional groups.

Using next generation transcriptome sequencing to predict an ectomycorrhizal metablome.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Larsen, P. E.; Sreedasyam, A.; Trivedi, G

Mycorrhizae, symbiotic interactions between soil fungi and tree roots, are ubiquitous in terrestrial ecosystems. The fungi contribute phosphorous, nitrogen and mobilized nutrients from organic matter in the soil and in return the fungus receives photosynthetically-derived carbohydrates. This union of plant and fungal metabolisms is the mycorrhizal metabolome. Understanding this symbiotic relationship at a molecular level provides important contributions to the understanding of forest ecosystems and global carbon cycling. We generated next generation short-read transcriptomic sequencing data from fully-formed ectomycorrhizae between Laccaria bicolor and aspen (Populus tremuloides) roots. The transcriptomic data was used to identify statistically significantly expressed gene models usingmore » a bootstrap-style approach, and these expressed genes were mapped to specific metabolic pathways. Integration of expressed genes that code for metabolic enzymes and the set of expressed membrane transporters generates a predictive model of the ectomycorrhizal metabolome. The generated model of mycorrhizal metabolome predicts that the specific compounds glycine, glutamate, and allantoin are synthesized by L. bicolor and that these compounds or their metabolites may be used for the benefit of aspen in exchange for the photosynthetically-derived sugars fructose and glucose. The analysis illustrates an approach to generate testable biological hypotheses to investigate the complex molecular interactions that drive ectomycorrhizal symbiosis. These models are consistent with experimental environmental data and provide insight into the molecular exchange processes for organisms in this complex ecosystem. The method used here for predicting metabolomic models of mycorrhizal systems from deep RNA sequencing data can be generalized and is broadly applicable to transcriptomic data derived from complex systems.« less

Modeling for Ecosystem Services: Challenges and Opportunities

NASA Astrophysics Data System (ADS)

Guswa, A. J.; Brauman, K. A.; Ghile, Y.

2012-12-01

Ecosystem services are those values provided to human society by the structure and processes of ecosystems and landscapes. Water-related services include the transformation of precipitation impulses into supplies of water for hydropower, irrigation, and industrial and municipal uses, the retention and removal of applied nutrients and pollutants, flood-damage mitigation, recreation, and the provision of cultural and aesthetic values. Incorporation of changes to the value of these services in land-use planning and decision making requires identification of the relevant services, engagement of stakeholders, knowledge of how land-use changes impact water quality, quantity, and timing, and mechanisms for putting value on the hydrologic and biogeochemical changes. We present three examples that highlight the characteristics, challenges, and opportunities associated with prototypical decisions that incorporate ecosystem services values: scenario analysis, payment for ecosystem services, and optimal spatial planning. Through these examples, we emphasize the challenges of data availability, model resolution and complexity, and attribution of value. We also provide some suggestions for ways forward.

DayCent model simulations for estimating soil carbon dynamics and greenhouse gas fluxes from agricultural production systems

USDA-ARS?s Scientific Manuscript database

DayCent is a biogeochemical model of intermediate complexity used to simulate carbon, nutrient, and greenhouse gas fluxes for crop, grassland, forest, and savanna ecosystems. Model inputs include: soil texture and hydraulic properties, current and historical land use, vegetation cover, daily maximum...

A Testbed for Model Development

NASA Astrophysics Data System (ADS)

Berry, J. A.; Van der Tol, C.; Kornfeld, A.

2014-12-01

Carbon cycle and land-surface models used in global simulations need to be computationally efficient and have a high standard of software engineering. These models also make a number of scaling assumptions to simplify the representation of complex biochemical and structural properties of ecosystems. This makes it difficult to use these models to test new ideas for parameterizations or to evaluate scaling assumptions. The stripped down nature of these models also makes it difficult to "connect" with current disciplinary research which tends to be focused on much more nuanced topics than can be included in the models. In our opinion/experience this indicates the need for another type of model that can more faithfully represent the complexity ecosystems and which has the flexibility to change or interchange parameterizations and to run optimization codes for calibration. We have used the SCOPE (Soil Canopy Observation, Photochemistry and Energy fluxes) model in this way to develop, calibrate, and test parameterizations for solar induced chlorophyll fluorescence, OCS exchange and stomatal parameterizations at the canopy scale. Examples of the data sets and procedures used to develop and test new parameterizations are presented.

When 1+1 can be >2: Uncertainties compound when simulating climate, fisheries and marine ecosystems

NASA Astrophysics Data System (ADS)

Evans, Karen; Brown, Jaclyn N.; Sen Gupta, Alex; Nicol, Simon J.; Hoyle, Simon; Matear, Richard; Arrizabalaga, Haritz

2015-03-01

Multi-disciplinary approaches that combine oceanographic, biogeochemical, ecosystem, fisheries population and socio-economic models are vital tools for modelling whole ecosystems. Interpreting the outputs from such complex models requires an appreciation of the many different types of modelling frameworks being used and their associated limitations and uncertainties. Both users and developers of particular model components will often have little involvement or understanding of other components within such modelling frameworks. Failure to recognise limitations and uncertainties associated with components and how these uncertainties might propagate throughout modelling frameworks can potentially result in poor advice for resource management. Unfortunately, many of the current integrative frameworks do not propagate the uncertainties of their constituent parts. In this review, we outline the major components of a generic whole of ecosystem modelling framework incorporating the external pressures of climate and fishing. We discuss the limitations and uncertainties associated with each component of such a modelling system, along with key research gaps. Major uncertainties in modelling frameworks are broadly categorised into those associated with (i) deficient knowledge in the interactions of climate and ocean dynamics with marine organisms and ecosystems; (ii) lack of observations to assess and advance modelling efforts and (iii) an inability to predict with confidence natural ecosystem variability and longer term changes as a result of external drivers (e.g. greenhouse gases, fishing effort) and the consequences for marine ecosystems. As a result of these uncertainties and intrinsic differences in the structure and parameterisation of models, users are faced with considerable challenges associated with making appropriate choices on which models to use. We suggest research directions required to address these uncertainties, and caution against overconfident predictions. Understanding the full impact of uncertainty makes it clear that full comprehension and robust certainty about the systems themselves are not feasible. A key research direction is the development of management systems that are robust to this unavoidable uncertainty.

Using nocturnal cold air drainage flow to monitor ecosystem processes in complex terrain

Treesearch

Thomas G. Pypker; Michael H. Unsworth; Alan C. Mix; William Rugh; Troy Ocheltree; Karrin Alstad; Barbara J. Bond

2007-01-01

This paper presents initial investigations of a new approach to monitor ecosystem processes in complex terrain on large scales. Metabolic processes in mountainous ecosystems are poorly represented in current ecosystem monitoring campaigns because the methods used for monitoring metabolism at the ecosystem scale (e.g., eddy covariance) require flat study sites. Our goal...

Pattern formation--A missing link in the study of ecosystem response to environmental changes.

PubMed

Meron, Ehud

2016-01-01

Environmental changes can affect the functioning of an ecosystem directly, through the response of individual life forms, or indirectly, through interspecific interactions and community dynamics. The feasibility of a community-level response has motivated numerous studies aimed at understanding the mutual relationships between three elements of ecosystem dynamics: the abiotic environment, biodiversity and ecosystem function. Since ecosystems are inherently nonlinear and spatially extended, environmental changes can also induce pattern-forming instabilities that result in spatial self-organization of life forms and resources. This, in turn, can affect the relationships between these three elements, and make the response of ecosystems to environmental changes far more complex. Responses of this kind can be expected in dryland ecosystems, which show a variety of self-organizing vegetation patterns along the rainfall gradient. This paper describes the progress that has been made in understanding vegetation patterning in dryland ecosystems, and the roles it plays in ecosystem response to environmental variability. The progress has been achieved by modeling pattern-forming feedbacks at small spatial scales and up-scaling their effects to large scales through model studies. This approach sets the basis for integrating pattern formation theory into the study of ecosystem dynamics and addressing ecologically significant questions such as the dynamics of desertification, restoration of degraded landscapes, biodiversity changes along environmental gradients, and shrubland-grassland transitions. Copyright © 2015 Elsevier Inc. All rights reserved.

A Carbon Cycle Model for the Social-Ecological Process in Coastal Wetland: A Case Study on Gouqi Island, East China

PubMed Central

Xiong, Lihu; Zhu, Wenjia

2017-01-01

Coastal wetlands offer many important ecosystem services both in natural and in social systems. How to simultaneously decrease the destructive effects flowing from human activities and maintaining the sustainability of regional wetland ecosystems are an important issue for coastal wetlands zones. We use carbon credits as the basis for regional sustainable developing policy-making. With the case of Gouqi Island, a typical coastal wetlands zone that locates in the East China Sea, a carbon cycle model was developed to illustrate the complex social-ecological processes. Carbon-related processes in natural ecosystem, primary industry, secondary industry, tertiary industry, and residents on the island were identified in the model. The model showed that 36780 tons of carbon is released to atmosphere with the form of CO2, and 51240 tons of carbon is captured by the ecosystem in 2014 and the three major resources of carbon emission are transportation and tourism development and seawater desalination. Based on the carbon-related processes and carbon balance, we proposed suggestions on the sustainable development strategy of Gouqi Island as coastal wetlands zone. PMID:28286690

A Carbon Cycle Model for the Social-Ecological Process in Coastal Wetland: A Case Study on Gouqi Island, East China.

PubMed

Li, Yanxia; Xiong, Lihu; Zhu, Wenjia

2017-01-01

Coastal wetlands offer many important ecosystem services both in natural and in social systems. How to simultaneously decrease the destructive effects flowing from human activities and maintaining the sustainability of regional wetland ecosystems are an important issue for coastal wetlands zones. We use carbon credits as the basis for regional sustainable developing policy-making. With the case of Gouqi Island, a typical coastal wetlands zone that locates in the East China Sea, a carbon cycle model was developed to illustrate the complex social-ecological processes. Carbon-related processes in natural ecosystem, primary industry, secondary industry, tertiary industry, and residents on the island were identified in the model. The model showed that 36780 tons of carbon is released to atmosphere with the form of CO 2 , and 51240 tons of carbon is captured by the ecosystem in 2014 and the three major resources of carbon emission are transportation and tourism development and seawater desalination. Based on the carbon-related processes and carbon balance, we proposed suggestions on the sustainable development strategy of Gouqi Island as coastal wetlands zone.

Meta-Modeling: A Knowledge-Based Approach to Facilitating Model Construction and Reuse

NASA Technical Reports Server (NTRS)

Keller, Richard M.; Dungan, Jennifer L.

1997-01-01

In this paper, we introduce a new modeling approach called meta-modeling and illustrate its practical applicability to the construction of physically-based ecosystem process models. As a critical adjunct to modeling codes meta-modeling requires explicit specification of certain background information related to the construction and conceptual underpinnings of a model. This information formalizes the heretofore tacit relationship between the mathematical modeling code and the underlying real-world phenomena being investigated, and gives insight into the process by which the model was constructed. We show how the explicit availability of such information can make models more understandable and reusable and less subject to misinterpretation. In particular, background information enables potential users to better interpret an implemented ecosystem model without direct assistance from the model author. Additionally, we show how the discipline involved in specifying background information leads to improved management of model complexity and fewer implementation errors. We illustrate the meta-modeling approach in the context of the Scientists' Intelligent Graphical Modeling Assistant (SIGMA) a new model construction environment. As the user constructs a model using SIGMA the system adds appropriate background information that ties the executable model to the underlying physical phenomena under investigation. Not only does this information improve the understandability of the final model it also serves to reduce the overall time and programming expertise necessary to initially build and subsequently modify models. Furthermore, SIGMA's use of background knowledge helps eliminate coding errors resulting from scientific and dimensional inconsistencies that are otherwise difficult to avoid when building complex models. As a. demonstration of SIGMA's utility, the system was used to reimplement and extend a well-known forest ecosystem dynamics model: Forest-BGC.

Bayesian calibration of terrestrial ecosystem models: a study of advanced Markov chain Monte Carlo methods

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lu, Dan; Ricciuto, Daniel M.; Walker, Anthony P.

Calibration of terrestrial ecosystem models is important but challenging. Bayesian inference implemented by Markov chain Monte Carlo (MCMC) sampling provides a comprehensive framework to estimate model parameters and associated uncertainties using their posterior distributions. The effectiveness and efficiency of the method strongly depend on the MCMC algorithm used. In this work, a differential evolution adaptive Metropolis (DREAM) algorithm is used to estimate posterior distributions of 21 parameters for the data assimilation linked ecosystem carbon (DALEC) model using 14 years of daily net ecosystem exchange data collected at the Harvard Forest Environmental Measurement Site eddy-flux tower. The calibration of DREAM results inmore » a better model fit and predictive performance compared to the popular adaptive Metropolis (AM) scheme. Moreover, DREAM indicates that two parameters controlling autumn phenology have multiple modes in their posterior distributions while AM only identifies one mode. The application suggests that DREAM is very suitable to calibrate complex terrestrial ecosystem models, where the uncertain parameter size is usually large and existence of local optima is always a concern. In addition, this effort justifies the assumptions of the error model used in Bayesian calibration according to the residual analysis. Here, the result indicates that a heteroscedastic, correlated, Gaussian error model is appropriate for the problem, and the consequent constructed likelihood function can alleviate the underestimation of parameter uncertainty that is usually caused by using uncorrelated error models.« less

Bayesian calibration of terrestrial ecosystem models: a study of advanced Markov chain Monte Carlo methods

DOE PAGES

Lu, Dan; Ricciuto, Daniel M.; Walker, Anthony P.; ...

2017-09-27

Calibration of terrestrial ecosystem models is important but challenging. Bayesian inference implemented by Markov chain Monte Carlo (MCMC) sampling provides a comprehensive framework to estimate model parameters and associated uncertainties using their posterior distributions. The effectiveness and efficiency of the method strongly depend on the MCMC algorithm used. In this work, a differential evolution adaptive Metropolis (DREAM) algorithm is used to estimate posterior distributions of 21 parameters for the data assimilation linked ecosystem carbon (DALEC) model using 14 years of daily net ecosystem exchange data collected at the Harvard Forest Environmental Measurement Site eddy-flux tower. The calibration of DREAM results inmore » a better model fit and predictive performance compared to the popular adaptive Metropolis (AM) scheme. Moreover, DREAM indicates that two parameters controlling autumn phenology have multiple modes in their posterior distributions while AM only identifies one mode. The application suggests that DREAM is very suitable to calibrate complex terrestrial ecosystem models, where the uncertain parameter size is usually large and existence of local optima is always a concern. In addition, this effort justifies the assumptions of the error model used in Bayesian calibration according to the residual analysis. Here, the result indicates that a heteroscedastic, correlated, Gaussian error model is appropriate for the problem, and the consequent constructed likelihood function can alleviate the underestimation of parameter uncertainty that is usually caused by using uncorrelated error models.« less

Bacterial biodiversity-ecosystem functioning relations are modified by environmental complexity.

PubMed

Langenheder, Silke; Bulling, Mark T; Solan, Martin; Prosser, James I

2010-05-26

With the recognition that environmental change resulting from anthropogenic activities is causing a global decline in biodiversity, much attention has been devoted to understanding how changes in biodiversity may alter levels of ecosystem functioning. Although environmental complexity has long been recognised as a major driving force in evolutionary processes, it has only recently been incorporated into biodiversity-ecosystem functioning investigations. Environmental complexity is expected to strengthen the positive effect of species richness on ecosystem functioning, mainly because it leads to stronger complementarity effects, such as resource partitioning and facilitative interactions among species when the number of available resource increases. Here we implemented an experiment to test the combined effect of species richness and environmental complexity, more specifically, resource richness on ecosystem functioning over time. We show, using all possible combinations of species within a bacterial community consisting of six species, and all possible combinations of three substrates, that diversity-functioning (metabolic activity) relationships change over time from linear to saturated. This was probably caused by a combination of limited complementarity effects and negative interactions among competing species as the experiment progressed. Even though species richness and resource richness both enhanced ecosystem functioning, they did so independently from each other. Instead there were complex interactions between particular species and substrate combinations. Our study shows clearly that both species richness and environmental complexity increase ecosystem functioning. The finding that there was no direct interaction between these two factors, but that instead rather complex interactions between combinations of certain species and resources underlie positive biodiversity ecosystem functioning relationships, suggests that detailed knowledge of how individual species interact with complex natural environments will be required in order to make reliable predictions about how altered levels of biodiversity will most likely affect ecosystem functioning.

Bacterial Biodiversity-Ecosystem Functioning Relations Are Modified by Environmental Complexity

PubMed Central

Langenheder, Silke; Bulling, Mark T.; Solan, Martin; Prosser, James I.

2010-01-01

Background With the recognition that environmental change resulting from anthropogenic activities is causing a global decline in biodiversity, much attention has been devoted to understanding how changes in biodiversity may alter levels of ecosystem functioning. Although environmental complexity has long been recognised as a major driving force in evolutionary processes, it has only recently been incorporated into biodiversity-ecosystem functioning investigations. Environmental complexity is expected to strengthen the positive effect of species richness on ecosystem functioning, mainly because it leads to stronger complementarity effects, such as resource partitioning and facilitative interactions among species when the number of available resource increases. Methodology/Principal Findings Here we implemented an experiment to test the combined effect of species richness and environmental complexity, more specifically, resource richness on ecosystem functioning over time. We show, using all possible combinations of species within a bacterial community consisting of six species, and all possible combinations of three substrates, that diversity-functioning (metabolic activity) relationships change over time from linear to saturated. This was probably caused by a combination of limited complementarity effects and negative interactions among competing species as the experiment progressed. Even though species richness and resource richness both enhanced ecosystem functioning, they did so independently from each other. Instead there were complex interactions between particular species and substrate combinations. Conclusions/Significance Our study shows clearly that both species richness and environmental complexity increase ecosystem functioning. The finding that there was no direct interaction between these two factors, but that instead rather complex interactions between combinations of certain species and resources underlie positive biodiversity ecosystem functioning relationships, suggests that detailed knowledge of how individual species interact with complex natural environments will be required in order to make reliable predictions about how altered levels of biodiversity will most likely affect ecosystem functioning. PMID:20520808

iMarNet: an ocean biogeochemistry model inter-comparison project within a common physical ocean modelling framework

NASA Astrophysics Data System (ADS)

Kwiatkowski, L.; Yool, A.; Allen, J. I.; Anderson, T. R.; Barciela, R.; Buitenhuis, E. T.; Butenschön, M.; Enright, C.; Halloran, P. R.; Le Quéré, C.; de Mora, L.; Racault, M.-F.; Sinha, B.; Totterdell, I. J.; Cox, P. M.

2014-07-01

Ocean biogeochemistry (OBGC) models span a wide range of complexities from highly simplified, nutrient-restoring schemes, through nutrient-phytoplankton-zooplankton-detritus (NPZD) models that crudely represent the marine biota, through to models that represent a broader trophic structure by grouping organisms as plankton functional types (PFT) based on their biogeochemical role (Dynamic Green Ocean Models; DGOM) and ecosystem models which group organisms by ecological function and trait. OBGC models are now integral components of Earth System Models (ESMs), but they compete for computing resources with higher resolution dynamical setups and with other components such as atmospheric chemistry and terrestrial vegetation schemes. As such, the choice of OBGC in ESMs needs to balance model complexity and realism alongside relative computing cost. Here, we present an inter-comparison of six OBGC models that were candidates for implementation within the next UK Earth System Model (UKESM1). The models cover a large range of biological complexity (from 7 to 57 tracers) but all include representations of at least the nitrogen, carbon, alkalinity and oxygen cycles. Each OBGC model was coupled to the Nucleus for the European Modelling of the Ocean (NEMO) ocean general circulation model (GCM), and results from physically identical hindcast simulations were compared. Model skill was evaluated for biogeochemical metrics of global-scale bulk properties using conventional statistical techniques. The computing cost of each model was also measured in standardised tests run at two resource levels. No model is shown to consistently outperform or underperform all other models across all metrics. Nonetheless, the simpler models that are easier to tune are broadly closer to observations across a number of fields, and thus offer a high-efficiency option for ESMs that prioritise high resolution climate dynamics. However, simpler models provide limited insight into more complex marine biogeochemical processes and ecosystem pathways, and a parallel approach of low resolution climate dynamics and high complexity biogeochemistry is desirable in order to provide additional insights into biogeochemistry-climate interactions.

iMarNet: an ocean biogeochemistry model intercomparison project within a common physical ocean modelling framework

NASA Astrophysics Data System (ADS)

Kwiatkowski, L.; Yool, A.; Allen, J. I.; Anderson, T. R.; Barciela, R.; Buitenhuis, E. T.; Butenschön, M.; Enright, C.; Halloran, P. R.; Le Quéré, C.; de Mora, L.; Racault, M.-F.; Sinha, B.; Totterdell, I. J.; Cox, P. M.

2014-12-01

Ocean biogeochemistry (OBGC) models span a wide variety of complexities, including highly simplified nutrient-restoring schemes, nutrient-phytoplankton-zooplankton-detritus (NPZD) models that crudely represent the marine biota, models that represent a broader trophic structure by grouping organisms as plankton functional types (PFTs) based on their biogeochemical role (dynamic green ocean models) and ecosystem models that group organisms by ecological function and trait. OBGC models are now integral components of Earth system models (ESMs), but they compete for computing resources with higher resolution dynamical setups and with other components such as atmospheric chemistry and terrestrial vegetation schemes. As such, the choice of OBGC in ESMs needs to balance model complexity and realism alongside relative computing cost. Here we present an intercomparison of six OBGC models that were candidates for implementation within the next UK Earth system model (UKESM1). The models cover a large range of biological complexity (from 7 to 57 tracers) but all include representations of at least the nitrogen, carbon, alkalinity and oxygen cycles. Each OBGC model was coupled to the ocean general circulation model Nucleus for European Modelling of the Ocean (NEMO) and results from physically identical hindcast simulations were compared. Model skill was evaluated for biogeochemical metrics of global-scale bulk properties using conventional statistical techniques. The computing cost of each model was also measured in standardised tests run at two resource levels. No model is shown to consistently outperform all other models across all metrics. Nonetheless, the simpler models are broadly closer to observations across a number of fields and thus offer a high-efficiency option for ESMs that prioritise high-resolution climate dynamics. However, simpler models provide limited insight into more complex marine biogeochemical processes and ecosystem pathways, and a parallel approach of low-resolution climate dynamics and high-complexity biogeochemistry is desirable in order to provide additional insights into biogeochemistry-climate interactions.

Modelling the pelagic nitrogen cycle and vertical particle flux in the Norwegian sea

NASA Astrophysics Data System (ADS)

Haupt, Olaf J.; Wolf, Uli; v. Bodungen, Bodo

1999-02-01

A 1D Eulerian ecosystem model (BIological Ocean Model) for the Norwegian Sea was developed to investigate the dynamics of pelagic ecosystems. The BIOM combines six biochemical compartments and simulates the annual nitrogen cycle with specific focus on production, modification and sedimentation of particles in the water column. The external forcing and physical framework is based on a simulated annual cycle of global radiation and an annual mixed-layer cycle derived from field data. The vertical resolution of the model is given by an exponential grid with 200 depth layers, allowing specific parameterization of various sinking velocities, breakdown of particles and the remineralization processes. The aim of the numerical experiments is the simulation of ecosystem dynamics considering the specific biogeochemical properties of the Norwegian Sea, for example the life cycle of the dominant copepod Calanus finmarchicus. The results of the simulations were validated with field data. Model results are in good agreement with field data for the lower trophic levels of the food web. With increasing complexity of the organisms the differences increase between simulated processes and field data. Results of the numerical simulations suggest that BIOM is well adapted to investigate a physically controlled ecosystem. The simulation of grazing controlled pelagic ecosystems, like the Norwegian Sea, requires adaptations of parameterization to the specific ecosystem features. By using seasonally adaptation of the most sensible processes like utilization of light by phytoplankton and grazing by zooplankton results were greatly improved.

Trophic cascades triggered by overfishing reveal possible mechanisms of ecosystem regime shifts.

PubMed

Daskalov, Georgi M; Grishin, Alexander N; Rodionov, Sergei; Mihneva, Vesselina

2007-06-19

Large-scale transitions between alternative states in ecosystems are known as regime shifts. Once described as healthy and dominated by various marine predators, the Black Sea ecosystem by the late 20th century had experienced anthropogenic impacts such as heavy fishing, cultural eutrophication, and invasions by alien species. We studied changes related to these "natural experiments" to reveal the mechanisms of regime shifts. Two major shifts were detected, the first related to a depletion of marine predators and the second to an outburst of the alien comb jelly Mnemiopsis leidyi; both shifts were triggered by intense fishing resulting in system-wide trophic cascades. The complex nature of ecosystem responses to human activities calls for more elaborate approaches than currently provided by traditional environmental and fisheries management. This implies challenging existing practices and implementing explanatory models of ecosystem interactions that can better reconcile conservation and ecosystem management ideals.

Special features of the dayCent modeling package and additional procedures for parameterization, calibration, validation, and applications

USDA-ARS?s Scientific Manuscript database

DayCent (Daily Century) is a biogeochemical model of intermediate complexity used to simulate flows of carbon and nutrients for crop, grassland, forest, and savanna ecosystems. Required model inputs are: soil texture, current and historical land use, vegetation cover, and daily maximum/minimum tempe...

Complex carbon cycle responses to multi-level warming and supplemental summer rain in the high Arctic.

PubMed

Sharp, Elizabeth D; Sullivan, Patrick F; Steltzer, Heidi; Csank, Adam Z; Welker, Jeffrey M

2013-06-01

The Arctic has experienced rapid warming and, although there are uncertainties, increases in precipitation are projected to accompany future warming. Climate changes are expected to affect magnitudes of gross ecosystem photosynthesis (GEP), ecosystem respiration (ER) and the net ecosystem exchange of CO2 (NEE). Furthermore, ecosystem responses to climate change are likely to be characterized by nonlinearities, thresholds and interactions among system components and the driving variables. These complex interactions increase the difficulty of predicting responses to climate change and necessitate the use of manipulative experiments. In 2003, we established a long-term, multi-level and multi-factor climate change experiment in a polar semidesert in northwest Greenland. Two levels of heating (30 and 60 W m(-2) ) were applied and the higher level was combined with supplemental summer rain. We made plot-level measurements of CO2 exchange, plant community composition, foliar nitrogen concentrations, leaf δ(13) C and NDVI to examine responses to our treatments at ecosystem- and leaf-levels. We confronted simple models of GEP and ER with our data to test hypotheses regarding key drivers of CO2 exchange and to estimate growing season CO2 -C budgets. Low-level warming increased the magnitude of the ecosystem C sink. Meanwhile, high-level warming made the ecosystem a source of C to the atmosphere. When high-level warming was combined with increased summer rain, the ecosystem became a C sink of magnitude similar to that observed under low-level warming. Competition among our ER models revealed the importance of soil moisture as a driving variable, likely through its effects on microbial activity and nutrient cycling. Measurements of community composition and proxies for leaf-level physiology suggest GEP responses largely reflect changes in leaf area of Salix arctica, rather than changes in leaf-level physiology. Our findings indicate that the sign and magnitude of the future High Arctic C budget may depend upon changes in summer rain. © 2013 Blackwell Publishing Ltd.

Seasonality of semi-arid and savanna-type ecosystems in an Earth system model

NASA Astrophysics Data System (ADS)

Dahlin, K.; Swenson, S. C.; Lombardozzi, D.; Kamoske, A.

2016-12-01

Recent work has identified semi-arid and savanna-type (SAST) ecosystems as a critical component of interannual variability in the Earth system (Poulter et al. 2014, Ahlström et al. 2015), yet our understanding of the spatial and temporal patterns present in these systems remains limited. There are three major factors that contribute to the complex behavior of SAST ecosystems, globally. First is leaf phenology, the timing of the appearance, presence, and senescence of plant leaves. Plants grow and drop their leaves in response to a variety of cues, including soil moisture, rainfall, day length, and relative humidity, and alternative phenological strategies might often co-exist in the same location. The second major factor in savannas is soil moisture. The complex nature of soil behavior under extremely dry, then extremely wet conditions is critical to our understanding of how savannas function. The third factor is fire. Globally, virtually all savanna-type ecosystems operate with some non-zero fire return interval. Here we compare model output from the Community Land Model (CLM5-BGC) in SAST regions to remotely sensed data on these three variables - phenology (MODIS LAI), soil moisture (SMAP), and fire (GFED4) - assessing both annual spatial patterns and intra-annual variability, which is critical in these highly variable systems. We present new SAST-specific first- and second-order benchmarks, including numbers of annual LAI peaks (often >1 in SAST systems) and correlations between soil moisture, LAI, and fire. Developing a better understanding of how plants respond to seasonal patterns is a critical first step in understanding how SAST ecosystems will respond to and influence climate under future scenarios.

SIMPPLLE, version 2.5 user's guide

Treesearch

Jimmie D. Chew; Kirk Moeller; Christine Stalling

2012-01-01

SIMPPLLE is a spatially-interactive, dynamic landscape modeling system for projecting temporal changes in the spatial distribution of vegetation in response to insects, disease, wildland fire, and other natural and management-caused disturbances. SIMPPLLE is designed to provide a balance between incorporating enough complexity and interactions in modeling ecosystem...

MODELLING QUALITY ASSURANCE PLAN FOR THE LAKE MICHIGAN MASS BALANCE PROJECT

EPA Science Inventory

With the ever increasing complexity and costs of ecosystem protection and remediation, the USEPA is placing more emphasis on ensuring the quality and credibility of scientific tools, such as models, that are used to help guide decision-makers who are faced with difficult manageme...

Interpreting Carbon Fluxes from a Spatially Heterogeneous Peatland with Thawing Permafrost: Scaling from Plant Community Scale to Ecosystem Scale

NASA Astrophysics Data System (ADS)

Harder, S. R.; Roulet, N. T.; Strachan, I. B.; Crill, P. M.; Persson, A.; Pelletier, L.; Watt, C.

2014-12-01

Various microforms, created by spatial differential thawing of permafrost, make up the subarctic heterogeneous Stordalen peatland complex (68°22'N, 19°03'E), near Abisko, Sweden. This results in significantly different peatland vegetation communities across short distances, as well as differences in wetness, temperature and peat substrates. We have been measuring the spatially integrated CO2, heat and water vapour fluxes from this peatland complex using eddy covariance and the CO2 exchange from specific plant communities within the EC tower footprint since spring 2008. With this data we are examining if it is possible to derive the spatially integrated ecosystem-wide fluxes from community-level simple light use efficiency (LUE) and ecosystem respiration (ER) models. These models have been developed using several years of continuous autochamber flux measurements for the three major plant functional types (PFTs) as well as knowledge of the spatial variability of the vegetation, water table and active layer depths. LIDAR was used to produce a 1 m resolution digital evaluation model of the complex and the spatial distribution of PFTs was obtained from concurrent high-resolution digital colour air photography trained from vegetation surveys. Continuous water table depths have been measured for four years at over 40 locations in the complex, and peat temperatures and active layer depths are surveyed every 10 days at more than 100 locations. The EC footprint is calculated for every half-hour and the PFT based models are run with the corresponding environmental variables weighted for the PFTs within the EC footprint. Our results show that the Sphagnum, palsa, and sedge PFTs have distinctly different LUE models, and that the tower fluxes are dominated by a blend of the Sphagnum and palsa PFTs. We also see a distinctly different energy partitioning between the fetches containing intact palsa and those with thawed palsa: the evaporative efficiency is higher and the Bowen ration lower for the thawed palsa fetches.

Soil fertility assessment in the 3 PG model using site index in the southeastern United States

Treesearch

Santosh Subedi; Thomas R. Fox

2016-01-01

Soil fertility is one of the most important, yet least understood aspects of forest ecosystems. Study of soil fertility in forest ecosystems is complicated by the complex relationship between soil properties and stand productivity and immense variability in properties and characteristics of soils within relatively small geographic areas. Furthermore, the deep rooting...

A Socio-Ecological Approach for Identifying and Contextualising Spatial Ecosystem-Based Adaptation Priorities at the Sub-National Level

PubMed Central

Bourne, Amanda; Holness, Stephen; Holden, Petra; Scorgie, Sarshen; Donatti, Camila I.; Midgley, Guy

2016-01-01

Climate change adds an additional layer of complexity to existing sustainable development and biodiversity conservation challenges. The impacts of global climate change are felt locally, and thus local governance structures will increasingly be responsible for preparedness and local responses. Ecosystem-based adaptation (EbA) options are gaining prominence as relevant climate change solutions. Local government officials seldom have an appropriate understanding of the role of ecosystem functioning in sustainable development goals, or access to relevant climate information. Thus the use of ecosystems in helping people adapt to climate change is limited partially by the lack of information on where ecosystems have the highest potential to do so. To begin overcoming this barrier, Conservation South Africa in partnership with local government developed a socio-ecological approach for identifying spatial EbA priorities at the sub-national level. Using GIS-based multi-criteria analysis and vegetation distribution models, the authors have spatially integrated relevant ecological and social information at a scale appropriate to inform local level political, administrative, and operational decision makers. This is the first systematic approach of which we are aware that highlights spatial priority areas for EbA implementation. Nodes of socio-ecological vulnerability are identified, and the inclusion of areas that provide ecosystem services and ecological resilience to future climate change is innovative. The purpose of this paper is to present and demonstrate a methodology for combining complex information into user-friendly spatial products for local level decision making on EbA. The authors focus on illustrating the kinds of products that can be generated from combining information in the suggested ways, and do not discuss the nuance of climate models nor present specific technical details of the model outputs here. Two representative case studies from rural South Africa demonstrate the replicability of this approach in rural and peri-urban areas of other developing and least developed countries around the world. PMID:27227671

A Socio-Ecological Approach for Identifying and Contextualising Spatial Ecosystem-Based Adaptation Priorities at the Sub-National Level.

PubMed

Bourne, Amanda; Holness, Stephen; Holden, Petra; Scorgie, Sarshen; Donatti, Camila I; Midgley, Guy

2016-01-01

Climate change adds an additional layer of complexity to existing sustainable development and biodiversity conservation challenges. The impacts of global climate change are felt locally, and thus local governance structures will increasingly be responsible for preparedness and local responses. Ecosystem-based adaptation (EbA) options are gaining prominence as relevant climate change solutions. Local government officials seldom have an appropriate understanding of the role of ecosystem functioning in sustainable development goals, or access to relevant climate information. Thus the use of ecosystems in helping people adapt to climate change is limited partially by the lack of information on where ecosystems have the highest potential to do so. To begin overcoming this barrier, Conservation South Africa in partnership with local government developed a socio-ecological approach for identifying spatial EbA priorities at the sub-national level. Using GIS-based multi-criteria analysis and vegetation distribution models, the authors have spatially integrated relevant ecological and social information at a scale appropriate to inform local level political, administrative, and operational decision makers. This is the first systematic approach of which we are aware that highlights spatial priority areas for EbA implementation. Nodes of socio-ecological vulnerability are identified, and the inclusion of areas that provide ecosystem services and ecological resilience to future climate change is innovative. The purpose of this paper is to present and demonstrate a methodology for combining complex information into user-friendly spatial products for local level decision making on EbA. The authors focus on illustrating the kinds of products that can be generated from combining information in the suggested ways, and do not discuss the nuance of climate models nor present specific technical details of the model outputs here. Two representative case studies from rural South Africa demonstrate the replicability of this approach in rural and peri-urban areas of other developing and least developed countries around the world.

A Web Interface for Eco System Modeling

NASA Astrophysics Data System (ADS)

McHenry, K.; Kooper, R.; Serbin, S. P.; LeBauer, D. S.; Desai, A. R.; Dietze, M. C.

2012-12-01

We have developed the Predictive Ecosystem Analyzer (PEcAn) as an open-source scientific workflow system and ecoinformatics toolbox that manages the flow of information in and out of regional-scale terrestrial biosphere models, facilitates heterogeneous data assimilation, tracks data provenance, and enables more effective feedback between models and field research. The over-arching goal of PEcAn is to make otherwise complex analyses transparent, repeatable, and accessible to a diverse array of researchers, allowing both novice and expert users to focus on using the models to examine complex ecosystems rather than having to deal with complex computer system setup and configuration questions in order to run the models. Through the developed web interface we hide much of the data and model details and allow the user to simply select locations, ecosystem models, and desired data sources as inputs to the model. Novice users are guided by the web interface through setting up a model execution and plotting the results. At the same time expert users are given enough freedom to modify specific parameters before the model gets executed. This will become more important as more and more models are added to the PEcAn workflow as well as more and more data that will become available as NEON comes online. On the backend we support the execution of potentially computationally expensive models on different High Performance Computers (HPC) and/or clusters. The system can be configured with a single XML file that gives it the flexibility needed for configuring and running the different models on different systems using a combination of information stored in a database as well as pointers to files on the hard disk. While the web interface usually creates this configuration file, expert users can still directly edit it to fine tune the configuration.. Once a workflow is finished the web interface will allow for the easy creation of plots over result data while also allowing the user to download the results for further processing. The current workflow in the web interface is a simple linear workflow, but will be expanded to allow for more complex workflows. We are working with Kepler and Cyberintegrator to allow for these more complex workflows as well as collecting provenance of the workflow being executed. This provenance regarding model executions is stored in a database along with the derived results. All of this information is then accessible using the BETY database web frontend. The PEcAn interface.

Historical Trends in pH and Carbonate Biogeochemistry on the Belize Mesoamerican Barrier Reef System

NASA Astrophysics Data System (ADS)

Fowell, S. E.; Foster, G. L.; Ries, J. B.; Castillo, K. D.; de la Vega, E.; Tyrrell, T.; Donald, H. K.; Chalk, T. B.

2018-04-01

Coral reefs are important ecosystems that are increasingly negatively impacted by human activities. Understanding which anthropogenic stressors play the most significant role in their decline is vital for the accurate prediction of future trends in coral reef health and for effective mitigation of these threats. Here we present annually resolved boron and carbon isotope measurements of two cores capturing the past 90 years of growth of the tropical reef-building coral Siderastrea siderea from the Belize Mesoamerican Barrier Reef System. The pairing of these two isotope systems allows us to parse the reconstructed pH change into relative changes in net ecosystem productivity and net ecosystem calcification between the two locations. This approach reveals that the relationship between seawater pH and coral calcification, at both a colony and ecosystem level, is complex and cannot simply be modeled as linear or even positive. This study also underscores both the utility of coupled δ11B-δ13C measurements in tracing past biogeochemical cycling in coral reefs and the complexity of this cycling relative to the open ocean.

Controlled Environments Enable Adaptive Management in Aquatic Ecosystems Under Altered Environments

NASA Technical Reports Server (NTRS)

Bubenheim, David L.

2016-01-01

Ecosystems worldwide are impacted by altered environment conditions resulting from climate, drought, and land use changes. Gaps in the science knowledge base regarding plant community response to these novel and rapid changes limit both science understanding and management of ecosystems. We describe how CE Technologies have enabled the rapid supply of gap-filling science, development of ecosystem simulation models, and remote sensing assessment tools to provide science-informed, adaptive management methods in the impacted aquatic ecosystem of the California Sacramento-San Joaquin River Delta. The Delta is the hub for California's water, supplying Southern California agriculture and urban communities as well as the San Francisco Bay area. The changes in environmental conditions including temperature, light, and water quality and associated expansion of invasive aquatic plants negatively impact water distribution and ecology of the San Francisco Bay/Delta complex. CE technologies define changes in resource use efficiencies, photosynthetic productivity, evapotranspiration, phenology, reproductive strategies, and spectral reflectance modifications in native and invasive species in response to altered conditions. We will discuss how the CE technologies play an enabling role in filling knowledge gaps regarding plant response to altered environments, parameterization and validation of ecosystem models, development of satellite-based, remote sensing tools, and operational management strategies.

Wetland Hydrology

EPA Science Inventory

This chapter discusses the state of the science in wetland hydrology by touching upon the major hydraulic and hydrologic processes in these complex ecosystems, their measurement/estimation techniques, and modeling methods. It starts with the definition of wetlands, their benefit...

Modeling the impact of forest biomass change on the subsequent ground level solar energy to enhance the understanding of ecosystem service tradeoffs

EPA Science Inventory

Background/Question/Methods Solar radiation is a significant environmental driver that impacts the quality and resilience of terrestrial and aquatic habitats, yet its spatiotemporal variations are complicated to model accurately at high resolution over large, complex watersheds. ...

Functional responses and scaling in predator-prey interactions of marine fishes: contemporary issues and emerging concepts.

PubMed

Hunsicker, Mary E; Ciannelli, Lorenzo; Bailey, Kevin M; Buckel, Jeffrey A; Wilson White, J; Link, Jason S; Essington, Timothy E; Gaichas, Sarah; Anderson, Todd W; Brodeur, Richard D; Chan, Kung-Sik; Chen, Kun; Englund, Göran; Frank, Kenneth T; Freitas, Vânia; Hixon, Mark A; Hurst, Thomas; Johnson, Darren W; Kitchell, James F; Reese, Doug; Rose, George A; Sjodin, Henrik; Sydeman, William J; van der Veer, Henk W; Vollset, Knut; Zador, Stephani

2011-12-01

Predator-prey interactions are a primary structuring force vital to the resilience of marine communities and sustainability of the world's oceans. Human influences on marine ecosystems mediate changes in species interactions. This generality is evinced by the cascading effects of overharvesting top predators on the structure and function of marine ecosystems. It follows that ecological forecasting, ecosystem management, and marine spatial planning require a better understanding of food web relationships. Characterising and scaling predator-prey interactions for use in tactical and strategic tools (i.e. multi-species management and ecosystem models) are paramount in this effort. Here, we explore what issues are involved and must be considered to advance the use of predator-prey theory in the context of marine fisheries science. We address pertinent contemporary ecological issues including (1) the approaches and complexities of evaluating predator responses in marine systems; (2) the 'scaling up' of predator-prey interactions to the population, community, and ecosystem level; (3) the role of predator-prey theory in contemporary fisheries and ecosystem modelling approaches; and (4) directions for the future. Our intent is to point out needed research directions that will improve our understanding of predator-prey interactions in the context of the sustainable marine fisheries and ecosystem management. 2011 Blackwell Publishing Ltd/CNRS.

Disturbance, complexity, and succession of net ecosystem production in North America’s temperate deciduous forests

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gough, Christopher; Curtis, Peter; Hardiman, Brady

Century-old forests in the U.S. upper Midwest and Northeast power much of North Amer- ica’s terrestrial carbon (C) sink, but these forests’ production and C sequestration capacity are expected to soon decline as fast-growing early successional species die and are replaced by slower growing late successional species. But will this really happen? Here we marshal empirical data and ecological theory to argue that substantial declines in net ecosystem production (NEP) owing to reduced forest growth, or net primary production (NPP), are not imminent in regrown temperate deciduous forests over the next several decades. Forest age and production data for temperatemore » deciduous forests, synthesized from published literature, suggest slight declines in NEP and increasing or stable NPP during middle successional stages. We revisit long-held hypotheses by EP Odum and others that suggest low-severity, high-frequency disturbances occurring in the region’s aging forests will, against intuition, maintain NEP at higher-than- expected rates by increasing ecosystem complexity, sustaining or enhancing NPP to a level that largely o sets rising C losses as heterotrophic respiration increases. This theoretical model is also supported by biological evidence and observations from the Forest Accelerated Succession Experiment in Michigan, USA. Ecosystems that experience high-severity disturbances that simplify ecosystem complexity can exhibit substantial declines in production during middle stages of succession. However, observations from these ecosystems have exerted a disproportionate in uence on assumptions regarding the trajectory and magnitude of age-related declines in forest production. We conclude that there is a wide ecological space for forests to maintain NPP and, in doing so, lessens the declines in NEP, with signi cant implications for the future of the North American carbon sink. Our intellectual frameworks for understanding forest C cycle dynamics and resilience need to catch up to our more complex and nuanced understanding of ecological succession.« less

Ecosystem services provided by a complex coastal region: challenges of classification and mapping.

PubMed

Sousa, Lisa P; Sousa, Ana I; Alves, Fátima L; Lillebø, Ana I

2016-03-11

A variety of ecosystem services classification systems and mapping approaches are available in the scientific and technical literature, which needs to be selected and adapted when applied to complex territories (e.g. in the interface between water and land, estuary and sea). This paper provides a framework for addressing ecosystem services in complex coastal regions. The roadmap comprises the definition of the exact geographic boundaries of the study area; the use of CICES (Common International Classification of Ecosystem Services) for ecosystem services identification and classification; and the definition of qualitative indicators that will serve as basis to map the ecosystem services. Due to its complexity, the Ria de Aveiro coastal region was selected as case study, presenting an opportunity to explore the application of such approaches at a regional scale. The main challenges of implementing the proposed roadmap, together with its advantages are discussed in this research. The results highlight the importance of considering both the connectivity of natural systems and the complexity of the governance framework; the flexibility and robustness, but also the challenges when applying CICES at regional scale; and the challenges regarding ecosystem services mapping.

Ecosystem services provided by a complex coastal region: challenges of classification and mapping

PubMed Central

Sousa, Lisa P.; Sousa, Ana I.; Alves, Fátima L.; Lillebø, Ana I.

2016-01-01

A variety of ecosystem services classification systems and mapping approaches are available in the scientific and technical literature, which needs to be selected and adapted when applied to complex territories (e.g. in the interface between water and land, estuary and sea). This paper provides a framework for addressing ecosystem services in complex coastal regions. The roadmap comprises the definition of the exact geographic boundaries of the study area; the use of CICES (Common International Classification of Ecosystem Services) for ecosystem services identification and classification; and the definition of qualitative indicators that will serve as basis to map the ecosystem services. Due to its complexity, the Ria de Aveiro coastal region was selected as case study, presenting an opportunity to explore the application of such approaches at a regional scale. The main challenges of implementing the proposed roadmap, together with its advantages are discussed in this research. The results highlight the importance of considering both the connectivity of natural systems and the complexity of the governance framework; the flexibility and robustness, but also the challenges when applying CICES at regional scale; and the challenges regarding ecosystem services mapping. PMID:26964892

Climate change and the EU Water Framework Directive: how to deal with indirect effects of changes in hydrology on water quality and ecology?

PubMed

Heerdt, G N J Ter; Schep, S A; Janse, J H; Ouboter, M

2007-01-01

In order to set ecological goals and determine measures for the European Water Framework Directive, the effects of climate change on lake ecosystems should be estimated. It is thought that the complexity of lake ecosystems makes this effect inherently unpredictable. However, models that deal with this complexity are available and well calibrated and tested. In this study we use the ecosystem model PCLake to demonstrate how climate change might affect the ecological status of a shallow peaty lake in 2050. With the model PCLake, combined with a long-term water and nutrient balance, it is possible to describe adequately the present status of the lake. Simulations of future scenarios with increasing precipitation, evaporation and temperature, showed that climate change will lead to higher nutrient loadings. At the same time, it will lead to lower critical loadings. Together this might cause the lake to shift easier from a clear water to a turbid state. The amount of algae, expressed as the concentration Chl-a, will increase, as a consequence turbidity will increase. The outcome of this study; increasing stability of the turbid state of the lake, and thus the need for more drastic measures, is consistent with some earlier studies.

Diversification versus specialization in complex ecosystems.

PubMed

Di Clemente, Riccardo; Chiarotti, Guido L; Cristelli, Matthieu; Tacchella, Andrea; Pietronero, Luciano

2014-01-01

By analyzing the distribution of revenues across the production sectors of quoted firms we suggest a novel dimension that drives the firms diversification process at country level. Data show a non trivial macro regional clustering of the diversification process, which underlines the relevance of geopolitical environments in determining the microscopic dynamics of economic entities. These findings demonstrate the possibility of singling out in complex ecosystems those micro-features that emerge at macro-levels, which could be of particular relevance for decision-makers in selecting the appropriate parameters to be acted upon in order to achieve desirable results. The understanding of this micro-macro information exchange is further deepened through the introduction of a simplified dynamic model.

Diversification versus Specialization in Complex Ecosystems

PubMed Central

Di Clemente, Riccardo; Chiarotti, Guido L.; Cristelli, Matthieu; Tacchella, Andrea; Pietronero, Luciano

2014-01-01

By analyzing the distribution of revenues across the production sectors of quoted firms we suggest a novel dimension that drives the firms diversification process at country level. Data show a non trivial macro regional clustering of the diversification process, which underlines the relevance of geopolitical environments in determining the microscopic dynamics of economic entities. These findings demonstrate the possibility of singling out in complex ecosystems those micro-features that emerge at macro-levels, which could be of particular relevance for decision-makers in selecting the appropriate parameters to be acted upon in order to achieve desirable results. The understanding of this micro-macro information exchange is further deepened through the introduction of a simplified dynamic model. PMID:25384059

System Thinking and Feeding Relations: Learning with a Live Ecosystem Model

ERIC Educational Resources Information Center

Eilam, Billie

2012-01-01

Considering well-documented difficulties in mastering ecology concepts and system thinking, the aim of the study was to examine 9th graders' understanding of the complex, multilevel, systemic construct of feeding relations, nested within a larger system of a live model. Fifty students interacted with the model and manipulated a variable within it…

Fort Collins Science Center Ecosystem Dynamics Branch

USGS Publications Warehouse

Wilson, Jim; Melcher, C.; Bowen, Z.

2009-01-01

Complex natural resource issues require understanding a web of interactions among ecosystem components that are (1) interdisciplinary, encompassing physical, chemical, and biological processes; (2) spatially complex, involving movements of animals, water, and airborne materials across a range of landscapes and jurisdictions; and (3) temporally complex, occurring over days, weeks, or years, sometimes involving response lags to alteration or exhibiting large natural variation. Scientists in the Ecosystem Dynamics Branch of the U.S. Geological Survey, Fort Collins Science Center, investigate a diversity of these complex natural resource questions at the landscape and systems levels. This Fact Sheet describes the work of the Ecosystems Dynamics Branch, which is focused on energy and land use, climate change and long-term integrated assessments, herbivore-ecosystem interactions, fire and post-fire restoration, and environmental flows and river restoration.

Broad-scale climate influences on spring-spawning herring (Clupea harengus, L.) recruitment in the Western Baltic Sea.

PubMed

Gröger, Joachim P; Hinrichsen, Hans-Harald; Polte, Patrick

2014-01-01

Climate forcing in complex ecosystems can have profound implications for ecosystem sustainability and may thus challenge a precautionary ecosystem management. Climatic influences documented to affect various ecological functions on a global scale, may themselves be observed on quantitative or qualitative scales including regime shifts in complex marine ecosystems. This study investigates the potential climatic impact on the reproduction success of spring-spawning herring (Clupea harengus) in the Western Baltic Sea (WBSS herring). To test for climate effects on reproduction success, the regionally determined and scientifically well-documented spawning grounds of WBSS herring represent an ideal model system. Climate effects on herring reproduction were investigated using two global indices of atmospheric variability and sea surface temperature, represented by the North Atlantic Oscillation (NAO) and the Atlantic Multi-decadal Oscillation (AMO), respectively, and the Baltic Sea Index (BSI) which is a regional-scale atmospheric index for the Baltic Sea. Moreover, we combined a traditional approach with modern time series analysis based on a recruitment model connecting parental population components with reproduction success. Generalized transfer functions (ARIMAX models) allowed evaluating the dynamic nature of exogenous climate processes interacting with the endogenous recruitment process. Using different model selection criteria our results reveal that in contrast to NAO and AMO, the BSI shows a significant positive but delayed signal on the annual dynamics of herring recruitment. The westward influence of the Siberian high is considered strongly suppressing the influence of the NAO in this area leading to a higher explanatory power of the BSI reflecting the atmospheric pressure regime on a North-South transect between Oslo, Norway and Szczecin, Poland. We suggest incorporating climate-induced effects into stock and risk assessments and management strategies as part of the EU ecosystem approach to support sustainable herring fisheries in the Western Baltic Sea.

Broad-Scale Climate Influences on Spring-Spawning Herring (Clupea harengus, L.) Recruitment in the Western Baltic Sea

PubMed Central

Gröger, Joachim P.; Hinrichsen, Hans-Harald; Polte, Patrick

2014-01-01

Climate forcing in complex ecosystems can have profound implications for ecosystem sustainability and may thus challenge a precautionary ecosystem management. Climatic influences documented to affect various ecological functions on a global scale, may themselves be observed on quantitative or qualitative scales including regime shifts in complex marine ecosystems. This study investigates the potential climatic impact on the reproduction success of spring-spawning herring (Clupea harengus) in the Western Baltic Sea (WBSS herring). To test for climate effects on reproduction success, the regionally determined and scientifically well-documented spawning grounds of WBSS herring represent an ideal model system. Climate effects on herring reproduction were investigated using two global indices of atmospheric variability and sea surface temperature, represented by the North Atlantic Oscillation (NAO) and the Atlantic Multi-decadal Oscillation (AMO), respectively, and the Baltic Sea Index (BSI) which is a regional-scale atmospheric index for the Baltic Sea. Moreover, we combined a traditional approach with modern time series analysis based on a recruitment model connecting parental population components with reproduction success. Generalized transfer functions (ARIMAX models) allowed evaluating the dynamic nature of exogenous climate processes interacting with the endogenous recruitment process. Using different model selection criteria our results reveal that in contrast to NAO and AMO, the BSI shows a significant positive but delayed signal on the annual dynamics of herring recruitment. The westward influence of the Siberian high is considered strongly suppressing the influence of the NAO in this area leading to a higher explanatory power of the BSI reflecting the atmospheric pressure regime on a North-South transect between Oslo, Norway and Szczecin, Poland. We suggest incorporating climate-induced effects into stock and risk assessments and management strategies as part of the EU ecosystem approach to support sustainable herring fisheries in the Western Baltic Sea. PMID:24586279

Revisiting the Holy Grail: using plant functional traits to understand ecological processes.

PubMed

Funk, Jennifer L; Larson, Julie E; Ames, Gregory M; Butterfield, Bradley J; Cavender-Bares, Jeannine; Firn, Jennifer; Laughlin, Daniel C; Sutton-Grier, Ariana E; Williams, Laura; Wright, Justin

2017-05-01

One of ecology's grand challenges is developing general rules to explain and predict highly complex systems. Understanding and predicting ecological processes from species' traits has been considered a 'Holy Grail' in ecology. Plant functional traits are increasingly being used to develop mechanistic models that can predict how ecological communities will respond to abiotic and biotic perturbations and how species will affect ecosystem function and services in a rapidly changing world; however, significant challenges remain. In this review, we highlight recent work and outstanding questions in three areas: (i) selecting relevant traits; (ii) describing intraspecific trait variation and incorporating this variation into models; and (iii) scaling trait data to community- and ecosystem-level processes. Over the past decade, there have been significant advances in the characterization of plant strategies based on traits and trait relationships, and the integration of traits into multivariate indices and models of community and ecosystem function. However, the utility of trait-based approaches in ecology will benefit from efforts that demonstrate how these traits and indices influence organismal, community, and ecosystem processes across vegetation types, which may be achieved through meta-analysis and enhancement of trait databases. Additionally, intraspecific trait variation and species interactions need to be incorporated into predictive models using tools such as Bayesian hierarchical modelling. Finally, existing models linking traits to community and ecosystem processes need to be empirically tested for their applicability to be realized. © 2016 Cambridge Philosophical Society.

Modelling and predicting the spatial distribution of tree root density in heterogeneous forest ecosystems

PubMed Central

Mao, Zhun; Saint-André, Laurent; Bourrier, Franck; Stokes, Alexia; Cordonnier, Thomas

2015-01-01

Background and Aims In mountain ecosystems, predicting root density in three dimensions (3-D) is highly challenging due to the spatial heterogeneity of forest communities. This study presents a simple and semi-mechanistic model, named ChaMRoots, that predicts root interception density (RID, number of roots m–2). ChaMRoots hypothesizes that RID at a given point is affected by the presence of roots from surrounding trees forming a polygon shape. Methods The model comprises three sub-models for predicting: (1) the spatial heterogeneity – RID of the finest roots in the top soil layer as a function of tree basal area at breast height, and the distance between the tree and a given point; (2) the diameter spectrum – the distribution of RID as a function of root diameter up to 50 mm thick; and (3) the vertical profile – the distribution of RID as a function of soil depth. The RID data used for fitting in the model were measured in two uneven-aged mountain forest ecosystems in the French Alps. These sites differ in tree density and species composition. Key Results In general, the validation of each sub-model indicated that all sub-models of ChaMRoots had good fits. The model achieved a highly satisfactory compromise between the number of aerial input parameters and the fit to the observed data. Conclusions The semi-mechanistic ChaMRoots model focuses on the spatial distribution of root density at the tree cluster scale, in contrast to the majority of published root models, which function at the level of the individual. Based on easy-to-measure characteristics, simple forest inventory protocols and three sub-models, it achieves a good compromise between the complexity of the case study area and that of the global model structure. ChaMRoots can be easily coupled with spatially explicit individual-based forest dynamics models and thus provides a highly transferable approach for modelling 3-D root spatial distribution in complex forest ecosystems. PMID:26173892

A Conceptual Model of Natural and Anthropogenic Drivers and Their Influence on the Prince William Sound, Alaska, Ecosystem

PubMed Central

Harwell, Mark A.; Gentile, John H.; Cummins, Kenneth W.; Highsmith, Raymond C.; Hilborn, Ray; McRoy, C. Peter; Parrish, Julia; Weingartner, Thomas

2010-01-01

Prince William Sound (PWS) is a semi-enclosed fjord estuary on the coast of Alaska adjoining the northern Gulf of Alaska (GOA). PWS is highly productive and diverse, with primary productivity strongly coupled to nutrient dynamics driven by variability in the climate and oceanography of the GOA and North Pacific Ocean. The pelagic and nearshore primary productivity supports a complex and diverse trophic structure, including large populations of forage and large fish that support many species of marine birds and mammals. High intra-annual, inter-annual, and interdecadal variability in climatic and oceanographic processes as drives high variability in the biological populations. A risk-based conceptual ecosystem model (CEM) is presented describing the natural processes, anthropogenic drivers, and resultant stressors that affect PWS, including stressors caused by the Great Alaska Earthquake of 1964 and the Exxon Valdez oil spill of 1989. A trophodynamic model incorporating PWS valued ecosystem components is integrated into the CEM. By representing the relative strengths of driver/stressors/effects, the CEM graphically demonstrates the fundamental dynamics of the PWS ecosystem, the natural forces that control the ecological condition of the Sound, and the relative contribution of natural processes and human activities to the health of the ecosystem. The CEM illustrates the dominance of natural processes in shaping the structure and functioning of the GOA and PWS ecosystems. PMID:20862192

A Conceptual Model of Natural and Anthropogenic Drivers and Their Influence on the Prince William Sound, Alaska, Ecosystem.

PubMed

Harwell, Mark A; Gentile, John H; Cummins, Kenneth W; Highsmith, Raymond C; Hilborn, Ray; McRoy, C Peter; Parrish, Julia; Weingartner, Thomas

2010-07-01

Prince William Sound (PWS) is a semi-enclosed fjord estuary on the coast of Alaska adjoining the northern Gulf of Alaska (GOA). PWS is highly productive and diverse, with primary productivity strongly coupled to nutrient dynamics driven by variability in the climate and oceanography of the GOA and North Pacific Ocean. The pelagic and nearshore primary productivity supports a complex and diverse trophic structure, including large populations of forage and large fish that support many species of marine birds and mammals. High intra-annual, inter-annual, and interdecadal variability in climatic and oceanographic processes as drives high variability in the biological populations. A risk-based conceptual ecosystem model (CEM) is presented describing the natural processes, anthropogenic drivers, and resultant stressors that affect PWS, including stressors caused by the Great Alaska Earthquake of 1964 and the Exxon Valdez oil spill of 1989. A trophodynamic model incorporating PWS valued ecosystem components is integrated into the CEM. By representing the relative strengths of driver/stressors/effects, the CEM graphically demonstrates the fundamental dynamics of the PWS ecosystem, the natural forces that control the ecological condition of the Sound, and the relative contribution of natural processes and human activities to the health of the ecosystem. The CEM illustrates the dominance of natural processes in shaping the structure and functioning of the GOA and PWS ecosystems.

Using global sensitivity analysis to understand higher order interactions in complex models: an application of GSA on the Revised Universal Soil Loss Equation (RUSLE) to quantify model sensitivity and implications for ecosystem services management in Costa Rica

NASA Astrophysics Data System (ADS)

Fremier, A. K.; Estrada Carmona, N.; Harper, E.; DeClerck, F.

2011-12-01

Appropriate application of complex models to estimate system behavior requires understanding the influence of model structure and parameter estimates on model output. To date, most researchers perform local sensitivity analyses, rather than global, because of computational time and quantity of data produced. Local sensitivity analyses are limited in quantifying the higher order interactions among parameters, which could lead to incomplete analysis of model behavior. To address this concern, we performed a GSA on a commonly applied equation for soil loss - the Revised Universal Soil Loss Equation. USLE is an empirical model built on plot-scale data from the USA and the Revised version (RUSLE) includes improved equations for wider conditions, with 25 parameters grouped into six factors to estimate long-term plot and watershed scale soil loss. Despite RUSLE's widespread application, a complete sensitivity analysis has yet to be performed. In this research, we applied a GSA to plot and watershed scale data from the US and Costa Rica to parameterize the RUSLE in an effort to understand the relative importance of model factors and parameters across wide environmental space. We analyzed the GSA results using Random Forest, a statistical approach to evaluate parameter importance accounting for the higher order interactions, and used Classification and Regression Trees to show the dominant trends in complex interactions. In all GSA calculations the management of cover crops (C factor) ranks the highest among factors (compared to rain-runoff erosivity, topography, support practices, and soil erodibility). This is counter to previous sensitivity analyses where the topographic factor was determined to be the most important. The GSA finding is consistent across multiple model runs, including data from the US, Costa Rica, and a synthetic dataset of the widest theoretical space. The three most important parameters were: Mass density of live and dead roots found in the upper inch of soil (C factor), slope angle (L and S factor), and percentage of land area covered by surface cover (C factor). Our findings give further support to the importance of vegetation as a vital ecosystem service provider - soil loss reduction. Concurrent, progress is already been made in Costa Rica, where dam managers are moving forward on a Payment for Ecosystem Services scheme to help keep private lands forested and to improve crop management through targeted investments. Use of complex watershed models, such as RUSLE can help managers quantify the effect of specific land use changes. Moreover, effective land management of vegetation has other important benefits, such as bundled ecosystem services (e.g. pollination, habitat connectivity, etc) and improvements of communities' livelihoods.

Integrated evaluation of the vulnerability to thermokarst disturbance and its implications for the regional carbon balance in boreal Alaska

NASA Astrophysics Data System (ADS)

Helene, G.; Lara, M. J.; McGuire, A. D.; Euskirchen, E. S.; Bolton, W. R.; Romanovsky, V. E.

2017-12-01

Our capacity to project future ecosystem trajectories in northern permafrost regions depends on our ability to characterize complex interactions between climatic and ecological processes at play in the soil, the vegetation, and the atmosphere. We present a study that uses remote sensing analyses, field observations, and data synthesis to inform models for the prediction of ecosystem responses to climate change in the boreal zone of Alaska. Recent warming, altered precipitation and fire regimes are driving permafrost degradation, threatening to mobilize vast reservoirs of ancient carbon previously protected from decomposition. Although large scale, progressive, top-down permafrost thaw have been well studied and represented in high-latitude ecosystem models, the consequences of abrupt and local thermokarst disturbances (TK) are less well understood. To fill this gap, we conducted a detection analysis characterizing 60 years of land cover change in the Tanana Flats, a wetland complex subjected to TK disturbance in Interior Alaska, using aerial and satellite images. We observed a nonlinear loss of permafrost plateau forest associated with TK and driven by precipitation and forest fragmentation. The results of this analysis were integrated into the Alaska Thermokarst Model (ATM), a state-and-transition model that simulates land cover change associated with TK disturbance. Thermokarst-related land cover change was simulated from 2000 to 2100 across the Tanana Flats. By 2100, the model predicts a mean decrease of 7.4% (sd 1.8%) in permafrost plateau forests associated with an increase in TK fens and bogs. Transitions from permafrost plateau forests to TK wetlands are accompanied with changes in physical and biogeochemical processes affecting ecosystem carbon balance. We evaluated the consequences of TK disturbances on the regional carbon balance by coupling outputs from the ATM and from a process-based biogeochemical model. We used long-term field observations of vegetation and soil physical and biogeochemical attributes to develop new parameterizations for TK wetlands and permafrost plateau forest land cover types. Preliminary simulations from 2000 to 2100 estimate that the conversion of permafrost plateau forest to young TK wetlands would result in a 7.5% (sd 3.5%) decrease in Net Ecosystem Exchange.

Trophic flow structure of a neotropical estuary in northeastern Brazil and the comparison of ecosystem model indicators of estuaries

NASA Astrophysics Data System (ADS)

Lira, Alex; Angelini, Ronaldo; Le Loc'h, François; Ménard, Frédéric; Lacerda, Carlos; Frédou, Thierry; Lucena Frédou, Flávia

2018-06-01

We developed an Ecopath model for the Estuary of Sirinhaém River (SIR), a small-sized system surrounded by mangroves, subject to high impact, mainly by the sugar cane and other farming industries in order to describe the food web structure and trophic interactions. In addition, we compared our findings with those of 20 available Ecopath estuarine models for tropical, subtropical and temperate regions, aiming to synthesize the knowledge on trophic dynamics and provide a comprehensive analysis of the structures and functioning of estuaries. Our model consisted of 25 compartments and its indicators were within the expected range for estuarine areas around the world. The average trophic transfer efficiency for the entire system was 11.8%, similar to the theoretical value of 10%. The Keystone Index and MTI (Mixed Trophic Impact) analysis indicated that the snook (Centropomus undecimalis and Centropomus parallelus) and jack (Caranx latus and Caranx hippos) are considered as key resources in the system, revealing their high impact in the food web. Both groups have a high ecological and commercial relevance, despite the unregulated fisheries. As result of the comparison of ecosystem model indicators in estuaries, differences in the ecosystem structure from the low latitude zones (tropical estuaries) to the high latitude zones (temperate system) were noticed. The structure of temperate and sub-tropical estuaries is based on high flows of detritus and export, while tropical systems have high biomass, respiration and consumption rates. Higher values of System Omnivory Index (SOI) and Overhead (SO) were observed in the tropical and subtropical estuaries, denoting a more complex food chain. Globally, none of the estuarine models were classified as fully mature ecosystems, although the tropical ecosystems were considered more mature than the subtropical and temperate ecosystems. This study is an important contribution to the trophic modeling of estuaries, which may also help the knowledge of the role of key ecosystem processes in SIR.

Moderate forest disturbance as a stringent test for gap and big-leaf models

NASA Astrophysics Data System (ADS)

Bond-Lamberty, B.; Fisk, J. P.; Holm, J. A.; Bailey, V.; Bohrer, G.; Gough, C. M.

2015-01-01

Disturbance-induced tree mortality is a key factor regulating the carbon balance of a forest, but tree mortality and its subsequent effects are poorly represented processes in terrestrial ecosystem models. It is thus unclear whether models can robustly simulate moderate (non-catastrophic) disturbances, which tend to increase biological and structural complexity and are increasingly common in aging US forests. We tested whether three forest ecosystem models - Biome-BGC (BioGeochemical Cycles), a classic big-leaf model, and the ZELIG and ED (Ecosystem Demography) gap-oriented models - could reproduce the resilience to moderate disturbance observed in an experimentally manipulated forest (the Forest Accelerated Succession Experiment in northern Michigan, USA, in which 38% of canopy dominants were stem girdled and compared to control plots). Each model was parameterized, spun up, and disturbed following similar protocols and run for 5 years post-disturbance. The models replicated observed declines in aboveground biomass well. Biome-BGC captured the timing and rebound of observed leaf area index (LAI), while ZELIG and ED correctly estimated the magnitude of LAI decline. None of the models fully captured the observed post-disturbance C fluxes, in particular gross primary production or net primary production (NPP). Biome-BGC NPP was correctly resilient but for the wrong reasons, and could not match the absolute observational values. ZELIG and ED, in contrast, exhibited large, unobserved drops in NPP and net ecosystem production. The biological mechanisms proposed to explain the observed rapid resilience of the C cycle are typically not incorporated by these or other models. It is thus an open question whether most ecosystem models will simulate correctly the gradual and less extensive tree mortality characteristic of moderate disturbances.

Moderate forest disturbance as a stringent test for gap and big-leaf models

DOE PAGES

Bond-Lamberty, Benjamin; Fisk, Justin P.; Holm, Jennifer; ...

2015-01-27

Disturbance-induced tree mortality is a key factor regulating the carbon balance of a forest, but tree mortality and its subsequent effects are poorly represented processes in terrestrial ecosystem models. It is thus unclear whether models can robustly simulate moderate (non-catastrophic) disturbances, which tend to increase biological and structural complexity and are increasingly common in aging US forests. We tested whether three forest ecosystem models – Biome-BGC (BioGeochemical Cycles), a classic big-leaf model, and the ZELIG and ED (Ecosystem Demography) gap-oriented models – could reproduce the resilience to moderate disturbance observed in an experimentally manipulated forest (the Forest Accelerated Succession Experimentmore » in northern Michigan, USA, in which 38% of canopy dominants were stem girdled and compared to control plots). Each model was parameterized, spun up, and disturbed following similar protocols and run for 5 years post-disturbance. The models replicated observed declines in aboveground biomass well. Biome-BGC captured the timing and rebound of observed leaf area index (LAI), while ZELIG and ED correctly estimated the magnitude of LAI decline. None of the models fully captured the observed post-disturbance C fluxes, in particular gross primary production or net primary production (NPP). Biome-BGC NPP was correctly resilient but for the wrong reasons, and could not match the absolute observational values. ZELIG and ED, in contrast, exhibited large, unobserved drops in NPP and net ecosystem production. The biological mechanisms proposed to explain the observed rapid resilience of the C cycle are typically not incorporated by these or other models. It is thus an open question whether most ecosystem models will simulate correctly the gradual and less extensive tree mortality characteristic of moderate disturbances.« less

Ecological scenarios analyzed and evaluated by a shallow lake model.

PubMed

Kardaetz, Sascha; Strube, Torsten; Brüggemann, Rainer; Nützmann, Gunnar

2008-07-01

We applied the complex ecosystem model EMMO, which was adopted to the shallow lake Müggelsee (Germany), in order to evaluate a large set of ecological scenarios. By means of EMMO, 33 scenarios and 17 indicators were defined to characterize their effects on the lake ecosystem. The indicators were based on model outputs of EMMO and can be separated into biological indicators, such as chlorophyll-a and cyanobacteria, and hydro-chemical indicators, such as phosphorus. The question to be solved was, what is the ranking of the scenarios based on their characterization by these 17 indicators? And how can we handle high quantities of complex data within evaluation procedures? The scenario evaluation was performed by partial order theory which, however, did not provide a clear result. By subsequently applying the hierarchical cluster analysis (complete linkage) it was possible to reduce the data matrix to indicator and scenario representatives. Even though this step implies losses of information, it simplifies the application of partial order theory and the post processing by METEOR. METEOR is derived from partial order theory and allows the stepwise aggregation of indicators, which subsequently leads to a distinct and clear decision. In the final evaluation result the best scenario was the one which defines a minimum nutrient input and no phosphorus release from the sediment while the worst scenario is characterized by a maximum nutrient input and extensive phosphorus release from the sediment. The reasonable and comprehensive results show that the combination of partial order, cluster analysis and METEOR can handle big amounts of data in a very clear and transparent way, and therefore is ideal in the context of complex ecosystem models, like that we applied.

Challenges and opportunities for integrating lake ecosystem modelling approaches

USGS Publications Warehouse

Mooij, Wolf M.; Trolle, Dennis; Jeppesen, Erik; Arhonditsis, George; Belolipetsky, Pavel V.; Chitamwebwa, Deonatus B.R.; Degermendzhy, Andrey G.; DeAngelis, Donald L.; Domis, Lisette N. De Senerpont; Downing, Andrea S.; Elliott, J. Alex; Ruberto, Carlos Ruberto; Gaedke, Ursula; Genova, Svetlana N.; Gulati, Ramesh D.; Hakanson, Lars; Hamilton, David P.; Hipsey, Matthew R.; Hoen, Jochem 't; Hulsmann, Stephan; Los, F. Hans; Makler-Pick, Vardit; Petzoldt, Thomas; Prokopkin, Igor G.; Rinke, Karsten; Schep, Sebastiaan A.; Tominaga, Koji; Van Dam, Anne A.; Van Nes, Egbert H.; Wells, Scott A.; Janse, Jan H.

2010-01-01

A large number and wide variety of lake ecosystem models have been developed and published during the past four decades. We identify two challenges for making further progress in this field. One such challenge is to avoid developing more models largely following the concept of others ('reinventing the wheel'). The other challenge is to avoid focusing on only one type of model, while ignoring new and diverse approaches that have become available ('having tunnel vision'). In this paper, we aim at improving the awareness of existing models and knowledge of concurrent approaches in lake ecosystem modelling, without covering all possible model tools and avenues. First, we present a broad variety of modelling approaches. To illustrate these approaches, we give brief descriptions of rather arbitrarily selected sets of specific models. We deal with static models (steady state and regression models), complex dynamic models (CAEDYM, CE-QUAL-W2, Delft 3D-ECO, LakeMab, LakeWeb, MyLake, PCLake, PROTECH, SALMO), structurally dynamic models and minimal dynamic models. We also discuss a group of approaches that could all be classified as individual based: super-individual models (Piscator, Charisma), physiologically structured models, stage-structured models and trait-based models. We briefly mention genetic algorithms, neural networks, Kalman filters and fuzzy logic. Thereafter, we zoom in, as an in-depth example, on the multi-decadal development and application of the lake ecosystem model PCLake and related models (PCLake Metamodel, Lake Shira Model, IPH-TRIM3D-PCLake). In the discussion, we argue that while the historical development of each approach and model is understandable given its 'leading principle', there are many opportunities for combining approaches. We take the point of view that a single 'right' approach does not exist and should not be strived for. Instead, multiple modelling approaches, applied concurrently to a given problem, can help develop an integrative view on the functioning of lake ecosystems. We end with a set of specific recommendations that may be of help in the further development of lake ecosystem models.

Ecological determinants of health: food and environment on human health.

PubMed

Li, Alice M L

2017-04-01

Human health and diseases are determined by many complex factors. Health threats from the human-animal-ecosystems interface (HAEI) and zoonotic diseases (zoonoses) impose an increasing risk continuously to public health, from those emerging pathogens transmitted through contact with animals, food, water and contaminated environments. Immense challenges forced on the ecological perspectives on food and the eco-environments, including aquaculture, agriculture and the entire food systems. Impacts of food and eco-environments on human health will be examined amongst the importance of human interventions for intended purposes in lowering the adverse effects on the biodiversity. The complexity of relevant conditions defined as factors contributing to the ecological determinants of health will be illuminated from different perspectives based on concepts, citations, examples and models, in conjunction with harmful consequential effects of human-induced disturbances to our environments and food systems, together with the burdens from ecosystem disruption, environmental hazards and loss of ecosystem functions. The eco-health literacy should be further promoting under the "One Health" vision, with "One World" concept under Ecological Public Health Model for sustaining our environments and the planet earth for all beings, which is coincidentally echoing Confucian's theory for the environmental ethics of ecological harmony.

Dry season limnological conditions and basin geology exhibit complex relationships with δ13C and δ15N of carbon sources in four Neotropical floodplains.

PubMed

Zaia Alves, Gustavo H; Hoeinghaus, David J; Manetta, Gislaine I; Benedito, Evanilde

2017-01-01

Studies in freshwater ecosystems are seeking to improve understanding of carbon flow in food webs and stable isotopes have been influential in this work. However, variation in isotopic values of basal production sources could either be an asset or a hindrance depending on study objectives. We assessed the potential for basin geology and local limnological conditions to predict stable carbon and nitrogen isotope values of six carbon sources at multiple locations in four Neotropical floodplain ecosystems (Paraná, Pantanal, Araguaia, and Amazon). Limnological conditions exhibited greater variation within than among systems. δ15N differed among basins for most carbon sources, but δ13C did not (though high within-basin variability for periphyton, phytoplankton and particulate organic carbon was observed). Although δ13C and δ15N values exhibited significant correlations with some limnological factors within and among basins, those relationships differed among carbon sources. Regression trees for both carbon and nitrogen isotopes for all sources depicted complex and in some cases nested relationships, and only very limited similarity was observed among trees for different carbon sources. Although limnological conditions predicted variation in isotope values of carbon sources, we suggest the resulting models were too complex to enable mathematical corrections of source isotope values among sites based on these parameters. The importance of local conditions in determining variation in source isotope values suggest that isotopes may be useful for examining habitat use, dispersal and patch dynamics within heterogeneous floodplain ecosystems, but spatial variability in isotope values needs to be explicitly considered when testing ecosystem models of carbon flow in these systems.

Dry season limnological conditions and basin geology exhibit complex relationships with δ13C and δ15N of carbon sources in four Neotropical floodplains

PubMed Central

Hoeinghaus, David J.; Manetta, Gislaine I.; Benedito, Evanilde

2017-01-01

Studies in freshwater ecosystems are seeking to improve understanding of carbon flow in food webs and stable isotopes have been influential in this work. However, variation in isotopic values of basal production sources could either be an asset or a hindrance depending on study objectives. We assessed the potential for basin geology and local limnological conditions to predict stable carbon and nitrogen isotope values of six carbon sources at multiple locations in four Neotropical floodplain ecosystems (Paraná, Pantanal, Araguaia, and Amazon). Limnological conditions exhibited greater variation within than among systems. δ15N differed among basins for most carbon sources, but δ13C did not (though high within-basin variability for periphyton, phytoplankton and particulate organic carbon was observed). Although δ13C and δ15N values exhibited significant correlations with some limnological factors within and among basins, those relationships differed among carbon sources. Regression trees for both carbon and nitrogen isotopes for all sources depicted complex and in some cases nested relationships, and only very limited similarity was observed among trees for different carbon sources. Although limnological conditions predicted variation in isotope values of carbon sources, we suggest the resulting models were too complex to enable mathematical corrections of source isotope values among sites based on these parameters. The importance of local conditions in determining variation in source isotope values suggest that isotopes may be useful for examining habitat use, dispersal and patch dynamics within heterogeneous floodplain ecosystems, but spatial variability in isotope values needs to be explicitly considered when testing ecosystem models of carbon flow in these systems. PMID:28358822

Modelling the diurnal and seasonal dynamics of soil CO2 exchange in a semiarid ecosystem with high plant-interspace heterogeneity

NASA Astrophysics Data System (ADS)

Gong, Jinnan; Wang, Ben; Jia, Xin; Feng, Wei; Zha, Tianshan; Kellomäki, Seppo; Peltola, Heli

2018-01-01

We used process-based modelling to investigate the roles of carbon-flux (C-flux) components and plant-interspace heterogeneities in regulating soil CO2 exchanges (FS) in a dryland ecosystem with sparse vegetation. To simulate the diurnal and seasonal dynamics of FS, the modelling considered simultaneously the CO2 production, transport and surface exchanges (e.g. biocrust photosynthesis, respiration and photodegradation). The model was parameterized and validated with multivariate data measured during the years 2013-2014 in a semiarid shrubland ecosystem in Yanchi, northwestern China. The model simulation showed that soil rewetting could enhance CO2 dissolution and delay the emission of CO2 produced from rooting zone. In addition, an ineligible fraction of respired CO2 might be removed from soil volumes under respiration chambers by lateral water flows and root uptakes. During rewetting, the lichen-crusted soil could shift temporally from net CO2 source to sink due to the activated photosynthesis of biocrust but the restricted CO2 emissions from subsoil. The presence of plant cover could decrease the root-zone CO2 production and biocrust C sequestration but increase the temperature sensitivities of these fluxes. On the other hand, the sensitivities of root-zone emissions to water content were lower under canopy, which may be due to the advection of water flows from the interspace to canopy. To conclude, the complexity and plant-interspace heterogeneities of soil C processes should be carefully considered to extrapolate findings from chamber to ecosystem scales and to predict the ecosystem responses to climate change and extreme climatic events. Our model can serve as a useful tool to simulate the soil CO2 efflux dynamics in dryland ecosystems.

Implementation of marine spatial planning in shellfish aquaculture management: modeling studies in a Norwegian fjord.

PubMed

Filgueira, Ramon; Grant, Jon; Strand, Øivind

2014-06-01

Shellfish carrying capacity is determined by the interaction of a cultured species with its ecosystem, which is strongly influenced by hydrodynamics. Water circulation controls the exchange of matter between farms and the adjacent areas, which in turn establishes the nutrient supply that supports phytoplankton populations. The complexity of water circulation makes necessary the use of hydrodynamic models with detailed spatial resolution in carrying capacity estimations. This detailed spatial resolution also allows for the study of processes that depend on specific spatial arrangements, e.g., the most suitable location to place farms, which is crucial for marine spatial planning, and consequently for decision support systems. In the present study, a fully spatial physical-biogeochemical model has been combined with scenario building and optimization techniques as a proof of concept of the use of ecosystem modeling as an objective tool to inform marine spatial planning. The object of this exercise was to generate objective knowledge based on an ecosystem approach to establish new mussel aquaculture areas in a Norwegian fjord. Scenario building was used to determine the best location of a pump that can be used to bring nutrient-rich deep waters to the euphotic layer, increasing primary production, and consequently, carrying capacity for mussel cultivation. In addition, an optimization tool, parameter estimation (PEST), was applied to the optimal location and mussel standing stock biomass that maximize production, according to a preestablished carrying capacity criterion. Optimization tools allow us to make rational and transparent decisions to solve a well-defined question, decisions that are essential for policy makers. The outcomes of combining ecosystem models with scenario building and optimization facilitate planning based on an ecosystem approach, highlighting the capabilities of ecosystem modeling as a tool for marine spatial planning.

Comparison of Coral Reef Ecosystems along a Fishing Pressure Gradient

PubMed Central

Weijerman, Mariska; Fulton, Elizabeth A.; Parrish, Frank A.

2013-01-01

Three trophic mass-balance models representing coral reef ecosystems along a fishery gradient were compared to evaluate ecosystem effects of fishing. The majority of the biomass estimates came directly from a large-scale visual survey program; therefore, data were collected in the same way for all three models, enhancing comparability. Model outputs–such as net system production, size structure of the community, total throughput, production, consumption, production-to-respiration ratio, and Finn’s cycling index and mean path length–indicate that the systems around the unpopulated French Frigate Shoals and along the relatively lightly populated Kona Coast of Hawai’i Island are mature, stable systems with a high efficiency in recycling of biomass. In contrast, model results show that the reef system around the most populated island in the State of Hawai’i, O’ahu, is in a transitional state with reduced ecosystem resilience and appears to be shifting to an algal-dominated system. Evaluation of the candidate indicators for fishing pressure showed that indicators at the community level (e.g., total biomass, community size structure, trophic level of the community) were most robust (i.e., showed the clearest trend) and that multiple indicators are necessary to identify fishing perturbations. These indicators could be used as performance indicators when compared to a baseline for management purposes. This study shows that ecosystem models can be valuable tools in identification of the system state in terms of complexity, stability, and resilience and, therefore, can complement biological metrics currently used by monitoring programs as indicators for coral reef status. Moreover, ecosystem models can improve our understanding of a system’s internal structure that can be used to support management in identification of approaches to reverse unfavorable states. PMID:23737951

Global change modeling for Northern Eurasia: a review and strategies to move forward

NASA Astrophysics Data System (ADS)

Monier, E.; Kicklighter, D. W.; Sokolov, A. P.; Zhuang, Q.; Sokolik, I. N.; Lawford, R. G.; Kappas, M.; Paltsev, S.; Groisman, P. Y.

2017-12-01

Northern Eurasia is made up of a complex and diverse set of physical, ecological, climatic and human systems, which provide important ecosystem services including the storage of substantial stocks of carbon in its terrestrial ecosystems. At the same time, the region has experienced dramatic climate change, natural disturbances and changes in land management practices over the past century. For these reasons, Northern Eurasia is both a critical region to understand and a complex system with substantial challenges for the modeling community. This review is designed to highlight the state of past and ongoing efforts of the research community to understand and model these environmental, socioeconomic, and climatic changes. We further aim to provide perspectives on the future direction of global change modeling to improve our understanding of the role of Northern Eurasia in the coupled human-Earth system. Modeling efforts have shown that environmental and socioeconomic changes in Northern Eurasia can have major impacts on biodiversity, ecosystems services, environmental sustainability, and the carbon cycle of the region, and beyond. These impacts have the potential to feedback onto and alter the global Earth system. We find that past and ongoing studies have largely focused on specific components of Earth system dynamics and have not systematically examined their feedbacks to the global Earth system and to society. We identify the crucial role of Earth system models in advancing our understanding of feedbacks within the region and with the global system. We further argue for the need for integrated assessment models (IAMs), a suite of models that couple human activity models to Earth system models, which are key to address many emerging issues that require a representation of the coupled human-Earth system.

A review of and perspectives on global change modeling for Northern Eurasia

NASA Astrophysics Data System (ADS)

Monier, Erwan; Kicklighter, David W.; Sokolov, Andrei P.; Zhuang, Qianlai; Sokolik, Irina N.; Lawford, Richard; Kappas, Martin; Paltsev, Sergey V.; Groisman, Pavel Ya

2017-08-01

Northern Eurasia is made up of a complex and diverse set of physical, ecological, climatic and human systems, which provide important ecosystem services including the storage of substantial stocks of carbon in its terrestrial ecosystems. At the same time, the region has experienced dramatic climate change, natural disturbances and changes in land management practices over the past century. For these reasons, Northern Eurasia is both a critical region to understand and a complex system with substantial challenges for the modeling community. This review is designed to highlight the state of past and ongoing efforts of the research community to understand and model these environmental, socioeconomic, and climatic changes. We further aim to provide perspectives on the future direction of global change modeling to improve our understanding of the role of Northern Eurasia in the coupled human-Earth system. Modeling efforts have shown that environmental and socioeconomic changes in Northern Eurasia can have major impacts on biodiversity, ecosystems services, environmental sustainability, and the carbon cycle of the region, and beyond. These impacts have the potential to feedback onto and alter the global Earth system. We find that past and ongoing studies have largely focused on specific components of Earth system dynamics and have not systematically examined their feedbacks to the global Earth system and to society. We identify the crucial role of Earth system models in advancing our understanding of feedbacks within the region and with the global system. We further argue for the need for integrated assessment models (IAMs), a suite of models that couple human activity models to Earth system models, which are key to address many emerging issues that require a representation of the coupled human-Earth system.

High refuge availability on coral reefs increases the vulnerability of reef-associated predators to overexploitation.

PubMed

Rogers, Alice; Blanchard, Julia L; Newman, Steven P; Dryden, Charlie S; Mumby, Peter J

2018-02-01

Refuge availability and fishing alter predator-prey interactions on coral reefs, but our understanding of how they interact to drive food web dynamics, community structure and vulnerability of different trophic groups is unclear. Here, we apply a size-based ecosystem model of coral reefs, parameterized with empirical measures of structural complexity, to predict fish biomass, productivity and community structure in reef ecosystems under a broad range of refuge availability and fishing regimes. In unfished ecosystems, the expected positive correlation between reef structural complexity and biomass emerges, but a non-linear effect of predation refuges is observed for the productivity of predatory fish. Reefs with intermediate complexity have the highest predator productivity, but when refuge availability is high and prey are less available, predator growth rates decrease, with significant implications for fisheries. Specifically, as fishing intensity increases, predators in habitats with high refuge availability exhibit vulnerability to over-exploitation, resulting in communities dominated by herbivores. Our study reveals mechanisms for threshold dynamics in predators living in complex habitats and elucidates how predators can be food-limited when most of their prey are able to hide. We also highlight the importance of nutrient recycling via the detrital pathway, to support high predator biomasses on coral reefs. © 2018 by the Ecological Society of America.

Alternative stable states and the sustainability of forests, grasslands, and agriculture

PubMed Central

Henderson, Kirsten A.; Bauch, Chris T.; Anand, Madhur

2016-01-01

Endangered forest–grassland mosaics interspersed with expanding agriculture and silviculture occur across many parts of the world, including the southern Brazilian highlands. This natural mosaic ecosystem is thought to reflect alternative stable states driven by threshold responses of recruitment to fire and moisture regimes. The role of adaptive human behavior in such systems remains understudied, despite its pervasiveness and the fact that such ecosystems can exhibit complex dynamics. We develop a nonlinear mathematical model of coupled human–environment dynamics in mosaic systems and social processes regarding conservation and economic land valuation. Our objective is to better understand how the coupled dynamics respond to changes in ecological and social conditions. The model is parameterized with southern Brazilian data on mosaic ecology, land-use profits, and questionnaire results concerning landowner preferences and conservation values. We find that the mosaic presently resides at a crucial juncture where relatively small changes in social conditions can generate a wide variety of possible outcomes, including complete loss of mosaics; large-amplitude, long-term oscillations between land states that preclude ecosystem stability; and conservation of the mosaic even to the exclusion of agriculture/silviculture. In general, increasing the time horizon used for conservation decision making is more likely to maintain mosaic stability. In contrast, increasing the inherent conservation value of either forests or grasslands is more likely to induce large oscillations—especially for forests—due to feedback from rarity-based conservation decisions. Given the potential for complex dynamics, empirically grounded nonlinear dynamical models should play a larger role in policy formulation for human–environment mosaic ecosystems. PMID:27956605

Alternative stable states and the sustainability of forests, grasslands, and agriculture.

PubMed

Henderson, Kirsten A; Bauch, Chris T; Anand, Madhur

2016-12-20

Endangered forest-grassland mosaics interspersed with expanding agriculture and silviculture occur across many parts of the world, including the southern Brazilian highlands. This natural mosaic ecosystem is thought to reflect alternative stable states driven by threshold responses of recruitment to fire and moisture regimes. The role of adaptive human behavior in such systems remains understudied, despite its pervasiveness and the fact that such ecosystems can exhibit complex dynamics. We develop a nonlinear mathematical model of coupled human-environment dynamics in mosaic systems and social processes regarding conservation and economic land valuation. Our objective is to better understand how the coupled dynamics respond to changes in ecological and social conditions. The model is parameterized with southern Brazilian data on mosaic ecology, land-use profits, and questionnaire results concerning landowner preferences and conservation values. We find that the mosaic presently resides at a crucial juncture where relatively small changes in social conditions can generate a wide variety of possible outcomes, including complete loss of mosaics; large-amplitude, long-term oscillations between land states that preclude ecosystem stability; and conservation of the mosaic even to the exclusion of agriculture/silviculture. In general, increasing the time horizon used for conservation decision making is more likely to maintain mosaic stability. In contrast, increasing the inherent conservation value of either forests or grasslands is more likely to induce large oscillations-especially for forests-due to feedback from rarity-based conservation decisions. Given the potential for complex dynamics, empirically grounded nonlinear dynamical models should play a larger role in policy formulation for human-environment mosaic ecosystems.

Critical Watersheds: Climate Change, Tipping Points, and Energy-Water Impacts

NASA Astrophysics Data System (ADS)

Middleton, R. S.; Brown, M.; Coon, E.; Linn, R.; McDowell, N. G.; Painter, S. L.; Xu, C.

2014-12-01

Climate change, extreme climate events, and climate-induced disturbances will have a substantial and detrimental impact on terrestrial ecosystems. How ecosystems respond to these impacts will, in turn, have a significant effect on the quantity, quality, and timing of water supply for energy security, agriculture, industry, and municipal use. As a community, we lack sufficient quantitative and mechanistic understanding of the complex interplay between climate extremes (e.g., drought, floods), ecosystem dynamics (e.g., vegetation succession), and disruptive events (e.g., wildfire) to assess ecosystem vulnerabilities and to design mitigation strategies that minimize or prevent catastrophic ecosystem impacts. Through a combination of experimental and observational science and modeling, we are developing a unique multi-physics ecohydrologic framework for understanding and quantifying feedbacks between novel climate and extremes, surface and subsurface hydrology, ecosystem dynamics, and disruptive events in critical watersheds. The simulation capability integrates and advances coupled surface-subsurface hydrology from the Advanced Terrestrial Simulator (ATS), dynamic vegetation succession from the Ecosystem Demography (ED) model, and QUICFIRE, a novel wildfire behavior model developed from the FIRETEC platform. These advances are expected to make extensive contributions to the literature and to earth system modeling. The framework is designed to predict, quantify, and mitigate the impacts of climate change on vulnerable watersheds, with a focus on the US Mountain West and the energy-water nexus. This emerging capability is used to identify tipping points in watershed ecosystems, quantify impacts on downstream users, and formally evaluate mitigation efforts including forest (e.g., thinning, prescribed burns) and watershed (e.g., slope stabilization). The framework is being trained, validated, and demonstrated using field observations and remote data collections in the Valles Caldera National Preserve, including pre- and post-wildfire and infestation observations. Ultimately, the framework will be applied to the upper Colorado River basin. Here, we present an overview of the framework development strategy and latest field and modeling results.

Sampling and modeling riparian forest structure and riparian microclimate

Treesearch

Bianca N.I. Eskelson; Paul D. Anderson; Hailemariam Temesgen

2013-01-01

Riparian areas are extremely variable and dynamic, and represent some of the most complex terrestrial ecosystems in the world. The high variability within and among riparian areas poses challenges in developing efficient sampling and modeling approaches that accurately quantify riparian forest structure and riparian microclimate. Data from eight stream reaches that are...

Using landscape disturbance and succession models to support forest management

Treesearch

Eric J. Gustafson; Brian R. Sturtevant; Anatoly S. Shvidenko; Robert M. Scheller

2010-01-01

Managers of forested landscapes must account for multiple, interacting ecological processes operating at broad spatial and temporal scales. These interactions can be of such complexity that predictions of future forest ecosystem states are beyond the analytical capability of the human mind. Landscape disturbance and succession models (LDSM) are predictive and...

Sources of Uncertainty in Predicting Land Surface Fluxes Using Diverse Data and Models

NASA Technical Reports Server (NTRS)

Dungan, Jennifer L.; Wang, Weile; Michaelis, Andrew; Votava, Petr; Nemani, Ramakrishma

2010-01-01

In the domain of predicting land surface fluxes, models are used to bring data from large observation networks and satellite remote sensing together to make predictions about present and future states of the Earth. Characterizing the uncertainty about such predictions is a complex process and one that is not yet fully understood. Uncertainty exists about initialization, measurement and interpolation of input variables; model parameters; model structure; and mixed spatial and temporal supports. Multiple models or structures often exist to describe the same processes. Uncertainty about structure is currently addressed by running an ensemble of different models and examining the distribution of model outputs. To illustrate structural uncertainty, a multi-model ensemble experiment we have been conducting using the Terrestrial Observation and Prediction System (TOPS) will be discussed. TOPS uses public versions of process-based ecosystem models that use satellite-derived inputs along with surface climate data and land surface characterization to produce predictions of ecosystem fluxes including gross and net primary production and net ecosystem exchange. Using the TOPS framework, we have explored the uncertainty arising from the application of models with different assumptions, structures, parameters, and variable definitions. With a small number of models, this only begins to capture the range of possible spatial fields of ecosystem fluxes. Few attempts have been made to systematically address the components of uncertainty in such a framework. We discuss the characterization of uncertainty for this approach including both quantifiable and poorly known aspects.

MEDUSA-2.0: an intermediate complexity biogeochemical model of the marine carbon cycle for climate change and ocean acidification studies

NASA Astrophysics Data System (ADS)

Yool, A.; Popova, E. E.; Anderson, T. R.

2013-10-01

MEDUSA-1.0 (Model of Ecosystem Dynamics, nutrient Utilisation, Sequestration and Acidification) was developed as an "intermediate complexity" plankton ecosystem model to study the biogeochemical response, and especially that of the so-called "biological pump", to anthropogenically driven change in the World Ocean (Yool et al., 2011). The base currency in this model was nitrogen from which fluxes of organic carbon, including export to the deep ocean, were calculated by invoking fixed C:N ratios in phytoplankton, zooplankton and detritus. However, due to anthropogenic activity, the atmospheric concentration of carbon dioxide (CO2) has significantly increased above its natural, inter-glacial background. As such, simulating and predicting the carbon cycle in the ocean in its entirety, including ventilation of CO2 with the atmosphere and the resulting impact of ocean acidification on marine ecosystems, requires that both organic and inorganic carbon be afforded a more complete representation in the model specification. Here, we introduce MEDUSA-2.0, an expanded successor model which includes additional state variables for dissolved inorganic carbon, alkalinity, dissolved oxygen and detritus carbon (permitting variable C:N in exported organic matter), as well as a simple benthic formulation and extended parameterizations of phytoplankton growth, calcification and detritus remineralisation. A full description of MEDUSA-2.0, including its additional functionality, is provided and a multi-decadal spin-up simulation (1860-2005) is performed. The biogeochemical performance of the model is evaluated using a diverse range of observational data, and MEDUSA-2.0 is assessed relative to comparable models using output from the Coupled Model Intercomparison Project (CMIP5).

Habitat Complexity in Aquatic Microcosms Affects Processes Driven by Detritivores

PubMed Central

Flores, Lorea; Bailey, R. A.; Elosegi, Arturo; Larrañaga, Aitor; Reiss, Julia

2016-01-01

Habitat complexity can influence predation rates (e.g. by providing refuge) but other ecosystem processes and species interactions might also be modulated by the properties of habitat structure. Here, we focussed on how complexity of artificial habitat (plastic plants), in microcosms, influenced short-term processes driven by three aquatic detritivores. The effects of habitat complexity on leaf decomposition, production of fine organic matter and pH levels were explored by measuring complexity in three ways: 1. as the presence vs. absence of habitat structure; 2. as the amount of structure (3 or 4.5 g of plastic plants); and 3. as the spatial configuration of structures (measured as fractal dimension). The experiment also addressed potential interactions among the consumers by running all possible species combinations. In the experimental microcosms, habitat complexity influenced how species performed, especially when comparing structure present vs. structure absent. Treatments with structure showed higher fine particulate matter production and lower pH compared to treatments without structures and this was probably due to higher digestion and respiration when structures were present. When we explored the effects of the different complexity levels, we found that the amount of structure added explained more than the fractal dimension of the structures. We give a detailed overview of the experimental design, statistical models and R codes, because our statistical analysis can be applied to other study systems (and disciplines such as restoration ecology). We further make suggestions of how to optimise statistical power when artificially assembling, and analysing, ‘habitat complexity’ by not confounding complexity with the amount of structure added. In summary, this study highlights the importance of habitat complexity for energy flow and the maintenance of ecosystem processes in aquatic ecosystems. PMID:27802267

An integrated multi-criteria scenario evaluation web tool for participatory land-use planning in urbanized areas: The Ecosystem Portfolio Model

USGS Publications Warehouse

Labiosa, Bill; Forney, William M.; Hearn,, Paul P.; Hogan, Dianna M.; Strong, David R.; Swain, Eric D.; Esnard, Ann-Margaret; Mitsova-Boneva, D.; Bernknopf, R.; Pearlstine, Leonard; Gladwin, Hugh

2013-01-01

Land-use land-cover change is one of the most important and direct drivers of changes in ecosystem functions and services. Given the complexity of the decision-making, there is a need for Internet-based decision support systems with scenario evaluation capabilities to help planners, resource managers and communities visualize, compare and consider trade-offs among the many values at stake in land use planning. This article presents details on an Ecosystem Portfolio Model (EPM) prototype that integrates ecological, socio-economic information and associated values of relevance to decision-makers and stakeholders. The EPM uses a multi-criteria scenario evaluation framework, Geographic Information Systems (GIS) analysis and spatially-explicit land-use/land-cover change-sensitive models to characterize changes in important land-cover related ecosystem values related to ecosystem services and functions, land parcel prices, and community quality-of-life (QoL) metrics. Parameters in the underlying models can be modified through the interface, allowing users in a facilitated group setting to explore simultaneously issues of scientific uncertainty and divergence in the preferences of stakeholders. One application of the South Florida EPM prototype reported in this article shows the modeled changes (which are significant) in aggregate ecological value, landscape patterns and fragmentation, biodiversity potential and ecological restoration potential for current land uses compared to the 2050 land-use scenario. Ongoing refinements to EPM, and future work especially in regard to modifiable sea level rise scenarios are also discussed.

Model-experiment synthesis at two FACE sites in the southeastern US. Forest ecosystem responses to elevated CO[2]. (Invited)

NASA Astrophysics Data System (ADS)

Walker, A. P.; Zaehle, S.; De Kauwe, M. G.; Medlyn, B. E.; Dietze, M.; Hickler, T.; Iversen, C. M.; Jain, A. K.; Luo, Y.; McCarthy, H. R.; Parton, W. J.; Prentice, C.; Thornton, P. E.; Wang, S.; Wang, Y.; Warlind, D.; Warren, J.; Weng, E.; Hanson, P. J.; Oren, R.; Norby, R. J.

2013-12-01

Ecosystem observations from two long-term Free-Air CO[2] Enrichment (FACE) experiments (Duke forest and Oak Ridge forest) were used to evaluate the assumptions of 11 terrestrial ecosystem models and the consequences of those assumptions for the responses of ecosystem water, carbon (C) and nitrogen (N) fluxes to elevated CO[2] (eCO[2]). Nitrogen dynamics were the main constraint on simulated productivity responses to eCO[2]. At Oak Ridge some models reproduced the declining response of C and N fluxes, while at Duke none of the models were able to maintain the observed sustained responses. C and N cycles are coupled through a number of complex interactions, which causes uncertainty in model simulations in multiple ways. Nonetheless, the major difference between models and experiments was a larger than observed increase in N-use efficiency and lower than observed response of N uptake. The results indicate that at Duke there were mechanisms by which trees accessed additional N in response to eCO[2] that were not represented in the ecosystem models, and which did not operate with the same efficiency at Oak Ridge. Sequestration of the additional productivity under eCO[2] into forest biomass depended largely on C allocation. Allocation assumptions were classified into three main categories--fixed partitioning coefficients, functional relationships and a partial (leaf allocation only) optimisation. The assumption which best constrained model results was a functional relationship between leaf area and sapwood area (pipe-model) and increased root allocation when nitrogen or water were limiting. Both, productivity and allocation responses to eCO[2] determined the ecosystem-level response of LAI, which together with the response of stomatal conductance (and hence water-use efficiency; WUE) determined the ecosystem response of transpiration. Differences in the WUE response across models were related to the representation of the relationship of stomatal conductance to CO[2] and the relative importance of the combined boundary and aerodynamic resistances in the total resistance to leaf-atmosphere water transport.

Stoichiometric vs hydroclimatic controls on soil biogeochemical processes

NASA Astrophysics Data System (ADS)

Manzoni, Stefano; Porporato, Amilcare

2010-05-01

Soil nutrient cycles are controlled by both stoichiometric constraints (e.g., carbon to nutrient ratios) and hydroclimatic conditions (e.g., soil moisture and temperature). Both controls tend to act in a nonlinear manner and give rise to complex dynamics in soil biogeochemistry at different space-time scales. We first review the theoretical basis of soil biogeochemical models, looking for the general principles underlying these models across space-time scales and scientific disciplines. By comparing more than 250 models, we show that similar kinetic and stoichiometric laws, formulated to mechanistically represent the complex biochemical constraints to decomposition, are common to most models, providing a basis for their classification. Moreover, a historic analysis reveals that the complexity (e.g., phase space dimension, model architecture) and degree and number of nonlinearities generally increased with date, while they decreased with increasing spatial and temporal scale of interest. Soil biogeochmical dynamics may be suitable conceptualized using a number of compartments (e.g., decomposers, organic substrates, inorganic ions) interacting among each other at rates that depend (nonlinearly) on climatic drivers. As a consequence, hydroclimatic-induced fluctuations at the daily scale propagate through the various soil compartments leading to cascading effects ranging from short-term fluctuations in the smaller pools to long-lasting changes in the larger ones. Such cascading effects are known to occur in dryland ecosystems, and are increasingly being recongnized to control the long-term carbon and nutrient balances in more mesic ecosystems. We also show that separating biochemical from climatic impacts on organic matter decomposition results in universal curves describing data of plant residue decomposition and nutrient mineralization across the globe. Future extensions to larger spatial scales and managed ecosystems are also briefly outlined. It is critical that future modeling efforts carefully account for the scale-dependence of their mathematical formulations, especially when applied to a wide range of scales.

An interdisciplinary swat ecohydrological model to define catchment-scale hydrologic partitioning

NASA Astrophysics Data System (ADS)

Shope, C. L.; Maharjan, G. R.; Tenhunen, J.; Seo, B.; Kim, K.; Riley, J.; Arnhold, S.; Koellner, T.; Ok, Y. S.; Peiffer, S.; Kim, B.; Park, J.-H.; Huwe, B.

2013-06-01

Land use and climate change have long been implicated in modifying ecosystem services, such as water quality and water yield, biodiversity, and agricultural production. To account for future effects on ecosystem services, the integration of physical, biological, economic, and social data over several scales must be implemented to assess the effects on natural resource availability and use. Our objective is to assess the capability of the SWAT model to capture short-duration monsoonal rainfall-runoff processes in complex mountainous terrain under rapid, event-driven processes in a monsoonal environment. To accomplish this, we developed a unique quality-control gap-filling algorithm for interpolation of high frequency meteorological data. We used a novel multi-location, multi-optimization calibration technique to improve estimations of catchment-wide hydrologic partitioning. We calibrated the interdisciplinary model to a combination of statistical, hydrologic, and plant growth metrics. In addition, we used multiple locations of different drainage area, aspect, elevation, and geologic substrata distributed throughout the catchment. Results indicate scale-dependent sensitivity of hydrologic partitioning and substantial influence of engineered features. While our model accurately reproduced observed discharge variability, the addition of hydrologic and plant growth objective functions identified the importance of culverts in catchment-wide flow distribution. The results of this study provide a valuable resource to describe landscape controls and their implication on discharge, sediment transport, and nutrient loading. This study also shows the challenges of applying the SWAT model to complex terrain and extreme environments. By incorporating anthropogenic features into modeling scenarios, we can greatly enhance our understanding of the hydroecological impacts on ecosystem services.

Everglqades Mercury: Biogeochemistry, Modeling, and Possible Mitigation

NASA Astrophysics Data System (ADS)

Orem, W. H.

2015-12-01

In the 1980s high levels of methylmercury (MeHg) were found in fish and other biota in the Florida Everglades, prompting fish consumption advisories. As part of Everglades restoration efforts Federal and State Agencies initiated a research program to study the underlying causes of the MeHg contamination. As part of this multi-agency effort, the U.S. Geological Survey developed the ACME (Aquatic Cycling of Mercury in the Everglades) project to examine the underlying biogeochemical factors controlling MeHg production and bioaccumulation in the ecosystem. Field studies by ACME and others identified the many factors impacting MeHg production in the Everglades. Thes factors include: high mercury deposition, large wetland area with organic-rich anaerobic soil, high sulfate loading in surface runoff, circumneutral pH, and high dissolved organic matter (DOM) content. Florida Department of Environmental Protection efforts that reduced local mercury emissions by 90%, produced only a small reduction in mercury deposition on the Everglades, suggesting that most Hg deposited on the ecosystem originates from distant sources, and beyond the reach of regulators. ACME studies demonstrated that high sulfate loading to the Everglades comes from discharge of canal water originating in the Everglades Agricultural Area (EAA). The use of sulfur in agriculture and soil oxidation in the EAA have been shown to be the principal sources of the sulfate loading. Sulfate entering the ecosystem drives microbial sulfate reduction and MeHg production, but inhibition of MeHg production by sulfide (a byproduct of microbial sulfate reduction) makes the biogeochemistry complex. Laboratory microcosm and field mesocosm experiments by ACME helped define the complexity of the sulfur/MeHg biogeochemistry, and demonstrated the key role of dissolved organic matter in MeHg production. A conceptual model was developed that relates MeHg production to sulfate loading, DOM, and soil composition. This conceptual model was then used in the development of a mathematical model that relates how changes in sulfate loading affect MeHg production in the ecosystem. This model is currently being used to examine how limits on sulfate loading to the ecosystem could be used as a mitigation strategy to control MeHg production and levels of MeHg in Everglades biota.

Stability and complexity in model meta-ecosystems

PubMed Central

Gravel, Dominique; Massol, François; Leibold, Mathew A.

2016-01-01

The diversity of life and its organization in networks of interacting species has been a long-standing theoretical puzzle for ecologists. Ever since May's provocative paper challenging whether ‘large complex systems [are] stable' various hypotheses have been proposed to explain when stability should be the rule, not the exception. Spatial dynamics may be stabilizing and thus explain high community diversity, yet existing theory on spatial stabilization is limited, preventing comparisons of the role of dispersal relative to species interactions. Here we incorporate dispersal of organisms and material into stability–complexity theory. We find that stability criteria from classic theory are relaxed in direct proportion to the number of ecologically distinct patches in the meta-ecosystem. Further, we find the stabilizing effect of dispersal is maximal at intermediate intensity. Our results highlight how biodiversity can be vulnerable to factors, such as landscape fragmentation and habitat loss, that isolate local communities. PMID:27555100

Navigating complexity through knowledge coproduction: Mainstreaming ecosystem services into disaster risk reduction.

PubMed

Reyers, Belinda; Nel, Jeanne L; O'Farrell, Patrick J; Sitas, Nadia; Nel, Deon C

2015-06-16

Achieving the policy and practice shifts needed to secure ecosystem services is hampered by the inherent complexities of ecosystem services and their management. Methods for the participatory production and exchange of knowledge offer an avenue to navigate this complexity together with the beneficiaries and managers of ecosystem services. We develop and apply a knowledge coproduction approach based on social-ecological systems research and assess its utility in generating shared knowledge and action for ecosystem services. The approach was piloted in South Africa across four case studies aimed at reducing the risk of disasters associated with floods, wildfires, storm waves, and droughts. Different configurations of stakeholders (knowledge brokers, assessment teams, implementers, and bridging agents) were involved in collaboratively designing each study, generating and exchanging knowledge, and planning for implementation. The approach proved useful in the development of shared knowledge on the sizable contribution of ecosystem services to disaster risk reduction. This knowledge was used by stakeholders to design and implement several actions to enhance ecosystem services, including new investments in ecosystem restoration, institutional changes in the private and public sector, and innovative partnerships of science, practice, and policy. By bringing together multiple disciplines, sectors, and stakeholders to jointly produce the knowledge needed to understand and manage a complex system, knowledge coproduction approaches offer an effective avenue for the improved integration of ecosystem services into decision making.

Navigating complexity through knowledge coproduction: Mainstreaming ecosystem services into disaster risk reduction

PubMed Central

Reyers, Belinda; Nel, Jeanne L.; O’Farrell, Patrick J.; Sitas, Nadia; Nel, Deon C.

2015-01-01

Achieving the policy and practice shifts needed to secure ecosystem services is hampered by the inherent complexities of ecosystem services and their management. Methods for the participatory production and exchange of knowledge offer an avenue to navigate this complexity together with the beneficiaries and managers of ecosystem services. We develop and apply a knowledge coproduction approach based on social–ecological systems research and assess its utility in generating shared knowledge and action for ecosystem services. The approach was piloted in South Africa across four case studies aimed at reducing the risk of disasters associated with floods, wildfires, storm waves, and droughts. Different configurations of stakeholders (knowledge brokers, assessment teams, implementers, and bridging agents) were involved in collaboratively designing each study, generating and exchanging knowledge, and planning for implementation. The approach proved useful in the development of shared knowledge on the sizable contribution of ecosystem services to disaster risk reduction. This knowledge was used by stakeholders to design and implement several actions to enhance ecosystem services, including new investments in ecosystem restoration, institutional changes in the private and public sector, and innovative partnerships of science, practice, and policy. By bringing together multiple disciplines, sectors, and stakeholders to jointly produce the knowledge needed to understand and manage a complex system, knowledge coproduction approaches offer an effective avenue for the improved integration of ecosystem services into decision making. PMID:26082541

Assimilation of Leaf and Canopy Spectroscopic Data to Improve the Representation of Vegetation Dynamics in Terrestrial Ecosystem Models

NASA Astrophysics Data System (ADS)

Serbin, S. P.; Dietze, M.; Desai, A. R.; LeBauer, D.; Viskari, T.; Kooper, R.; McHenry, K. G.; Townsend, P. A.

2013-12-01

The ability to seamlessly integrate information on vegetation structure and function across a continuum of scales, from field to satellite observations, greatly enhances our ability to understand how terrestrial vegetation-atmosphere interactions change over time and in response to disturbances. In particular, terrestrial ecosystem models require detailed information on ecosystem states and canopy properties in order to properly simulate the fluxes of carbon (C), water and energy from the land to the atmosphere as well as address the vulnerability of ecosystems to environmental and other perturbations. Over the last several decades the amount of available data to constrain ecological predictions has increased substantially, resulting in a progressively data-rich era for global change research. In particular remote sensing data, specifically optical data (leaf and canopy), offers the potential for an important and direct data constraint on ecosystem model projections of C and energy fluxes. Here we highlight the utility of coupling information provided through the Ecosystem Spectral Information System (EcoSIS) with complex process models through the Predictive Ecosystem Analyzer (PEcAn; http://www.pecanproject.org/) eco-informatics framework as a means to improve the description of canopy optical properties, vegetation composition, and modeled radiation balance. We also present this an efficient approach for understanding and correcting implicit assumptions and model structural deficiencies. We first illustrate the challenges and issues in adequately characterizing ecosystem fluxes with the Ecosystem Demography model (ED2, Medvigy et al., 2009) due to improper parameterization of leaf and canopy properties, as well as assumptions describing radiative transfer within the canopy. ED2 is especially relevant to these efforts because it contains a sophisticated structure for scaling ecological processes across a range of spatial scales: from the tree-level (demography, physiology) to the distribution of stands across a landscape, which allows for the direct use of remotely sensed data at the appropriate spatial scale. A sensitivity analysis is employed within PEcAn to illustrate the influence of ED2 parameterizations on modeled C and energy fluxes for a northern temperate forest ecosystem as an example of the need for more detailed information on leaf and canopy optical properties. We then demonstrate a data assimilation approach to synthesize spectral data contained within EcoSIS in order to update model parameterizations across key vegetation plant functional types, as well as a means to update vegetation state information (i.e. composition, LAI) and improve the description of radiation transfer through model structural updates. A better understanding of the radiation balance of ecosystems will improve regional and global scale C and energy balance projections.

COMPLEXITY IN ECOLOGICAL SYSTEMS

EPA Science Inventory

The enormous complexity of ecosystems is generally obvious under even the most cursory examination. In the modern world, this complexity is further augmented by the linkage of ecosystems to economic and social systems through the human use of the environment for technological pu...

A methodology for adaptable and robust ecosystem services assessment.

PubMed

Villa, Ferdinando; Bagstad, Kenneth J; Voigt, Brian; Johnson, Gary W; Portela, Rosimeiry; Honzák, Miroslav; Batker, David

2014-01-01

Ecosystem Services (ES) are an established conceptual framework for attributing value to the benefits that nature provides to humans. As the promise of robust ES-driven management is put to the test, shortcomings in our ability to accurately measure, map, and value ES have surfaced. On the research side, mainstream methods for ES assessment still fall short of addressing the complex, multi-scale biophysical and socioeconomic dynamics inherent in ES provision, flow, and use. On the practitioner side, application of methods remains onerous due to data and model parameterization requirements. Further, it is increasingly clear that the dominant "one model fits all" paradigm is often ill-suited to address the diversity of real-world management situations that exist across the broad spectrum of coupled human-natural systems. This article introduces an integrated ES modeling methodology, named ARIES (ARtificial Intelligence for Ecosystem Services), which aims to introduce improvements on these fronts. To improve conceptual detail and representation of ES dynamics, it adopts a uniform conceptualization of ES that gives equal emphasis to their production, flow and use by society, while keeping model complexity low enough to enable rapid and inexpensive assessment in many contexts and for multiple services. To improve fit to diverse application contexts, the methodology is assisted by model integration technologies that allow assembly of customized models from a growing model base. By using computer learning and reasoning, model structure may be specialized for each application context without requiring costly expertise. In this article we discuss the founding principles of ARIES--both its innovative aspects for ES science and as an example of a new strategy to support more accurate decision making in diverse application contexts.

A methodology for adaptable and robust ecosystem services assessment

USGS Publications Warehouse

Villa, Ferdinando; Bagstad, Kenneth J.; Voigt, Brian; Johnson, Gary W.; Portela, Rosimeiry; Honzák, Miroslav; Batker, David

2014-01-01

Ecosystem Services (ES) are an established conceptual framework for attributing value to the benefits that nature provides to humans. As the promise of robust ES-driven management is put to the test, shortcomings in our ability to accurately measure, map, and value ES have surfaced. On the research side, mainstream methods for ES assessment still fall short of addressing the complex, multi-scale biophysical and socioeconomic dynamics inherent in ES provision, flow, and use. On the practitioner side, application of methods remains onerous due to data and model parameterization requirements. Further, it is increasingly clear that the dominant “one model fits all” paradigm is often ill-suited to address the diversity of real-world management situations that exist across the broad spectrum of coupled human-natural systems. This article introduces an integrated ES modeling methodology, named ARIES (ARtificial Intelligence for Ecosystem Services), which aims to introduce improvements on these fronts. To improve conceptual detail and representation of ES dynamics, it adopts a uniform conceptualization of ES that gives equal emphasis to their production, flow and use by society, while keeping model complexity low enough to enable rapid and inexpensive assessment in many contexts and for multiple services. To improve fit to diverse application contexts, the methodology is assisted by model integration technologies that allow assembly of customized models from a growing model base. By using computer learning and reasoning, model structure may be specialized for each application context without requiring costly expertise. In this article we discuss the founding principles of ARIES - both its innovative aspects for ES science and as an example of a new strategy to support more accurate decision making in diverse application contexts.

A Methodology for Adaptable and Robust Ecosystem Services Assessment

PubMed Central

Villa, Ferdinando; Bagstad, Kenneth J.; Voigt, Brian; Johnson, Gary W.; Portela, Rosimeiry; Honzák, Miroslav; Batker, David

2014-01-01

Ecosystem Services (ES) are an established conceptual framework for attributing value to the benefits that nature provides to humans. As the promise of robust ES-driven management is put to the test, shortcomings in our ability to accurately measure, map, and value ES have surfaced. On the research side, mainstream methods for ES assessment still fall short of addressing the complex, multi-scale biophysical and socioeconomic dynamics inherent in ES provision, flow, and use. On the practitioner side, application of methods remains onerous due to data and model parameterization requirements. Further, it is increasingly clear that the dominant “one model fits all” paradigm is often ill-suited to address the diversity of real-world management situations that exist across the broad spectrum of coupled human-natural systems. This article introduces an integrated ES modeling methodology, named ARIES (ARtificial Intelligence for Ecosystem Services), which aims to introduce improvements on these fronts. To improve conceptual detail and representation of ES dynamics, it adopts a uniform conceptualization of ES that gives equal emphasis to their production, flow and use by society, while keeping model complexity low enough to enable rapid and inexpensive assessment in many contexts and for multiple services. To improve fit to diverse application contexts, the methodology is assisted by model integration technologies that allow assembly of customized models from a growing model base. By using computer learning and reasoning, model structure may be specialized for each application context without requiring costly expertise. In this article we discuss the founding principles of ARIES - both its innovative aspects for ES science and as an example of a new strategy to support more accurate decision making in diverse application contexts. PMID:24625496

Functional complexity and ecosystem stability: an experimental approach

DOE Office of Scientific and Technical Information (OSTI.GOV)

Van Voris, P.; O'Neill, R.V.; Shugart, H.H.

1978-01-01

The complexity-stability hypothesis was experimentally tested using intact terrestrial microcosms. Functional complexity was defined as the number and significance of component interactions (i.e., population interactions, physical-chemical reactions, biological turnover rates) influenced by nonlinearities, feedbacks, and time delays. It was postulated that functional complexity could be nondestructively measured through analysis of a signal generated from the system. Power spectral analysis of hourly CO/sub 2/ efflux, from eleven old-field microcosms, was analyzed for the number of low frequency peaks and used to rank the functional complexity of each system. Ranking of ecosystem stability was based on the capacity of the system tomore » retain essential nutrients and was measured by net loss of Ca after the system was stressed. Rank correlation supported the hypothesis that increasing ecosystem functional complexity leads to increasing ecosystem stability. The results indicated that complex functional dynamics can serve to stabilize the system. The results also demonstrated that microcosms are useful tools for system-level investigations.« less

Hyperspectral Remote Sensing of the Coastal Ocean: Adaptive Sampling and Forecasting of In situ Optical Properties

DTIC Science & Technology

2002-09-30

integrated observation system that is being coupled to a data assimilative hydrodynamic bio-optical ecosystem model. The system was used adaptively to develop hyperspectral remote sensing techniques in optically complex nearshore coastal waters.

A process-based framework for soil ecosystem services study and management.

PubMed

Su, Changhong; Liu, Huifang; Wang, Shuai

2018-06-15

Soil provides various indispensable ecosystem services for human society. Soil's complex structure and property makes the soil ecological processes complicated and brings about tough challenges for soil ecosystem services study. Most of the current frameworks on soil services focus exclusively on services per se, neglecting the links and underlying ecological mechanisms. This article put forward a framework on soil services by stressing the underlying soil mechanisms and processes, which includes: 1) analyzing soil natural capital stock based on soil structure and property, 2) disentangling the underlying complex links and soil processes, 3) soil services valuation based on field investigation and spatial explicit models, and 4) enacting soil management strategy based on soil services and their driving factors. By application of this framework, we assessed the soil services of sediment retention, water yield, and grain production in the Upper-reach Fenhe Watershed. Based on the ecosystem services and human driving factors, the whole watershed was clustered into five groups: 1) municipal area, 2) typical coal mining area, 3) traditional farming area, 4) unsustainable urbanizing area, and 5) ecological conservation area. Management strategies on soils were made according to the clustering based soil services and human activities. Copyright © 2018 Elsevier B.V. All rights reserved.

Ecosystem engineering by seagrasses interacts with grazing to shape an intertidal landscape.

PubMed

van der Heide, Tjisse; Eklöf, Johan S; van Nes, Egbert H; van der Zee, Els M; Donadi, Serena; Weerman, Ellen J; Olff, Han; Eriksson, Britas Klemens

2012-01-01

Self-facilitation through ecosystem engineering (i.e., organism modification of the abiotic environment) and consumer-resource interactions are both major determinants of spatial patchiness in ecosystems. However, interactive effects of these two mechanisms on spatial complexity have not been extensively studied. We investigated the mechanisms underlying a spatial mosaic of low-tide exposed hummocks and waterlogged hollows on an intertidal mudflat in the Wadden Sea dominated by the seagrass Zostera noltii. A combination of field measurements, an experiment and a spatially explicit model indicated that the mosaic resulted from localized sediment accretion by seagrass followed by selective waterfowl grazing. Hollows were bare in winter, but were rapidly colonized by seagrass during the growth season. Colonized hollows were heavily grazed by brent geese and widgeon in autumn, converting these patches to a bare state again and disrupting sediment accretion by seagrass. In contrast, hummocks were covered by seagrass throughout the year and were rarely grazed, most likely because the waterfowl were not able to employ their preferred but water requiring feeding strategy ('dabbling') here. Our study exemplifies that interactions between ecosystem engineering by a foundation species (seagrass) and consumption (waterfowl grazing) can increase spatial complexity at the landscape level.

Landscape Level Carbon and Water Balances and Agricultural Production in Mountainous Terrain of the Haean Basin, South Korea

NASA Astrophysics Data System (ADS)

Lee, B.; Geyer, R.; Seo, B.; Lindner, S.; Walther, G.; Tenhunen, J. D.

2009-12-01

The process-based spatial simulation model PIXGRO was used to estimate gross primary production, ecosystem respiration, net ecosystem CO2 exchange and water use by forest and crop fields of Haean Basin, South Korea at landscape scale. Simulations are run for individual years from early spring to late fall, providing estimates for dry land crops and rice paddies with respect to carbon gain, biomass and leaf area development, allocation of photoproducts to the belowground ecosystem compartment, and harvest yields. In the case of deciduous oak forests, gas exchange is estimated, but spatial simulation of growth over the single annual cycles is not included. Spatial parameterization of the model is derived for forest LAI based on remote sensing, for forest and cropland fluxes via eddy covariance and chamber studies, for soil characteristics by generalization from spatial surveys, for climate drivers by generalizing observations at ca. 20 monitoring stations distributed throughout the basin and along the elevation gradient from 500 to 1000 m, and for incident radiation via modelling of the radiation components in complex terrain. Validation of the model is being carried out at point scale based on comparison of model output at selected locations with observations as well as with known trends in ecosystem response documented in the literature. The resulting modelling tool is useful for estimation of ecosystem services at landscape scale, first expressed as kg ha-1 crop yield, but via future cooperative studies also in terms of monetary gain to individual farms and farming cooperatives applying particular management strategies.

Land management in the American southwest: a state-and-transition approach to ecosystem complexity.

PubMed

Bestelmeyer, Brandon T; Herrick, Jeffrey E; Brown, Joel R; Trujillo, David A; Havstad, Kris M

2004-07-01

State-and-transition models are increasingly being used to guide rangeland management. These models provide a relatively simple, management-oriented way to classify land condition (state) and to describe the factors that might cause a shift to another state (a transition). There are many formulations of state-and-transition models in the literature. The version we endorse does not adhere to any particular generalities about ecosystem dynamics, but it includes consideration of several kinds of dynamics and management response to them. In contrast to previous uses of state-and-transition models, we propose that models can, at present, be most effectively used to specify and qualitatively compare the relative benefits and potential risks of different management actions (e.g., fire and grazing) and other factors (e.g., invasive species and climate change) on specified areas of land. High spatial and temporal variability and complex interactions preclude the meaningful use of general quantitative models. Forecasts can be made on a case-by-case basis by interpreting qualitative and quantitative indicators, historical data, and spatially structured monitoring data based on conceptual models. We illustrate how science- based conceptual models are created using several rangeland examples that vary in complexity. In doing so, we illustrate the implications of designating plant communities and states in models, accounting for varying scales of pattern in vegetation and soils, interpreting the presence of plant communities on different soils and dealing with our uncertainty about how those communities were assembled and how they will change in the future. We conclude with observations about how models have helped to improve management decision-making.

Self-feedbacks determine the sustainability of human interventions in eco-social complex systems: Impacts on biodiversity and ecosystem health

PubMed Central

Ortiz, Marco

2017-01-01

Several administrative polices have been implemented in order to reduce the negative impacts of fishing on natural ecosystems. Four eco-social models with different levels of complexity were constructed, which represent the seaweed harvest in central-northern Chile under two different regimes, Management and Exploitation Areas for Benthic Resources (MAEBRs) and Open Access Areas (OAAs). The dynamics of both regimes were analyzed using the following theoretical frameworks: (1) Loop Analysis, which allows the local stability or sustainability of the models and scenarios to be assessed; and (2) Hessian´s optimization procedure of a global fishery function (GFF) that represents each dynamics of each harvest. The results suggest that the current fishing dynamics in MAEBRs are not sustainable unless the market demand presents some type of control (i.e. taxes). Further, the results indicated that if the demand changes to a self-negative feedback (self-control) in MAEBRs, the stability is increased and, simultaneously, a relative maximum for the GFF is reached. Contrarily, the sustainability of the model/system representing the harvest (principally by cutting plants) in OAAs is not reached. The implementation of an “ecological” tax for intensive artisanal fisheries with low operational cost is proposed. The network analysis developed here is proposed as a general strategy for studying the effects of human interventions in marine coastal ecosystems under transient (short-term) dynamics. PMID:28453548

Self-feedbacks determine the sustainability of human interventions in eco-social complex systems: Impacts on biodiversity and ecosystem health.

PubMed

Ortiz, Marco; Levins, Richard

2017-01-01

Several administrative polices have been implemented in order to reduce the negative impacts of fishing on natural ecosystems. Four eco-social models with different levels of complexity were constructed, which represent the seaweed harvest in central-northern Chile under two different regimes, Management and Exploitation Areas for Benthic Resources (MAEBRs) and Open Access Areas (OAAs). The dynamics of both regimes were analyzed using the following theoretical frameworks: (1) Loop Analysis, which allows the local stability or sustainability of the models and scenarios to be assessed; and (2) Hessian´s optimization procedure of a global fishery function (GFF) that represents each dynamics of each harvest. The results suggest that the current fishing dynamics in MAEBRs are not sustainable unless the market demand presents some type of control (i.e. taxes). Further, the results indicated that if the demand changes to a self-negative feedback (self-control) in MAEBRs, the stability is increased and, simultaneously, a relative maximum for the GFF is reached. Contrarily, the sustainability of the model/system representing the harvest (principally by cutting plants) in OAAs is not reached. The implementation of an "ecological" tax for intensive artisanal fisheries with low operational cost is proposed. The network analysis developed here is proposed as a general strategy for studying the effects of human interventions in marine coastal ecosystems under transient (short-term) dynamics.

A phase transition induces chaos in a predator-prey ecosystem with a dynamic fitness landscape.

PubMed

Gilpin, William; Feldman, Marcus W

2017-07-01

In many ecosystems, natural selection can occur quickly enough to influence the population dynamics and thus future selection. This suggests the importance of extending classical population dynamics models to include such eco-evolutionary processes. Here, we describe a predator-prey model in which the prey population growth depends on a prey density-dependent fitness landscape. We show that this two-species ecosystem is capable of exhibiting chaos even in the absence of external environmental variation or noise, and that the onset of chaotic dynamics is the result of the fitness landscape reversibly alternating between epochs of stabilizing and disruptive selection. We draw an analogy between the fitness function and the free energy in statistical mechanics, allowing us to use the physical theory of first-order phase transitions to understand the onset of rapid cycling in the chaotic predator-prey dynamics. We use quantitative techniques to study the relevance of our model to observational studies of complex ecosystems, finding that the evolution-driven chaotic dynamics confer community stability at the "edge of chaos" while creating a wide distribution of opportunities for speciation during epochs of disruptive selection-a potential observable signature of chaotic eco-evolutionary dynamics in experimental studies.

The Role of Herbivory in Structuring Tropical Seagrass Ecosystem Service Delivery

PubMed Central

Scott, Abigail L.; York, Paul H.; Duncan, Clare; Macreadie, Peter I.; Connolly, Rod M.; Ellis, Megan T.; Jarvis, Jessie C.; Jinks, Kristin I.; Marsh, Helene; Rasheed, Michael A.

2018-01-01

Seagrass meadows support key ecosystem services, via provision of food directly for herbivores, and indirectly to their predators. The importance of herbivores in seagrass meadows has been well-documented, but the links between food webs and ecosystem services in seagrass meadows have not previously been made explicit. Herbivores interact with ecosystem services – including carbon sequestration, cultural values, and coastal protection. Interactions can be positive or negative and depend on a range of factors including the herbivore identity and the grazing type and intensity. There can be unintended consequences from management actions based on a poor understanding of trade-offs that occur with complex seagrass-herbivore interactions. Tropical seagrass meadows support a diversity of grazers spanning the meso-, macro-, and megaherbivore scales. We present a conceptual model to describe how multiple ecosystem services are influenced by herbivore pressure in tropical seagrass meadows. Our model suggests that a balanced ecosystem, incorporating both seagrass and herbivore diversity, is likely to sustain the broadest range of ecosystem services. Our framework suggests the pathway to achieve desired ecosystem services outcomes requires knowledge on four key areas: (1) how size classes of herbivores interact to structure seagrass; (2) desired community and management values; (3) seagrass responses to top–down and bottom–up controls; (4) the pathway from intermediate to final ecosystem services and human benefits. We suggest research should be directed to these areas. Herbivory is a major structuring influence in tropical seagrass systems and needs to be considered for effective management of these critical habitats and their services. PMID:29487606

DayCent-Chem Simulations of Ecological and Biogeochemical Processes of Eight Mountain Ecosystems in the United States

USGS Publications Warehouse

Hartman, Melannie D.; Baron, Jill S.; Clow, David W.; Creed, Irena F.; Driscoll, Charles T.; Ewing, Holly A.; Haines, Bruce D.; Knoepp, Jennifer; Lajtha, Kate; Ojima, Dennis S.; Parton, William J.; Renfro, Jim; Robinson, R. Bruce; Van Miegroet, Helga; Weathers, Kathleen C.; Williams, Mark W.

2009-01-01

Atmospheric deposition of nitrogen (N) and sulfur (S) cause complex responses in ecosystems, from fertilization to forest ecosystem decline, freshwater eutrophication to acidification, loss of soil base cations, and alterations of disturbance regimes. DayCent-Chem, an ecosystem simulation model that combines ecosystem nutrient cycling and plant dynamics with aqueous geochemical equilibrium calculations, was developed to address ecosystem responses to combined atmospheric N and S deposition. It is unique among geochemically-based models in its dynamic biological cycling of N and its daily timestep for investigating ecosystem and surface water chemical response to episodic events. The model was applied to eight mountainous watersheds in the United States. The sites represent a gradient of N deposition across locales, from relatively pristine to N-saturated, and a variety of ecosystem types and climates. Overall, the model performed best in predicting stream chemistry for snowmelt-dominated sites. It was more difficult to predict daily stream chemistry for watersheds with deep soils, high amounts of atmospheric deposition, and a large degree of spatial heterogeneity. DayCent-Chem did well in representing plant and soil carbon and nitrogen pools and fluxes. Modeled stream nitrate (NO3-) and ammonium (NH4+) concentrations compared well with measurements at all sites, with few exceptions. Simulated daily stream sulfate (SO42-) concentrations compared well to measured values for sites where SO42- deposition has been low and where SO42- adsorption/desorption reactions did not seem to be important. The concentrations of base cations and silica in streams are highly dependent on the geochemistry and weathering rates of minerals in each catchment, yet these were rarely, if ever, known. Thus, DayCent-Chem could not accurately predict weathering products for some catchments. Additionally, few data were available for exchangeable soil cations or the magnitude of base cation deposition as a result of dry and fog inputs. The uncertainties related to weathering reactions, deposition, soil cation exchange capacity, and groundwater contributions influenced how well the simulated acid neutralizing capacity (ANC) and pH estimates compared to observed values. Daily discharge was well represented by the model for most sites. The chapters of this report describe the parameterization for each site and summarize model results for ecosystem variables, stream discharge, and stream chemistry. This intersite comparison exercise provided insight about important and possibly not well understood processes.

Modeling silviculture after natural disturbance to sustain biodiversity in the longleaf pine (Pinus palustris) ecosystem : balancing complexity and implementation

Treesearch

Brian J. Palik; Robert J. Mitchell; J. Kevin Hiers

2002-01-01

Modeling silviculture after natural disturbance to maintain biodiversity is a popular concept, yet its application remains elusive. We discuss difficulties inherent to this idea, and suggest approaches to facilitate implementation, using longleaf pine (Pinus palustris) as an example. Natural disturbance regimes are spatially and temporally variable. Variability...

Lessons learned studying design issues for lunar and Mars settlements

NASA Technical Reports Server (NTRS)

Litton, C. E.

1997-01-01

In a study of lunar and Mars settlement concepts, an analysis was made of fundamental design assumptions in five technical areas against a model list of occupational and environmental health concerns. The technical areas included the proposed science projects to be supported, habitat and construction issues, closed ecosystem issues, the "MMM" issues (mining, material processing, and manufacturing), and the human elements of physiology, behavior, and mission approach. Four major lessons were learned. First it is possible to relate public health concerns to complex technological development in a proactive design mode, which has the potential for long-term cost savings. Second, it became very apparent that prior to committing any nation or international group to spending the billions to start and complete a lunar settlement, over the next century, that a significantly different approach must be taken from those previously proposed, to solve the closed ecosystem and "MMM" problems. Third, it also appears that the health concerns and technology issues to be addressed for human exploration into space are fundamentally those to be solved for human habitation of the Earth (as a closed ecosystem) in the 21st century. Finally, it is proposed that ecosystem design modeling must develop new tools, based on probabilistic models as a step up from closed circuit models.

Lessons learned studying design issues for lunar and Mars settlements.

PubMed

Litton, C E

1997-01-01

In a study of lunar and Mars settlement concepts, an analysis was made of fundamental design assumptions in five technical areas against a model list of occupational and environmental health concerns. The technical areas included the proposed science projects to be supported, habitat and construction issues, closed ecosystem issues, the "MMM" issues (mining, material processing, and manufacturing), and the human elements of physiology, behavior, and mission approach. Four major lessons were learned. First it is possible to relate public health concerns to complex technological development in a proactive design mode, which has the potential for long-term cost savings. Second, it became very apparent that prior to committing any nation or international group to spending the billions to start and complete a lunar settlement, over the next century, that a significantly different approach must be taken from those previously proposed, to solve the closed ecosystem and "MMM" problems. Third, it also appears that the health concerns and technology issues to be addressed for human exploration into space are fundamentally those to be solved for human habitation of the Earth (as a closed ecosystem) in the 21st century. Finally, it is proposed that ecosystem design modeling must develop new tools, based on probabilistic models as a step up from closed circuit models.

Modeling the dynamic responses of riparian vegetation and salmon habitat in the Oregon Coast Range with state-and-transition models

Treesearch

Steven M. Wondzell; Agnieszka Przeszlowska; Dirk Pflugmacher; Miles A. Hemstrom; Peter A. Bisson

2012-01-01

Interactions between landuse and ecosystem change are complex, especially in riparian zones. To date, few models are available to project the influence of alternative landuse practices, natural disturbance and plant succession on the likely future conditions of riparian zones and aquatic habitats across large spatial extents. A state and transition approach was used to...

Using DCOM to support interoperability in forest ecosystem management decision support systems

Treesearch

W.D. Potter; S. Liu; X. Deng; H.M. Rauscher

2000-01-01

Forest ecosystems exhibit complex dynamics over time and space. Management of forest ecosystems involves the need to forecast future states of complex systems that are often undergoing structural changes. This in turn requires integration of quantitative science and engineering components with sociopolitical, regulatory, and economic considerations. The amount of data...

Development of a 3D coupled physical-biogeochemical model for the Marseille coastal area (NW Mediterranean Sea): what complexity is required in the coastal zone?

PubMed

Fraysse, Marion; Pinazo, Christel; Faure, Vincent Martin; Fuchs, Rosalie; Lazzari, Paolo; Raimbault, Patrick; Pairaud, Ivane

2013-01-01

Terrestrial inputs (natural and anthropogenic) from rivers, the atmosphere and physical processes strongly impact the functioning of coastal pelagic ecosystems. The objective of this study was to develop a tool for the examination of these impacts on the Marseille coastal area, which experiences inputs from the Rhone River and high rates of atmospheric deposition. Therefore, a new 3D coupled physical/biogeochemical model was developed. Two versions of the biogeochemical model were tested, one model considering only the carbon (C) and nitrogen (N) cycles and a second model that also considers the phosphorus (P) cycle. Realistic simulations were performed for a period of 5 years (2007-2011). The model accuracy assessment showed that both versions of the model were able of capturing the seasonal changes and spatial characteristics of the ecosystem. The model also reproduced upwelling events and the intrusion of Rhone River water into the Bay of Marseille well. Those processes appeared to greatly impact this coastal oligotrophic area because they induced strong increases in chlorophyll-a concentrations in the surface layer. The model with the C, N and P cycles better reproduced the chlorophyll-a concentrations at the surface than did the model without the P cycle, especially for the Rhone River water. Nevertheless, the chlorophyll-a concentrations at depth were better represented by the model without the P cycle. Therefore, the complexity of the biogeochemical model introduced errors into the model results, but it also improved model results during specific events. Finally, this study suggested that in coastal oligotrophic areas, improvements in the description and quantification of the hydrodynamics and the terrestrial inputs should be preferred over increasing the complexity of the biogeochemical model.

Development of a 3D Coupled Physical-Biogeochemical Model for the Marseille Coastal Area (NW Mediterranean Sea): What Complexity Is Required in the Coastal Zone?

PubMed Central

Fraysse, Marion; Pinazo, Christel; Faure, Vincent Martin; Fuchs, Rosalie; Lazzari, Paolo; Raimbault, Patrick; Pairaud, Ivane

2013-01-01

Terrestrial inputs (natural and anthropogenic) from rivers, the atmosphere and physical processes strongly impact the functioning of coastal pelagic ecosystems. The objective of this study was to develop a tool for the examination of these impacts on the Marseille coastal area, which experiences inputs from the Rhone River and high rates of atmospheric deposition. Therefore, a new 3D coupled physical/biogeochemical model was developed. Two versions of the biogeochemical model were tested, one model considering only the carbon (C) and nitrogen (N) cycles and a second model that also considers the phosphorus (P) cycle. Realistic simulations were performed for a period of 5 years (2007–2011). The model accuracy assessment showed that both versions of the model were able of capturing the seasonal changes and spatial characteristics of the ecosystem. The model also reproduced upwelling events and the intrusion of Rhone River water into the Bay of Marseille well. Those processes appeared to greatly impact this coastal oligotrophic area because they induced strong increases in chlorophyll-a concentrations in the surface layer. The model with the C, N and P cycles better reproduced the chlorophyll-a concentrations at the surface than did the model without the P cycle, especially for the Rhone River water. Nevertheless, the chlorophyll-a concentrations at depth were better represented by the model without the P cycle. Therefore, the complexity of the biogeochemical model introduced errors into the model results, but it also improved model results during specific events. Finally, this study suggested that in coastal oligotrophic areas, improvements in the description and quantification of the hydrodynamics and the terrestrial inputs should be preferred over increasing the complexity of the biogeochemical model. PMID:24324589

Using models in Integrated Ecosystem Assessment of coastal areas

NASA Astrophysics Data System (ADS)

Solidoro, Cosimo; Bandelj, Vinko; Cossarini, Gianpiero; Melaku Canu, Donata; Libralato, Simone

2014-05-01

Numerical Models can greatly contribute to integrated ecological assessment of coastal and marine systems. Indeed, models can: i) assist in the identification of efficient sampling strategy; ii) provide space interpolation and time extrapolation of experiemtanl data which are based on the knowedge on processes dynamics and causal realtionships which is coded within the model, iii) provide estimates of hardly measurable indicators. Furthermore model can provide indication on potential effects of implementation of alternative management policies. Finally, by providing a synthetic representation of an ideal system, based on its essential dynamic, model return a picture of ideal behaviour of a system in the absence of external perturbation, alteration, noise, which might help in the identification of reference behaivuor. As an important example, model based reanalyses of biogeochemical and ecological properties are an urgent need for the estimate of the environmental status and the assessment of efficacy of conservation and environmental policies, also with reference to the enforcement of the European MSFD. However, the use of numerical models, and particularly of ecological models, in modeling and in environmental management still is far from be the rule, possibly because of a lack in realizing the benefits which a full integration of modeling and montoring systems might provide, possibly because of a lack of trust in modeling results, or because many problems still exists in the development, validation and implementation of models. For istance, assessing the validity of model results is a complex process that requires the definition of appropriate indicators, metrics, methodologies and faces with the scarcity of real-time in-situ biogeochemical data. Furthermore, biogeochemical models typically consider dozens of variables which are heavily undersampled. Here we show how the integration of mathematical model and monitoring data can support integrated ecosystem assessment of a waterbody by reviewing applications from a complex coastal ecosystem, the Lagoon of Venice, and explore potential applications to other coastal and open sea system, up to the scale of the Mediterannean Sea.

Fen ecohydrologic trajectories in response to groundwater drawdown with edaphic, floristic, and hydrologic feedbacks

NASA Astrophysics Data System (ADS)

Booth, E.; Steven, L. I.; Bart, D.

2017-12-01

Calcareous fens are unique and often isolated ecosystems of high conservation value worldwide because they provide habitat for many rare plant and animal species. Their identity is inextricably linked to an absolute dependence on a consistent discharge of groundwater that saturates the near surface for most of the growing season leading to the accumulation of carbon as peat or tufa and sequestration of nutrients. The stresses resulting from consistent saturation and low-nutrient availability result in high native plant diversity including very high rare species richness compared to other ecosystems. Decreases in the saturation stress by reduced groundwater inputs (e.g., from nearby pumping) can result in losses of native diversity, decreases in rare-species abundance, and increased invasion by non-native species. As such, fen ecosystems are particularly susceptible to changes in groundwater conditions including reduction in water levels due to nearby groundwater pumping. Trajectories of degradation are complex due to feedbacks between loss of soil organic carbon, changes in soil properties, and plant water use. We present a model of an archetype fen that couples a hydrological niche model with a variably-saturated groundwater flow model to predict changes in vegetation composition in response to different groundwater drawdown scenarios (step change, declining trend, and periodic drawdown during dry periods). The model also includes feedbacks among vegetation composition, plant water use, and soil properties. The hydrological niche models (using surface soil moisture as predictor) and relationships between vegetation composition, plant water use (via stomatal conductance and leaf-area index), and soil hydraulic properties (van Genuchten parameters) were determined based on data collected from six fens in Wisconsin under various states of degradation. Results reveal a complex response to drawdown and provide insight into other ecosystems with linkages between the hydrologic regime, plants, water use, and soil properties.

Capturing Ecosystem Services, Stakeholders' Preferences and Trade-Offs in Coastal Aquaculture Decisions: A Bayesian Belief Network Application

PubMed Central

Schmitt, Laetitia Helene Marie; Brugere, Cecile

2013-01-01

Aquaculture activities are embedded in complex social-ecological systems. However, aquaculture development decisions have tended to be driven by revenue generation, failing to account for interactions with the environment and the full value of the benefits derived from services provided by local ecosystems. Trade-offs resulting from changes in ecosystem services provision and associated impacts on livelihoods are also often overlooked. This paper proposes an innovative application of Bayesian belief networks - influence diagrams - as a decision support system for mediating trade-offs arising from the development of shrimp aquaculture in Thailand. Senior experts were consulted (n = 12) and primary farm data on the economics of shrimp farming (n = 20) were collected alongside secondary information on ecosystem services, in order to construct and populate the network. Trade-offs were quantitatively assessed through the generation of a probabilistic impact matrix. This matrix captures nonlinearity and uncertainty and describes the relative performance and impacts of shrimp farming management scenarios on local livelihoods. It also incorporates export revenues and provision and value of ecosystem services such as coastal protection and biodiversity. This research shows that Bayesian belief modeling can support complex decision-making on pathways for sustainable coastal aquaculture development and thus contributes to the debate on the role of aquaculture in social-ecological resilience and economic development. PMID:24155876

Introducing mixotrophy into a biogeochemical model describing an eutrophied coastal ecosystem: The Southern North Sea

NASA Astrophysics Data System (ADS)

Ghyoot, Caroline; Lancelot, Christiane; Flynn, Kevin J.; Mitra, Aditee; Gypens, Nathalie

2017-09-01

Most biogeochemical/ecological models divide planktonic protists between phototrophs (phytoplankton) and heterotrophs (zooplankton). However, a large number of planktonic protists are able to combine several mechanisms of carbon and nutrient acquisition. Not representing these multiple mechanisms in biogeochemical/ecological models describing eutrophied coastal ecosystems can potentially lead to different conclusions regarding ecosystem functioning, especially regarding the success of harmful algae, which are often reported as mixotrophic. This modelling study investigates the implications for trophic dynamics of including 3 contrasting forms of mixotrophy, namely osmotrophy (using alkaline phosphatase activity, APA), non-constitutive mixotrophy (acquired phototrophy by microzooplankton) and also constitutive mixotrophy. The application is in the Southern North Sea, an ecosystem that faced, between 1985 and 2005, a significant increase in the nutrient supply N:P ratio (from 31 to 81 mol N:P). The comparison with a traditional model shows that, when the winter N:P ratio in the Southern North Sea is above 22 molN molP-1 (as occurred from mid-1990s), APA allows a 3-32% increase of annual gross primary production (GPP). In result of the higher GPP, the annual sedimentation increases as well as the bacterial production. By contrast, APA does not affect the export of matter to higher trophic levels because the increased GPP is mainly due to Phaeocystis colonies, which are not grazed by copepods. Under high irradiance, non-constitutive mixotrophy appreciably increases annual GPP, transfer to higher trophic levels, sedimentation, and nutrient remineralisation. In this ecosystem, non-constitutive mixotrophy is also observed to have an indirect stimulating effect on diatoms. Constitutive mixotrophy in nanoflagellates appears to have little influence on this ecosystem functioning. An important conclusion from this work is that contrasting forms of mixotrophy have different impacts on system dynamics and, due to the complex interactions in the ecosystem, their combined effect is not exactly the addition of the effects individually observed. It is thus important to describe such contrasting forms in an appropriate fashion.

Identifying habitats at risk: simple models can reveal complex ecosystem dynamics.

PubMed

Maxwell, Paul S; Pitt, Kylie A; Olds, Andrew D; Rissik, David; Connolly, Rod M

2015-03-01

The relationship between ecological impact and ecosystem structure is often strongly nonlinear, so that small increases in impact levels can cause a disproportionately large response in ecosystem structure. Nonlinear ecosystem responses can be difficult to predict because locally relevant data sets can be difficult or impossible to obtain. Bayesian networks (BN) are an emerging tool that can help managers to define ecosystem relationships using a range of data types from comprehensive quantitative data sets to expert opinion. We show how a simple BN can reveal nonlinear dynamics in seagrass ecosystems using ecological relationships sourced from the literature. We first developed a conceptual diagram by cataloguing the ecological responses of seagrasses to a range of drivers and impacts. We used the conceptual diagram to develop a BN populated with values sourced from published studies. We then applied the BN to show that the amount of initial seagrass biomass has a mitigating effect on the level of impact a meadow can withstand without loss, and that meadow recovery can often require disproportionately large improvements in impact levels. This mitigating effect resulted in the middle ranges of impact levels having a wide likelihood of seagrass presence, a situation known as bistability. Finally, we applied the model in a case study to identify the risk of loss and the likelihood of recovery for the conservation and management of seagrass meadows in Moreton Bay, Queensland, Australia. We used the model to predict the likelihood of bistability in 23 locations in the Bay. The model predicted bistability in seven locations, most of which have experienced seagrass loss at some stage in the past 25 years providing essential information for potential future restoration efforts. Our results demonstrate the capacity of simple, flexible modeling tools to facilitate collation and synthesis of disparate information. This approach can be adopted in the initial stages of conservation programs as a low-cost and relatively straightforward way to provide preliminary assessments of.nonlinear dynamics in ecosystems.

Moderate forest disturbance as a stringent test for gap and big-leaf models

NASA Astrophysics Data System (ADS)

Bond-Lamberty, B.; Fisk, J.; Holm, J. A.; Bailey, V.; Gough, C. M.

2014-07-01

Disturbance-induced tree mortality is a key factor regulating the carbon balance of a forest, but tree mortality and its subsequent effects are poorly represented processes in terrestrial ecosystem models. In particular, it is unclear whether models can robustly simulate moderate (non-catastrophic) disturbances, which tend to increase biological and structural complexity and are increasingly common in aging US forests. We tested whether three forest ecosystem models - Biome-BGC, a classic big-leaf model, and the ED and ZELIG gap-oriented models - could reproduce the resilience to moderate disturbance observed in an experimentally manipulated forest (the Forest Accelerated Succession Experiment in northern Michigan, USA, in which 38% of canopy dominants were stem girdled and compared to control plots). Each model was parameterized, spun up, and disturbed following similar protocols, and run for 5 years post-disturbance. The models replicated observed declines in aboveground biomass well. Biome-BGC captured the timing and rebound of observed leaf area index (LAI), while ED and ZELIG correctly estimated the magnitude of LAI decline. None of the models fully captured the observed post-disturbance C fluxes. Biome-BGC net primary production (NPP) was correctly resilient, but for the wrong reasons, while ED and ZELIG exhibited large, unobserved drops in NPP and net ecosystem production. The biological mechanisms proposed to explain the observed rapid resilience of the C cycle are typically not incorporated by these or other models. As a result we expect that most ecosystem models, developed to simulate processes following stand-replacing disturbances, will not simulate well the gradual and less extensive tree mortality characteristic of moderate disturbances.

Vegetation Demographics in Earth System Models: a review of progress and priorities

DOE PAGES

Fisher, Rosie A.; Koven, Charles D.; Anderegg, William R. L.; ...

2017-09-18

Numerous current efforts seek to improve the representation of ecosystem ecology and vegetation demographic processes within Earth System Models (ESMs). Furthermore, these developments are widely viewed as an important step in developing greater realism in predictions of future ecosystem states and fluxes. Increased realism, however, leads to increased model complexity, with new features raising a suite of ecological questions that require empirical constraints. We review the developments that permit the representation of plant demographics in ESMs, and identify issues raised by these developments that highlight important gaps in ecological understanding. These issues inevitably translate into uncertainty in model projections butmore » also allow models to be applied to new processes and questions concerning the dynamics of real-world ecosystems. We also argue that stronger and more innovative connections to data, across the range of scales considered, are required to address these gaps in understanding. The development of first-generation land surface models as a unifying framework for ecophysiological understanding stimulated much research into plant physiological traits and gas exchange. Constraining predictions at ecologically relevant spatial and temporal scales will require a similar investment of effort and intensified inter-disciplinary communication.« less

Vegetation Demographics in Earth System Models: a review of progress and priorities

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fisher, Rosie A.; Koven, Charles D.; Anderegg, William R. L.

Numerous current efforts seek to improve the representation of ecosystem ecology and vegetation demographic processes within Earth System Models (ESMs). Furthermore, these developments are widely viewed as an important step in developing greater realism in predictions of future ecosystem states and fluxes. Increased realism, however, leads to increased model complexity, with new features raising a suite of ecological questions that require empirical constraints. We review the developments that permit the representation of plant demographics in ESMs, and identify issues raised by these developments that highlight important gaps in ecological understanding. These issues inevitably translate into uncertainty in model projections butmore » also allow models to be applied to new processes and questions concerning the dynamics of real-world ecosystems. We also argue that stronger and more innovative connections to data, across the range of scales considered, are required to address these gaps in understanding. The development of first-generation land surface models as a unifying framework for ecophysiological understanding stimulated much research into plant physiological traits and gas exchange. Constraining predictions at ecologically relevant spatial and temporal scales will require a similar investment of effort and intensified inter-disciplinary communication.« less

Potential Applications of Gosat Based Carbon Budget Products to Refine Terrestrial Ecosystem Model

NASA Astrophysics Data System (ADS)

Kondo, M.; Ichii, K.

2011-12-01

Estimation of carbon exchange in terrestrial ecosystem associates with difficulties due to complex entanglement of physical and biological processes: thus, the net ecosystem productivity (NEP) estimated from simulation often differs among process-based terrestrial ecosystem models. In addition to complexity of the system, validation can only be conducted in a point scale since reliable observation is only available from ground observations. With a lack of large spatial data, extension of model simulation to a global scale results in significant uncertainty in the future carbon balance and climate change. Greenhouse gases Observing SATellite (GOSAT), launched by the Japanese space agency (JAXA) in January, 2009, is the 1st operational satellite promised to deliver the net land-atmosphere carbon budget to the terrestrial biosphere research community. Using that information, the model reproducibility of carbon budget is expected to improve: hence, gives a better estimation of the future climate change. This initial analysis is to seek and evaluate the potential applications of GOSAT observation toward the sophistication of terrestrial ecosystem model. The present study was conducted in two processes: site-based analysis using eddy covariance observation data to assess the potential use of terrestrial carbon fluxes (GPP, RE, and NEP) to refine the model, and extension of the point scale analysis to spatial using Carbon Tracker product as a prototype of GOSAT product. In the first phase of the experiment, it was verified that an optimization routine adapted to a terrestrial model, Biome-BGC, yielded the improved result with respect to eddy covariance observation data from AsiaFlux Network. Spatial data sets used in the second phase were consists of GPP from empirical algorithm (e.g. support vector machine), NEP from Carbon Tracker, and RE from the combination of these. These spatial carbon flux estimations was used to refine the model applying the exactly same optimization procedure as the point analysis, and found that these spatial data help to improve the model's overall reproducibility. The GOSAT product is expected to have higher accuracy since it uses global CO2 observations. Therefore, with the application of GOSAT data, a better estimation of terrestrial carbon cycle can be achieved with optimization. It is anticipated to carry out more detailed analysis upon the arrival of GOSAT product and to verify the reduction in the uncertainty in the future carbon budget and the climate change with the calibrated models, which is the major contribution can be achieved from GOSAT.

Site closure management strategies and the responsiveness of conservation outcomes in recreational fishing.

PubMed

Gao, Lei; Hailu, Atakelty

2018-02-01

We develop and use an empirically based model, which integrates fishing behaviour and a coral reef system, to evaluate outcomes from site closure strategies to manage the effects of recreational fishing. The model is designed to estimate management effects in complex settings with two-way feedback effects (between fishing and ecosystem dynamics) as well as spillover effects where the closure of a site (or sites) leads to the redistribution of fishing effort. An iconic coral reef system is used as a case study. The results demonstrate that some site closure strategies provide little incremental benefits over less stringent approaches. They also show that some strategies targeting more sites are actually inferior to more limited strategies, demonstrating that, in the analysis of complex problems involving feedback effects and substitutions, there is little substitute for the use of empirically based and sound modelling as the basis for informed conservation decision making and stakeholder consultation. These findings have direct relevance not only for policies aimed at improving recreational fishing management but also for securing the supply of marine ecosystem services. Copyright © 2017 Elsevier Ltd. All rights reserved.

Modeling multiple resource limitation in tropical dry forests

NASA Astrophysics Data System (ADS)

Medvigy, D.; Xu, X.; Zarakas, C.

2015-12-01

Tropical dry forests (TDFs) are characterized by a long dry season when little rain falls. At the same time, many neotropical soils are highly weathered and relatively nutrient poor. Because TDFs are often subject to both water and nutrient constraints, the question of how they will respond to environmental perturbations is both complex and highly interesting. Models, our basic tools for projecting ecosystem responses to global change, can be used to address this question. However, few models have been specifically parameterized for TDFs. Here, we present a new version of the Ecosystem Demography 2 (ED2) model that includes a new parameterization of TDFs. In particular, we focus on the model's framework for representing limitation by multiple resources (carbon, water, nitrogen, and phosphorus). Plant functional types are represented in terms of a dichotomy between "acquisitive" and "conservative" resource acquisition strategies. Depending on their resource acquisition strategy and basic stoichiometry, plants can dynamically adjust their allocation to organs (leaves, stem, roots), symbionts (e.g. N2-fixing bacteria), and mycorrhizal fungi. Several case studies are used to investigate how resource acquisition strategies affect ecosystem responses to environmental perturbations. Results are described in terms of the basic setting (e.g., rich vs. poor soils; longer vs. shorter dry season), and well as the type and magnitude of environmental perturbation (e.g., changes in precipitation or temperature; changes in nitrogen deposition). Implications for ecosystem structure and functioning are discussed.

Simulated Carbon Cycling in a Model Microbial Mat.

NASA Astrophysics Data System (ADS)

Decker, K. L.; Potter, C. S.

2006-12-01

We present here the novel addition of detailed organic carbon cycling to our model of a hypersaline microbial mat ecosystem. This ecosystem model, MBGC (Microbial BioGeoChemistry), simulates carbon fixation through oxygenic and anoxygenic photosynthesis, and the release of C and electrons for microbial heterotrophs via cyanobacterial exudates and also via a pool of dead cells. Previously in MBGC, the organic portion of the carbon cycle was simplified into a black-box rate of accumulation of simple and complex organic compounds based on photosynthesis and mortality rates. We will discuss the novel inclusion of fermentation as a source of carbon and electrons for use in methanogenesis and sulfate reduction, and the influence of photorespiration on labile carbon exudation rates in cyanobacteria. We will also discuss the modeling of decomposition of dead cells and the ultimate release of inorganic carbon. The detailed modeling of organic carbon cycling is important to the accurate representation of inorganic carbon flux through the mat, as well as to accurate representation of growth models of the heterotrophs under different environmental conditions. Because the model ecosystem is an analog of ancient microbial mats that had huge impacts on the atmosphere of early earth, this MBGC can be useful as a biological component to either early earth models or models of other planets that potentially harbor life.

An Integrated Coral Reef Ecosystem Model to Support Resource Management under a Changing Climate

PubMed Central

Weijerman, Mariska; Fulton, Elizabeth A.; Kaplan, Isaac C.; Gorton, Rebecca; Leemans, Rik; Mooij, Wolf M.; Brainard, Russell E.

2015-01-01

Millions of people rely on the ecosystem services provided by coral reefs, but sustaining these benefits requires an understanding of how reefs and their biotic communities are affected by local human-induced disturbances and global climate change. Ecosystem-based management that explicitly considers the indirect and cumulative effects of multiple disturbances has been recommended and adopted in policies in many places around the globe. Ecosystem models give insight into complex reef dynamics and their responses to multiple disturbances and are useful tools to support planning and implementation of ecosystem-based management. We adapted the Atlantis Ecosystem Model to incorporate key dynamics for a coral reef ecosystem around Guam in the tropical western Pacific. We used this model to quantify the effects of predicted climate and ocean changes and current levels of current land-based sources of pollution (LBSP) and fishing. We used the following six ecosystem metrics as indicators of ecosystem state, resilience and harvest potential: 1) ratio of calcifying to non-calcifying benthic groups, 2) trophic level of the community, 3) biomass of apex predators, 4) biomass of herbivorous fishes, 5) total biomass of living groups and 6) the end-to-start ratio of exploited fish groups. Simulation tests of the effects of each of the three drivers separately suggest that by mid-century climate change will have the largest overall effect on this suite of ecosystem metrics due to substantial negative effects on coral cover. The effects of fishing were also important, negatively influencing five out of the six metrics. Moreover, LBSP exacerbates this effect for all metrics but not quite as badly as would be expected under additive assumptions, although the magnitude of the effects of LBSP are sensitive to uncertainty associated with primary productivity. Over longer time spans (i.e., 65 year simulations), climate change impacts have a slight positive interaction with other drivers, generally meaning that declines in ecosystem metrics are not as steep as the sum of individual effects of the drivers. These analyses offer one way to quantify impacts and interactions of particular stressors in an ecosystem context and so provide guidance to managers. For example, the model showed that improving water quality, rather than prohibiting fishing, extended the timescales over which corals can maintain high abundance by at least 5–8 years. This result, in turn, provides more scope for corals to adapt or for resilient species to become established and for local and global management efforts to reduce or reverse stressors. PMID:26672983

An Integrated Coral Reef Ecosystem Model to Support Resource Management under a Changing Climate.

PubMed

Weijerman, Mariska; Fulton, Elizabeth A; Kaplan, Isaac C; Gorton, Rebecca; Leemans, Rik; Mooij, Wolf M; Brainard, Russell E

2015-01-01

Millions of people rely on the ecosystem services provided by coral reefs, but sustaining these benefits requires an understanding of how reefs and their biotic communities are affected by local human-induced disturbances and global climate change. Ecosystem-based management that explicitly considers the indirect and cumulative effects of multiple disturbances has been recommended and adopted in policies in many places around the globe. Ecosystem models give insight into complex reef dynamics and their responses to multiple disturbances and are useful tools to support planning and implementation of ecosystem-based management. We adapted the Atlantis Ecosystem Model to incorporate key dynamics for a coral reef ecosystem around Guam in the tropical western Pacific. We used this model to quantify the effects of predicted climate and ocean changes and current levels of current land-based sources of pollution (LBSP) and fishing. We used the following six ecosystem metrics as indicators of ecosystem state, resilience and harvest potential: 1) ratio of calcifying to non-calcifying benthic groups, 2) trophic level of the community, 3) biomass of apex predators, 4) biomass of herbivorous fishes, 5) total biomass of living groups and 6) the end-to-start ratio of exploited fish groups. Simulation tests of the effects of each of the three drivers separately suggest that by mid-century climate change will have the largest overall effect on this suite of ecosystem metrics due to substantial negative effects on coral cover. The effects of fishing were also important, negatively influencing five out of the six metrics. Moreover, LBSP exacerbates this effect for all metrics but not quite as badly as would be expected under additive assumptions, although the magnitude of the effects of LBSP are sensitive to uncertainty associated with primary productivity. Over longer time spans (i.e., 65 year simulations), climate change impacts have a slight positive interaction with other drivers, generally meaning that declines in ecosystem metrics are not as steep as the sum of individual effects of the drivers. These analyses offer one way to quantify impacts and interactions of particular stressors in an ecosystem context and so provide guidance to managers. For example, the model showed that improving water quality, rather than prohibiting fishing, extended the timescales over which corals can maintain high abundance by at least 5-8 years. This result, in turn, provides more scope for corals to adapt or for resilient species to become established and for local and global management efforts to reduce or reverse stressors.

Integrating health and environmental impact analysis.

PubMed

Reis, S; Morris, G; Fleming, L E; Beck, S; Taylor, T; White, M; Depledge, M H; Steinle, S; Sabel, C E; Cowie, H; Hurley, F; Dick, J McP; Smith, R I; Austen, M

2015-10-01

Scientific investigations have progressively refined our understanding of the influence of the environment on human health, and the many adverse impacts that human activities exert on the environment, from the local to the planetary level. Nonetheless, throughout the modern public health era, health has been pursued as though our lives and lifestyles are disconnected from ecosystems and their component organisms. The inadequacy of the societal and public health response to obesity, health inequities, and especially global environmental and climate change now calls for an ecological approach which addresses human activity in all its social, economic and cultural complexity. The new approach must be integral to, and interactive, with the natural environment. We see the continuing failure to truly integrate human health and environmental impact analysis as deeply damaging, and we propose a new conceptual model, the ecosystems-enriched Drivers, Pressures, State, Exposure, Effects, Actions or 'eDPSEEA' model, to address this shortcoming. The model recognizes convergence between the concept of ecosystems services which provides a human health and well-being slant to the value of ecosystems while equally emphasizing the health of the environment, and the growing calls for 'ecological public health' as a response to global environmental concerns now suffusing the discourse in public health. More revolution than evolution, ecological public health will demand new perspectives regarding the interconnections among society, the economy, the environment and our health and well-being. Success must be built on collaborations between the disparate scientific communities of the environmental sciences and public health as well as interactions with social scientists, economists and the legal profession. It will require outreach to political and other stakeholders including a currently largely disengaged general public. The need for an effective and robust science-policy interface has never been more pressing. Conceptual models can facilitate this by providing theoretical frameworks and supporting stakeholder engagement process simplifications for inherently complex situations involving environment and human health and well-being. They can be tools to think with, to engage, to communicate and to help navigate in a sea of complexity. We believe models such as eDPSEEA can help frame many of the issues which have become the challenges of the new public health era and can provide the essential platforms necessary for progress. Crown Copyright © 2013. Published by Elsevier Ltd. All rights reserved.

Information technology challenges of biodiversity and ecosystems informatics

USGS Publications Warehouse

Schnase, J.L.; Cushing, J.; Frame, M.; Frondorf, A.; Landis, E.; Maier, D.; Silberschatz, A.

2003-01-01

Computer scientists, biologists, and natural resource managers recently met to examine the prospects for advancing computer science and information technology research by focusing on the complex and often-unique challenges found in the biodiversity and ecosystem domain. The workshop and its final report reveal that the biodiversity and ecosystem sciences are fundamentally information sciences and often address problems having distinctive attributes of scale and socio-technical complexity. The paper provides an overview of the emerging field of biodiversity and ecosystem informatics and demonstrates how the demands of biodiversity and ecosystem research can advance our understanding and use of information technologies.

ECOSYSTEM MODELING IN COBSCOOK BAY, MAINE:A SUMMARY, PERSPECTIVE, AND LOOK FORWARD

EPA Science Inventory

In the mid-1990s, an interdisciplinary, multi-institutional team of scientists was assembled to address basic issues concerning biological productivity and the unique co-occurrence of many unusual ecological features in Cobscook Bay, Maine. Cobscook Bay is a geologically complex,...

The impact of exploiting grazers (Scaridae) on the dynamics of Caribbean coral reefs.

PubMed

Mumby, Peter J

2006-04-01

Coral reefs provide a number of ecosystem services including coastal defense from storms, the generation of building materials, and fisheries. It is increasingly clear that the management of reef resources requires an ecosystem approach in which extractive activities are weighed against the needs of the ecosystem and its functions rather than solely those of the fishery. Here, I use a spatially explicit simulation model of a Caribbean coral reef to examine the ecosystem requirements for grazing which is primarily conducted by parrotfishes (Scaridae). The model allows the impact of fishing grazers to be assessed in the wider context of other ecosystem processes including coral-algal competition, hurricanes, and mass extinction of the herbivorous urchin Diadema antillarum. Using a new analytical model of scarid grazing, it is estimated that parrotfishes can only maintain between 10% and 30% of a structurally complex forereef in a grazed state. Predictions from this grazing model were then incorporated into a broader simulation model of the ecosystem. Simulations predict that scarid grazing is unable to maintain high levels of coral cover (> or = 30%) when severe hurricanes occur on a decadal basis, such as occurs in parts of the northern Caribbean. However, reefs can withstand such intense disturbance when grazing is undertaken by both scarids and the urchin Diadema. Scarid grazing is predicted to allow recovery from hurricanes when their incidence falls to 20 years or less (e.g., most of Central and South America). Sensitivity analyses revealed that scarid grazing had the most acute impact on model behavior, and depletion led to the emergence of a stable, algal-dominated community state. Under conditions of heavy grazer depletion, coral cover was predicted to decline rapidly from an initial level of 30% to less than 1% within 40 years, even when hurricane frequency was low at 60 years. Depleted grazers caused a population bottleneck in juvenile corals in which algal overgrowth caused elevated levels of postsettlement mortality and resulted in a bimodal distribution of coral sizes. Several new hypotheses were generated including a region-wide change in the spatial heterogeneity of coral reefs following extinction of Diadema. The management of parrotfishes on Caribbean reefs is usually approached implicitly through no-take marine reserves. The model predicts that depletion of grazers in nonreserve areas can severely limit coral accretion. Other studies have shown that low coral accretion can reduce the structural complexity and therefore quality of the reef habitat for many organisms. A speculative yet rational inference from the model is that failure to manage scarid populations outside reserves will have a profoundly negative impact on the functioning of the reserve system and status of non-reserve reefs.

A hierarchical analysis of terrestrial ecosystem model Biome-BGC: Equilibrium analysis and model calibration

DOE Office of Scientific and Technical Information (OSTI.GOV)

Thornton, Peter E; Wang, Weile; Law, Beverly E.

2009-01-01

The increasing complexity of ecosystem models represents a major difficulty in tuning model parameters and analyzing simulated results. To address this problem, this study develops a hierarchical scheme that simplifies the Biome-BGC model into three functionally cascaded tiers and analyzes them sequentially. The first-tier model focuses on leaf-level ecophysiological processes; it simulates evapotranspiration and photosynthesis with prescribed leaf area index (LAI). The restriction on LAI is then lifted in the following two model tiers, which analyze how carbon and nitrogen is cycled at the whole-plant level (the second tier) and in all litter/soil pools (the third tier) to dynamically supportmore » the prescribed canopy. In particular, this study analyzes the steady state of these two model tiers by a set of equilibrium equations that are derived from Biome-BGC algorithms and are based on the principle of mass balance. Instead of spinning-up the model for thousands of climate years, these equations are able to estimate carbon/nitrogen stocks and fluxes of the target (steady-state) ecosystem directly from the results obtained by the first-tier model. The model hierarchy is examined with model experiments at four AmeriFlux sites. The results indicate that the proposed scheme can effectively calibrate Biome-BGC to simulate observed fluxes of evapotranspiration and photosynthesis; and the carbon/nitrogen stocks estimated by the equilibrium analysis approach are highly consistent with the results of model simulations. Therefore, the scheme developed in this study may serve as a practical guide to calibrate/analyze Biome-BGC; it also provides an efficient way to solve the problem of model spin-up, especially for applications over large regions. The same methodology may help analyze other similar ecosystem models as well.« less

Ecosystem properties self-organize in response to a directional fog-vegetation interaction.

PubMed

Stanton, Daniel E; Armesto, Juan J; Hedin, Lars O

2014-05-01

Feedbacks between vegetation and resource inputs can lead to the local, self-organization of ecosystem properties. In particular, feedbacks in response to directional resources (e.g., coastal fog, slope runoff) can create complex spatial patterns, such as vegetation banding. Although similar feedbacks are thought to be involved in the development of ecosystems, clear empirical examples are rare. We created a simple model of a fog-influenced, temperate rainforest in central Chile, which allows the comparison of natural banding patterns to simulations of various putative mechanisms. We show that only feedbacks between plants and fog were able to replicate the characteristic distributions of vegetation, soil water, and soil nutrients observed in field transects. Other processes, such as rainfall, were unable to match these diagnostic distributions. Furthermore, fog interception by windward trees leads to increased downwind mortality, leading to progressive extinction of the leeward edge. This pattern of ecosystem development and decay through self-organized processes illustrates, on a relatively small spatial and temporal scale, the patterns predicted for ecosystem evolution.

Land use changes and socio-economic development strongly deteriorate river ecosystem health in one of the largest basins in China.

PubMed

Cheng, Xian; Chen, Liding; Sun, Ranhao; Kong, Peiru

2018-03-01

It is important to assess river ecosystem health in large-scale basins when considering the complex influence of anthropogenic activities on these ecosystems. This study investigated the river ecosystem health in the Haihe River Basin (HRB) by sampling 148 river sites during the pre- and post-rainy seasons in 2013. A model was established to assess the river ecosystem health based on water physicochemical, nutrient, and macroinvertebrate indices, and the health level was divided into "very poor," "poor," "fair," "good," and "excellent" according to the health score calculated from the assessment model. The assessment results demonstrated that the river ecosystem health of the HRB was "poor" overall, and no catchments were labeled "excellent." The percentages of catchments deemed to have "very poor," "poor," "fair," or "good" river ecosystem health were 12.88%, 40.91%, 40.15%, and 6.06%, respectively. From the pre- to the post-rainy season, the macroinvertebrate health levels improved from "poor" to "fair." The results of a redundancy analysis (RDA), path analysis of the structural equation model (SEM), and X-Y plots indicated that the land use types of forest land and grassland had positive relationships with river ecosystem health, whereas arable land, urban land, gross domestic product (GDP) per capita, and population density had negative relationships with river ecosystem health. The variance partitioning (VP) results showed that anthropogenic activities (including land use and socio-economy) together explained 30.9% of the variations in river ecosystem health in the pre-rainy season, and this value increased to 35.9% in the post-rainy season. Land use intensity was the first driver of river ecosystem health, and socio-economic activities was the second driver. Land use variables explained 20.5% and 25.7% of the variations in river ecosystem health in the pre- and post-rainy season samples, respectively, and socio-economic variables explained 12.3% and 17.2% of the variations, respectively. The SEM results revealed that urban land had the strongest impact on water quality health and that forest land had the strongest impact on macroinvertebrate health. This study has implications for the selection of appropriate indicators to assess river ecosystem health and generated data to examine the effects of anthropogenic activities on river ecosystem health in a fast-growing region. Copyright © 2017 Elsevier B.V. All rights reserved.

Long-term potential and actual evapotranspiration of two different forests on the Atlantic Coastal Plain

Treesearch

Devendra Amatya; S. Tian; Z. Dai; Ge Sun

2016-01-01

A reliable estimate of potential evapotranspiration (PET) for a forest ecosystem is critical in ecohydrologic modeling related with water supply, vegetation dynamics, and climate change and yet is a challenging task due to its complexity. Based on long-term on-site measured hydro-climatic data and predictions from earlier validated hydrologic modeling studies...

Multi-model inference for incorporating trophic and climate uncertainty into stock assessments

NASA Astrophysics Data System (ADS)

Ianelli, James; Holsman, Kirstin K.; Punt, André E.; Aydin, Kerim

2016-12-01

Ecosystem-based fisheries management (EBFM) approaches allow a broader and more extensive consideration of objectives than is typically possible with conventional single-species approaches. Ecosystem linkages may include trophic interactions and climate change effects on productivity for the relevant species within the system. Presently, models are evolving to include a comprehensive set of fishery and ecosystem information to address these broader management considerations. The increased scope of EBFM approaches is accompanied with a greater number of plausible models to describe the systems. This can lead to harvest recommendations and biological reference points that differ considerably among models. Model selection for projections (and specific catch recommendations) often occurs through a process that tends to adopt familiar, often simpler, models without considering those that incorporate more complex ecosystem information. Multi-model inference provides a framework that resolves this dilemma by providing a means of including information from alternative, often divergent models to inform biological reference points and possible catch consequences. We apply an example of this approach to data for three species of groundfish in the Bering Sea: walleye pollock, Pacific cod, and arrowtooth flounder using three models: 1) an age-structured "conventional" single-species model, 2) an age-structured single-species model with temperature-specific weight at age, and 3) a temperature-specific multi-species stock assessment model. The latter two approaches also include consideration of alternative future climate scenarios, adding another dimension to evaluate model projection uncertainty. We show how Bayesian model-averaging methods can be used to incorporate such trophic and climate information to broaden single-species stock assessments by using an EBFM approach that may better characterize uncertainty.

A Coupled SD and CLUE-S Model for Exploring the Impact of Land Use Change on Ecosystem Service Value: A Case Study in Baoshan District, Shanghai, China

NASA Astrophysics Data System (ADS)

Wu, Meng; Ren, Xiangyu; Che, Yue; Yang, Kai

2015-08-01

Most of the cities in developing countries are experiencing rapid urbanization. Land use change driven by urban sprawl, population growth, and intensified socio-economic activities have led to a steep decline of ecosystem service value (ESV) in rapid urbanization areas, and decision-makers often ignore some valuable ecosystem service functions and values in land use planning. In this paper, we attempt to build a modeling framework which integrated System Dynamics model with Conversion of Land Use and its Effects at Small Extent model to simulate the dynamics of ESV of landscape and explore the potential impacts of land use change on ESV. We take Baoshan district of Shanghai as an example which is a fast urbanization area of metropolitan in China. The results of the study indicate that: (1) The integrated methodology can improve the characterization and presentation of the dynamics of ESV, which may give insight into understanding the possible impacts of land use change on ESV and provide information for land use planning. (2) Land use polices can affect the magnitude and location of ESV both directly and indirectly. Land use changes tend to weaken and simplify ecosystem service functions and values of landscape at urban rural fringe where land use change is more intensive. (3) The application of the methodology has proved that the integration of currently existing models within a single modeling framework could be a beneficial exploration, and should be encouraged and enhanced in the future research on the changing dynamics of ESV due to the complexity of ecosystem services and land use system.

Assessment of watershed scale nitrogen cycling and dynamics by hydrochemical modeling

NASA Astrophysics Data System (ADS)

Onishi, T.; Hiramatsu, K.; Somura, H.

2017-12-01

Nitrogen cycling in terrestrial areas is affecting water quality and ecosystem of aquatic area such as lakes and oceans through rivers. Owing to the intensive researches on nitrogen cycling in each different type of ecosystem, we acquired rich knowledge on nitrogen cycling of each ecosystem. On the other hand, since watershed are composed of many different kinds of ecosystems, nitrogen cycling in a watershed as a complex of these ecosystems is not well quantified. Thus, comprehensive understanding of nitrogen cycling of watersheds by modelling efforts are required. In this study, we attempted to construct hydrochemical model of the Ise Bay watershed to reproduce discharge, TN, and NO3 concentration. The model is based on SWAT (Soil and Water Assessment Tools) model. As anthropogenic impacts related to both hydrological cycling and nitrogen cycling, agricultural water intake/drainage, and domestic water intake/drainage were considered. In addition, fertilizer input to agricultural lands were also considered. Calibration period and validation period are 2004-2006, and 2007-2009, respectively. As a result of calibration using 2000 times LCS (Latin Cubic Sampling) method, discharge of rivers were reproduced fairly well with NS of 0.6-0.8. In contrast, the calibration result of TN and NO3 concentration tended to show overestimate values in spite of considering parameter uncertainties. This implies that unimplemented denitrification processes in the model. Through exploring the results, it is indicated that riparian areas, and agricultural drainages might be important spots for denitrification. Based on the result, we also attempted to evaluate the impact of climate change on nitrogen cycling. Though it is fully explored, this result will also be reported.

A Coupled SD and CLUE-S Model for Exploring the Impact of Land Use Change on Ecosystem Service Value: A Case Study in Baoshan District, Shanghai, China.

PubMed

Wu, Meng; Ren, Xiangyu; Che, Yue; Yang, Kai

2015-08-01

Most of the cities in developing countries are experiencing rapid urbanization. Land use change driven by urban sprawl, population growth, and intensified socio-economic activities have led to a steep decline of ecosystem service value (ESV) in rapid urbanization areas, and decision-makers often ignore some valuable ecosystem service functions and values in land use planning. In this paper, we attempt to build a modeling framework which integrated System Dynamics model with Conversion of Land Use and its Effects at Small Extent model to simulate the dynamics of ESV of landscape and explore the potential impacts of land use change on ESV. We take Baoshan district of Shanghai as an example which is a fast urbanization area of metropolitan in China. The results of the study indicate that: (1) The integrated methodology can improve the characterization and presentation of the dynamics of ESV, which may give insight into understanding the possible impacts of land use change on ESV and provide information for land use planning. (2) Land use polices can affect the magnitude and location of ESV both directly and indirectly. Land use changes tend to weaken and simplify ecosystem service functions and values of landscape at urban rural fringe where land use change is more intensive. (3) The application of the methodology has proved that the integration of currently existing models within a single modeling framework could be a beneficial exploration, and should be encouraged and enhanced in the future research on the changing dynamics of ESV due to the complexity of ecosystem services and land use system.

Moderate forest disturbance as a stringent test for gap and big-leaf models

NASA Astrophysics Data System (ADS)

Bond-Lamberty, B. P.; Fisk, J.; Holm, J. A.; Bailey, V. L.; Gough, C. M.

2014-12-01

Disturbance-induced tree mortality is a key factor regulating the carbon balance of a forest, but tree mortality and its subsequent effects are poorly represented processes in terrestrial ecosystem models. In particular, it is unclear whether models can robustly simulate moderate (non-catastrophic) disturbances, which tend to increase biological and structural complexity and are increasingly common in aging U.S. forests. We tested whether three forest ecosystem models—Biome-BGC, a classic big-leaf model, and the ED and ZELIG gap-oriented models—could reproduce the resilience to moderate disturbance observed in an experimentally manipulated forest (the Forest Accelerated Succession Experiment in northern Michigan, USA, in which 38% of canopy dominants were stem girdled and compared to control plots). Each model was parameterized, spun up, and disturbed following similar protocols, and run for 5 years post-disturbance. The models replicated observed declines in aboveground biomass well. Biome-BGC captured the timing and rebound of observed leaf area index (LAI), while ED and ZELIG correctly estimated the magnitude of LAI decline. None of the models fully captured the observed post-disturbance C fluxes. Biome-BGC net primary production (NPP) was correctly resilient, but for the wrong reasons, while ED and ZELIG exhibited large, unobserved drops in NPP and net ecosystem production. The biological mechanisms proposed to explain the observed rapid resilience of the C cycle are typically not incorporated by these or other models. As a result we expect that most ecosystem models, developed to simulate processes following stand-replacing disturbances, will not simulate well the gradual and less extensive tree mortality characteristic of moderate disturbances.

Stable isotope views on ecosystem function: challenging or challenged?

PubMed

Resco, Víctor; Querejeta, José I; Ogle, Kiona; Voltas, Jordi; Sebastià, Maria-Teresa; Serrano-Ortiz, Penélope; Linares, Juan C; Moreno-Gutiérrez, Cristina; Herrero, Asier; Carreira, José A; Torres-Cañabate, Patricia; Valladares, Fernando

2010-06-23

Stable isotopes and their potential for detecting various and complex ecosystem processes are attracting an increasing number of scientists. Progress is challenging, particularly under global change scenarios, but some established views have been challenged. The IX meeting of the Spanish Association of Terrestrial Ecology (AAET, Ubeda, 18-22 October 2009) hosted a symposium on the ecology of stable isotopes where the linear mixing model approach of partitioning sinks and sources of carbon and water fluxes within an ecosystem was challenged, and new applications of stable isotopes for the study of plant interactions were evaluated. Discussion was also centred on the need for networks that monitor ecological processes using stable isotopes and key ideas for fostering future research with isotopes.

Stable isotope views on ecosystem function: challenging or challenged?

PubMed Central

Resco, Víctor; Querejeta, José I.; Ogle, Kiona; Voltas, Jordi; Sebastià, Maria-Teresa; Serrano-Ortiz, Penélope; Linares, Juan C.; Moreno-Gutiérrez, Cristina; Herrero, Asier; Carreira, José A.; Torres-Cañabate, Patricia; Valladares, Fernando

2010-01-01

Stable isotopes and their potential for detecting various and complex ecosystem processes are attracting an increasing number of scientists. Progress is challenging, particularly under global change scenarios, but some established views have been challenged. The IX meeting of the Spanish Association of Terrestrial Ecology (AAET, Úbeda, 18–22 October 2009) hosted a symposium on the ecology of stable isotopes where the linear mixing model approach of partitioning sinks and sources of carbon and water fluxes within an ecosystem was challenged, and new applications of stable isotopes for the study of plant interactions were evaluated. Discussion was also centred on the need for networks that monitor ecological processes using stable isotopes and key ideas for fostering future research with isotopes. PMID:20015858

From Rivers to Oceans and Back: Linking Models to Encompass the Full Salmon Life Cycle

NASA Astrophysics Data System (ADS)

Danner, E.; Hendrix, N.; Martin, B.; Lindley, S. T.

2016-02-01

Pacific salmon are a promising study subject for investigating the linkages between freshwater and coastal ocean ecosystems. Salmon use a wide range of habitats throughout their life cycle as they move with water from mountain streams, mainstem rivers, estuaries, bays, and coastal oceans, with adult fish swimming back through the same migration route they took as juveniles. Conditions in one habitat can have growth and survival consequences that manifest in the following habitat, so is key that full life cycle models are used to further our understanding salmon population dynamics. Given the wide range of habitats and potential stressors, this approach requires the coordination of a multidisciplinary suite of physical and biological models, including climate, hydrologic, hydraulic, food web, circulation, bioenergetic, and ecosystem models. Here we present current approaches to linking physical and biological models that capture the foundational drivers for salmon in complex and dynamic systems.

Impacts of weather versus climate and driver uncertainty on multi-centennial ecosystem model simulations

NASA Astrophysics Data System (ADS)

Rollinson, C.; Simkins, J.; Fer, I.; Desai, A. R.; Dietze, M.

2017-12-01

Simulations of ecosystem dynamics and comparisons with empirical data require accurate, continuous, and often sub-daily meteorology records that are spatially aligned to the scale of the empirical data. A wealth of meteorology data for the past, present, and future is available through site-specific observations, modern reanalysis products, and gridded GCM simulations. However, these products are mismatched in spatial and temporal resolution, often with both different means and seasonal patterns. We have designed and implemented a two-step meteorological downscaling and ensemble generation method that combines multiple meteorology data products through debiasing and temporal downscaling protocols. Our methodology is designed to preserve the covariance among seven meteorological variables for use as drivers in ecosystem model simulations: temperature, precipitation, short- and longwave radiation, surface pressure, humidity, and wind. Furthermore, our method propagates uncertainty through the downscaling process and results in ensembles of meteorology that can be compared to paleoclimate reconstructions and used to analyze the effects of both high- and low-frequency climate anomalies on ecosystem dynamics. Using a multiple linear regression approach, we have combined hourly, 0.125-degree gridded data from the NLDAS (1980-present) with CRUNCEP (1901-2010) and CMIP5 historical (1850-2005), past millennium (850-1849), and future (1950-2100) GCM simulations. This has resulted in an ensemble of continuous, hourly-resolved meteorology from from the paleo era into the future with variability in weather events as well as low-frequency climatic changes. We investigate the influence of extreme sub-daily weather phenomena versus long-term climatic changes in an ensemble of ecosystem models that range in atmospheric and biological complexity. Through data assimilation with paleoclimate reconstructions of past climate, we can improve data-model comparisons using observations of vegetation change from the past 1200 years. Accounting for driver uncertainty in model evaluation can help determine the relative influence of structural versus parameterization errors in ecosystem modelings.

Evidence-based evaluation of the cumulative effects of ecosystem restoration

DOE Office of Scientific and Technical Information (OSTI.GOV)

Diefenderfer, Heida L.; Johnson, Gary E.; Thom, Ronald M.

Evaluating the cumulative effects of large-scale ecological restoration programs is necessary to inform adaptive ecosystem management and provide society with resilient and sustainable services. However, complex linkages between restorative actions and ecosystem responses make evaluations problematic. Despite long-term federal investments in restoring aquatic ecosystems, no standard evaluation method has been adopted and most programs focus on monitoring and analysis, not synthesis and evaluation. In this paper, we demonstrate a new transdisciplinary approach integrating techniques from evidence-based medicine, critical thinking, and cumulative effects assessment. Tiered hypotheses are identified using an ecosystem conceptual model. The systematic literature review at the core ofmore » evidence-based assessment becomes one of many lines of evidence assessed collectively, using critical thinking strategies and causal criteria from a cumulative effects perspective. As a demonstration, we analyzed data from 166 locations on the Columbia River and estuary representing 12 indicators of habitat and fish response to floodplain restoration actions intended to benefit threatened and endangered salmon. Synthesis of seven lines of evidence showed that hydrologic reconnection promoted macrodetritis export, prey availability, and fish access and feeding. The evidence was sufficient to infer cross-boundary, indirect, compounding and delayed cumulative effects, and suggestive of nonlinear, landscape-scale, and spatial density effects. On the basis of causal inferences regarding food web functions, we concluded that the restoration program has a cumulative beneficial effect on juvenile salmon. As a result, this evidence-based approach will enable the evaluation of restoration in complex coastal and riverine ecosystems where data have accumulated without sufficient synthesis.« less

Evidence-based evaluation of the cumulative effects of ecosystem restoration

DOE PAGES

Diefenderfer, Heida L.; Johnson, Gary E.; Thom, Ronald M.; ...

2016-03-18

Evaluating the cumulative effects of large-scale ecological restoration programs is necessary to inform adaptive ecosystem management and provide society with resilient and sustainable services. However, complex linkages between restorative actions and ecosystem responses make evaluations problematic. Despite long-term federal investments in restoring aquatic ecosystems, no standard evaluation method has been adopted and most programs focus on monitoring and analysis, not synthesis and evaluation. In this paper, we demonstrate a new transdisciplinary approach integrating techniques from evidence-based medicine, critical thinking, and cumulative effects assessment. Tiered hypotheses are identified using an ecosystem conceptual model. The systematic literature review at the core ofmore » evidence-based assessment becomes one of many lines of evidence assessed collectively, using critical thinking strategies and causal criteria from a cumulative effects perspective. As a demonstration, we analyzed data from 166 locations on the Columbia River and estuary representing 12 indicators of habitat and fish response to floodplain restoration actions intended to benefit threatened and endangered salmon. Synthesis of seven lines of evidence showed that hydrologic reconnection promoted macrodetritis export, prey availability, and fish access and feeding. The evidence was sufficient to infer cross-boundary, indirect, compounding and delayed cumulative effects, and suggestive of nonlinear, landscape-scale, and spatial density effects. On the basis of causal inferences regarding food web functions, we concluded that the restoration program has a cumulative beneficial effect on juvenile salmon. As a result, this evidence-based approach will enable the evaluation of restoration in complex coastal and riverine ecosystems where data have accumulated without sufficient synthesis.« less

Catastrophic Shifts in Semiarid Vegetation-Soil Systems May Unfold Rapidly or Slowly.

PubMed

Karssenberg, Derek; Bierkens, Marc F P; Rietkerk, Max

2017-12-01

Under gradual change of a driver, complex systems may switch between contrasting stable states. For many ecosystems it is unknown how rapidly such a critical transition unfolds. Here we explore the rate of change during the degradation of a semiarid ecosystem with a model coupling the vegetation and geomorphological system. Two stable states-vegetated and bare-are identified, and it is shown that the change between these states is a critical transition. Surprisingly, the critical transition between the vegetated and bare state can unfold either rapidly over a few years or gradually over decennia up to millennia, depending on parameter values. An important condition for the phenomenon is the linkage between slow and fast ecosystems components. Our results show that, next to climate change and disturbance rates, the geological and geomorphological setting of a semiarid ecosystem is crucial in predicting its fate.

Adverse outcome pathways linked to population models as a methodology for investigating effects of chemical stressors

EPA Science Inventory

In addressing the complexity and toxicity of chemical contaminants in Great Lakes ecosystems, we describe an approach to link chemically induced alterations in molecular and biochemical endpoints to adverse outcomes in whole organisms and populations. Analysis of population impac...

Modeling Diel Oxygen Dynamics and Ecosystem Metabolism in Weeks Bay, Alabama.

EPA Science Inventory

Weeks Bay is a shallow eutrophic estuary that exhibits frequent summertime diel-cycling hypoxia and periods of dissolved oxygen (DO) oversaturation during the day. Diel DO dynamics in shallow estuaries like Weeks Bay are complex, and may be influenced by wind forcing, vertical an...

A dynamic nitrogen budget model of a Pacific Northwest salt marsh

EPA Science Inventory

The role of salt marshes as either nitrogen sinks or sources in relation to their adjacent estuaries has been a focus of ecosystem service research for many decades. The complex hydrology of these systems is driven by tides, upland surface runoff, precipitation, evapotranspirati...

Selective predation and productivity jointly drive complex behavior in host-parasite systems.

PubMed

Hall, Spencer R; Duffy, Meghan A; Cáceres, Carla E

2005-01-01

Successful invasion of a parasite into a host population and resulting host-parasite dynamics can depend crucially on other members of a host's community such as predators. We do not fully understand how predation intensity and selectivity shape host-parasite dynamics because the interplay between predator density, predator foraging behavior, and ecosystem productivity remains incompletely explored. By modifying a standard susceptible-infected model, we show how productivity can modulate complex behavior induced by saturating and selective foraging behavior of predators in an otherwise stable host-parasite system. When predators strongly prefer parasitized hosts, the host-parasite system can oscillate, but predators can also create alternative stable states, Allee effects, and catastrophic extinction of parasites. In the latter three cases, parasites have difficulty invading and/or persisting in ecosystems. When predators are intermediately selective, these more complex behaviors become less important, but the host-parasite system can switch from stable to oscillating and then back to stable states along a gradient of predator control. Surprisingly, at higher productivity, predators that neutrally select or avoid parasitized hosts can catalyze extinction of both hosts and parasites. Thus, synergy between two enemies can end disastrously for the host. Such diverse outcomes underscore the crucial importance of the community and ecosystem context in which host-parasite interactions occur.

Assessing model sensitivity and uncertainty across multiple Free-Air CO2 Enrichment experiments.

NASA Astrophysics Data System (ADS)

Cowdery, E.; Dietze, M.

2015-12-01

As atmospheric levels of carbon dioxide levels continue to increase, it is critical that terrestrial ecosystem models can accurately predict ecological responses to the changing environment. Current predictions of net primary productivity (NPP) in response to elevated atmospheric CO2 concentrations are highly variable and contain a considerable amount of uncertainty. It is necessary that we understand which factors are driving this uncertainty. The Free-Air CO2 Enrichment (FACE) experiments have equipped us with a rich data source that can be used to calibrate and validate these model predictions. To identify and evaluate the assumptions causing inter-model differences we performed model sensitivity and uncertainty analysis across ambient and elevated CO2 treatments using the Data Assimilation Linked Ecosystem Carbon (DALEC) model and the Ecosystem Demography Model (ED2), two process-based models ranging from low to high complexity respectively. These modeled process responses were compared to experimental data from the Kennedy Space Center Open Top Chamber Experiment, the Nevada Desert Free Air CO2 Enrichment Facility, the Rhinelander FACE experiment, the Wyoming Prairie Heating and CO2 Enrichment Experiment, the Duke Forest Face experiment and the Oak Ridge Experiment on CO2 Enrichment. By leveraging data access proxy and data tilling services provided by the BrownDog data curation project alongside analysis modules available in the Predictive Ecosystem Analyzer (PEcAn), we produced automated, repeatable benchmarking workflows that are generalized to incorporate different sites and ecological models. Combining the observed patterns of uncertainty between the two models with results of the recent FACE-model data synthesis project (FACE-MDS) can help identify which processes need further study and additional data constraints. These findings can be used to inform future experimental design and in turn can provide informative starting point for data assimilation.

Future changes in coastal upwelling ecosystems with global warming: The case of the California Current System.

PubMed

Xiu, Peng; Chai, Fei; Curchitser, Enrique N; Castruccio, Frederic S

2018-02-12

Coastal upwelling ecosystems are among the most productive ecosystems in the world, meaning that their response to climate change is of critical importance. Our understanding of climate change impacts on marine ecosystems is largely limited to the open ocean, mainly because coastal upwelling is poorly reproduced by current earth system models. Here, a high-resolution model is used to examine the response of nutrients and plankton dynamics to future climate change in the California Current System (CCS). The results show increased upwelling intensity associated with stronger alongshore winds in the coastal region, and enhanced upper-ocean stratification in both the CCS and open ocean. Warming of the open ocean forces isotherms downwards, where they make contact with water masses with higher nutrient concentrations, thereby enhancing the nutrient flux to the deep source waters of the CCS. Increased winds and eddy activity further facilitate upward nutrient transport to the euphotic zone. However, the plankton community exhibits a complex and nonlinear response to increased nutrient input, as the food web dynamics tend to interact differently. This analysis highlights the difficulty in understanding how the marine ecosystem responds to a future warming climate, given to range of relevant processes operating at different scales.

The big data-big model (BDBM) challenges in ecological research

NASA Astrophysics Data System (ADS)

Luo, Y.

2015-12-01

The field of ecology has become a big-data science in the past decades due to development of new sensors used in numerous studies in the ecological community. Many sensor networks have been established to collect data. For example, satellites, such as Terra and OCO-2 among others, have collected data relevant on global carbon cycle. Thousands of field manipulative experiments have been conducted to examine feedback of terrestrial carbon cycle to global changes. Networks of observations, such as FLUXNET, have measured land processes. In particular, the implementation of the National Ecological Observatory Network (NEON), which is designed to network different kinds of sensors at many locations over the nation, will generate large volumes of ecological data every day. The raw data from sensors from those networks offer an unprecedented opportunity for accelerating advances in our knowledge of ecological processes, educating teachers and students, supporting decision-making, testing ecological theory, and forecasting changes in ecosystem services. Currently, ecologists do not have the infrastructure in place to synthesize massive yet heterogeneous data into resources for decision support. It is urgent to develop an ecological forecasting system that can make the best use of multiple sources of data to assess long-term biosphere change and anticipate future states of ecosystem services at regional and continental scales. Forecasting relies on big models that describe major processes that underlie complex system dynamics. Ecological system models, despite great simplification of the real systems, are still complex in order to address real-world problems. For example, Community Land Model (CLM) incorporates thousands of processes related to energy balance, hydrology, and biogeochemistry. Integration of massive data from multiple big data sources with complex models has to tackle Big Data-Big Model (BDBM) challenges. Those challenges include interoperability of multiple, heterogeneous data sets; intractability of structural complexity of big models; equifinality of model structure selection and parameter estimation; and computational demand of global optimization with Big Models.

Towards Integration of Ecosystem and Human Health: A Novel Conceptual Framework to Operationalise Ecological Public Health and to Incorporate Distal and Proximal Effects of Climate Change

NASA Astrophysics Data System (ADS)

Reis, S.; Fleming, L. E.; Beck, S.; Austen, M.; Morris, G.; White, M.; Taylor, T. J.; Orr, N.; Osborne, N. J.; Depledge, M.

2014-12-01

Conceptual models for problem framing in environmental (EIA) and health impact assessment (HIA) share similar concepts, but differ in their scientific or policy focus, methodologies and underlying causal chains, and the degree of complexity and scope. The Driver-Pressure-State-Impact-Response (DPSIR) framework used by the European Environment Agency, the OECD and others and the Integrated Science for Society and the Environment (ISSE) frameworks are widely applied in policy appraisal and impact assessments. While DPSIR is applied across different policy domains, the ISSE framework is used in Ecosystem Services assessments. The modified Driver-Pressure-State-Exposure-Effect-Action (DPSEEA) model extends DPSIR by separating exposure from effect, adding context as a modifier of effect, and susceptibility to exposures due to socio-economic, demographic or other determinants. While continuously evolving, the application of conceptual frameworks in policy appraisals mainly occurs within established discipline boundaries. However, drivers and environmental states, as well as policy measures and actions, affect both human and ecosystem receptors. Furthermore, unintended consequences of policy actions are seldom constrained within discipline or policy silos. Thus, an integrated conceptual model is needed, accounting for the full causal chain affecting human and ecosystem health in any assessment. We propose a novel model integrating HIA methods and ecosystem services in an attempt to operationalise the emerging concept of "Ecological Public Health." The conceptual approach of the ecosystem-enriched DPSEEA model ("eDPSEEA") has stimulated wide-spread debates and feedback. We will present eDPSEEA as a stakeholder engagement process and a conceptual model, using illustrative case studies of climate change as a starting point, not a complete solution, for the integration of human and ecosystem health impact assessment as a key challenge in a rapidly changing world. Rayner G and Lang T Ecological Public Health: Reshaping the Conditions for Good Health. Routledge Publishers; 2012.Reis S, Morris G, Fleming LE, Beck S, Taylor T, White M, Depledge MH, Steinle S, Sabel CE, Cowie H, Hurley F, Dick JMcP, Smith RI, Austen M (2013) Integrating Health & Environmental Impact Analysis. Public Health.

Multiscale approach to pest insect monitoring: Random walks, pattern formation, synchronization, and networks

NASA Astrophysics Data System (ADS)

Petrovskii, Sergei; Petrovskaya, Natalia; Bearup, Daniel

2014-09-01

Pest insects pose a significant threat to food production worldwide resulting in annual losses worth hundreds of billions of dollars. Pest control attempts to prevent pest outbreaks that could otherwise destroy a sward. It is good practice in integrated pest management to recommend control actions (usually pesticides application) only when the pest density exceeds a certain threshold. Accurate estimation of pest population density in ecosystems, especially in agro-ecosystems, is therefore very important, and this is the overall goal of the pest insect monitoring. However, this is a complex and challenging task; providing accurate information about pest abundance is hardly possible without taking into account the complexity of ecosystems' dynamics, in particular, the existence of multiple scales. In the case of pest insects, monitoring has three different spatial scales, each of them having their own scale-specific goal and their own approaches to data collection and interpretation. In this paper, we review recent progress in mathematical models and methods applied at each of these scales and show how it helps to improve the accuracy and robustness of pest population density estimation.

Urban habitat complexity affects species richness but not environmental filtering of morphologically-diverse ants

PubMed Central

Nash, Michael A.; Christie, Fiona J.; Hahs, Amy K.; Livesley, Stephen J.

2015-01-01

Habitat complexity is a major determinant of structure and diversity of ant assemblages. Following the size-grain hypothesis, smaller ant species are likely to be advantaged in more complex habitats compared to larger species. Habitat complexity can act as an environmental filter based on species size and morphological traits, therefore affecting the overall structure and diversity of ant assemblages. In natural and semi-natural ecosystems, habitat complexity is principally regulated by ecological successions or disturbance such as fire and grazing. Urban ecosystems provide an opportunity to test relationships between habitat, ant assemblage structure and ant traits using novel combinations of habitat complexity generated and sustained by human management. We sampled ant assemblages in low-complexity and high-complexity parks, and high-complexity woodland remnants, hypothesizing that (i) ant abundance and species richness would be higher in high-complexity urban habitats, (ii) ant assemblages would differ between low- and high-complexity habitats and (iii) ants living in high-complexity habitats would be smaller than those living in low-complexity habitats. Contrary to our hypothesis, ant species richness was higher in low-complexity habitats compared to high-complexity habitats. Overall, ant assemblages were significantly different among the habitat complexity types investigated, although ant size and morphology remained the same. Habitat complexity appears to affect the structure of ant assemblages in urban ecosystems as previously observed in natural and semi-natural ecosystems. However, the habitat complexity filter does not seem to be linked to ant morphological traits related to body size. PMID:26528416

A phase transition induces chaos in a predator-prey ecosystem with a dynamic fitness landscape

PubMed Central

2017-01-01

In many ecosystems, natural selection can occur quickly enough to influence the population dynamics and thus future selection. This suggests the importance of extending classical population dynamics models to include such eco-evolutionary processes. Here, we describe a predator-prey model in which the prey population growth depends on a prey density-dependent fitness landscape. We show that this two-species ecosystem is capable of exhibiting chaos even in the absence of external environmental variation or noise, and that the onset of chaotic dynamics is the result of the fitness landscape reversibly alternating between epochs of stabilizing and disruptive selection. We draw an analogy between the fitness function and the free energy in statistical mechanics, allowing us to use the physical theory of first-order phase transitions to understand the onset of rapid cycling in the chaotic predator-prey dynamics. We use quantitative techniques to study the relevance of our model to observational studies of complex ecosystems, finding that the evolution-driven chaotic dynamics confer community stability at the “edge of chaos” while creating a wide distribution of opportunities for speciation during epochs of disruptive selection—a potential observable signature of chaotic eco-evolutionary dynamics in experimental studies. PMID:28678792

Evaluating the agreement between measurements and models of net ecosystem exchange at different times and timescales using wavelet coherence: an example using data from the North American Carbon Program Site-Level Interim Synthesis

Treesearch

P.C. Stoy; M.C. Dietze; A.D. Richardson; R. Vargas; A.G. Barr; R.S. Anderson; M.A. Arain; I.T. Baker; T.A. Black; J.M. Chen; R.B. Cook; C.M. Gough; R.F. Grant; D.Y. Hollinger; R.C. Izaurralde; C.J. Kucharik; P. Lafleur; B.E. Law; S. Liu; E. Lokupitiya; Y. Luo; J. W. Munger; C. Peng; B. Poulter; D.T. Price; D. M. Ricciuto; W. J. Riley; A. K. Sahoo; K. Schaefer; C.R. Schwalm; H. Tian; H. Verbeeck; E. Weng

2013-01-01

Earth system processes exhibit complex patterns across time, as do the models that seek to replicate these processes. Model output may or may not be significantly related to observations at different times and on different frequencies. Conventional model diagnostics provide an aggregate view of model-data agreement, but usually do not identify the time and frequency...

How to make complexity look simple? Conveying ecosystems restoration complexity for socio-economic research and public engagement.

PubMed

Martin-Ortega, Julia; Glenk, Klaus; Byg, Anja

2017-01-01

Ecosystems degradation represents one of the major global challenges at the present time, threating people's livelihoods and well-being worldwide. Ecosystem restoration therefore seems no longer an option, but an imperative. Restoration challenges are such that a dialogue has begun on the need to re-shape restoration as a science. A critical aspect of that reshaping process is the acceptance that restoration science and practice needs to be coupled with socio-economic research and public engagement. This inescapably means conveying complex ecosystem's information in a way that is accessible to the wider public. In this paper we take up this challenge with the ultimate aim of contributing to making a step change in science's contribution to ecosystems restoration practice. Using peatlands as a paradigmatically complex ecosystem, we put in place a transdisciplinary process to articulate a description of the processes and outcomes of restoration that can be understood widely by the public. We provide evidence of the usefulness of the process and tools in addressing four key challenges relevant to restoration of any complex ecosystem: (1) how to represent restoration outcomes; (2) how to establish a restoration reference; (3) how to cope with varying restoration time-lags and (4) how to define spatial units for restoration. This evidence includes the way the process resulted in the creation of materials that are now being used by restoration practitioners for communication with the public and in other research contexts. Our main contribution is of an epistemological nature: while ecosystem services-based approaches have enhanced the integration of academic disciplines and non-specialist knowledge, this has so far only followed one direction (from the biophysical underpinning to the description of ecosystem services and their appreciation by the public). We propose that it is the mix of approaches and epistemological directions (including from the public to the biophysical parameters) what will make a definitive contribution to restoration practice.

Elevated temperature alters carbon cycling in a model microbial community

NASA Astrophysics Data System (ADS)

Mosier, A.; Li, Z.; Thomas, B. C.; Hettich, R. L.; Pan, C.; Banfield, J. F.

2013-12-01

Earth's climate is regulated by biogeochemical carbon exchanges between the land, oceans and atmosphere that are chiefly driven by microorganisms. Microbial communities are therefore indispensible to the study of carbon cycling and its impacts on the global climate system. In spite of the critical role of microbial communities in carbon cycling processes, microbial activity is currently minimally represented or altogether absent from most Earth System Models. Method development and hypothesis-driven experimentation on tractable model ecosystems of reduced complexity, as presented here, are essential for building molecularly resolved, benchmarked carbon-climate models. Here, we use chemoautotropic acid mine drainage biofilms as a model community to determine how elevated temperature, a key parameter of global climate change, regulates the flow of carbon through microbial-based ecosystems. This study represents the first community proteomics analysis using tandem mass tags (TMT), which enable accurate, precise, and reproducible quantification of proteins. We compare protein expression levels of biofilms growing over a narrow temperature range expected to occur with predicted climate changes. We show that elevated temperature leads to up-regulation of proteins involved in amino acid metabolism and protein modification, and down-regulation of proteins involved in growth and reproduction. Closely related bacterial genotypes differ in their response to temperature: Elevated temperature represses carbon fixation by two Leptospirillum genotypes, whereas carbon fixation is significantly up-regulated at higher temperature by a third closely related genotypic group. Leptospirillum group III bacteria are more susceptible to viral stress at elevated temperature, which may lead to greater carbon turnover in the microbial food web through the release of viral lysate. Overall, this proteogenomics approach revealed the effects of climate change on carbon cycling pathways and other microbial activities. When scaled to more complex ecosystems and integrated into Earth System Models, this approach could significantly improve predictions of global carbon-climate feedbacks. Experiments such as these are a critical first step designed at understanding climate change impacts in order to better predict ecosystem adaptations, assess the viability of mitigation strategies, and inform relevant policy decisions.

Microbes as engines of ecosystem function: When does community structure enhance predictions of ecosystem processes?

DOE PAGES

Graham, Emily B.; Knelman, Joseph E.; Schindlbacher, Andreas; ...

2016-02-24

In this study, microorganisms are vital in mediating the earth’s biogeochemical cycles; yet, despite our rapidly increasing ability to explore complex environmental microbial communities, the relationship between microbial community structure and ecosystem processes remains poorly understood. Here, we address a fundamental and unanswered question in microbial ecology: ‘When do we need to understand microbial community structure to accurately predict function?’ We present a statistical analysis investigating the value of environmental data and microbial community structure independently and in combination for explaining rates of carbon and nitrogen cycling processes within 82 global datasets. Environmental variables were the strongest predictors of processmore » rates but left 44% of variation unexplained on average, suggesting the potential for microbial data to increase model accuracy. Although only 29% of our datasets were significantly improved by adding information on microbial community structure, we observed improvement in models of processes mediated by narrow phylogenetic guilds via functional gene data, and conversely, improvement in models of facultative microbial processes via community diversity metrics. Our results also suggest that microbial diversity can strengthen predictions of respiration rates beyond microbial biomass parameters, as 53% of models were improved by incorporating both sets of predictors compared to 35% by microbial biomass alone. Our analysis represents the first comprehensive analysis of research examining links between microbial community structure and ecosystem function. Taken together, our results indicate that a greater understanding of microbial communities informed by ecological principles may enhance our ability to predict ecosystem process rates relative to assessments based on environmental variables and microbial physiology.« less

Microbes as engines of ecosystem function: When does community structure enhance predictions of ecosystem processes?

DOE Office of Scientific and Technical Information (OSTI.GOV)

Graham, Emily B.; Knelman, Joseph E.; Schindlbacher, Andreas

In this study, microorganisms are vital in mediating the earth’s biogeochemical cycles; yet, despite our rapidly increasing ability to explore complex environmental microbial communities, the relationship between microbial community structure and ecosystem processes remains poorly understood. Here, we address a fundamental and unanswered question in microbial ecology: ‘When do we need to understand microbial community structure to accurately predict function?’ We present a statistical analysis investigating the value of environmental data and microbial community structure independently and in combination for explaining rates of carbon and nitrogen cycling processes within 82 global datasets. Environmental variables were the strongest predictors of processmore » rates but left 44% of variation unexplained on average, suggesting the potential for microbial data to increase model accuracy. Although only 29% of our datasets were significantly improved by adding information on microbial community structure, we observed improvement in models of processes mediated by narrow phylogenetic guilds via functional gene data, and conversely, improvement in models of facultative microbial processes via community diversity metrics. Our results also suggest that microbial diversity can strengthen predictions of respiration rates beyond microbial biomass parameters, as 53% of models were improved by incorporating both sets of predictors compared to 35% by microbial biomass alone. Our analysis represents the first comprehensive analysis of research examining links between microbial community structure and ecosystem function. Taken together, our results indicate that a greater understanding of microbial communities informed by ecological principles may enhance our ability to predict ecosystem process rates relative to assessments based on environmental variables and microbial physiology.« less

Microbes as Engines of Ecosystem Function: When Does Community Structure Enhance Predictions of Ecosystem Processes?

PubMed Central

Graham, Emily B.; Knelman, Joseph E.; Schindlbacher, Andreas; Siciliano, Steven; Breulmann, Marc; Yannarell, Anthony; Beman, J. M.; Abell, Guy; Philippot, Laurent; Prosser, James; Foulquier, Arnaud; Yuste, Jorge C.; Glanville, Helen C.; Jones, Davey L.; Angel, Roey; Salminen, Janne; Newton, Ryan J.; Bürgmann, Helmut; Ingram, Lachlan J.; Hamer, Ute; Siljanen, Henri M. P.; Peltoniemi, Krista; Potthast, Karin; Bañeras, Lluís; Hartmann, Martin; Banerjee, Samiran; Yu, Ri-Qing; Nogaro, Geraldine; Richter, Andreas; Koranda, Marianne; Castle, Sarah C.; Goberna, Marta; Song, Bongkeun; Chatterjee, Amitava; Nunes, Olga C.; Lopes, Ana R.; Cao, Yiping; Kaisermann, Aurore; Hallin, Sara; Strickland, Michael S.; Garcia-Pausas, Jordi; Barba, Josep; Kang, Hojeong; Isobe, Kazuo; Papaspyrou, Sokratis; Pastorelli, Roberta; Lagomarsino, Alessandra; Lindström, Eva S.; Basiliko, Nathan; Nemergut, Diana R.

2016-01-01

Microorganisms are vital in mediating the earth’s biogeochemical cycles; yet, despite our rapidly increasing ability to explore complex environmental microbial communities, the relationship between microbial community structure and ecosystem processes remains poorly understood. Here, we address a fundamental and unanswered question in microbial ecology: ‘When do we need to understand microbial community structure to accurately predict function?’ We present a statistical analysis investigating the value of environmental data and microbial community structure independently and in combination for explaining rates of carbon and nitrogen cycling processes within 82 global datasets. Environmental variables were the strongest predictors of process rates but left 44% of variation unexplained on average, suggesting the potential for microbial data to increase model accuracy. Although only 29% of our datasets were significantly improved by adding information on microbial community structure, we observed improvement in models of processes mediated by narrow phylogenetic guilds via functional gene data, and conversely, improvement in models of facultative microbial processes via community diversity metrics. Our results also suggest that microbial diversity can strengthen predictions of respiration rates beyond microbial biomass parameters, as 53% of models were improved by incorporating both sets of predictors compared to 35% by microbial biomass alone. Our analysis represents the first comprehensive analysis of research examining links between microbial community structure and ecosystem function. Taken together, our results indicate that a greater understanding of microbial communities informed by ecological principles may enhance our ability to predict ecosystem process rates relative to assessments based on environmental variables and microbial physiology. PMID:26941732

Microbes as Engines of Ecosystem Function: When Does Community Structure Enhance Predictions of Ecosystem Processes?

PubMed

Graham, Emily B; Knelman, Joseph E; Schindlbacher, Andreas; Siciliano, Steven; Breulmann, Marc; Yannarell, Anthony; Beman, J M; Abell, Guy; Philippot, Laurent; Prosser, James; Foulquier, Arnaud; Yuste, Jorge C; Glanville, Helen C; Jones, Davey L; Angel, Roey; Salminen, Janne; Newton, Ryan J; Bürgmann, Helmut; Ingram, Lachlan J; Hamer, Ute; Siljanen, Henri M P; Peltoniemi, Krista; Potthast, Karin; Bañeras, Lluís; Hartmann, Martin; Banerjee, Samiran; Yu, Ri-Qing; Nogaro, Geraldine; Richter, Andreas; Koranda, Marianne; Castle, Sarah C; Goberna, Marta; Song, Bongkeun; Chatterjee, Amitava; Nunes, Olga C; Lopes, Ana R; Cao, Yiping; Kaisermann, Aurore; Hallin, Sara; Strickland, Michael S; Garcia-Pausas, Jordi; Barba, Josep; Kang, Hojeong; Isobe, Kazuo; Papaspyrou, Sokratis; Pastorelli, Roberta; Lagomarsino, Alessandra; Lindström, Eva S; Basiliko, Nathan; Nemergut, Diana R

2016-01-01

Microorganisms are vital in mediating the earth's biogeochemical cycles; yet, despite our rapidly increasing ability to explore complex environmental microbial communities, the relationship between microbial community structure and ecosystem processes remains poorly understood. Here, we address a fundamental and unanswered question in microbial ecology: 'When do we need to understand microbial community structure to accurately predict function?' We present a statistical analysis investigating the value of environmental data and microbial community structure independently and in combination for explaining rates of carbon and nitrogen cycling processes within 82 global datasets. Environmental variables were the strongest predictors of process rates but left 44% of variation unexplained on average, suggesting the potential for microbial data to increase model accuracy. Although only 29% of our datasets were significantly improved by adding information on microbial community structure, we observed improvement in models of processes mediated by narrow phylogenetic guilds via functional gene data, and conversely, improvement in models of facultative microbial processes via community diversity metrics. Our results also suggest that microbial diversity can strengthen predictions of respiration rates beyond microbial biomass parameters, as 53% of models were improved by incorporating both sets of predictors compared to 35% by microbial biomass alone. Our analysis represents the first comprehensive analysis of research examining links between microbial community structure and ecosystem function. Taken together, our results indicate that a greater understanding of microbial communities informed by ecological principles may enhance our ability to predict ecosystem process rates relative to assessments based on environmental variables and microbial physiology.

A framework for modelling the complexities of food and water security under globalisation

NASA Astrophysics Data System (ADS)

Dermody, Brian J.; Sivapalan, Murugesu; Stehfest, Elke; van Vuuren, Detlef P.; Wassen, Martin J.; Bierkens, Marc F. P.; Dekker, Stefan C.

2018-01-01

We present a new framework for modelling the complexities of food and water security under globalisation. The framework sets out a method to capture regional and sectoral interdependencies and cross-scale feedbacks within the global food system that contribute to emergent water use patterns. The framework integrates aspects of existing models and approaches in the fields of hydrology and integrated assessment modelling. The core of the framework is a multi-agent network of city agents connected by infrastructural trade networks. Agents receive socio-economic and environmental constraint information from integrated assessment models and hydrological models respectively and simulate complex, socio-environmental dynamics that operate within those constraints. The emergent changes in food and water resources are aggregated and fed back to the original models with minimal modification of the structure of those models. It is our conviction that the framework presented can form the basis for a new wave of decision tools that capture complex socio-environmental change within our globalised world. In doing so they will contribute to illuminating pathways towards a sustainable future for humans, ecosystems and the water they share.

Decline of the marine ecosystem caused by a reduction in the Atlantic overturning circulation.

PubMed

Schmittner, Andreas

2005-03-31

Reorganizations of the Atlantic meridional overturning circulation were associated with large and abrupt climatic changes in the North Atlantic region during the last glacial period. Projections with climate models suggest that similar reorganizations may also occur in response to anthropogenic global warming. Here I use ensemble simulations with a coupled climate-ecosystem model of intermediate complexity to investigate the possible consequences of such disturbances to the marine ecosystem. In the simulations, a disruption of the Atlantic meridional overturning circulation leads to a collapse of the North Atlantic plankton stocks to less than half of their initial biomass, owing to rapid shoaling of winter mixed layers and their associated separation from the deep ocean nutrient reservoir. Globally integrated export production declines by more than 20 per cent owing to reduced upwelling of nutrient-rich deep water and gradual depletion of upper ocean nutrient concentrations. These model results are consistent with the available high-resolution palaeorecord, and suggest that global ocean productivity is sensitive to changes in the Atlantic meridional overturning circulation.

Changes in ecosystem resilience detected in automated measures of ecosystem metabolism during a whole-lake manipulation

PubMed Central

Batt, Ryan D.; Carpenter, Stephen R.; Cole, Jonathan J.; Pace, Michael L.; Johnson, Robert A.

2013-01-01

Environmental sensor networks are developing rapidly to assess changes in ecosystems and their services. Some ecosystem changes involve thresholds, and theory suggests that statistical indicators of changing resilience can be detected near thresholds. We examined the capacity of environmental sensors to assess resilience during an experimentally induced transition in a whole-lake manipulation. A trophic cascade was induced in a planktivore-dominated lake by slowly adding piscivorous bass, whereas a nearby bass-dominated lake remained unmanipulated and served as a reference ecosystem during the 4-y experiment. In both the manipulated and reference lakes, automated sensors were used to measure variables related to ecosystem metabolism (dissolved oxygen, pH, and chlorophyll-a concentration) and to estimate gross primary production, respiration, and net ecosystem production. Thresholds were detected in some automated measurements more than a year before the completion of the transition to piscivore dominance. Directly measured variables (dissolved oxygen, pH, and chlorophyll-a concentration) related to ecosystem metabolism were better indicators of the approaching threshold than were the estimates of rates (gross primary production, respiration, and net ecosystem production); this difference was likely a result of the larger uncertainties in the derived rate estimates. Thus, relatively simple characteristics of ecosystems that were observed directly by the sensors were superior indicators of changing resilience. Models linked to thresholds in variables that are directly observed by sensor networks may provide unique opportunities for evaluating resilience in complex ecosystems. PMID:24101479

Changes in ecosystem resilience detected in automated measures of ecosystem metabolism during a whole-lake manipulation.

PubMed

Batt, Ryan D; Carpenter, Stephen R; Cole, Jonathan J; Pace, Michael L; Johnson, Robert A

2013-10-22

Environmental sensor networks are developing rapidly to assess changes in ecosystems and their services. Some ecosystem changes involve thresholds, and theory suggests that statistical indicators of changing resilience can be detected near thresholds. We examined the capacity of environmental sensors to assess resilience during an experimentally induced transition in a whole-lake manipulation. A trophic cascade was induced in a planktivore-dominated lake by slowly adding piscivorous bass, whereas a nearby bass-dominated lake remained unmanipulated and served as a reference ecosystem during the 4-y experiment. In both the manipulated and reference lakes, automated sensors were used to measure variables related to ecosystem metabolism (dissolved oxygen, pH, and chlorophyll-a concentration) and to estimate gross primary production, respiration, and net ecosystem production. Thresholds were detected in some automated measurements more than a year before the completion of the transition to piscivore dominance. Directly measured variables (dissolved oxygen, pH, and chlorophyll-a concentration) related to ecosystem metabolism were better indicators of the approaching threshold than were the estimates of rates (gross primary production, respiration, and net ecosystem production); this difference was likely a result of the larger uncertainties in the derived rate estimates. Thus, relatively simple characteristics of ecosystems that were observed directly by the sensors were superior indicators of changing resilience. Models linked to thresholds in variables that are directly observed by sensor networks may provide unique opportunities for evaluating resilience in complex ecosystems.

Science, Semantics, and Social Change.

ERIC Educational Resources Information Center

Lemke, J. L.

Social semiotics suggests that social and cultural formations, including the language and practice of science and the ways in which new generations and communities advance them, develop as an integral part of the evolution of social ecosystems. Some recent models of complex dynamic systems in physics, chemistry, and biology focus more on the…

Forest-management modelling

Treesearch

Mark J. Twery; Aaron R. Weiskittel

2013-01-01

Forests are complex and dynamic ecosystems comprising individual trees that can vary in both size and species. In comparison to other organisms, trees are relatively long lived (40-2000 years), quite plastic in terms of their morphology and ecological niche, and adapted to a wide variety of habitats, which can make predicting their behaviour exceedingly difficult....

ASSESSING THE RISK ASSOCIATED WITH MERCURY: USING REVA'S WEBTOOL TO COMPARE DATA, ASSUMPTIONS, AND MODELS

EPA Science Inventory

The problem of assessing risk from mercury across the nation is extremely complex involving integration of I) our understanding of the methylation process in ecosystems, 2) the identification and spatial distribution of sensitive populations, and 3) the spatial pattern of mercury...

Model-based approach to study the impact of biofuels on the sustainability of an ecological system

EPA Science Inventory

The importance and complexity of sustainability have been well recognized and a formal study of sustainability based on system theory approaches is imperative as many of the relationships between various components of the ecosystem could be nonlinear, intertwined and non-intuitiv...

Model based approach to Study the Impact of Biofuels on the Sustainability of an Ecological System

EPA Science Inventory

The importance and complexity of sustainability has been well recognized and a formal study of sustainability based on system theory approaches is imperative as many of the relationships between various components of the ecosystem could be nonlinear, intertwined and non intuitive...

US EPA'S LANDSCAPE ECOLOGY RESEARCH: ASSESSING TRENDS FOR WETLANDS AND SURFACE WATERS USING REMORE SENSING, GIS, AND FIELD-BASED TECHNIQUES

EPA Science Inventory

The US EPA, Environmental Sciences Division-Las Vegas is using a variety of geopspatical and statistical modeling approaches to locate and assess the complex functions of wetland ecosystems. These assessments involve measuring landscape characteristrics and change, at multiple s...

The Theory behind the Theory in DCT and SCDT: A Response to Rigazio-DiGilio.

ERIC Educational Resources Information Center

Terry, Linda L.

1994-01-01

Responds to previous article by Rigazio-DiGilio on Developmental Counseling and Therapy and Systemic Cognitive-Developmental Therapy as two integrative models that unify individual, family, and network treatment within coconstructive-developmental framework. Discusses hidden complexities in cognitive-developmental ecosystemic integration and…

Modeling the vegetation-atmosphere carbon dioxide and water vapor interactions along a controlled CO2 gradient

USDA-ARS?s Scientific Manuscript database

Ecosystem functioning is intimately linked to the physical environment by complex two-way interactions. These two-way interactions arise because vegetation both responds to the external environment and actively regulates its micro-environment. By altering stomatal aperture, for example, plants modif...

Modeling Diel Oxygen Dynamics and Ecosystem Metabolism in a Shallow, Eutrophic Estuary

EPA Science Inventory

Weeks Bay is a shallow eutrophic estuary that exhibits frequent summertime diel-cycling hypoxia and periods of dissolved oxygen (DO) oversaturation during the day. Diel DO dynamics in shallow estuaries like Weeks Bay are complex, and may be influenced by wind forcing, vertical an...

MODELING OF THE MISSISSIPPI SOUND AND ADJOINING RIVERS, BAYS, AND SHELF WATERS

EPA Science Inventory

The Gulf of Mexico and its coastal watersheds are a complex ecosystem that is receiving negative impacts from human activities both in the Gulf and its watersheds. The Gulf of Mexico Program (GMP), as a multi-agency effort, is working with the Gulf States, citizens, and private ...

Vaginal ecosystem modeling of growth patterns of anaerobic bacteria in microaerophilic conditions.

PubMed

Medina-Colorado, Audrie A; Vincent, Kathleen L; Miller, Aaron L; Maxwell, Carrie A; Dawson, Lauren N; Olive, Trevelyn; Kozlova, Elena V; Baum, Marc M; Pyles, Richard B

2017-06-01

The human vagina constitutes a complex ecosystem created through relationships established between host mucosa and bacterial communities. In this ecosystem, classically defined bacterial aerobes and anaerobes thrive as communities in the microaerophilic environment. Levels of CO 2 and O 2 present in the vaginal lumen are impacted by both the ecosystem's physiology and the behavior and health of the human host. Study of such complex relationships requires controlled and reproducible causational approaches that are not possible in the human host that, until recently, was the only place these bacterial communities thrived. To address this need we have utilized our ex vivo human vaginal mucosa culture system to support controlled, reproducible colonization by vaginal bacterial communities (VBC) collected from healthy, asymptomatic donors. Parallel vaginal epithelial cells (VEC)-VBC co-cultures were exposed to two different atmospheric conditions to study the impact of CO 2 concentrations upon the anaerobic bacteria associated with dysbiosis and inflammation. Our data suggest that in the context of transplanted VBC, increased CO 2 favored specific lactobacilli species defined as microaerophiles when grown as monocultures. In preliminary studies, the observed community changes also led to shifts in host VEC phenotypes with significant changes in the host transcriptome, including altered expression of select molecular transporter genes. These findings support the need for additional study of the environmental changes associated with behavior and health upon the symbiotic and adversarial relationships that are formed in microbial communities present in the human vaginal ecosystem. Copyright © 2017 Elsevier Ltd. All rights reserved.

EMDS 3.0: A modeling framework for coping with complexity in environmental assessment and planning.

Treesearch

K.M. Reynolds

2006-01-01

EMDS 3.0 is implemented as an ArcMap® extension and integrates the logic engine of NetWeaver® to perform landscape evaluations, and the decision modeling engine of Criterium DecisionPlus® for evaluating management priorities. Key features of the system's evaluation component include abilities to (1) reason about large, abstract, multifaceted ecosystem management...

Application of a predator-prey overlap metric to determine the impact of sub-grid scale feeding dynamics on ecosystem productivity

NASA Astrophysics Data System (ADS)

Greer, A. T.; Woodson, C. B.

2016-02-01

Because of the complexity and extremely large size of marine ecosystems, research attention has a strong focus on modelling the system through space and time to elucidate processes driving ecosystem state. One of the major weaknesses of current modelling approaches is the reliance on a particular grid cell size (usually 10's of km in the horizontal & water column mean) to capture the relevant processes, even though empirical research has shown that marine systems are highly structured on fine scales, and this structure can persist over relatively long time scales (days to weeks). Fine-scale features can have a strong influence on the predator-prey interactions driving trophic transfer. Here we apply a statistic, the AB ratio, used to quantify increased predator production due to predator-prey overlap on fine scales in a manner that is computationally feasible for larger scale models. We calculated the AB ratio for predator-prey distributions throughout the scientific literature, as well as for data obtained with a towed plankton imaging system, demonstrating that averaging across a typical model grid cell neglects the fine-scale predator-prey overlap that is an essential component of ecosystem productivity. Organisms from a range of trophic levels and oceanographic regions tended to overlap with their prey both in the horizontal and vertical dimensions. When predator swimming over a diel cycle was incorporated, the amount of production indicated by the AB ratio increased substantially. For the plankton image data, the AB ratio was higher with increasing sampling resolution, especially when prey were highly aggregated. We recommend that ecosystem models incorporate more fine-scale information both to more accurately capture trophic transfer processes and to capitalize on the increasing sampling resolution and data volume from empirical studies.

Linking vegetation structure, function and physiology through spectroscopic remote sensing

NASA Astrophysics Data System (ADS)

Serbin, S.; Singh, A.; Couture, J. J.; Shiklomanov, A. N.; Rogers, A.; Desai, A. R.; Kruger, E. L.; Townsend, P. A.

2015-12-01

Terrestrial ecosystem process models require detailed information on ecosystem states and canopy properties to properly simulate the fluxes of carbon (C), water and energy from the land to the atmosphere and assess the vulnerability of ecosystems to perturbations. Current models fail to adequately capture the magnitude, spatial variation, and seasonality of terrestrial C uptake and storage, leading to significant uncertainties in the size and fate of the terrestrial C sink. By and large, these parameter and process uncertainties arise from inadequate spatial and temporal representation of plant traits, vegetation structure, and functioning. With increases in computational power and changes to model architecture and approaches, it is now possible for models to leverage detailed, data rich and spatially explicit descriptions of ecosystems to inform parameter distributions and trait tradeoffs. In this regard, spectroscopy and imaging spectroscopy data have been shown to be invaluable observational datasets to capture broad-scale spatial and, eventually, temporal dynamics in important vegetation properties. We illustrate the linkage of plant traits and spectral observations to supply key data constraints for model parameterization. These constraints can come either in the form of the raw spectroscopic data (reflectance, absorbtance) or physiological traits derived from spectroscopy. In this presentation we highlight our ongoing work to build ecological scaling relationships between critical vegetation characteristics and optical properties across diverse and complex canopies, including temperate broadleaf and conifer forests, Mediterranean vegetation, Arctic systems, and agriculture. We focus on work at the leaf, stand, and landscape scales, illustrating the importance of capturing the underlying variability in a range of parameters (including vertical variation within canopies) to enable more efficient scaling of traits related to functional diversity of ecosystems.

Unraveling the Relationships between Ecosystems and Human Wellbeing in Spain

PubMed Central

Santos-Martín, Fernando; Martín-López, Berta; García-Llorente, Marina; Aguado, Mateo; Benayas, Javier; Montes, Carlos

2013-01-01

National ecosystem assessments provide evidence on the status and trends of biodiversity, ecosystem conditions, and the delivery of ecosystem services to society. I this study, we analyze the complex relationships established between ecosystems and human systems in Spain through the combination of Driver-Pressure-State-Impact-Response framework and structural equation models. Firstly, to operationalize the framework, we selected 53 national scale indicators that provide accurate, long-term information on each of the components. Secondly, structural equation models were performed to understand the relationships among the components of the framework. Trend indicators have shown an overall progressive biodiversity loss, trade-offs between provisioning and cultural services associated with urban areas vs. regulating and cultural services associated with rural areas, a decoupling effect between material and non-material dimensions of human wellbeing, a rapid growing trend of conservation responses in recent years and a constant growing linear trend of direct or indirect drivers of change. Results also show that all the components analyzed in the model are strongly related. On one hand, the model shows that biodiversity erosion negatively affect the supply of regulating services, while it is positively related with the increase of provisioning service delivery. On the other hand, the most important relationship found in the model is the effect of pressures on biodiversity loss, indicating that response options for conserving nature cannot counteract the effect of the drivers of change. These results suggest that there is an insufficient institutional response to address the underlying causes (indirect drivers of change) of biodiversity loos in Spain. We conclude that more structural changes are required in the Spanish institutional framework to reach 2020 biodiversity conservation international targets. PMID:24039894

Unraveling the relationships between ecosystems and human wellbeing in Spain.

PubMed

Santos-Martín, Fernando; Martín-López, Berta; García-Llorente, Marina; Aguado, Mateo; Benayas, Javier; Montes, Carlos

2013-01-01

National ecosystem assessments provide evidence on the status and trends of biodiversity, ecosystem conditions, and the delivery of ecosystem services to society. I this study, we analyze the complex relationships established between ecosystems and human systems in Spain through the combination of Driver-Pressure-State-Impact-Response framework and structural equation models. Firstly, to operationalize the framework, we selected 53 national scale indicators that provide accurate, long-term information on each of the components. Secondly, structural equation models were performed to understand the relationships among the components of the framework. Trend indicators have shown an overall progressive biodiversity loss, trade-offs between provisioning and cultural services associated with urban areas vs. regulating and cultural services associated with rural areas, a decoupling effect between material and non-material dimensions of human wellbeing, a rapid growing trend of conservation responses in recent years and a constant growing linear trend of direct or indirect drivers of change. Results also show that all the components analyzed in the model are strongly related. On one hand, the model shows that biodiversity erosion negatively affect the supply of regulating services, while it is positively related with the increase of provisioning service delivery. On the other hand, the most important relationship found in the model is the effect of pressures on biodiversity loss, indicating that response options for conserving nature cannot counteract the effect of the drivers of change. These results suggest that there is an insufficient institutional response to address the underlying causes (indirect drivers of change) of biodiversity loos in Spain. We conclude that more structural changes are required in the Spanish institutional framework to reach 2020 biodiversity conservation international targets.

Strengthening governance for intertidal ecosystems requires a consistent definition of boundaries between land and sea.

PubMed

Rog, Stefanie M; Cook, Carly N

2017-07-15

The protection of intertidal ecosystems is complex because they straddle both marine and terrestrial realms. This leads to inconsistent characterisation as marine and/or terrestrial systems, or neither. Vegetated intertidal ecosystems are especially complex to classify because they can have an unclear border with terrestrial vegetation, causing confusion around taxonomy (e.g., mangrove-like plants). This confusion and inconsistency in classification can impact these systems through poor governance and incomplete protection. Using Australian mangrove ecosystems as a case study, we explore the complexity of how land and sea boundaries are defined among jurisdictions and different types of legislation, and how these correspond to ecosystem boundaries. We demonstrate that capturing vegetated intertidal ecosystems under native vegetation laws and prioritizing the mitigation of threats with a terrestrial origin offers the greatest protection to these systems. We also show the impact of inconsistent boundaries on the inclusion of intertidal ecosystems within protected areas. The evidence presented here highlights problems within the Australian context, but most of these issues are also challenges for the management of intertidal ecosystems around the world. Our study demonstrates the urgent need for a global review of legislation governing the boundaries of land and sea to determine whether the suggestions we offer may provide global solutions to ensuring these critical systems do not fall through the cracks in ecosystem protection and management. Copyright © 2017 Elsevier Ltd. All rights reserved.

Modeling the lake eutrophication stochastic ecosystem and the research of its stability.

PubMed

Wang, Bo; Qi, Qianqian

2018-06-01

In the reality, the lake system will be disturbed by stochastic factors including the external and internal factors. By adding the additive noise and the multiplicative noise to the right-hand sides of the model equation, the additive stochastic model and the multiplicative stochastic model are established respectively in order to reduce model errors induced by the absence of some physical processes. For both the two kinds of stochastic ecosystems, the authors studied the bifurcation characteristics with the FPK equation and the Lyapunov exponent method based on the Stratonovich-Khasminiskii stochastic average principle. Results show that, for the additive stochastic model, when control parameter (i.e., nutrient loading rate) falls into the interval [0.388644, 0.66003825], there exists bistability for the ecosystem and the additive noise intensities cannot make the bifurcation point drift. In the region of the bistability, the external stochastic disturbance which is one of the main triggers causing the lake eutrophication, may make the ecosystem unstable and induce a transition. When control parameter (nutrient loading rate) falls into the interval (0,  0.388644) and (0.66003825,  1.0), there only exists a stable equilibrium state and the additive noise intensity could not change it. For the multiplicative stochastic model, there exists more complex bifurcation performance and the multiplicative ecosystem will be broken by the multiplicative noise. Also, the multiplicative noise could reduce the extent of the bistable region, ultimately, the bistable region vanishes for sufficiently large noise. What's more, both the nutrient loading rate and the multiplicative noise will make the ecosystem have a regime shift. On the other hand, for the two kinds of stochastic ecosystems, the authors also discussed the evolution of the ecological variable in detail by using the Four-stage Runge-Kutta method of strong order γ=1.5. The numerical method was found to be capable of effectively explaining the regime shift theory and agreed with the realistic analyze. These conclusions also confirms the two paths for the system to move from one stable state to another proposed by Beisner et al. [3], which may help understand the occurrence mechanism related to the lake eutrophication from the view point of the stochastic model and mathematical analysis. Copyright © 2018 Elsevier Inc. All rights reserved.

Review and synthesis: Changing permafrost in a warming world and feedbacks to the Earth System

USGS Publications Warehouse

Grosse, Guido; Goetz, Scott; McGuire, A. David; Romanovsky, Vladimir E.; Schuur, Edward A.G.

2016-01-01

The permafrost component of the cryosphere is changing dramatically, but the permafrost region is not well monitored and the consequences of change are not well understood. Changing permafrost interacts with ecosystems and climate on various spatial and temporal scales. The feedbacks resulting from these interactions range from local impacts on topography, hydrology, and biology to complex influences on global scale biogeochemical cycling. This review contributes to this focus issue by synthesizing its 28 multidisciplinary studies which provide field evidence, remote sensing observations, and modeling results on various scales. We synthesize study results from a diverse range of permafrost landscapes and ecosystems by reporting key observations and modeling outcomes for permafrost thaw dynamics, identifying feedbacks between permafrost and ecosystem processes, and highlighting biogeochemical feedbacks from permafrost thaw. We complete our synthesis by discussing the progress made, stressing remaining challenges and knowledge gaps, and providing an outlook on future needs and research opportunities in the study of permafrost–ecosystem–climate interactions.

Alternative states of a semiarid grassland ecosystem: implications for ecosystem services

USGS Publications Warehouse

Miller, Mark E.; Belote, R. Travis; Bowker, Matthew A.; Garman, Steven L.

2011-01-01

Ecosystems can shift between alternative states characterized by persistent differences in structure, function, and capacity to provide ecosystem services valued by society. We examined empirical evidence for alternative states in a semiarid grassland ecosystem where topographic complexity and contrasting management regimes have led to spatial variations in levels of livestock grazing. Using an inventory data set, we found that plots (n = 72) cluster into three groups corresponding to generalized alternative states identified in an a priori conceptual model. One cluster (biocrust) is notable for high coverage of a biological soil crust functional group in addition to vascular plants. Another (grass-bare) lacks biological crust but retains perennial grasses at levels similar to the biocrust cluster. A third (annualized-bare) is dominated by invasive annual plants. Occurrence of grass-bare and annualized-bare conditions in areas where livestock have been excluded for over 30 years demonstrates the persistence of these states. Significant differences among all three clusters were found for percent bare ground, percent total live cover, and functional group richness. Using data for vegetation structure and soil erodibility, we also found large among-cluster differences in average levels of dust emissions predicted by a wind-erosion model. Predicted emissions were highest for the annualized-bare cluster and lowest for the biocrust cluster, which was characterized by zero or minimal emissions even under conditions of extreme wind. Results illustrate potential trade-offs among ecosystem services including livestock production, soil retention, carbon storage, and biodiversity conservation. Improved understanding of these trade-offs may assist ecosystem managers when evaluating alternative management strategies.

A Disease-Mediated Trophic Cascade in the Serengeti and its Implications for Ecosystem C

PubMed Central

Holdo, Ricardo M.; Sinclair, Anthony R. E.; Dobson, Andrew P.; Metzger, Kristine L.; Bolker, Benjamin M.; Ritchie, Mark E.; Holt, Robert D.

2009-01-01

Tree cover is a fundamental structural characteristic and driver of ecosystem processes in terrestrial ecosystems, and trees are a major global carbon (C) sink. Fire and herbivores have been hypothesized to play dominant roles in regulating trees in African savannas, but the evidence for this is conflicting. Moving up a trophic scale, the factors that regulate fire occurrence and herbivores, such as disease and predation, are poorly understood for any given ecosystem. We used a Bayesian state-space model to show that the wildebeest population irruption that followed disease (rinderpest) eradication in the Serengeti ecosystem of East Africa led to a widespread reduction in the extent of fire and an ongoing recovery of the tree population. This supports the hypothesis that disease has played a key role in the regulation of this ecosystem. We then link our state-space model with theoretical and empirical results quantifying the effects of grazing and fire on soil carbon to predict that this cascade may have led to important shifts in the size of pools of C stored in soil and biomass. Our results suggest that the dynamics of herbivores and fire are tightly coupled at landscape scales, that fire exerts clear top-down effects on tree density, and that disease outbreaks in dominant herbivores can lead to complex trophic cascades in savanna ecosystems. We propose that the long-term status of the Serengeti and other intensely grazed savannas as sources or sinks for C may be fundamentally linked to the control of disease outbreaks and poaching. PMID:19787022

Towards a holistic understanding of the beneficial interactions across the Populus microbiome

DOE PAGES

Hacquard, Stéphane; Schadt, Christopher W.

2014-11-24

Interactions between trees and microorganisms are extremely complex and the multispecies networks resulting from these associations have consequences for plant growth and productivity. However, a more holistic view is needed to better understand trees as ecosystems and superorganisms, where many interacting species contribute to the overall stability of the system. While much progress has been made on microbial communities associated with individual tree niches and the molecular interactions between model symbiotic partners, there is still a lack of knowledge of the multi-component interactions necessary for holistic ecosystem-level understanding. Finally, we review recent studies in Populus to emphasize the importance ofmore » such holistic efforts across the leaf, stem and rooting zones, and discuss prospects for future research in these important ecosystems.« less

Collards and Caterpillars

ERIC Educational Resources Information Center

Ashbrook, Peggy

2007-01-01

"Community," "assemblage," "network," "complex," "interdependent," "web," and "synergism"--definitions of an ecosystem often include these words to highlight the dynamic interrelated workings of plants and animals with their physical environment. Young children don't understand the complexities of ecosystems, but they can begin to understand that…

Modeling species invasions in Ecopath with Ecosim: an evaluation using Laurentian Great Lakes models

USGS Publications Warehouse

Langseth, Brian J.; Rogers, Mark; Zhang, Hongyan

2012-01-01

Invasive species affect the structure and processes of ecosystems they invade. Invasive species have been particularly relevant to the Laurentian Great Lakes, where they have played a part in both historical and recent changes to Great Lakes food webs and the fisheries supported therein. There is increased interest in understanding the effects of ecosystem changes on fisheries within the Great Lakes, and ecosystem models provide an essential tool from which this understanding can take place. A commonly used model for exploring fisheries management questions within an ecosystem context is the Ecopath with Ecosim (EwE) modeling software. Incorporating invasive species into EwE models is a challenging process, and descriptions and comparisons of methods for modeling species invasions are lacking. We compared four methods for incorporating invasive species into EwE models for both Lake Huron and Lake Michigan based on the ability of each to reproduce patterns in observed data time series. The methods differed in whether invasive species biomass was forced in the model, the initial level of invasive species biomass at the beginning of time dynamic simulations, and the approach to cause invasive species biomass to increase at the time of invasion. The overall process of species invasion could be reproduced by all methods, but fits to observed time series varied among the methods and models considered. We recommend forcing invasive species biomass when model objectives are to understand ecosystem impacts in the past and when time series of invasive species biomass are available. Among methods where invasive species time series were not forced, mediating the strength of predator–prey interactions performed best for the Lake Huron model, but worse for the Lake Michigan model. Starting invasive species biomass at high values and then artificially removing biomass until the time of invasion performed well for both models, but was more complex than starting invasive species biomass at low values. In general, for understanding the effect of invasive species on future fisheries management actions, we recommend initiating invasive species biomass at low levels based on the greater simplicity and realism of the method compared to others.

Distribution of phytoplankton functional types in high-nitrate, low-chlorophyll waters in a new diagnostic ecological indicator model

NASA Astrophysics Data System (ADS)

Palacz, A. P.; St. John, M. A.; Brewin, R. J. W.; Hirata, T.; Gregg, W. W.

2013-11-01

Modeling and monitoring plankton functional types (PFTs) is challenged by the insufficient amount of field measurements of ground truths in both plankton models and bio-optical algorithms. In this study, we combine remote sensing data and a dynamic plankton model to simulate an ecologically sound spatial and temporal distribution of phyto-PFTs. We apply an innovative ecological indicator approach to modeling PFTs and focus on resolving the question of diatom-coccolithophore coexistence in the subpolar high-nitrate and low-chlorophyll regions. We choose an artificial neural network as our modeling framework because it has the potential to interpret complex nonlinear interactions governing complex adaptive systems, of which marine ecosystems are a prime example. Using ecological indicators that fulfill the criteria of measurability, sensitivity and specificity, we demonstrate that our diagnostic model correctly interprets some basic ecological rules similar to ones emerging from dynamic models. Our time series highlight a dynamic phyto-PFT community composition in all high-latitude areas and indicate seasonal coexistence of diatoms and coccolithophores. This observation, though consistent with in situ and remote sensing measurements, has so far not been captured by state-of-the-art dynamic models, which struggle to resolve this "paradox of the plankton". We conclude that an ecological indicator approach is useful for ecological modeling of phytoplankton and potentially higher trophic levels. Finally, we speculate that it could serve as a powerful tool in advancing ecosystem-based management of marine resources.

Distribution of phytoplankton functional types in high-nitrate low-chlorophyll waters in a new diagnostic ecological indicator model

NASA Astrophysics Data System (ADS)

Palacz, A. P.; St. John, M. A.; Brewin, R. J. W.; Hirata, T.; Gregg, W. W.

2013-05-01

Modeling and monitoring plankton functional types (PFTs) is challenged by insufficient amount of field measurements to ground-truth both plankton models and bio-optical algorithms. In this study, we combine remote sensing data and a dynamic plankton model to simulate an ecologically-sound spatial and temporal distribution of phyto-PFTs. We apply an innovative ecological indicator approach to modeling PFTs, and focus on resolving the question of diatom-coccolithophore co-existence in the subpolar high-nitrate and low-chlorophyll regions. We choose an artificial neural network as our modeling framework because it has the potential to interpret complex nonlinear interactions governing complex adaptive systems, of which marine ecosystems are a prime example. Using ecological indicators that fulfill the criteria of measurability, sensitivity and specificity, we demonstrate that our diagnostic model correctly interprets some basic ecological rules similar to ones emerging from dynamic models. Our time series highlight a dynamic phyto-PFT community composition in all high latitude areas, and indicate seasonal co-existence of diatoms and coccolithophores. This observation, though consistent with in situ and remote sensing measurements, was so far not captured by state-of-the-art dynamic models which struggle to resolve this "paradox of the plankton". We conclude that an ecological indicator approach is useful for ecological modeling of phytoplankton and potentially higher trophic levels. Finally, we speculate that it could serve as a powerful tool in advancing ecosystem-based management of marine resources.

Landscape co-evolution and river discharge.

NASA Astrophysics Data System (ADS)

van der Velde, Ype; Temme, Arnaud

2015-04-01

Fresh water is crucial for society and ecosystems. However, our ability to secure fresh water resources under climatic and anthropogenic change is impaired by the complexity of interactions between human society, ecosystems, soils, and topography. These interactions cause landscape properties to co-evolve, continuously changing the flow paths of water through the landscape. These co-evolution driven flow path changes and their effect on river runoff are, to-date, poorly understood. In this presentation we introduce a spatially distributed landscape evolution model that incorporates growing vegetation and its effect on evapotranspiration, interception, infiltration, soil permeability, groundwater-surface water exchange and erosion. This landscape scale (10km2) model is calibrated to evolve towards well known empirical organising principles such as the Budyko curve and Hacks law under different climate conditions. To understand how positive and negative feedbacks within the model structure form complex landscape patterns of forests and peat bogs that resemble observed landscapes under humid and boreal climates, we analysed the effects of individual processes on the spatial distribution of vegetation and river peak and mean flows. Our results show that especially river peak flows and droughts decrease with increasing evolution of the landscape, which is a result that has direct implications for flood management.

Architecture of collapse: regime shift and recovery in an hierarchically structured marine ecosystem.

PubMed

Daskalov, Georgi M; Boicenco, Laura; Grishin, Alexandre N; Lazar, Luminita; Mihneva, Vesselina; Shlyakhov, Vladislav A; Zengin, Mustafa

2017-04-01

By the late 20th century, a series of events or 'natural experiments', for example the depletion of apex predators, extreme eutrophication and blooms of invasive species, had suggested that the Black Sea could be considered as a large ecosystem 'laboratory'. The events resulted in regime shifts cascading through all trophic levels, disturbing ecosystem functioning and damaging the water environment. Causal pathways by which the external (hydroclimate, overfishing) and internal (food web interactions) drivers provoke regime shifts are investigated. Statistical data analyses supported by an interpretative framework based on hierarchical ecosystem theory revealed mechanisms of hierarchical incorporation of environmental factors into the ecosystem. Evidence links Atlantic teleconnections to Black Sea hydroclimate, which together with fishing shapes variability in fish stocks. The hydroclimatic signal is conveyed through the food web via changes in productivity at all levels, to planktivorous fish. Fluctuating fish abundance is believed to induce a lagged change in competitor jelly plankton that cascades down to phytoplankton and influences water quality. Deprived of the stabilising role of apex predators, the Black Sea's hierarchical ecosystem organisation is susceptible to both environmental and anthropogenic stresses, and increased fishing makes fish stock collapses highly probable. When declining stocks are confronted with burgeoning fishing effort associated with the inability of fishery managers and decision-makers to adapt rapidly to changes in fish abundance, there is overfishing and stock collapse. Management procedures are ineffective at handling complex phenomena such as ecosystem regime shifts because of the shortage of suitable explanatory models. The proposed concepts and models reported here relate the hydroclimate, overfishing and invasive species to shifts in ecosystem functioning and water quality, unravelling issues such as the causality of ecosystem interactions and mechanisms and offering potential for finding ways to reverse regime shifts. We advocate a management approach aiming at restoring ecosystem hierarchy that might mitigate the costly consequences of regime shifts. © 2016 John Wiley & Sons Ltd.

Reconciling the temperature dependence of respiration across timescales and ecosystem types.

PubMed

Yvon-Durocher, Gabriel; Caffrey, Jane M; Cescatti, Alessandro; Dossena, Matteo; del Giorgio, Paul; Gasol, Josep M; Montoya, José M; Pumpanen, Jukka; Staehr, Peter A; Trimmer, Mark; Woodward, Guy; Allen, Andrew P

2012-07-26

Ecosystem respiration is the biotic conversion of organic carbon to carbon dioxide by all of the organisms in an ecosystem, including both consumers and primary producers. Respiration exhibits an exponential temperature dependence at the subcellular and individual levels, but at the ecosystem level respiration can be modified by many variables including community abundance and biomass, which vary substantially among ecosystems. Despite its importance for predicting the responses of the biosphere to climate change, it is as yet unknown whether the temperature dependence of ecosystem respiration varies systematically between aquatic and terrestrial environments. Here we use the largest database of respiratory measurements yet compiled to show that the sensitivity of ecosystem respiration to seasonal changes in temperature is remarkably similar for diverse environments encompassing lakes, rivers, estuaries, the open ocean and forested and non-forested terrestrial ecosystems, with an average activation energy similar to that of the respiratory complex (approximately 0.65 electronvolts (eV)). By contrast, annual ecosystem respiration shows a substantially greater temperature dependence across aquatic (approximately 0.65 eV) versus terrestrial ecosystems (approximately 0.32 eV) that span broad geographic gradients in temperature. Using a model derived from metabolic theory, these findings can be reconciled by similarities in the biochemical kinetics of metabolism at the subcellular level, and fundamental differences in the importance of other variables besides temperature—such as primary productivity and allochthonous carbon inputs—on the structure of aquatic and terrestrial biota at the community level.

Incorporating grassland management in ORCHIDEE: model description and evaluation at 11 eddy-covariance sites in Europe

NASA Astrophysics Data System (ADS)

Chang, J. F.; Viovy, N.; Vuichard, N.; Ciais, P.; Wang, T.; Cozic, A.; Lardy, R.; Graux, A.-I.; Klumpp, K.; Martin, R.; Soussana, J.-F.

2013-12-01

This study describes how management of grasslands is included in the Organizing Carbon and Hydrology in Dynamic Ecosystems (ORCHIDEE) process-based ecosystem model designed for large-scale applications, and how management affects modeled grassland-atmosphere CO2 fluxes. The new model, ORCHIDEE-GM (grassland management) is enabled with a management module inspired from a grassland model (PaSim, version 5.0), with two grassland management practices being considered, cutting and grazing. The evaluation of the results from ORCHIDEE compared with those of ORCHIDEE-GM at 11 European sites, equipped with eddy covariance and biometric measurements, shows that ORCHIDEE-GM can realistically capture the cut-induced seasonal variation in biometric variables (LAI: leaf area index; AGB: aboveground biomass) and in CO2 fluxes (GPP: gross primary productivity; TER: total ecosystem respiration; and NEE: net ecosystem exchange). However, improvements at grazing sites are only marginal in ORCHIDEE-GM due to the difficulty in accounting for continuous grazing disturbance and its induced complex animal-vegetation interactions. Both NEE and GPP on monthly to annual timescales can be better simulated in ORCHIDEE-GM than in ORCHIDEE without management. For annual CO2 fluxes, the NEE bias and RMSE (root mean square error) in ORCHIDEE-GM are reduced by 53% and 20%, respectively, compared to ORCHIDEE. ORCHIDEE-GM is capable of modeling the net carbon balance (NBP) of managed temperate grasslands (37 ± 30 gC m-2 yr-1 (P < 0.01) over the 11 sites) because the management module contains provisions to simulate the carbon fluxes of forage yield, herbage consumption, animal respiration and methane emissions.

Habitat structure mediates biodiversity effects on ecosystem properties

PubMed Central

Godbold, J. A.; Bulling, M. T.; Solan, M.

2011-01-01

Much of what we know about the role of biodiversity in mediating ecosystem processes and function stems from manipulative experiments, which have largely been performed in isolated, homogeneous environments that do not incorporate habitat structure or allow natural community dynamics to develop. Here, we use a range of habitat configurations in a model marine benthic system to investigate the effects of species composition, resource heterogeneity and patch connectivity on ecosystem properties at both the patch (bioturbation intensity) and multi-patch (nutrient concentration) scale. We show that allowing fauna to move and preferentially select patches alters local species composition and density distributions, which has negative effects on ecosystem processes (bioturbation intensity) at the patch scale, but overall positive effects on ecosystem functioning (nutrient concentration) at the multi-patch scale. Our findings provide important evidence that community dynamics alter in response to localized resource heterogeneity and that these small-scale variations in habitat structure influence species contributions to ecosystem properties at larger scales. We conclude that habitat complexity forms an important buffer against disturbance and that contemporary estimates of the level of biodiversity required for maintaining future multi-functional systems may need to be revised. PMID:21227969

Habitat structure mediates biodiversity effects on ecosystem properties.

PubMed

Godbold, J A; Bulling, M T; Solan, M

2011-08-22

Much of what we know about the role of biodiversity in mediating ecosystem processes and function stems from manipulative experiments, which have largely been performed in isolated, homogeneous environments that do not incorporate habitat structure or allow natural community dynamics to develop. Here, we use a range of habitat configurations in a model marine benthic system to investigate the effects of species composition, resource heterogeneity and patch connectivity on ecosystem properties at both the patch (bioturbation intensity) and multi-patch (nutrient concentration) scale. We show that allowing fauna to move and preferentially select patches alters local species composition and density distributions, which has negative effects on ecosystem processes (bioturbation intensity) at the patch scale, but overall positive effects on ecosystem functioning (nutrient concentration) at the multi-patch scale. Our findings provide important evidence that community dynamics alter in response to localized resource heterogeneity and that these small-scale variations in habitat structure influence species contributions to ecosystem properties at larger scales. We conclude that habitat complexity forms an important buffer against disturbance and that contemporary estimates of the level of biodiversity required for maintaining future multi-functional systems may need to be revised.

Process-Based Thinking in Ecosystem Education

ERIC Educational Resources Information Center

Jordan, Rebecca C.; Gray, Steven A.; Brooks, Wesley R.; Honwad, Sameer; Hmelo-Silver, Cindy E.

2013-01-01

Understanding complex systems such as ecosystems is difficult for young K-12 students, and students' representations of ecosystems are often limited to nebulously defined relationships between macro-level structural components inherent to the ecosystem in focus (rainforest, desert, pond, etc.) instead of generalizing processes across ecosystems…

Effect of Freeze-Thaw Cycles on Soil Nitrogen Reactive Transport in a Polygonal Arctic Tundra Ecosystem at Barrow AK Using 3-D Coupled ALM-PFLOTRAN

NASA Astrophysics Data System (ADS)

Yuan, F.; Wang, G.; Painter, S. L.; Tang, G.; Xu, X.; Kumar, J.; Bisht, G.; Hammond, G. E.; Mills, R. T.; Thornton, P. E.; Wullschleger, S. D.

2017-12-01

In Arctic tundra ecosystem soil freezing-thawing is one of dominant physical processes through which biogeochemical (e.g., carbon and nitrogen) cycles are tightly coupled. Besides hydraulic transport, freezing-thawing can cause pore water movement and aqueous species gradients, which are additional mechanisms for soil nitrogen (N) reactive-transport in Tundra ecosystem. In this study, we have fully coupled an in-development ESM(i.e., Advanced Climate Model for Energy, ACME)'s Land Model (ALM) aboveground processes with a state-of-the-art massively parallel 3-D subsurface thermal-hydrology and reactive transport code, PFLOTRAN. The resulting coupled ALM-PFLOTRAN model is a Land Surface Model (LSM) capable of resolving 3-D soil thermal-hydrological-biogeochemical cycles. This specific version of PFLOTRAN has incorporated CLM-CN Converging Trophic Cascade (CTC) model and a full and simple but robust soil N cycle. It includes absorption-desorption for soil NH4+ and gas dissolving-degasing process as well. It also implements thermal-hydrology mode codes with three newly-modified freezing-thawing algorithms which can greatly improve computing performance in regarding to numerical stiffness at freezing-point. Here we tested the model in fully 3-D coupled mode at the Next Generation Ecosystem Experiment-Arctic (NGEE-Arctic) field intensive study site at the Barrow Environmental Observatory (BEO), AK. The simulations show that: (1) synchronous coupling of soil thermal-hydrology and biogeochemistry in 3-D can greatly impact ecosystem dynamics across polygonal tundra landscape; and (2) freezing-thawing cycles can add more complexity to the system, resulting in greater mobility of soil N vertically and laterally, depending upon local micro-topography. As a preliminary experiment, the model is also implemented for Pan-Arctic region in 1-D column mode (i.e. no lateral connection), showing significant differences compared to stand-alone ALM. The developed ALM-PFLOTRAN coupling codes embeded within ESM will be used for Pan-Arctic regional evaluation of climate change-caused ecosystem responses and their feedbacks to climate system at various scales.

2016 International Land Model Benchmarking (ILAMB) Workshop Report

NASA Technical Reports Server (NTRS)

Hoffman, Forrest M.; Koven, Charles D.; Keppel-Aleks, Gretchen; Lawrence, David M.; Riley, William J.; Randerson, James T.; Ahlstrom, Anders; Abramowitz, Gabriel; Baldocchi, Dennis D.; Best, Martin J.;

2016 International Land Model Benchmarking (ILAMB) Workshop Report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hoffman, Forrest M.; Koven, Charles D.; Keppel-Aleks, Gretchen

As Earth system models become increasingly complex, there is a growing need for comprehensive and multi-faceted evaluation of model projections. To advance understanding of biogeochemical processes and their interactions with hydrology and climate under conditions of increasing atmospheric carbon dioxide, new analysis methods are required that use observations to constrain model predictions, inform model development, and identify needed measurements and field experiments. Better representations of biogeochemistry–climate feedbacks and ecosystem processes in these models are essential for reducing uncertainties associated with projections of climate change during the remainder of the 21st century.

Quantifying the web browser ecosystem

PubMed Central

Ferdman, Sela; Minkov, Einat; Gefen, David

2017-01-01

Contrary to the assumption that web browsers are designed to support the user, an examination of a 900,000 distinct PCs shows that web browsers comprise a complex ecosystem with millions of addons collaborating and competing with each other. It is possible for addons to “sneak in” through third party installations or to get “kicked out” by their competitors without user involvement. This study examines that ecosystem quantitatively by constructing a large-scale graph with nodes corresponding to users, addons, and words (terms) that describe addon functionality. Analyzing addon interactions at user level using the Personalized PageRank (PPR) random walk measure shows that the graph demonstrates ecological resilience. Adapting the PPR model to analyzing the browser ecosystem at the level of addon manufacturer, the study shows that some addon companies are in symbiosis and others clash with each other as shown by analyzing the behavior of 18 prominent addon manufacturers. Results may herald insight on how other evolving internet ecosystems may behave, and suggest a methodology for measuring this behavior. Specifically, applying such a methodology could transform the addon market. PMID:28644833

Species richness and biomass explain spatial turnover in ecosystem functioning across tropical and temperate ecosystems.

PubMed

Barnes, Andrew D; Weigelt, Patrick; Jochum, Malte; Ott, David; Hodapp, Dorothee; Haneda, Noor Farikhah; Brose, Ulrich

2016-05-19

Predicting ecosystem functioning at large spatial scales rests on our ability to scale up from local plots to landscapes, but this is highly contingent on our understanding of how functioning varies through space. Such an understanding has been hampered by a strong experimental focus of biodiversity-ecosystem functioning research restricted to small spatial scales. To address this limitation, we investigate the drivers of spatial variation in multitrophic energy flux-a measure of ecosystem functioning in complex communities-at the landscape scale. We use a structural equation modelling framework based on distance matrices to test how spatial and environmental distances drive variation in community energy flux via four mechanisms: species composition, species richness, niche complementarity and biomass. We found that in both a tropical and a temperate study region, geographical and environmental distance indirectly influence species richness and biomass, with clear evidence that these are the dominant mechanisms explaining variability in community energy flux over spatial and environmental gradients. Our results reveal that species composition and trait variability may become redundant in predicting ecosystem functioning at the landscape scale. Instead, we demonstrate that species richness and total biomass may best predict rates of ecosystem functioning at larger spatial scales. © 2016 The Author(s).

Evaluation of simulated biospheric carbon dioxide fluxes and atmospheric concentrations using global in situ observations

NASA Astrophysics Data System (ADS)

Philip, S.; Johnson, M. S.; Potter, C. S.; Genovese, V. B.

2016-12-01

Atmospheric mixing ratios of carbon dioxide (CO2) are largely controlled by anthropogenic emission sources and biospheric sources/sinks. Global biospheric fluxes of CO2 are controlled by complex processes facilitating the exchange of carbon between terrestrial ecosystems and the atmosphere. These processes which play a key role in these terrestrial ecosystem-atmosphere carbon exchanges are currently not fully understood, resulting in large uncertainties in the quantification of biospheric CO2 fluxes. Current models with these inherent deficiencies have difficulties simulating the global carbon cycle with high accuracy. We are developing a new modeling platform, GEOS-Chem-CASA by integrating the year-specific NASA-CASA (National Aeronautics and Space Administration - Carnegie Ames Stanford Approach) biosphere model with the GEOS-Chem (Goddard Earth Observation System-Chemistry) chemical transport model to improve the simulation of atmosphere-terrestrial ecosystem carbon exchange. We use NASA-CASA to explicitly represent the exchange of CO2 between terrestrial ecosystem and atmosphere by replacing the baseline GEOS-Chem land net CO2 flux and forest biomass burning CO2 emissions. We will present the estimation and evaluation of these "bottom-up" land CO2 fluxes, simulated atmospheric mixing ratios, and forest disturbance changes over the last decade. In addition, we will present our initial comparison of atmospheric column-mean dry air mole fraction of CO2 predicted by the model and those retrieved from NASA's OCO-2 (Orbiting Carbon Observatory-2) satellite instrument and model-predicted surface CO2 mixing ratios with global in situ observations. This evaluation is the first step necessary for our future work planned to constrain the estimates of biospheric carbon fluxes through "top-down" inverse modeling, which will improve our understanding of the processes controlling atmosphere-terrestrial ecosystem greenhouse gas exchanges, especially over regions which lack in situ observations.

B33C-0612: Evaluation of Simulated Biospheric Carbon Dioxide Fluxes and Atmospheric Concentrations Using Global in Situ Observations

NASA Technical Reports Server (NTRS)

Philip, Sajeev; Johnson, Matthew S.; Potter, Christopher S.; Genovese, Vanessa

2016-01-01

Atmospheric mixing ratios of carbon dioxide (CO2) are largely controlled by anthropogenic emission sources and biospheric sources/sinks. Global biospheric fluxes of CO2 are controlled by complex processes facilitating the exchange of carbon between terrestrial ecosystems and the atmosphere. These processes which play a key role in these terrestrial ecosystem-atmosphere carbon exchanges are currently not fully understood, resulting in large uncertainties in the quantification of biospheric CO2 fluxes. Current models with these inherent deficiencies have difficulties simulating the global carbon cycle with high accuracy. We are developing a new modeling platform, GEOS-Chem-CASA by integrating the year-specific NASA-CASA (National Aeronautics and Space Administration - Carnegie Ames Stanford Approach) biosphere model with the GEOS-Chem (Goddard Earth Observation System-Chemistry) chemical transport model to improve the simulation of atmosphere-terrestrial ecosystem carbon exchange. We use NASA-CASA to explicitly represent the exchange of CO2 between terrestrial ecosystem and atmosphere by replacing the baseline GEOS-Chem land net CO2 flux and forest biomass burning CO2 emissions. We will present the estimation and evaluation of these "bottom-up" land CO2 fluxes, simulated atmospheric mixing ratios, and forest disturbance changes over the last decade. In addition, we will present our initial comparison of atmospheric column-mean dry air mole fraction of CO2 predicted by the model and those retrieved from NASA's OCO-2 (Orbiting Carbon Observatory-2) satellite instrument and model-predicted surface CO2 mixing ratios with global in situ observations. This evaluation is the first step necessary for our future work planned to constrain the estimates of biospheric carbon fluxes through "top-down" inverse modeling, which will improve our understanding of the processes controlling atmosphere-terrestrial ecosystem greenhouse gas exchanges, especially over regions which lack in situ observations.

Carbon fluxes in ecosystems of Yellowstone National Park predicted from remote sensing data and simulation modeling

PubMed Central

2011-01-01

Background A simulation model based on remote sensing data for spatial vegetation properties has been used to estimate ecosystem carbon fluxes across Yellowstone National Park (YNP). The CASA (Carnegie Ames Stanford Approach) model was applied at a regional scale to estimate seasonal and annual carbon fluxes as net primary production (NPP) and soil respiration components. Predicted net ecosystem production (NEP) flux of CO2 is estimated from the model for carbon sinks and sources over multi-year periods that varied in climate and (wildfire) disturbance histories. Monthly Enhanced Vegetation Index (EVI) image coverages from the NASA Moderate Resolution Imaging Spectroradiometer (MODIS) instrument (from 2000 to 2006) were direct inputs to the model. New map products have been added to CASA from airborne remote sensing of coarse woody debris (CWD) in areas burned by wildfires over the past two decades. Results Model results indicated that relatively cooler and wetter summer growing seasons were the most favorable for annual plant production and net ecosystem carbon gains in representative landscapes of YNP. When summed across vegetation class areas, the predominance of evergreen forest and shrubland (sagebrush) cover was evident, with these two classes together accounting for 88% of the total annual NPP flux of 2.5 Tg C yr-1 (1 Tg = 1012 g) for the entire Yellowstone study area from 2000-2006. Most vegetation classes were estimated as net ecosystem sinks of atmospheric CO2 on annual basis, making the entire study area a moderate net sink of about +0.13 Tg C yr-1. This average sink value for forested lands nonetheless masks the contribution of areas burned during the 1988 wildfires, which were estimated as net sources of CO2 to the atmosphere, totaling to a NEP flux of -0.04 Tg C yr-1 for the entire burned area. Several areas burned in the 1988 wildfires were estimated to be among the lowest in overall yearly NPP, namely the Hellroaring Fire, Mink Fire, and Falls Fire areas. Conclusions Rates of recovery for burned forest areas to pre-1988 biomass levels were estimated from a unique combination of remote sensing and CASA model predictions. Ecosystem production and carbon fluxes in the Greater Yellowstone Ecosystem (GYE) result from complex interactions between climate, forest age structure, and disturbance-recovery patterns of the landscape. PMID:21835025

Carbon fluxes in ecosystems of Yellowstone National Park predicted from remote sensing data and simulation modeling.

PubMed

Potter, Christopher; Klooster, Steven; Crabtree, Robert; Huang, Shengli; Gross, Peggy; Genovese, Vanessa

2011-08-11

A simulation model based on remote sensing data for spatial vegetation properties has been used to estimate ecosystem carbon fluxes across Yellowstone National Park (YNP). The CASA (Carnegie Ames Stanford Approach) model was applied at a regional scale to estimate seasonal and annual carbon fluxes as net primary production (NPP) and soil respiration components. Predicted net ecosystem production (NEP) flux of CO2 is estimated from the model for carbon sinks and sources over multi-year periods that varied in climate and (wildfire) disturbance histories. Monthly Enhanced Vegetation Index (EVI) image coverages from the NASA Moderate Resolution Imaging Spectroradiometer (MODIS) instrument (from 2000 to 2006) were direct inputs to the model. New map products have been added to CASA from airborne remote sensing of coarse woody debris (CWD) in areas burned by wildfires over the past two decades. Model results indicated that relatively cooler and wetter summer growing seasons were the most favorable for annual plant production and net ecosystem carbon gains in representative landscapes of YNP. When summed across vegetation class areas, the predominance of evergreen forest and shrubland (sagebrush) cover was evident, with these two classes together accounting for 88% of the total annual NPP flux of 2.5 Tg C yr-1 (1 Tg = 1012 g) for the entire Yellowstone study area from 2000-2006. Most vegetation classes were estimated as net ecosystem sinks of atmospheric CO2 on annual basis, making the entire study area a moderate net sink of about +0.13 Tg C yr-1. This average sink value for forested lands nonetheless masks the contribution of areas burned during the 1988 wildfires, which were estimated as net sources of CO2 to the atmosphere, totaling to a NEP flux of -0.04 Tg C yr-1 for the entire burned area. Several areas burned in the 1988 wildfires were estimated to be among the lowest in overall yearly NPP, namely the Hellroaring Fire, Mink Fire, and Falls Fire areas. Rates of recovery for burned forest areas to pre-1988 biomass levels were estimated from a unique combination of remote sensing and CASA model predictions. Ecosystem production and carbon fluxes in the Greater Yellowstone Ecosystem (GYE) result from complex interactions between climate, forest age structure, and disturbance-recovery patterns of the landscape.

How to make complexity look simple? Conveying ecosystems restoration complexity for socio-economic research and public engagement

PubMed Central

Glenk, Klaus; Byg, Anja

2017-01-01

Ecosystems degradation represents one of the major global challenges at the present time, threating people’s livelihoods and well-being worldwide. Ecosystem restoration therefore seems no longer an option, but an imperative. Restoration challenges are such that a dialogue has begun on the need to re-shape restoration as a science. A critical aspect of that reshaping process is the acceptance that restoration science and practice needs to be coupled with socio-economic research and public engagement. This inescapably means conveying complex ecosystem’s information in a way that is accessible to the wider public. In this paper we take up this challenge with the ultimate aim of contributing to making a step change in science’s contribution to ecosystems restoration practice. Using peatlands as a paradigmatically complex ecosystem, we put in place a transdisciplinary process to articulate a description of the processes and outcomes of restoration that can be understood widely by the public. We provide evidence of the usefulness of the process and tools in addressing four key challenges relevant to restoration of any complex ecosystem: (1) how to represent restoration outcomes; (2) how to establish a restoration reference; (3) how to cope with varying restoration time-lags and (4) how to define spatial units for restoration. This evidence includes the way the process resulted in the creation of materials that are now being used by restoration practitioners for communication with the public and in other research contexts. Our main contribution is of an epistemological nature: while ecosystem services-based approaches have enhanced the integration of academic disciplines and non-specialist knowledge, this has so far only followed one direction (from the biophysical underpinning to the description of ecosystem services and their appreciation by the public). We propose that it is the mix of approaches and epistemological directions (including from the public to the biophysical parameters) what will make a definitive contribution to restoration practice. PMID:28753629

Decision support for sustainable forestry: enhancing the basic rational model.

Treesearch

H.R. Ekbia; K.M. Reynolds

2007-01-01

Decision-support systems (DSS) have been extensively used in the management of natural resources for nearly two decades. However, practical difficulties with the application of DSS in real-world situations have become increasingly apparent. Complexities of decisionmaking, encountered in the context of ecosystem management, are equally present in sustainable forestry....

Integrated modelling of ecosystem services and energy systems research

NASA Astrophysics Data System (ADS)

Agarwala, Matthew; Lovett, Andrew; Bateman, Ian; Day, Brett; Agnolucci, Paolo; Ziv, Guy

2016-04-01

The UK Government is formally committed to reducing carbon emissions and protecting and improving natural capital and the environment. However, actually delivering on these objectives requires an integrated approach to addressing two parallel challenges: de-carbonising future energy system pathways; and safeguarding natural capital to ensure the continued flow of ecosystem services. Although both emphasise benefiting from natural resources, efforts to connect natural capital and energy systems research have been limited, meaning opportunities to improve management of natural resources and meet society's energy needs could be missed. The ecosystem services paradigm provides a consistent conceptual framework that applies in multiple disciplines across the natural and economic sciences, and facilitates collaboration between them. At the forefront of the field, integrated ecosystem service - economy models have guided public- and private-sector decision making at all levels. Models vary in sophistication from simple spreadsheet tools to complex software packages integrating biophysical, GIS and economic models and draw upon many fields, including ecology, hydrology, geography, systems theory, economics and the social sciences. They also differ in their ability to value changes in natural capital and ecosystem services at various spatial and temporal scales. Despite these differences, current models share a common feature: their treatment of energy systems is superficial at best. In contrast, energy systems research has no widely adopted, unifying conceptual framework that organises thinking about key system components and interactions. Instead, the literature is organised around modelling approaches, including life cycle analyses, econometric investigations, linear programming and computable general equilibrium models. However, some consistencies do emerge. First, often contain a linear set of steps, from exploration to resource supply, fuel processing, conversion/generation, transmission, distribution, and finally, end energy use. Although each step clearly impacts upon natural capital, links to the natural environment are rarely identified or quantified within energy research. In short, the respective conceptual frameworks guiding ecosystem service and energy research are not well integrated. Major knowledge and research gaps appear at the system boundaries: while energy models may mention flows of residuals, exploring where exactly these flows enter the environment, and how they impact ecosystems and natural capital is often considered to be 'outside the system boundary'. While integrated modelling represents the frontier of ecosystem service research, current efforts largely ignore the future energy pathways set out by energy systems models and government carbon targets. This disconnect means that policy-oriented research on how best to (i) maintain natural capital and (ii) meet specific climate targets may be poorly aligned, or worse, offer conflicting advice. We present a re-imagined version of the ecosystem services conceptual framework, in which emphasis is placed on interactions between energy systems and the natural environment. Using the UK as a case study, we employ a recent integrated environmental-economic ecosystem service model, TIM, developed by Bateman et al (2014) and energy pathways developed by the UK Energy Research Centre and the UK Government Committee on Climate Change to illustrate how the new conceptual framework might apply in real world applications.

Experimental and numerical analysis of coastal protection provided by natural ecosystems

NASA Astrophysics Data System (ADS)

Maza, M.; Lara, J. L.; Losada, I. J.; Nepf, H. M.

2016-12-01

The risk of flooding and erosion is increasing for many coastal areas owing to global and regional changes in climate conditions together with increasing exposure and vulnerability. After hurricane Katrina (2005) and Sandy (2012) and the tsunami in Indonesia (2004), coastal managers have become interested in low environmental impact alternatives, or nature-based solutions, to protect the coast. Although capacity for coastal ecosystems to damp flow energy has been widely recognized, they have not been firmly considered in the portfolio of coastal protection options. This is mainly due to the complexity of flow-vegetation interaction and of quantifying the value of coastal protection provided by these ecosystems. This complex problem involves different temporal and spatial scales and disciplines, such as engineering, ecology and economics. This work aims to make a step forward in better understanding the physics involved in flow-vegetation interaction leading to new formulations and parameterizations to address some unsolved questions in literature: the representation of plants and field properties; the influence of wave parameters on the relevant processes; the role of the combined effect of waves and currents and the effect of extreme events on vegetation elements. The three main coastal vegetated ecosystems (seagrasses, saltmarshes and mangroves) are studied with an experimental and numerical approach. Experimental analysis is carried out using mimics and real vegetation, considering different flow and vegetation parameters and characterizing flow energy attenuation for the different scenarios. Numerical simulations are performed using 2-D and 3-D Navier-Stokes models in which the effect of vegetation is implemented and validated. These models are used to extend experimental results by simulating different vegetation distributions and analyzing variables such as high-spatial-resolution free surface and velocity data and forces exerted on vegetation elements.

A new framework to evaluate ecosystem health: a case study in the Wei River basin, China.

PubMed

Wu, Wei; Xu, Zongxue; Zhan, Chesheng; Yin, Xuwang; Yu, Songyan

2015-07-01

Due to the rapid growth of the population and the development of economies in the Guanzhong district, central China, the river ecosystem is gradually deteriorating, which makes it important to assess the aquatic ecosystem health and take measures to restore the damaged ecosystem. An index of catchment ecosystem health has been developed to assist large-scale management of watersheds by providing an integrated measure of ecosystem health, including aquatic and terrestrial ecosystem. Most researches focus on aquatic ecosystem or terrestrial ecosystem, but little research integrates both of them to assess the catchment ecosystem health. In this paper, we combine these two aspects into catchment ecosystem health. Ecosystem indicators derived from field samples and modeling are identified to integrate into ecosystem health. These included indicators of ecological landscape pattern (based on normalized difference vegetation index (NDVI), vegetation cover, dominance index, Shannon's diversity index, Shannon's evenness index, and fragmentation index), hydrology regime (based on 33 hydrological parameters), physical form condition (based on substrate, habitat complexity, velocity/depth regimes, bank stability, channel alteration), water quality (based on electrical conductivity (Cond), dissolved oxygen (DO), NH3_N, total nitrogen (TN), total phosphorus (TP), chemical oxygen demand-permanganate (CODMn)), and biological quality (based on fish abundance). The index of ecosystem health is applied in the Guanzhong district, and the ecosystem health was fair. The ecosystem health in the upstream to Linjiacun (U-L) and Linjiacun to Weijiabao (L-W) reaches was in good situation, while that in Weijiabao to Xianyang (W-X), Xianyang-Weijiabao (X-W), and Weijiabao to Tongguan (W-T) reaches was in fair situation. There is a trend that the ecosystem health in the upstream was better than that in the downstream. The ecosystem health assessment is expected to play a key role in future water and watershed management of the Wei River basin, or even the Yellow River basin.

Modelling impacts of offshore wind farms on trophic web: the Courseulles-sur-Mer case study

NASA Astrophysics Data System (ADS)

Raoux, Aurore; Pezy, Jean-Philippe; Dauvin, Jean-Claude; Tecchio, samuele; Degraer, Steven; Wilhelmsson, Dan; Niquil, Nathalie

2016-04-01

The French government is planning the construction of three offshore wind farms in Normandy. These offshore wind farms will integrate into an ecosystem already subject to a growing number of anthropogenic disturbances such as transportation, fishing, sediment deposit, and sediment extraction. The possible effects of this cumulative stressors on ecosystem functioning are still unknown, but they could impact their resilience, making them susceptible to changes from one stable state to another. Understanding the behaviour of these marine coastal complex systems is essential in order to anticipate potential state changes, and to implement conservation actions in a sustainable manner. Currently, there are no global and integrated studies on the effects of construction and exploitation of offshore wind farms. Moreover, approaches are generally focused on the conservation of some species or groups of species. Here, we develop a holistic and integrated view of ecosystem impacts through the use of trophic webs modelling tools. Trophic models describe the interaction between biological compartments at different trophic levels and are based on the quantification of flow of energy and matter in ecosystems. They allow the application of numerical methods for the characterization of emergent properties of the ecosystem, also called Ecological Network Analysis (ENA). These indices have been proposed as ecosystem health indicators as they have been demonstrated to be sensitive to different impacts on marine ecosystems. We present here in detail the strategy for analysing the potential environmental impacts of the construction of the Courseulles-sur-Mer offshore wind farm (Bay of Seine) such as the reef effect through the use of the Ecopath with Ecosim software. Similar Ecopath simulations will be made in the future on the Le Tréport offshore wind farm site. Results will contribute to a better knowledge of the impacts of the offshore wind farms on ecosystems. They also allow to define recommendations for environmental managers and industry in terms of monitoring the effects of Marine Renewable Energy, not only locally, but also on other sites, national and European levels. Finally, this approach could contribute to a better social acceptability of Marine Renewable Energy projects allowing a holistic vision of all pressures on ecosystems. Keywords: Marine Renewable Energies, trophic model Contact author: Aurore Raoux, UNICAEN, raoux.aurore@gmail.com

Incorporating grassland management in a global vegetation model: model description and evaluation at 11 eddy-covariance sites in Europe

NASA Astrophysics Data System (ADS)

Chang, J.; Viovy, N.; Vuichard, N.; Ciais, P.; Wang, T.; Cozic, A.; Lardy, R.; Graux, A.-I.; Klumpp, K.; Martin, R.; Soussana, J.-F.

2013-05-01

This study describes how management of grasslands is included in the ORCHIDEE process-based ecosystem model designed for large-scale applications, and how management affects modeled grassland-atmosphere CO2 fluxes. The new model, ORCHIDEE-GM (Grassland Management) is enabled with a management module inspired from a grassland model (PaSim, version 5.0), with two grassland management practices being considered, cutting and grazing, respectively. The evaluation of the results from ORCHIDEE compared with those of ORCHIDEE-GM at 11 European sites equipped with eddy covariance and biometric measurements, shows that ORCHIDEE-GM can capture realistically the cut-induced seasonal variation in biometric variables (LAI: Leaf Area Index; AGB: Aboveground Biomass) and in CO2 fluxes (GPP: Gross Primary Productivity; TER: Total Ecosystem Respiration; and NEE: Net Ecosystem Exchange). But improvements at grazing sites are only marginal in ORCHIDEE-GM, which relates to the difficulty in accounting for continuous grazing disturbance and its induced complex animal-vegetation interactions. Both NEE and GPP on monthly to annual timescales can be better simulated in ORCHIDEE-GM than in ORCHIDEE without management. ORCHIDEE-GM is capable to model the net carbon balance (NBP) of managed grasslands better than ORCHIDEE, because the management module allows to simulate the carbon fluxes of forage yield, herbage consumption, animal respiration and methane emissions.

The dynamics of mergers and acquisitions: ancestry as the seminal determinant

PubMed Central

Viegas, Eduardo; Cockburn, Stuart P.; Jensen, Henrik J.; West, Geoffrey B.

2014-01-01

Understanding the fundamental mechanisms behind the complex landscape of corporate mergers and acquisitions is of crucial importance to economies across the world. Adapting ideas from the fields of complexity and evolutionary dynamics to analyse business ecosystems, we show here that ancestry, i.e. the cumulative sum of historical mergers across all ancestors, is the key characteristic to company mergers and acquisitions. We verify this by comparing an agent-based model to an extensive range of business data, covering the period from the 1830s to the present day and a range of industries and geographies. This seemingly universal mechanism leads to imbalanced business ecosystems, with the emergence of a few very large, but sluggish ‘too big to fail’ entities, and very small, niche entities, thereby creating a paradigm where a configuration akin to effective oligopoly or monopoly is a likely outcome for free market systems. PMID:25383025

The dynamics of mergers and acquisitions: ancestry as the seminal determinant.

PubMed

Viegas, Eduardo; Cockburn, Stuart P; Jensen, Henrik J; West, Geoffrey B

2014-11-08

Understanding the fundamental mechanisms behind the complex landscape of corporate mergers and acquisitions is of crucial importance to economies across the world. Adapting ideas from the fields of complexity and evolutionary dynamics to analyse business ecosystems, we show here that ancestry, i.e. the cumulative sum of historical mergers across all ancestors, is the key characteristic to company mergers and acquisitions. We verify this by comparing an agent-based model to an extensive range of business data, covering the period from the 1830s to the present day and a range of industries and geographies. This seemingly universal mechanism leads to imbalanced business ecosystems, with the emergence of a few very large, but sluggish 'too big to fail' entities, and very small, niche entities, thereby creating a paradigm where a configuration akin to effective oligopoly or monopoly is a likely outcome for free market systems.

Like will to like: abundances of closely related species can predict susceptibility to intestinal colonization by pathogenic and commensal bacteria.

PubMed

Stecher, Bärbel; Chaffron, Samuel; Käppeli, Rina; Hapfelmeier, Siegfried; Freedrich, Susanne; Weber, Thomas C; Kirundi, Jorum; Suar, Mrutyunjay; McCoy, Kathy D; von Mering, Christian; Macpherson, Andrew J; Hardt, Wolf-Dietrich

2010-01-01

The intestinal ecosystem is formed by a complex, yet highly characteristic microbial community. The parameters defining whether this community permits invasion of a new bacterial species are unclear. In particular, inhibition of enteropathogen infection by the gut microbiota ( = colonization resistance) is poorly understood. To analyze the mechanisms of microbiota-mediated protection from Salmonella enterica induced enterocolitis, we used a mouse infection model and large scale high-throughput pyrosequencing. In contrast to conventional mice (CON), mice with a gut microbiota of low complexity (LCM) were highly susceptible to S. enterica induced colonization and enterocolitis. Colonization resistance was partially restored in LCM-animals by co-housing with conventional mice for 21 days (LCM(con21)). 16S rRNA sequence analysis comparing LCM, LCM(con21) and CON gut microbiota revealed that gut microbiota complexity increased upon conventionalization and correlated with increased resistance to S. enterica infection. Comparative microbiota analysis of mice with varying degrees of colonization resistance allowed us to identify intestinal ecosystem characteristics associated with susceptibility to S. enterica infection. Moreover, this system enabled us to gain further insights into the general principles of gut ecosystem invasion by non-pathogenic, commensal bacteria. Mice harboring high commensal E. coli densities were more susceptible to S. enterica induced gut inflammation. Similarly, mice with high titers of Lactobacilli were more efficiently colonized by a commensal Lactobacillus reuteri(RR) strain after oral inoculation. Upon examination of 16S rRNA sequence data from 9 CON mice we found that closely related phylotypes generally display significantly correlated abundances (co-occurrence), more so than distantly related phylotypes. Thus, in essence, the presence of closely related species can increase the chance of invasion of newly incoming species into the gut ecosystem. We provide evidence that this principle might be of general validity for invasion of bacteria in preformed gut ecosystems. This might be of relevance for human enteropathogen infections as well as therapeutic use of probiotic commensal bacteria.

How does complex terrain influence responses of carbon and water cycle processes to climate variability and climate change? (Invited)

NASA Astrophysics Data System (ADS)

Bond, B. J.; Peterson, K.; McKane, R.; Lajtha, K.; Quandt, D. J.; Allen, S. T.; Sell, S.; Daly, C.; Harmon, M. E.; Johnson, S. L.; Spies, T.; Sollins, P.; Abdelnour, A. G.; Stieglitz, M.

2010-12-01

We are pursuing the ambitious goal of understanding how complex terrain influences the responses of carbon and water cycle processes to climate variability and climate change. Our studies take place in H.J. Andrews Experimental Forest, an LTER (Long Term Ecological Research) site situated in Oregon’s central-western Cascade Range. Decades of long-term measurements and intensive research have revealed influences of topography on vegetation patterns, disturbance history, and hydrology. More recent research has shown surprising interactions between microclimates and synoptic weather patterns due to cold air drainage and pooling in mountain valleys. Using these data and insights, in addition to a recent LiDAR (Light Detection and Ranging) reconnaissance and a small sensor network, we are employing process-based models, including “SPA” (Soil-Plant-Atmosphere, developed by Mathew Williams of the University of Edinburgh), and “VELMA” (Visualizing Ecosystems for Land Management Alternatives, developed by Marc Stieglitz and colleagues of the Georgia Institute of Technology) to focus on two important features of mountainous landscapes: heterogeneity (both spatial and temporal) and connectivity (atmosphere-canopy-hillslope-stream). Our research questions include: 1) Do fine-scale spatial and temporal heterogeneity result in emergent properties at the basin scale, and if so, what are they? 2) How does connectivity across ecosystem components affect system responses to climate variability and change? Initial results show that for environmental drivers that elicit non-linear ecosystem responses on the plot scale, such as solar radiation, soil depth and soil water content, fine-scale spatial heterogeneity may produce unexpected emergent properties at larger scales. The results from such modeling experiments are necessarily a function of the supporting algorithms. However, comparisons based on models such as SPA and VELMA that operate at much different spatial scales (plots vs. hillslopes) and levels of biophysical organization (individual plants vs. aggregate plant biomass) can help us to understand how and why mountainous ecosystems may have distinctive responses to climate variability and climate change.

Complex interactions between autotrophs in shallow marine and freshwater ecosystems: implications for community responses to nutrient stress.

PubMed

Havens, K E; Hauxwell, J; Tyler, A C; Thomas, S; McGlathery, K J; Cebrian, J; Valiela, I; Steinman, A D; Hwang, S J

2001-01-01

The relative biomass of autotrophs (vascular plants, macroalgae, microphytobenthos, phytoplankton) in shallow aquatic ecosystems is thought to be controlled by nutrient inputs and underwater irradiance. Widely accepted conceptual models indicate that this is the case both in marine and freshwater systems. In this paper we examine four case studies and test whether these models generally apply. We also identify other complex interactions among the autotrophs that may influence ecosystem response to cultural eutrophication. The marine case studies focus on macroalgae and its interactions with sediments and vascular plants. The freshwater case studies focus on interactions between phytoplankton, epiphyton, and benthic microalgae. In Waquoit Bay, MA (estuary), controlled experiments documented that blooms of macroalgae were responsible for the loss of eelgrass beds at nutrient-enriched locations. Macroalgae covered eelgrass and reduced irradiance to the extent that the plants could not maintain net growth. In Hog Island Bay, VA (estuary), a dense lawn of macroalgae covered the bottom sediments. There was reduced sediment-water nitrogen exchange when the algae were actively growing and high nitrogen release during algal senescence. In Lakes Brobo (West Africa) and Okeechobee (FL), there were dramatic seasonal changes in the biomass and phosphorus content of planktonic versus attached algae, and these changes were coupled with changes in water level and abiotic turbidity. Deeper water and/or greater turbidity favored dominance by phytoplankton. In Lake Brobo there also was evidence that phytoplankton growth was stimulated following a die-off of vascular plants. The case studies from Waquoit Bay and Lake Okeechobee support conceptual models of succession from vascular plants to benthic algae to phytoplankton along gradients of increasing nutrients and decreasing under-water irradiance. The case studies from Hog Island Bay and Lake Brobo illustrate additional effects (modified sediment-water nutrient fluxes, allelopathy or nutrient release during plant senescence) that could play a role in ecosystem response to nutrient stress.

Statistical Physics Approaches to Microbial Ecology

NASA Astrophysics Data System (ADS)

Mehta, Pankaj

The unprecedented ability to quantitatively measure and probe complex microbial communities has renewed interest in identifying the fundamental ecological principles governing community ecology in microbial ecosystems. Here, we present work from our group and others showing how ideas from statistical physics can help us uncover these ecological principles. Two major lessons emerge from this work. First, large, ecosystems with many species often display new, emergent ecological behaviors that are absent in small ecosystems with just a few species. To paraphrase Nobel laureate Phil Anderson, ''More is Different'', especially in community ecology. Second, the lack of trophic layer separation in microbial ecology fundamentally distinguishes microbial ecology from classical paradigms of community ecology and leads to qualitative different rules for community assembly in microbes. I illustrate these ideas using both theoretical modeling and novel new experiments on large microbial ecosystems performed by our collaborators (Joshua Goldford and Alvaro Sanchez). Work supported by Simons Investigator in MMLS and NIH R35 R35 GM119461.

If you take stand, how can you manage an ecosystem? The complex art of raising a forest.

Treesearch

Sally Duncan

2000-01-01

Managing whole ecosystem is a concept gaining considerable acceptance among forest managers throughout the Northwest, but it does not have a clear or simple definition. Terminology and definitions can be confusing. Forests are complex places, formed by complex processes, and the moment we try to simplify, we are likely to damage the healthy functioning of...

Modeling the Personal Health Ecosystem.

PubMed

Blobel, Bernd; Brochhausen, Mathias; Ruotsalainen, Pekka

2018-01-01

Complex ecosystems like the pHealth one combine different domains represented by a huge variety of different actors (human beings, organizations, devices, applications, components) belonging to different policy domains, coming from different disciplines, deploying different methodologies, terminologies, and ontologies, offering different levels of knowledge, skills, and experiences, acting in different scenarios and accommodating different business cases to meet the intended business objectives. For correctly modeling such systems, a system-oriented, architecture-centric, ontology-based, policy-driven approach is inevitable, thereby following established Good Modeling Best Practices. However, most of the existing standards, specifications and tools for describing, representing, implementing and managing health (information) systems reflect the advancement of information and communication technology (ICT) represented by different evolutionary levels of data modeling. The paper presents a methodology for integrating, adopting and advancing models, standards, specifications as well as implemented systems and components on the way towards the aforementioned ultimate approach, so meeting the challenge we face when transforming health systems towards ubiquitous, personalized, predictive, preventive, participative, and cognitive health and social care.

Stochastic Spatial Models in Ecology: A Statistical Physics Approach

NASA Astrophysics Data System (ADS)

Pigolotti, Simone; Cencini, Massimo; Molina, Daniel; Muñoz, Miguel A.

2018-07-01

Ecosystems display a complex spatial organization. Ecologists have long tried to characterize them by looking at how different measures of biodiversity change across spatial scales. Ecological neutral theory has provided simple predictions accounting for general empirical patterns in communities of competing species. However, while neutral theory in well-mixed ecosystems is mathematically well understood, spatial models still present several open problems, limiting the quantitative understanding of spatial biodiversity. In this review, we discuss the state of the art in spatial neutral theory. We emphasize the connection between spatial ecological models and the physics of non-equilibrium phase transitions and how concepts developed in statistical physics translate in population dynamics, and vice versa. We focus on non-trivial scaling laws arising at the critical dimension D = 2 of spatial neutral models, and their relevance for biological populations inhabiting two-dimensional environments. We conclude by discussing models incorporating non-neutral effects in the form of spatial and temporal disorder, and analyze how their predictions deviate from those of purely neutral theories.

Stochastic Spatial Models in Ecology: A Statistical Physics Approach

NASA Astrophysics Data System (ADS)

Pigolotti, Simone; Cencini, Massimo; Molina, Daniel; Muñoz, Miguel A.

2017-11-01

Ecosystems display a complex spatial organization. Ecologists have long tried to characterize them by looking at how different measures of biodiversity change across spatial scales. Ecological neutral theory has provided simple predictions accounting for general empirical patterns in communities of competing species. However, while neutral theory in well-mixed ecosystems is mathematically well understood, spatial models still present several open problems, limiting the quantitative understanding of spatial biodiversity. In this review, we discuss the state of the art in spatial neutral theory. We emphasize the connection between spatial ecological models and the physics of non-equilibrium phase transitions and how concepts developed in statistical physics translate in population dynamics, and vice versa. We focus on non-trivial scaling laws arising at the critical dimension D = 2 of spatial neutral models, and their relevance for biological populations inhabiting two-dimensional environments. We conclude by discussing models incorporating non-neutral effects in the form of spatial and temporal disorder, and analyze how their predictions deviate from those of purely neutral theories.

Temporal variation of ecosystem scale methane emission from a boreal fen in relation to common model drivers

NASA Astrophysics Data System (ADS)

Rinne, J.; Tuittila, E. S.; Peltola, O.; Li, X.; Raivonen, M.; Alekseychik, P.; Haapanala, S.; Pihlatie, M.; Aurela, M.; Mammarella, I.; Vesala, T.

2017-12-01

Models for calculating methane emission from wetland ecosystems typically relate the methane emission to carbon dioxide assimilation. Other parameters that control emission in these models are e.g. peat temperature and water table position. Many of these relations are derived from spatial variation between chamber measurements by space-for-time approach. Continuous longer term ecosystem scale methane emission measurements by eddy covariance method provide us independent data to assess the validity of the relations derived by space-for-time approach.We have analyzed eleven-year methane flux data-set, measured at a boreal fen, together with data on environmental parameters and carbon dioxide exchange to assess the relations to typical model drivers. The data was obtained by the eddy covariance method at Siikaneva mire complex, Southern Finland, during 2005-2015. The methane flux showed seasonal cycles in methane emission, with strongest correlation with peat temperature at 35 cm depth. The temperature relation was exponential throughout the whole peat temperature range of 0-16°C. The methane emission normalized to remove temperature dependence showed a non-monotonous relation on water table and positive correlation with gross primary production (GPP). However, inclusion of these as explaining variables improved algorithm-measurement correlation only slightly, with r2=0.74 for exponential temperature dependent algorithm, r2=0.76 for temperature - water table algorithm, and r2=0.79 for temperature - GPP algorithm. The methane emission lagged behind net ecosystem exchange (NEE) and GPP by two to three weeks. Annual methane emission ranged from 8.3 to 14 gC m-2, and was 20 % of NEE and 2.8 % of GPP. The inter-annual variation of methane emission was of similar magnitude as that of GPP and ecosystem respiration (Reco), but much smaller than that of NEE. The interannual variability of June-September average methane emission correlated significantly with that of GPP indicating a close link between these two processes in boreal fen ecosystems.

Global meta-analysis of leaf area index in wetlands indicates uncertainties in understanding of their ecosystem function

NASA Astrophysics Data System (ADS)

Dronova, I.; Taddeo, S.; Foster, K.

2017-12-01

Projecting ecosystem responses to global change relies on the accurate understanding of properties governing their functions in different environments. An important variable in models of ecosystem function is canopy leaf area index (LAI; leaf area per unit ground area) declared as one of the Essential Climate Variables in the Global Climate Observing System and extensively measured in terrestrial landscapes. However, wetlands have been largely under-represented in these efforts, which globally limits understanding of their contribution to carbon sequestration, climate regulation and resilience to natural and anthropogenic disturbances. This study provides a global synthesis of >350 wetland-specific LAI observations from 182 studies and compares LAI among wetland ecosystem and vegetation types, biomes and measurement approaches. Results indicate that most wetland types and even individual locations show a substantial local dispersion of LAI values (average coefficient of variation 65%) due to heterogeneity of environmental properties and vegetation composition. Such variation indicates that mean LAI values may not sufficiently represent complex wetland environments, and the use of this index in ecosystem function models needs to incorporate within-site variation in canopy properties. Mean LAI did not significantly differ between direct and indirect measurement methods on a pooled global sample; however, within some of the specific biomes and wetland types significant contrasts between these approaches were detected. These contrasts highlight unique aspects of wetland vegetation physiology and canopy structure affecting measurement principles that need to be considered in generalizing canopy properties in ecosystem models. Finally, efforts to assess wetland LAI using remote sensing strongly indicate the promise of this technology for cost-effective regional-scale modeling of canopy properties similar to terrestrial systems. However, such efforts urgently require more rigorous corrections for three-dimensional contributions of non-canopy material and non-vegetated surfaces to wetland canopy reflectance.

The sensitivity of ecosystem service models to choices of input data and spatial resolution

USGS Publications Warehouse

Bagstad, Kenneth J.; Cohen, Erika; Ancona, Zachary H.; McNulty, Steven; Sun, Ge

2018-01-01

Although ecosystem service (ES) modeling has progressed rapidly in the last 10–15 years, comparative studies on data and model selection effects have become more common only recently. Such studies have drawn mixed conclusions about whether different data and model choices yield divergent results. In this study, we compared the results of different models to address these questions at national, provincial, and subwatershed scales in Rwanda. We compared results for carbon, water, and sediment as modeled using InVEST and WaSSI using (1) land cover data at 30 and 300 m resolution and (2) three different input land cover datasets. WaSSI and simpler InVEST models (carbon storage and annual water yield) were relatively insensitive to the choice of spatial resolution, but more complex InVEST models (seasonal water yield and sediment regulation) produced large differences when applied at differing resolution. Six out of nine ES metrics (InVEST annual and seasonal water yield and WaSSI) gave similar predictions for at least two different input land cover datasets. Despite differences in mean values when using different data sources and resolution, we found significant and highly correlated results when using Spearman's rank correlation, indicating consistent spatial patterns of high and low values. Our results confirm and extend conclusions of past studies, showing that in certain cases (e.g., simpler models and national-scale analyses), results can be robust to data and modeling choices. For more complex models, those with different output metrics, and subnational to site-based analyses in heterogeneous environments, data and model choices may strongly influence study findings.

A dynamic ecosystem growth model for forests at high complexity structure

NASA Astrophysics Data System (ADS)

Collalti, A.; Perugini, L.; Chiti, T.; Matteucci, G.; Oriani, A.; Santini, M.; Papale, D.; Valentini, R.

2012-04-01

Forests ecosystem play an important role in carbon cycle, biodiversity conservation and for other ecosystem services and changes in their structure and status perturb a delicate equilibrium that involves not only vegetation components but also biogeochemical cycles and global climate. The approaches to determine the magnitude of these effects are nowadays various and one of those include the use of models able to simulate structural changes and the variations in forests yield The present work shows the development of a forest dynamic model, on ecosystem spatial scale using the well known light use efficiency to determine Gross Primary Production. The model is predictive and permits to simulate processes that determine forest growth, its dynamic and the effects of forest management using eco-physiological parameters easy to be assessed and to be measured. The model has been designed to consider a tri-dimensional cell structure composed by different vertical layers depending on the forest type that has to be simulated. These features enable the model to work on multi-layer and multi-species forest types, typical of Mediterranean environment, at the resolution of one hectare and at monthly time-step. The model simulates, for each layer, a value of available Photosynthetic Active Radiation (PAR) through Leaf Area Index, Light Extinction Coefficient and cell coverage, the transpiration rate that is closely linked to the intercepted light and the evaporation from soil. Using this model it is possible to evaluate the possible impacts of climate change on forests that may result in decrease or increase of productivity as well as the feedback of one or more dominated layers in terms of CO2 uptake in a forest stand and the effects of forest management activities during the forest harvesting cycle. The model has been parameterised, validated and applied in a multi-layer, multi-age and multi-species Italian turkey oak forest (Q. cerris L., C. betulus L. and C. avellana L.) where the medium-term (10 years) development of forest parameters were simulated. The results obtained for net primary production and for stem, root and foliage compartments as well as for forest structure i.e. Diameter at Breast Height, height and canopy cover are in good accordance with field data (R2>0.95). These results show how the model is able to predict forest yield as well as forest dynamic with good accuracy and encourage testing the model capability on other sites with a more complex forest structure and for long-time period with an higher spatial resolution.

Disturbance Regimes Predictably Alter Diversity in an Ecologically Complex Bacterial System

PubMed Central

Scholz, Monika; Hutchison, Alan L.; Dinner, Aaron R.; Gilbert, Jack A.; Coleman, Maureen L.

2016-01-01

ABSTRACT Diversity is often associated with the functional stability of ecological communities from microbes to macroorganisms. Understanding how diversity responds to environmental perturbations and the consequences of this relationship for ecosystem function are thus central challenges in microbial ecology. Unimodal diversity-disturbance relationships, in which maximum diversity occurs at intermediate levels of disturbance, have been predicted for ecosystems where life history tradeoffs separate organisms along a disturbance gradient. However, empirical support for such peaked relationships in macrosystems is mixed, and few studies have explored these relationships in microbial systems. Here we use complex microbial microcosm communities to systematically determine diversity-disturbance relationships over a range of disturbance regimes. We observed a reproducible switch between community states, which gave rise to transient diversity maxima when community states were forced to mix. Communities showed reduced compositional stability when diversity was highest. To further explore these dynamics, we formulated a simple model that reveals specific regimes under which diversity maxima are stable. Together, our results show how both unimodal and non-unimodal diversity-disturbance relationships can be observed as a system switches between two distinct microbial community states; this process likely occurs across a wide range of spatially and temporally heterogeneous microbial ecosystems. PMID:27999158

Multiscale approach to pest insect monitoring: random walks, pattern formation, synchronization, and networks.

PubMed

Petrovskii, Sergei; Petrovskaya, Natalia; Bearup, Daniel

2014-09-01

Pest insects pose a significant threat to food production worldwide resulting in annual losses worth hundreds of billions of dollars. Pest control attempts to prevent pest outbreaks that could otherwise destroy a sward. It is good practice in integrated pest management to recommend control actions (usually pesticides application) only when the pest density exceeds a certain threshold. Accurate estimation of pest population density in ecosystems, especially in agro-ecosystems, is therefore very important, and this is the overall goal of the pest insect monitoring. However, this is a complex and challenging task; providing accurate information about pest abundance is hardly possible without taking into account the complexity of ecosystems' dynamics, in particular, the existence of multiple scales. In the case of pest insects, monitoring has three different spatial scales, each of them having their own scale-specific goal and their own approaches to data collection and interpretation. In this paper, we review recent progress in mathematical models and methods applied at each of these scales and show how it helps to improve the accuracy and robustness of pest population density estimation. Copyright © 2014 Elsevier B.V. All rights reserved.

Impact of the Spatial Arrangement of Agricultural Land Use on Ecosystems Services and Peri-Urban Livelihoods at the Landscape Scale.

NASA Astrophysics Data System (ADS)

Inkoom, J. N.; Fürst, C.

2014-12-01

The relationship between agricultural land uses (ALU) and their impact on ecosystems services (ES) including biodiversity conservation is complex. This complexity has been augmented by isolated research on the impact of ALU on the landscape's capacity to provide ES in most climatically vulnerable areas of Sub-Saharan Africa. Though a considerable number of studies emphasise the nexus between specific land use types and their impact on ES, a sufficient modelling basis for an empirical consideration of spatial interactions between different agricultural land uses at the landscape scale within peri-urban areas in Sub-Saharan Africa is consistently missing. The need to assess and address significant issues regarding size, shape, spatial location, and interactivity of different land use patches in assessing land use interactions and their impact on ecosystem service provision necessitated this investigation. To formulate a methodology to correspond to this complexity, ES obtained from a characteristically agricultural and urbanizing landscapes were mapped using analytical hierarchical processes and management expert approaches. Further, landscape metrics and mean enrichment factor approaches are explored as neighbourhood assessment tools aimed at assessing the mutual impact gradient of agricultural and adjacent urban land uses on ES provision. Implementation is undertaken in GISCAME using a 2012 rapideye image classification and primary data collected on selected ES from local farmers within the VEA catchment of Upper East, Ghana. The outcome aims to provide the understanding of expected trade-offs and synergies varying ALU could pose to current and potential ES provision within urbanizing landscapes. Policy implications for observed trade-offs and synergies of ALU interaction on ES, rural livelihoods, and food security are communicated to farmers and decision makers. Keywords: Agricultural land use, neighbourhood interaction, ecosystems services, livelihoods, GISCAME.

Spatial structure of soil properties at different scales of Mt. Kilimanjaro, Tanzania

NASA Astrophysics Data System (ADS)

Kühnel, Anna; Huwe, Bernd

2013-04-01

Soils of tropical mountain ecosystems provide important ecosystem services like water and carbon storage, water filtration and erosion control. As these ecosystems are threatened by global warming and the conversion of natural to human-modified landscapes, it is important to understand the implications of these changes. Within the DFG Research Unit "Kilimanjaro ecosystems under global change: Linking biodiversity, biotic interactions and biogeochemical ecosystem processes", we study the spatial heterogeneity of soils and the available water capacity for different land use systems. In the savannah zone of Mt. Kilimanjaro, maize fields are compared to natural savannah ecosystems. In the lower montane forest zone, coffee plantations, traditional home gardens, grasslands and natural forests are studied. We characterize the soils with respect to soil hydrology, emphasizing on the spatial variability of soil texture and bulk density at different scales. Furthermore soil organic carbon and nitrogen, cation exchange capacity and the pH-value are measured. Vis/Nir-Spectroscopy is used to detect small scale physical and chemical heterogeneity within soil profiles, as well as to get information of soil properties on a larger scale. We aim to build a spectral database for these soil properties for the Kilimanjaro region in order to get rapid information for geostatistical analysis. Partial least square regression with leave one out cross validation is used for model calibration. Results for silt and clay content, as well as carbon and nitrogen content are promising, with adjusted R² ranging from 0.70 for silt to 0.86 for nitrogen. Furthermore models for other nutrients, cation exchange capacity and available water capacity will be calibrated. We compare heterogeneity within and across the different ecosystems and state that spatial structure characteristics and complexity patterns in soil parameters can be quantitatively related to biodiversity and functional diversity parameters.

Aerosols in atmospheric chemistry and biogeochemical cycles of nutrients

NASA Astrophysics Data System (ADS)

Kanakidou, Maria; Myriokefalitakis, Stelios; Tsigaridis, Kostas

2018-06-01

Atmospheric aerosols have complex and variable compositions and properties. While scientific interest is centered on the health and climatic effects of atmospheric aerosols, insufficient attention is given to their involvement in multiphase chemistry that alters their contribution as carriers of nutrients in ecosystems. However, there is experimental proof that the nutrient equilibria of both land and marine ecosystems have been disturbed during the Anthropocene period. This review study first summarizes our current understanding of aerosol chemical processing in the atmosphere as relevant to biogeochemical cycles. Then it binds together results of recent modeling studies based on laboratory and field experiments, focusing on the organic and dust components of aerosols that account for multiphase chemistry, aerosol ageing in the atmosphere, nutrient (N, P, Fe) emissions, atmospheric transport, transformation and deposition. The human-driven contribution to atmospheric deposition of these nutrients, derived by global simulations using past and future anthropogenic emissions of pollutants, is put into perspective with regard to potential changes in nutrient limitations and biodiversity. Atmospheric deposition of nutrients has been suggested to result in human-induced ecosystem limitations with regard to specific nutrients. Such modifications favor the development of certain species against others and affect the overall functioning of ecosystems. Organic forms of nutrients are found to contribute to the atmospheric deposition of the nutrients N, P and Fe by 20%–40%, 35%–45% and 7%–18%, respectively. These have the potential to be key components of the biogeochemical cycles since there is initial proof of their bioavailability to ecosystems. Bioaerosols have been found to make a significant contribution to atmospheric sources of N and P, indicating potentially significant interactions between terrestrial and marine ecosystems. These results deserve further experimental and modeling studies to reduce uncertainties and understand the feedbacks induced by atmospheric deposition of nutrients to ecosystems.

Cold air drainage flows subsidize montane valley ecosystem productivity.

PubMed

Novick, Kimberly A; Oishi, A Christopher; Miniat, Chelcy Ford

2016-12-01

In mountainous areas, cold air drainage from high to low elevations has pronounced effects on local temperature, which is a critical driver of many ecosystem processes, including carbon uptake and storage. Here, we leverage new approaches for interpreting ecosystem carbon flux observations in complex terrain to quantify the links between macro-climate condition, drainage flows, local microclimate, and ecosystem carbon cycling in a southern Appalachian valley. Data from multiple long-running climate stations and multiple eddy covariance flux towers are combined with simple models for ecosystem carbon fluxes. We show that cold air drainage into the valley suppresses local temperature by several degrees at night and for several hours before and after sunset, leading to reductions in growing season respiration on the order of ~8%. As a result, we estimate that drainage flows increase growing season and annual net carbon uptake in the valley by >10% and >15%, respectively, via effects on microclimate that are not be adequately represented in regional- and global-scale terrestrial ecosystem models. Analyses driven by chamber-based estimates of soil and plant respiration reveal cold air drainage effects on ecosystem respiration are dominated by reductions to the respiration of aboveground biomass. We further show that cold air drainage proceeds more readily when cloud cover and humidity are low, resulting in the greatest enhancements to net carbon uptake in the valley under clear, cloud-free (i.e., drought-like) conditions. This is a counterintuitive result that is neither observed nor predicted outside of the valley, where nocturnal temperature and respiration increase during dry periods. This result should motivate efforts to explore how topographic flows may buffer eco-physiological processes from macroscale climate change. © 2016 John Wiley & Sons Ltd.

COORDINATING, COMMUNICATING AND PERFORMING COMPLEX RESEARCH THAT IDENTIFIES VULNERABLE STREAM ECOSYSTEM IN THE MID-ATLANTIC REGION

EPA Science Inventory

The USEPA's Regional Vulnerability Assessment (ReVA) program was created to advance the scientific basis for protecting vulnerable ecosystems at a regional scale. As a first step, the ReVa program will coordinate, communicate and perform complex research that will identify vulner...

Resilience to stress and disturbance, and resistance to Bromus tectorum LBromus tectorum L. invasion in cold desert shrublands of western North America

Treesearch

Jeanne C. Chambers; Bethany A. Bradley; Cynthia S. Brown; Carla D' Antonio; Matthew J. Germino; James B. Grace; Stuart P. Hardegree; Richard F. Miller; David A. Pyke

2014-01-01

Alien grass invasions in arid and semi-arid ecosystems are resulting in grass-fire cycles and ecosystem-level transformations that severely diminish ecosystem services. Our capacity to address the rapid and complex changes occurring in these ecosystems can be enhanced by developing an understanding of the environmental factors and ecosystem attributes that determine...

Subsidy or subtraction: how do terrestrial inputs influence consumer production in lakes?

USGS Publications Warehouse

Jones, Stuart E.; Solomon, Christopher T.; Weidel, Brian C.

2012-01-01

Cross-ecosystem fluxes are ubiquitous in food webs and are generally thought of as subsidies to consumer populations. Yet external or allochthonous inputs may in fact have complex and habitat-specific effects on recipient ecosystems. In lakes, terrestrial inputs of organic carbon contribute to basal resource availability, but can also reduce resource availability via shading effects on phytoplankton and periphyton. Terrestrial inputs might therefore either subsidise or subtract from consumer production. We developed and parameterised a simple model to explore this idea. The model estimates basal resource supply and consumer production given lake-level characteristics including total phosphorus (TP) and dissolved organic carbon (DOC) concentration, and consumer-level characteristics including resource preferences and growth efficiencies. Terrestrial inputs diminished primary production and total basal resource supply at the whole-lake level, except in ultra-oligotrophic systems. However, this system-level generalisation masked complex habitat-specific effects. In the pelagic zone, dissolved and particulate terrestrial carbon inputs were available to zooplankton via several food web pathways. Consequently, zooplankton production usually increased with terrestrial inputs, even as total whole-lake resource availability decreased. In contrast, in the benthic zone the dominant, dissolved portion of the terrestrial carbon load had predominantly negative effects on resource availability via shading of periphyton. Consequently, terrestrial inputs always decreased zoobenthic production except under extreme and unrealistic parameterisations of the model. Appreciating the complex and habitat-specific effects of allochthonous inputs may be essential for resolving the effects of cross-habitat fluxes on consumers in lakes and other food webs.

Columbia River Estuary ecosystem classification—Concept and application

USGS Publications Warehouse

Simenstad, Charles A.; Burke, Jennifer L.; O'Connor, Jim E.; Cannon, Charles; Heatwole, Danelle W.; Ramirez, Mary F.; Waite, Ian R.; Counihan, Timothy D.; Jones, Krista L.

2011-01-01

This document describes the concept, organization, and application of a hierarchical ecosystem classification that integrates saline and tidal freshwater reaches of estuaries in order to characterize the ecosystems of large flood plain rivers that are strongly influenced by riverine and estuarine hydrology. We illustrate the classification by applying it to the Columbia River estuary (Oregon-Washington, USA), a system that extends about 233 river kilometers (rkm) inland from the Pacific Ocean. More than three-quarters of this length is tidal freshwater. The Columbia River Estuary Ecosystem Classification ("Classification") is based on six hierarchical levels, progressing from the coarsest, regional scale to the finest, localized scale: (1) Ecosystem Province; (2) Ecoregion; (3) Hydrogeomorphic Reach; (4) Ecosystem Complex; (5) Geomorphic Catena; and (6) Primary Cover Class. We define and map Levels 1-3 for the entire Columbia River estuary with existing geospatial datasets, and provide examples of Levels 4-6 for one hydrogeomorphic reach. In particular, three levels of the Classification capture the scales and categories of ecosystem structure and processes that are most tractable to estuarine research, monitoring, and management. These three levels are the (1) eight hydrogeomorphic reaches that embody the formative geologic and tectonic processes that created the existing estuarine landscape and encompass the influence of the resulting physiography on interactions between fluvial and tidal hydrology and geomorphology across 230 kilometers (km) of estuary, (2) more than 15 ecosystem complexes composed of broad landforms created predominantly by geologic processes during the Holocene, and (3) more than 25 geomorphic catenae embedded within ecosystem complexes that represent distinct geomorphic landforms, structures, ecosystems, and habitats, and components of the estuarine landscape most likely to change over short time periods.

The response of tropical rainforests to drought-lessons from recent research and future prospects.

PubMed

Bonal, Damien; Burban, Benoit; Stahl, Clément; Wagner, Fabien; Hérault, Bruno

We review the recent findings on the influence of drought on tree mortality, growth or ecosystem functioning in tropical rainforests. Drought plays a major role in shaping tropical rainforests and the response mechanisms are highly diverse and complex. The numerous gaps identified here require the international scientific community to combine efforts in order to conduct comprehensive studies in tropical rainforests on the three continents. These results are essential to simulate the future of these ecosystems under diverse climate scenarios and to predict the future of the global earth carbon balance. Tropical rainforest ecosystems are characterized by high annual rainfall. Nevertheless, rainfall regularly fluctuates during the year and seasonal soil droughts do occur. Over the past decades, a number of extreme droughts have hit tropical rainforests, not only in Amazonia but also in Asia and Africa. The influence of drought events on tree mortality and growth or on ecosystem functioning (carbon and water fluxes) in tropical rainforest ecosystems has been studied intensively, but the response mechanisms are complex. Herein, we review the recent findings related to the response of tropical forest ecosystems to seasonal and extreme droughts and the current knowledge about the future of these ecosystems. This review emphasizes the progress made over recent years and the importance of the studies conducted under extreme drought conditions or in through-fall exclusion experiments in understanding the response of these ecosystems. It also points to the great diversity and complexity of the response of tropical rainforest ecosystems to drought. The numerous gaps identified here require the international scientific community to combine efforts in order to conduct comprehensive studies in tropical forest regions. These results are essential to simulate the future of these ecosystems under diverse climate scenarios and to predict the future of the global earth carbon balance.

"I have a connection!": The situated sense-making of an elementary student about the role of water in modeled vs. experienced ecosystems

NASA Astrophysics Data System (ADS)

Roberts, Lisa Elisabeth N.

Current policy and research have led the field of science education towards a model of "science as practice." In the past decade, several research programs on model-based reasoning practices in education have articulated key dimensions of practice, including constructing and defending models, comparing models to empirical data, using representations to identify patterns in data and use those as inscriptions to buttress arguments. This study presents a detailed case of how the use of a physical microcosm and children's self-directed representations of an ecosystem constrained and afforded student sense-making in an urban elementary classroom. The case analyzed the experiences of a 10-year old fifth grade student, Jorge, and the variation in his expressed understanding of ecosystems as he interacted with academic tasks, along with models and representations, to design, observe and explain an ecological microcosm. The study used a conceptual framework that brings together theories of situated cognition and Doyle's work on academic task to explain how and why Jorge's perception and communication of dimensions of ecosystem structure, function, and behavior appear to "come in and out of focus," influenced by the affordances of the tools and resources available, the academic task as given by the teacher, and Jorge's own experiences and knowledge of phenomena related to ecosystems. Findings from this study suggest that elementary students' ability or inability to address particular ecological concepts in a given task relate less to gaps in their understanding and more to the structure of academic tasks and learning contexts. The process of a student interacting with curriculum follows a dynamic trajectory and leads to emergent outcomes. As a result of the complex interactions of task, tools, and his own interests and agency, Jorge's attunement to the role of water in ecosystems comes in and out of focus throughout the unit. The instructional constraint of needing to integrate the FOSS Water Cycle curriculum into the Bottle Biology Project became an affordance for Jorge to ask questions, observe, and theorize about the role of water and the water cycle in an ecosystem. The practice of modeling a closed ecosystem made salient to Jorge the boundaries of a system and the conservation of water within that system. The closed ecosystem model also presented constraints to students' sense making about the role of interactions when students lack domain knowledge in ecology. Relying on students' own talk, photographs and representations as explanations of phenomena in the Bio Bottle, without establishing norms of representational conventions and communication, resulted in missed opportunities for Jorge to reinforce his sense making during the activity and to develop conventions of scientific representation. Findings from this study can be used to inform the design and implementation of learning environments and curricular activities for elementary and middle school students that address all three dimensions of the Next Generation Science Standards: a) developing conceptual understanding of key concepts in the domain of ecology, b) the cross-cutting concept of systems, and c) multiple practices that ecologists use in developing and evaluating models that explain ecosystem structures, functions, and change over time.

Validation and application of a forest gap model to the southern Rocky Mountains

Treesearch

Adrianna C. Foster; Jacquelyn K. Shuman; Herman H. Shugart; Kathleen A. Dwire; Paula J. Fornwalt; Jason Sibold; Jose Negron

2017-01-01

Rocky Mountain forests are highly important for their part in carbon cycling and carbon storage as well as ecosystem services such as water retention and storage and recreational values. These forests are shaped by complex interactions among vegetation, climate, and disturbances. Thus, climate change and shifting disturbances may lead to significant changes in species...

Confronting challenges to economic analysis of biological invasions in forests

Treesearch

Thomas P Holmes

2010-01-01

Biological invasions of forests by non-indigenous organisms present a complex, persistent, and largely irreversible threat to forest ecosystems around the globe. Rigorous assessments of the economic impacts of introduced species, at a national scale, are needed to provide credible information to policy makers. It is proposed here that microeconomic models of damage due...

The Effect of Response Time on Conjoint Analysis Estimates of Rainforest Protection Values

Treesearch

Thomas Holmes; Keith Alger; Christian Zinkhan; D. Evan Mercer

1998-01-01

This paper reports the first estimutes of willingness to pay (WTP) for rain forest protection in the threatened Atlantic Coastal Forest ecosystem in northeastern Brazil. Conjoint analysis data were collected from Brazilian tourists for recreational bundles with complex prices. An ordered probit model with time-varying parameters and heteroskedastic errors was...

Stand structure influences nekton community composition and provides protection from natural disturbance in Micronesian mangroves

Treesearch

Richard A. MacKenzie; Nicole Cormier

2012-01-01

Structurally complex mangrove roots are thought to provide foraging habitat, predation refugia, and typhoon protection for resident fish, shrimp, and crabs. The spatially compact nature of Micronesian mangroves results in model ecosystems to test these ideas. Tidal creek nekton assemblages were compared among mangrove forests impacted by Typhoon Sudal and differing in...

DEVELOPMENT AND TEST APPLICATION A SCREENING-LEVEL MERCURY FATE MODEL AND TOOL FOR EVALUATING WILDLIFE EXPOSURE RISK FOR SURFACE WATERS WITH MERCURY-CONTAMINATED SEDIMENTS (SERAFM)

EPA Science Inventory

Complex chemical cycling of mercury in aquatic ecosystems means that tracing the linkage between anthropogenic and natural loadings of mercury to watersheds and water bodies and associated concentrations in the environment are difficult to establish without the assistance of nume...

A Comparison of Simulated and Field-Derived Leaf Area Index (LAI) and Canopy Height Values from Four Forest Complexes in the Southeastern USA

EPA Science Inventory

Vegetative leaf area is a critical input to models that simulate human and ecosystem exposure to atmospheric pollutants. Leaf area index (LAI) can be measured in the field or numerically simulated, but all contain some inherent uncertainty that is passed to the exposure assessmen...

Seeing the future impacts of climate change and forest management: a landscape visualization system for forest managers

Treesearch

Eric J. Gustafson; Melissa Lucash; Johannes Liem; Helen Jenny; Rob Scheller; Kelly Barrett; Brian R. Sturtevant

2016-01-01

Forest managers are increasingly considering how climate change may alter forests' capacity to provide ecosystem goods and services. But identifying potential climate change effects on forests is difficult because interactions among forest growth and mortality, climate change, management, and disturbances are complex and uncertain. Although forest landscape models...

Could ecosystem management provide a new framework for Alzheimer's disease?

PubMed

Hubin, Ellen; Vanschoenwinkel, Bram; Broersen, Kerensa; De Deyn, Peter P; Koedam, Nico; van Nuland, Nico A; Pauwels, Kris

2016-01-01

Alzheimer's disease (AD) is a progressive neurodegenerative brain disorder that involves a plethora of molecular pathways. In the context of therapeutic treatment and biomarker profiling, the amyloid-beta (Aβ) peptide constitutes an interesting research avenue that involves interactions within a complex mixture of Aβ alloforms and other disease-modifying factors. Here, we explore the potential of an ecosystem paradigm as a novel way to consider AD and Aβ dynamics in particular. We discuss the example that the complexity of the Aβ network not only exhibits interesting parallels with the functioning of complex systems such as ecosystems but that this analogy can also provide novel insights into the neurobiological phenomena in AD and serve as a communication tool. We propose that combining network medicine with general ecosystem management principles could be a new and holistic approach to understand AD pathology and design novel therapies. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Parameterization of aquatic ecosystem functioning and its natural variation: Hierarchical Bayesian modelling of plankton food web dynamics

NASA Astrophysics Data System (ADS)

Norros, Veera; Laine, Marko; Lignell, Risto; Thingstad, Frede

2017-10-01

Methods for extracting empirically and theoretically sound parameter values are urgently needed in aquatic ecosystem modelling to describe key flows and their variation in the system. Here, we compare three Bayesian formulations for mechanistic model parameterization that differ in their assumptions about the variation in parameter values between various datasets: 1) global analysis - no variation, 2) separate analysis - independent variation and 3) hierarchical analysis - variation arising from a shared distribution defined by hyperparameters. We tested these methods, using computer-generated and empirical data, coupled with simplified and reasonably realistic plankton food web models, respectively. While all methods were adequate, the simulated example demonstrated that a well-designed hierarchical analysis can result in the most accurate and precise parameter estimates and predictions, due to its ability to combine information across datasets. However, our results also highlighted sensitivity to hyperparameter prior distributions as an important caveat of hierarchical analysis. In the more complex empirical example, hierarchical analysis was able to combine precise identification of parameter values with reasonably good predictive performance, although the ranking of the methods was less straightforward. We conclude that hierarchical Bayesian analysis is a promising tool for identifying key ecosystem-functioning parameters and their variation from empirical datasets.

An Ontology for Modeling Complex Inter-relational Organizations

NASA Astrophysics Data System (ADS)

Wautelet, Yves; Neysen, Nicolas; Kolp, Manuel

This paper presents an ontology for organizational modeling through multiple complementary aspects. The primary goal of the ontology is to dispose of an adequate set of related concepts for studying complex organizations involved in a lot of relationships at the same time. In this paper, we define complex organizations as networked organizations involved in a market eco-system that are playing several roles simultaneously. In such a context, traditional approaches focus on the macro analytic level of transactions; this is supplemented here with a micro analytic study of the actors' rationale. At first, the paper overviews enterprise ontologies literature to position our proposal and exposes its contributions and limitations. The ontology is then brought to an advanced level of formalization: a meta-model in the form of a UML class diagram allows to overview the ontology concepts and their relationships which are formally defined. Finally, the paper presents the case study on which the ontology has been validated.

The Composition of Camembert Cheese-Ripening Cultures Modulates both Mycelial Growth and Appearance

PubMed Central

Lessard, Marie-Hélène; Bélanger, Gaétan; St-Gelais, Daniel

2012-01-01

The fungal microbiota of bloomy-rind cheeses, such as Camembert, forms a complex ecosystem that has not been well studied, and its monitoring during the ripening period remains a challenge. One limitation of enumerating yeasts and molds on traditional agar media is that hyphae are multicellular structures, and colonies on a petri dish rarely develop from single cells. In addition, fungi tend to rapidly invade agar surfaces, covering small yeast colonies and resulting in an underestimation of their number. In this study, we developed a real-time quantitative PCR (qPCR) method using TaqMan probes to quantify a mixed fungal community containing the most common dairy yeasts and molds: Penicillium camemberti, Geotrichum candidum, Debaryomyces hansenii, and Kluyveromyces lactis on soft-cheese model curds (SCMC). The qPCR method was optimized and validated on pure cultures and used to evaluate the growth dynamics of a ripening culture containing P. camemberti, G. candidum, and K. lactis on the surface of the SCMC during a 31-day ripening period. The results showed that P. camemberti and G. candidum quickly dominated the ecosystem, while K. lactis remained less abundant. When added to this ecosystem, D. hansenii completely inhibited the growth of K. lactis in addition to reducing the growth of the other fungi. This result was confirmed by the decrease in the mycelium biomass on SCMC. This study compares culture-dependent and qPCR methods to successfully quantify complex fungal microbiota on a model curd simulating Camembert-type cheese. PMID:22247164

The composition of Camembert cheese-ripening cultures modulates both mycelial growth and appearance.

PubMed

Lessard, Marie-Hélène; Bélanger, Gaétan; St-Gelais, Daniel; Labrie, Steve

2012-03-01

The fungal microbiota of bloomy-rind cheeses, such as Camembert, forms a complex ecosystem that has not been well studied, and its monitoring during the ripening period remains a challenge. One limitation of enumerating yeasts and molds on traditional agar media is that hyphae are multicellular structures, and colonies on a petri dish rarely develop from single cells. In addition, fungi tend to rapidly invade agar surfaces, covering small yeast colonies and resulting in an underestimation of their number. In this study, we developed a real-time quantitative PCR (qPCR) method using TaqMan probes to quantify a mixed fungal community containing the most common dairy yeasts and molds: Penicillium camemberti, Geotrichum candidum, Debaryomyces hansenii, and Kluyveromyces lactis on soft-cheese model curds (SCMC). The qPCR method was optimized and validated on pure cultures and used to evaluate the growth dynamics of a ripening culture containing P. camemberti, G. candidum, and K. lactis on the surface of the SCMC during a 31-day ripening period. The results showed that P. camemberti and G. candidum quickly dominated the ecosystem, while K. lactis remained less abundant. When added to this ecosystem, D. hansenii completely inhibited the growth of K. lactis in addition to reducing the growth of the other fungi. This result was confirmed by the decrease in the mycelium biomass on SCMC. This study compares culture-dependent and qPCR methods to successfully quantify complex fungal microbiota on a model curd simulating Camembert-type cheese.

Iron Supply and Demand in an Antarctic Shelf Ecosystem

NASA Astrophysics Data System (ADS)

McGillicuddy, D. J., Jr.; Sedwick, P.; Dinniman, M. S.; Arrigo, K. R.; Bibby, T. S.; Greenan, B. J. W.; Hofmann, E. E.; Klinck, J. M., II; Smith, W.; Mack, S. L.; Marsay, C. M.; Sohst, B. M.; van Dijken, G.

2016-02-01

The Ross Sea sustains a rich ecosystem and is the most productive sector of the Southern Ocean. Most of this production occurs within a polynya during the November-February period, when the availability of dissolved iron (dFe) is thought to exert the major control on phytoplankton growth. Here we combine new data on the distribution of dFe, high-resolution model simulations of ice melt and regional circulation, and satellite-based estimates of primary production to quantify iron supply and demand over the Ross Sea continental shelf. Our analysis suggests that the largest sources of dFe to the euphotic zone are wintertime mixing and melting sea ice, with a lesser input from intrusions of Circumpolar Deep Water, and a small amount from melting glacial ice. Together these sources are in approximate balance with the annual biological dFe demand inferred from satellite-based productivity algorithms, although both the supply and demand estimates have large uncertainties. Our findings illustrate the complexities of iron cycling in the Southern Ocean, highlighting the heterogeneity of the underlying processes along the Antarctic continental margin. Explicit representation of these complexities, and the temporal variability in both proximate and ultimate sources of iron, will be necessary to understand how a changing climate will affect this important ecosystem and its influence on biogeochemical cycles. Reduction of the present uncertainties in iron supply and demand will require coupled observational and modeling systems capable of resolving the wide range of physical, biological, and chemical processes involved.

A generic framework for individual-based modelling and physical-biological interaction

PubMed Central

2018-01-01

The increased availability of high-resolution ocean data globally has enabled more detailed analyses of physical-biological interactions and their consequences to the ecosystem. We present IBMlib, which is a versatile, portable and computationally effective framework for conducting Lagrangian simulations in the marine environment. The purpose of the framework is to handle complex individual-level biological models of organisms, combined with realistic 3D oceanographic model of physics and biogeochemistry describing the environment of the organisms without assumptions about spatial or temporal scales. The open-source framework features a minimal robust interface to facilitate the coupling between individual-level biological models and oceanographic models, and we provide application examples including forward/backward simulations, habitat connectivity calculations, assessing ocean conditions, comparison of physical circulation models, model ensemble runs and recently posterior Eulerian simulations using the IBMlib framework. We present the code design ideas behind the longevity of the code, our implementation experiences, as well as code performance benchmarking. The framework may contribute substantially to progresses in representing, understanding, predicting and eventually managing marine ecosystems. PMID:29351280

Forests tend to cool the land surface in the temperate zone: An analysis of the mechanisms controlling radiometric surface temperature change in managed temperate ecosystems

NASA Astrophysics Data System (ADS)

Stoy, P. C.; Katul, G. G.; Juang, J.; Siqueira, M. B.; Novick, K. A.; Essery, R.; Dore, S.; Kolb, T. E.; Montes-Helu, M. C.; Scott, R. L.

2010-12-01

Vegetation is an important control on the surface energy balance and thereby surface temperature. Boreal forests and arctic shrubs are thought to warm the land surface by absorbing more radiation than the vegetation they replace. The surface temperatures of tropical forests tend to be cooler than deforested landscapes due to enhanced evapotranspiration. The effects of reforestation on surface temperature change in the temperate zone is less-certain, but recent modeling efforts suggest forests have a global warming effect. We quantified the mechanisms driving radiometric surface changes following landcover changes using paired ecosystem case studies from the Ameriflux database with energy balance models of varying complexity. Results confirm previous findings that deciduous and coniferous forests in the southeastern U.S. are ca. 1 °C cooler than an adjacent field on an annual basis because aerodynamic/ecophysiological cooling of 2-3 °C outweighs an albedo-related warming of <1 °C. A 50-70% reduction in the aerodynamic resistance to sensible and latent heat exchange in the forests dominated the cooling effect. A grassland ecosystem that succeeded a stand-replacing ponderosa pine fire was ca. 1 °C warmer than unburned stands because a 1.5 °C aerodynamic warming offset a slight surface cooling due to greater albedo and soil heat flux. An ecosystem dominated by mesquite shrub encroachment was nearly 2 °C warmer than a native grassland ecosystem as aerodynamic and albedo-related warming outweighed a small cooling effect due to changes in soil heat flux. The forested ecosystems in these case studies are documented to have higher carbon uptake than the non-forested systems. Results suggest that temperate forests tend to cool the land surface and suggest that previous model-based findings that forests warm the Earth’s surface globally should be reconsidered.Changes to radiometric surface temperature (K) following changes in vegetation using paired ecosystem case studies C4 grassland and shrub ecosystem surface temperatures were adjusted for differences in air temperature across sites.

Towards a global participatory platform. Democratising open data, complexity science and collective intelligence

NASA Astrophysics Data System (ADS)

Buckingham Shum, S.; Aberer, K.; Schmidt, A.; Bishop, S.; Lukowicz, P.; Anderson, S.; Charalabidis, Y.; Domingue, J.; de Freitas, S.; Dunwell, I.; Edmonds, B.; Grey, F.; Haklay, M.; Jelasity, M.; Karpištšenko, A.; Kohlhammer, J.; Lewis, J.; Pitt, J.; Sumner, R.; Helbing, D.

2012-11-01

The FuturICT project seeks to use the power of big data, analytic models grounded in complexity science, and the collective intelligence they yield for societal benefit. Accordingly, this paper argues that these new tools should not remain the preserve of restricted government, scientific or corporate élites, but be opened up for societal engagement and critique. To democratise such assets as a public good, requires a sustainable ecosystem enabling different kinds of stakeholder in society, including but not limited to, citizens and advocacy groups, school and university students, policy analysts, scientists, software developers, journalists and politicians. Our working name for envisioning a sociotechnical infrastructure capable of engaging such a wide constituency is the Global Participatory Platform (GPP). We consider what it means to develop a GPP at the different levels of data, models and deliberation, motivating a framework for different stakeholders to find their ecological niches at different levels within the system, serving the functions of (i) sensing the environment in order to pool data, (ii) mining the resulting data for patterns in order to model the past/present/future, and (iii) sharing and contesting possible interpretations of what those models might mean, and in a policy context, possible decisions. A research objective is also to apply the concepts and tools of complexity science and social science to the project's own work. We therefore conceive the global participatory platform as a resilient, epistemic ecosystem, whose design will make it capable of self-organization and adaptation to a dynamic environment, and whose structure and contributions are themselves networks of stakeholders, challenges, issues, ideas and arguments whose structure and dynamics can be modelled and analysed.

Biodiversity in a complex world: consolidation and progress in functional biodiversity research.

PubMed

Hillebrand, Helmut; Matthiessen, Birte

2009-12-01

The global decline of biodiversity caused by human domination of ecosystems worldwide is supposed to alter important process rates and state variables in these ecosystems. However, there is considerable debate on the prevalence and importance of biodiversity effects on ecosystem function (BDEF). Here, we argue that much of the debate stems from two major shortcomings. First, most studies do not directly link the traits leading to increased or decreased function to the traits needed for species coexistence and dominance. We argue that implementing a trait-based approach and broadening the perception of diversity to include trait dissimilarity or trait divergence will result in more realistic predictions on the consequences of altered biodiversity. Second, the empirical and theoretical studies do not reflect the complexity of natural ecosystems, which makes it difficult to transfer the results to natural situations of species loss. We review how different aspects of complexity (trophic structure, multifunctionality, spatial or temporal heterogeneity, and spatial population dynamics) alter our perception of BDEF. We propose future research avenues concisely testing whether acknowledging this complexity will strengthen the observed biodiversity effects. Finally, we propose that a major future task is to disentangle biodiversity effects on ecosystem function from direct changes in function due to human alterations of abiotic constraints.

Using ecological production functions to link ecological ...

EPA Pesticide Factsheets

Ecological production functions (EPFs) link ecosystems, stressors, and management actions to ecosystem services (ES) production. Although EPFs are acknowledged as being essential to improve environmental management, their use in ecological risk assessment has received relatively little attention. Ecological production functions may be defined as usable expressions (i.e., models) of the processes by which ecosystems produce ES, often including external influences on those processes. We identify key attributes of EPFs and discuss both actual and idealized examples of their use to inform decision making. Whenever possible, EPFs should estimate final, rather than intermediate, ES. Although various types of EPFs have been developed, we suggest that EPFs are more useful for decision making if they quantify ES outcomes, respond to ecosystem condition, respond to stressor levels or management scenarios, reflect ecological complexity, rely on data with broad coverage, have performed well previously, are practical to use, and are open and transparent. In an example using pesticides, we illustrate how EPFs with these attributes could enable the inclusion of ES in ecological risk assessment. The biggest challenges to ES inclusion are limited data sets that are easily adapted for use in modeling EPFs and generally poor understanding of linkages among ecological components and the processes that ultimately deliver the ES. We conclude by advocating for the incorporation into E

International Land Model Benchmarking (ILAMB) Workshop Report, Technical Report DOE/SC-0186

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hoffman, Forrest M.; Koven, Charles D.; Kappel-Aleks, Gretchen

2016-11-01

As Earth system models become increasingly complex, there is a growing need for comprehensive and multi-faceted evaluation of model projections. To advance understanding of biogeochemical processes and their interactions with hydrology and climate under conditions of increasing atmospheric carbon dioxide, new analysis methods are required that use observations to constrain model predictions, inform model development, and identify needed measurements and field experiments. Better representations of biogeochemistry–climate feedbacks and ecosystem processes in these models are essential for reducing uncertainties associated with projections of climate change during the remainder of the 21st century.

Evaluation of 11 terrestrial carbon–nitrogen cycle models against observations from two temperate Free-Air CO2 Enrichment studies

PubMed Central

Zaehle, Sönke; Medlyn, Belinda E; De Kauwe, Martin G; Walker, Anthony P; Dietze, Michael C; Hickler, Thomas; Luo, Yiqi; Wang, Ying-Ping; El-Masri, Bassil; Thornton, Peter; Jain, Atul; Wang, Shusen; Warlind, David; Weng, Ensheng; Parton, William; Iversen, Colleen M; Gallet-Budynek, Anne; McCarthy, Heather; Finzi, Adrien; Hanson, Paul J; Prentice, I Colin; Oren, Ram; Norby, Richard J

2014-01-01

We analysed the responses of 11 ecosystem models to elevated atmospheric [CO2] (eCO2) at two temperate forest ecosystems (Duke and Oak Ridge National Laboratory (ORNL) Free-Air CO2 Enrichment (FACE) experiments) to test alternative representations of carbon (C)–nitrogen (N) cycle processes. We decomposed the model responses into component processes affecting the response to eCO2 and confronted these with observations from the FACE experiments. Most of the models reproduced the observed initial enhancement of net primary production (NPP) at both sites, but none was able to simulate both the sustained 10-yr enhancement at Duke and the declining response at ORNL: models generally showed signs of progressive N limitation as a result of lower than observed plant N uptake. Nonetheless, many models showed qualitative agreement with observed component processes. The results suggest that improved representation of above-ground–below-ground interactions and better constraints on plant stoichiometry are important for a predictive understanding of eCO2 effects. Improved accuracy of soil organic matter inventories is pivotal to reduce uncertainty in the observed C–N budgets. The two FACE experiments are insufficient to fully constrain terrestrial responses to eCO2, given the complexity of factors leading to the observed diverging trends, and the consequential inability of the models to explain these trends. Nevertheless, the ecosystem models were able to capture important features of the experiments, lending some support to their projections. PMID:24467623

Parallel ecological networks in ecosystems

PubMed Central

Olff, Han; Alonso, David; Berg, Matty P.; Eriksson, B. Klemens; Loreau, Michel; Piersma, Theunis; Rooney, Neil

2009-01-01

In ecosystems, species interact with other species directly and through abiotic factors in multiple ways, often forming complex networks of various types of ecological interaction. Out of this suite of interactions, predator–prey interactions have received most attention. The resulting food webs, however, will always operate simultaneously with networks based on other types of ecological interaction, such as through the activities of ecosystem engineers or mutualistic interactions. Little is known about how to classify, organize and quantify these other ecological networks and their mutual interplay. The aim of this paper is to provide new and testable ideas on how to understand and model ecosystems in which many different types of ecological interaction operate simultaneously. We approach this problem by first identifying six main types of interaction that operate within ecosystems, of which food web interactions are one. Then, we propose that food webs are structured among two main axes of organization: a vertical (classic) axis representing trophic position and a new horizontal ‘ecological stoichiometry’ axis representing decreasing palatability of plant parts and detritus for herbivores and detrivores and slower turnover times. The usefulness of these new ideas is then explored with three very different ecosystems as test cases: temperate intertidal mudflats; temperate short grass prairie; and tropical savannah. PMID:19451126

Assessment of Regional Ecosystem Health—A Case Study of the Golden Triangle of Southern Fujian Province, China

PubMed Central

Wang, Ziyan; Qiu, Quanyi; Wu, Tong; Shao, Guofan

2018-01-01

Intensifying urbanization and rapid population growth in Fujian Province, China, has caused pollution of air and water resources; this has adversely impacted ecosystems and human health. China has recently begun pursuing a massive infrastructure and economic development strategy called the Belt and Road Initiative, which could potentially cause further environmental damage. Evaluations of ecosystem health are therefore a first step towards identifying the potential impacts from the development and planning sustainable development strategies in the Golden Triangle of Southern Fujian. To this end, our study analyzed landscape patterns and evaluated ecosystem health in this region. We used an index system method to develop a pressure–state–response (PSR) model for assessing the region’s ecosystem health. We found that: (1) the landscape type with the greatest area in the study region is cultivated land and there were no areas that were undisturbed by human activity; (2) the overall ecological health of the region is good, but there is distinct variation across the region. This study incorporates the landscape pattern into an evaluation of ecosystem health. Using counties as evaluation units, we provide a general evaluation index for this scale. The methods reported here can be used in complex ecological environments to inform sustainable management decisions. PMID:29671817

VOC Metabolite Emissions from the Brachypodium/Soil/Microbe Ecosystem

NASA Astrophysics Data System (ADS)

Gu, D.; Shilling, J.; Guenther, A. B.; Lindenmaier, R.

2017-12-01

Volatile Organic Compounds (VOCs) emitted from plants and associated microbiota are important for understanding the plant responses to environmental perturbations. VOC emissions from plants are the largest source of hydrocarbons to the atmosphere, which influence oxidants and aerosols leading to complex feed backs and interactions between atmosphere and biosphere. The integrated Plant-Atmosphere-Soil Systems (iPASS) Initiative is a Pacific Northwest National Laboratory (PNNL) project aimed at deciphering fundamental principles that govern the plant ecosystem, from plant genotype through multiple scales to ecosystem traits and response. We take the opportunity of iPASS initiative, and measured VOC metabolite emissions from the Brachypodium/Soil/Microbe Ecosystem. In the experiments, we have been working on (1) identifying VOC metabolites emitted by Brachypodium plants using dynamic vegetation enclosure measurements, (2) understanding the relative contribution of plants, microbes, and soil to VOC emissions, (3) investigating changes that occur in these emissions under different induced stress, and (4) relating VOC emissions from the plant/soil/microbe ecosystem to plant genotype. Taking advantage of experiment results, we also can develop a noninvasive technique for quantifying plant stress by using VOC observations, use VOC observations to improve screening tool for identifying stress resistant phenotypes, and apply the measurements into earth system modeling for better understanding of the impacts of stress on ecosystems.

'Trophic whales' as biotic buffers: weak interactions stabilize ecosystems against nutrient enrichment.

PubMed

Schwarzmüller, Florian; Eisenhauer, Nico; Brose, Ulrich

2015-05-01

Human activities may compromise biodiversity if external stressors such as nutrient enrichment endanger overall network stability by inducing unstable dynamics. However, some ecosystems maintain relatively high diversity levels despite experiencing continuing disturbances. This indicates that some intrinsic properties prevent unstable dynamics and resulting extinctions. Identifying these 'ecosystem buffers' is crucial for our understanding of the stability of ecosystems and an important tool for environmental and conservation biologists. In this vein, weak interactions have been suggested as stabilizing elements of complex systems, but their relevance has rarely been tested experimentally. Here, using network and allometric theory, we present a novel concept for a priori identification of species that buffer against externally induced instability of increased population oscillations via weak interactions. We tested our model in a microcosm experiment using a soil food-web motif. Our results show that large-bodied species feeding at the food web's base, so called 'trophic whales', can buffer ecosystems against unstable dynamics induced by nutrient enrichment. Similar to the functionality of chemical or mechanical buffers, they serve as 'biotic buffers' that take up stressor effects and thus protect fragile systems from instability. We discuss trophic whales as common functional building blocks across ecosystems. Considering increasing stressor effects under anthropogenic global change, conservation of these network-intrinsic biotic buffers may help maintain the stability and diversity of natural ecosystems. © 2014 The Authors. Journal of Animal Ecology © 2014 British Ecological Society.

Disrupting the Networks of Cancer

PubMed Central

Camacho, Daniel F.; Pienta, Kenneth J.

2014-01-01

Ecosystems are interactive systems involving communities of species and their abiotic environment. Tumors are ecosystems in which cancer cells act as invasive species interacting with native host cell species in an established microenvironment within the larger host biosphere. At its heart, to study ecology is to study interconnectedness. In ecologic science, an ecologic network is a representation of the biotic interactions in an ecosystem in which species (nodes) are connected by pairwise interactions (links). Ecologic networks and signaling network models have been used to describe and compare the structures of ecosystems. It has been shown that disruption of ecologic networks through the loss of species or disruption of interactions between them can lead to the destruction of the ecosystem. Often, the destruction of a single node or link is not enough to disrupt the entire ecosystem. The more complex the network and its interactions, the more difficult it is to cause the extinction of a species, especially without leveraging other aspects of the ecosystem. Similarly, successful treatment of cancer with a single agent is rarely enough to cure a patient without strategically modifying the support systems conducive to survival of cancer. Cancer cells and the ecologic systems they reside in can be viewed as a series of nested networks. The most effective new paradigms for treatment will be developed through application of scaled network disruption. PMID:22442061

Disrupting the networks of cancer.

PubMed

Camacho, Daniel F; Pienta, Kenneth J

2012-05-15

Ecosystems are interactive systems involving communities of species and their abiotic environment. Tumors are ecosystems in which cancer cells act as invasive species interacting with native host cell species in an established microenvironment within the larger host biosphere. At its heart, to study ecology is to study interconnectedness. In ecologic science, an ecologic network is a representation of the biotic interactions in an ecosystem in which species (nodes) are connected by pairwise interactions (links). Ecologic networks and signaling network models have been used to describe and compare the structures of ecosystems. It has been shown that disruption of ecologic networks through the loss of species or disruption of interactions between them can lead to the destruction of the ecosystem. Often, the destruction of a single node or link is not enough to disrupt the entire ecosystem. The more complex the network and its interactions, the more difficult it is to cause the extinction of a species, especially without leveraging other aspects of the ecosystem. Similarly, successful treatment of cancer with a single agent is rarely enough to cure a patient without strategically modifying the support systems conducive to survival of cancer. Cancer cells and the ecologic systems they reside in can be viewed as a series of nested networks. The most effective new paradigms for treatment will be developed through application of scaled network disruption. ©2012 AACR.

Light, temperature, and leaf nitrogen distribution in the tropical rain forest of Biosphere 2 and their importance in the mathematical models for global environmental changes

NASA Technical Reports Server (NTRS)

Tohda, Motofumi

1997-01-01

As the environmental changes occur throughout the world in rapid rate, we need to have further understandings for our planet. Since the ecosystems are so complex, it is almost impossible for us to integrate every factor. However, mathematical models are powerful tools which can be used to simulate those ecosystems with limited data. In this project, I collected light intensity, canopy leaf temperature and Air Handler (AHU) temperature, and nitrogen concentration in the leaves for different profiles in the rainforest mesocosm. These data will later be put into mathematical models such as "big-leaf" and "sun/shade" models to determine how these factors will affect CO2 exchange in the rainforest. As rainforests are diminishing from our planet and their existence is very important for all living things on earth, it is necessary for us to learn more about the unique system of rainforests and how we can co-exist rather than destroy.

Scientists are from Mars, educators are from Venus: Relationships in the ecosystem of science teacher preparation

NASA Astrophysics Data System (ADS)

Duggan-Haas, Don Andrew

2000-10-01

Great problems exist in science teaching from kindergarten through the college level (NRC, 1996; NSF, 1996). The problem may be attributed to the failure of teachers to integrate their own understanding of science content with appropriate pedagogy (Shulman, 1986, 1987). All teachers were trained by college faculty and therefore some of the blame for these problems rests on those faculty. This dissertation presents three models for describing secondary science teacher preparation. Two Programs, Two Cultures adapts C. P. Snow's classic work (1959) to describe the work of a science teacher candidate as that of an individual who navigates between two discrete programs: one in college science and the second in teacher education. The second model, Scientists Are from Mars, Educators Are from Venus adapts the popular work of John Gray to describe the system of science teacher education as hobbled by the dysfunctional relationships among the major players and describes the teacher as progeny from this relationship. The third model, The Ecosystem of Science Teacher Preparation reveals some of the deeper complexities of science teacher education and posits that the traditional college science approach treats students as a monoculture when great diversity in fact exists. The three models are described in the context of a large Midwestern university's teacher education program as that program is construed for future biology teachers. Four undergraduate courses typically taken by future biology teachers were observed and described: an introductory biology course; an introductory teacher education course; an upper division course in biochemistry and a senior level science teaching methods course. Seven second semester seniors who were biological Science majors were interviewed. All seven students had taken all of the courses observed. An organization of scientists and educators working together to improve science teaching from kindergarten through graduate school is also described in a case study. The three models described in the dissertation build upon one another and the third model, that of the ecosystem is recognized as both the most accurate portrayal and most complex and therefore most difficult to apply. The system of science teacher preparation is in many ways a system under stress and that stress will result in system evolution. Through better understanding Complex Adaptive Systems and applying that understanding to the system of science teacher education, individuals may be able to influence the nature of system evolution.

Sea Ice Biogeochemistry: A Guide for Modellers

PubMed Central

Tedesco, Letizia; Vichi, Marcello

2014-01-01

Sea ice is a fundamental component of the climate system and plays a key role in polar trophic food webs. Nonetheless sea ice biogeochemical dynamics at large temporal and spatial scales are still rarely described. Numerical models may potentially contribute integrating among sparse observations, but available models of sea ice biogeochemistry are still scarce, whether their relevance for properly describing the current and future state of the polar oceans has been recently addressed. A general methodology to develop a sea ice biogeochemical model is presented, deriving it from an existing validated model application by extension of generic pelagic biogeochemistry model parameterizations. The described methodology is flexible and considers different levels of ecosystem complexity and vertical representation, while adopting a strategy of coupling that ensures mass conservation. We show how to apply this methodology step by step by building an intermediate complexity model from a published realistic application and applying it to analyze theoretically a typical season of first-year sea ice in the Arctic, the one currently needing the most urgent understanding. The aim is to (1) introduce sea ice biogeochemistry and address its relevance to ocean modelers of polar regions, supporting them in adding a new sea ice component to their modelling framework for a more adequate representation of the sea ice-covered ocean ecosystem as a whole, and (2) extend our knowledge on the relevant controlling factors of sea ice algal production, showing that beyond the light and nutrient availability, the duration of the sea ice season may play a key-role shaping the algal production during the on going and upcoming projected changes. PMID:24586604

Beyond the climate envelope: using trait filtering models to predict biome boundaries from plant physiology.

NASA Astrophysics Data System (ADS)

Fisher, R.; Hoffmann, W. A.; Muszala, S.

2014-12-01

The introduction of second-generation dynamic vegetation models - which simulate the distribution of light resources between plant types along the vertical canopy profile, and therefore facilitate the representation of plant competition explicitly - is a large increase in the complexity and fidelity with which the terrestrial biosphere is abstracted into Earth System Models. In this new class of model, biome boundaries are predicted as the emergent properties of plant physiology, and are therefore sensitive to the high-dimensional parameterizations of plant functional traits. These new approaches offer the facility to quantitatively test ecophysiological hypotheses of plant distribution at large scales, a field which remains surprisingly under-developed. Here we describe experiments conducted with the Community Land Model Ecosystem Demography component, CLM(ED), in which we reduce the complexity of the problem by testing how individual plant functional trait changes to control the location of biome boundaries between functional types. Specifically, we investigate which physiological trade-offs determine the boundary between frequently burned savanna and forest biomes, and attempt to distinguish how each strategic life-history trade-off (carbon storage, bark investment, re-sprouting strategy) contributes towards the maintenance of sharp geographical gradients between fire adapted and typically inflammable closed canopy ecosystems. This study forms part of the planning for a model-inspired fire manipulation experiment at the cerrado-forest boundary in South-Eastern Brazil, and the results will be used to guide future data-collection and analysis strategies.

Assessment of national biomass in complex forests and technical capacity scenarios

Treesearch

Matieu Henry; Javier G. P. Gamarra; Gael Sola; Luca Birigazzi; Emily Donegan; Julian Murillo; Tommaso Chiti; Nicolas Picard; Miguel Cifuentes-Jara; S Sandeep; Laurent Saint-André

2015-01-01

Understanding forest ecosystems is paramount for their sustainable management and for the livelihoods and ecosystem services which depend on them. However, the complexity and diversity of these systems poses a challenge to interpreting data patterns. The availability and accessibility of data and tools often determine the method selected for forest assessment. Capacity...

Efficient Ensemble State-Parameters Estimation Techniques in Ocean Ecosystem Models: Application to the North Atlantic

NASA Astrophysics Data System (ADS)

El Gharamti, M.; Bethke, I.; Tjiputra, J.; Bertino, L.

2016-02-01

Given the recent strong international focus on developing new data assimilation systems for biological models, we present in this comparative study the application of newly developed state-parameters estimation tools to an ocean ecosystem model. It is quite known that the available physical models are still too simple compared to the complexity of the ocean biology. Furthermore, various biological parameters remain poorly unknown and hence wrong specifications of such parameters can lead to large model errors. Standard joint state-parameters augmentation technique using the ensemble Kalman filter (Stochastic EnKF) has been extensively tested in many geophysical applications. Some of these assimilation studies reported that jointly updating the state and the parameters might introduce significant inconsistency especially for strongly nonlinear models. This is usually the case for ecosystem models particularly during the period of the spring bloom. A better handling of the estimation problem is often carried out by separating the update of the state and the parameters using the so-called Dual EnKF. The dual filter is computationally more expensive than the Joint EnKF but is expected to perform more accurately. Using a similar separation strategy, we propose a new EnKF estimation algorithm in which we apply a one-step-ahead smoothing to the state. The new state-parameters estimation scheme is derived in a consistent Bayesian filtering framework and results in separate update steps for the state and the parameters. Unlike the classical filtering path, the new scheme starts with an update step and later a model propagation step is performed. We test the performance of the new smoothing-based schemes against the standard EnKF in a one-dimensional configuration of the Norwegian Earth System Model (NorESM) in the North Atlantic. We use nutrients profile (up to 2000 m deep) data and surface partial CO2 measurements from Mike weather station (66o N, 2o E) to estimate different biological parameters of phytoplanktons and zooplanktons. We analyze the performance of the filters in terms of complexity and accuracy of the state and parameters estimates.

Resilience to stress and disturbance, and resistance to Bromus tectorum L. invasion in cold desert shrublands of western North America

USGS Publications Warehouse

Chambers, Jeanne C.; Bradley, Bethany A.; Brown, Cynthia S.; D'Antonio, Carla; Germino, Matthew J.; Grace, James B.; Hardegree, Stuart P.; Miller, Richard F.; Pyke, David A.

2013-01-01

Alien grass invasions in arid and semi-arid ecosystems are resulting in grass–fire cycles and ecosystem-level transformations that severely diminish ecosystem services. Our capacity to address the rapid and complex changes occurring in these ecosystems can be enhanced by developing an understanding of the environmental factors and ecosystem attributes that determine resilience of native ecosystems to stress and disturbance, and resistance to invasion. Cold desert shrublands occur over strong environmental gradients and exhibit significant differences in resilience and resistance. They provide an excellent opportunity to increase our understanding of these concepts. Herein, we examine a series of linked questions about (a) ecosystem attributes that determine resilience and resistance along environmental gradients, (b) effects of disturbances like livestock grazing and altered fire regimes and of stressors like rapid climate change, rising CO2, and N deposition on resilience and resistance, and (c) interacting effects of resilience and resistance on ecosystems with different environmental conditions. We conclude by providing strategies for the use of resilience and resistance concepts in a management context. At ecological site scales, state and transition models are used to illustrate how differences in resilience and resistance influence potential alternative vegetation states, transitions among states, and thresholds. At landscape scales management strategies based on resilience and resistance—protection, prevention, restoration, and monitoring and adaptive management—are used to determine priority management areas and appropriate actions.

Ecosystem service impacts of future changes in CO2, climate, and land use as simulated by a coupled vegetation/land-use model system

NASA Astrophysics Data System (ADS)

Rabin, S. S.; Alexander, P.; Henry, R.; Anthoni, P.; Pugh, T.; Rounsevell, M.; Arneth, A.

2017-12-01

In a future of increasing atmospheric carbon dioxide (CO2) concentrations, changing climate, increasing human populations, and changing socioeconomic dynamics, the global agricultural system will need to adapt in order to feed the world. Global modeling can help to explore what these adaptations will look like, and their potential impacts on ecosystem services. To do so, however, the complex interconnections among the atmosphere, terrestrial ecosystems, and society mean that these various parts of the Earth system must be examined as an interconnected whole. With the goal of answering these questions, a model system has been developed that couples a biologically-representative global vegetation model, LPJ-GUESS, with the PLUMv2 land use model. LPJ-GUESS first simulates—at 0.5º resolution across the world—the potential yield of various crops and pasture under a range of management intensities for a time step given its atmospheric CO2 level and climatic forcings. These potential yield simulations are fed into PLUMv2, which uses them in conjunction with endogenous agricultural commodity demand and prices to produce land use and management inputs (fertilizer and irrigation water) at a sub-national level for the next time step. This process is performed through 2100 for a range of future climate and societal scenarios—the Representative Concentration Pathways (RCPs) and the Shared Socioeconomic Pathways (SSPs), respectively—providing a thorough exploration of possible trajectories of land use and land cover change. The land use projections produced by PLUMv2 are fed back into LPJ-GUESS to simulate the future impacts of land use change, along with increasing CO2 and climate change, on terrestrial ecosystems. This integrated analysis examines the resulting impacts on regulating and provisioning ecosystem services affecting biophysics (albedo); carbon, nitrogen, and water cycling; and the emission of biogenic volatile organic compounds (BVOCs).

The plight of the Marsh Arabs, an environmental and human rights crisis: an application of complexity theory.

PubMed

Newman, Susan Dunreath

2007-01-01

Saddam Hussein's calculated destruction of the marshes of southern Iraq had an overwhelming impact on the marsh ecosystem, the physical environment, and its inhabitants. Hussein succeeded in disrupting the 5000-year-old culture of the Marsh Arabs, severely affecting the health and well-being of this unique culture. Complexity science provides a foundation that supports an appreciation of the effects that changes in environment and climate have on health. Application of a complexity model provides guidance for understanding the intricate networks of connectivity among the components of the ecological system of the marshes of Southern Iraq that is necessary for restoration efforts.

Implications of agricultural transitions and urbanization for ecosystem services.

PubMed

Cumming, Graeme S; Buerkert, Andreas; Hoffmann, Ellen M; Schlecht, Eva; von Cramon-Taubadel, Stephan; Tscharntke, Teja

2014-11-06

Historically, farmers and hunter-gatherers relied directly on ecosystem services, which they both exploited and enjoyed. Urban populations still rely on ecosystems, but prioritize non-ecosystem services (socioeconomic). Population growth and densification increase the scale and change the nature of both ecosystem- and non-ecosystem-service supply and demand, weakening direct feedbacks between ecosystems and societies and potentially pushing social-ecological systems into traps that can lead to collapse. The interacting and mutually reinforcing processes of technological change, population growth and urbanization contribute to over-exploitation of ecosystems through complex feedbacks that have important implications for sustainable resource use.

Remote analysis of anthropogenic effect on boreal forests using nonlinear multidimensional models

NASA Astrophysics Data System (ADS)

Shchemel, Anton; Ivanova, Yuliya; Larko, Alexander

Nowadays anthropogenic stress of mining and refining oil and gas is becoming significant prob-lem in Eastern Siberia. The task of revealing effect of that industry is not trivial because of complicated access to the sites of mining. Due to that, severe problem of supplying detection of oil and gas complex effect on forest ecosystems arises. That estimation should allow revealing the sites of any negative changes in forest communities in proper time. The intellectual system of analyzing remote sensing data of different resolution and different spectral characteristics with sophisticated nonlinear models is dedicated to solve the problem. The work considers re-mote detection and estimation of forest degradation using analysis of free remote sensing data without total field observations of oil and gas mining territory. To analyze a state of vegetation the following remote sensing data were used as input parameters for our models: albedo, surface temperature and data of about thirty spectral bands in visible and infrared region. The data of MODIS satellite from the year 2000 was used. Chosen data allowed producing complex estima-tion of parameters linked with the quality (set of species, physiological state) and the quantity of vegetation. To verify obtained estimation each index was calculated for a territory in which oil and gas mining is provided along with the same calculations for a sample "clear" territory. Monthly data for vegetation period and annual mean values were analyzed. The work revealed some trends of annual data probably linked with intensification of anthropogenic effect on the ecosystems. The models we managed to build are easy to apply for using by fair personnel of emergency control and oversight institutions. It was found to be helpful to use exactly the full set of values obtained from the satellite for multilateral estimation of anthropogenic effect on forest ecosystems of objects of the oil mining industry for producing generalized estimation indices by the developed models.

Interactions between drought and soil biogeochemistry: scaling from molecules to meters

NASA Astrophysics Data System (ADS)

Schimel, J.; Schaeffer, S. M.

2011-12-01

Water is the perhaps the single most critical resource for life, yet most terrestrial ecosystems experience regular drought. Reduced water potential causes physiological stress; reduced diffusion limits resource availability when microbes may need resources to acclimate. Most biogeochemical models, however, have assumed that soil processes either slow down or stop during drought. But organisms survive and enzymes remain viable. In California, as soils stay dry through the long summer drought, microbial biomass actually increases and pools of extractable organic C increase, probably because extracellular enzymes continue to break down plant detritus (notably roots). Yet 14C suggests that in deeper soils, the pulse of C released on rewetting comes from pools with turnover times of as long as 800 years. What are the mechanisms that regulate these complex dynamics? They appear to involve differential moisture sensitivity for the activity of extracellular enzymes, substrate diffusion, and microbial metabolism. Rewetting not only redistributes materials made available during the drought, but it also disrupts aggregates and may make previously-protected substrates available as well. We have used several methods to simply capture these linkages between water and carbon in models that are applicable at the ecosystem scale and that could improve our ability to model biogeochemical cycles in arid and semi-arid ecosystems. One is a simple empirical modification to the DAYCENT model while the other is a mechanistic model that incorporates microbial dry-season processes.

Influence of glacier runoff on ecosystem structure in Gulf of Alaska fjords

USGS Publications Warehouse

Arimitsu, Mayumi L.; Piatt, John F.; Mueter, Franz J.

2016-01-01

To better understand the influence of glacier runoff on fjord ecosystems, we sampled oceanographic conditions, nutrients, zooplankton, forage fish and seabirds within 4 fjords in coastal areas of the Gulf Alaska. We used generalized additive models and geostatistics to identify the range of glacier runoff influence into coastal waters within fjords of varying estuarine influence and topographic complexity. We also modeled the response of depth-integrated chlorophyll a concentration, copepod biomass, fish and seabird abundance to physical, nutrient and biotic predictor variables. The effects of glacial runoff were traced at least 10 km into coastal fjords by cold, turbid, stratified and generally nutrient-rich near-surface conditions. Glacially modified physical gradients, nutrient availability and among-fjord differences explained 67% of the variation in phytoplankton abundance, which is a driver of ecosystem structure at higher trophic levels. Copepod, euphausiid, fish and seabird distribution and abundance were related to environmental gradients that could be traced to glacial freshwater input, particularly turbidity and temperature. Seabird density was predicted by prey availability and silicate concentrations, which may be a proxy for upwelling areas where this nutrient is in excess. Similarities in ecosystem structure among fjords were attributable to an influx of cold, fresh and sediment-laden water, whereas differences were likely related to fjord topography and local differences in estuarine vs. ocean influence. We anticipate that continued changes in the timing and volume of glacial runoff will ultimately alter coastal ecosystems in the future.

Managing for resilience: an information theory-based approach to assessing ecosystems

EPA Science Inventory

Ecosystems are complex and multivariate; hence, methods to assess the dynamics of ecosystems should have the capacity to evaluate multiple indicators simultaneously. Most research on identifying leading indicators of regime shifts has focused on univariate methods and simple mod...

Development of an Unmanned Aerial System (UAS) for Scaling Terrestrial Ecosystem Traits

NASA Astrophysics Data System (ADS)

Meng, R.; McMahon, A. M.; Serbin, S.; Rogers, A.

2015-12-01

The next generation of Ecosystem and Earth System Models (EESMs) will require detailed information on ecosystem structure and function, including properties of vegetation related to carbon (C), water, and energy cycling, in order to project the future state of ecosystems. High spatial-temporal resolution measurements of terrestrial ecosystem are also important for EESMs, because they can provide critical inputs and benchmark datasets for evaluation of EESMs simulations across scales. The recent development of high-quality, low-altitude remote sensing platforms or small UAS (< 25 kg) enables measurements of terrestrial ecosystems at unprecedented temporal and spatial scales. Specifically, these new platforms can provide detailed information on patterns and processes of terrestrial ecosystems at a critical intermediate scale between point measurements and suborbital and satellite platforms. Given their potential for sub-decimeter spatial resolution, improved mission safety, high revisit frequency, and reduced operation cost, these platforms are of particular interest in the development of ecological scaling algorithms to parameterize and benchmark EESMs, particularly over complex and remote terrain. Our group is developing a small UAS platform and integrated sensor package focused on measurement needs for scaling and informing ecosystem modeling activities, as well as scaling and mapping plant functional traits. To do this we are developing an integrated software workflow and hardware package using off-the-shelf instrumentation including a high-resolution digital camera for Structure from Motion, spectroradiometer, and a thermal infrared camera. Our workflow includes platform design, measurement, image processing, data management, and information extraction. The fusion of 3D structure information, thermal-infrared imagery, and spectroscopic measurements, will provide a foundation for the development of ecological scaling and mapping algorithms. Our initial focus is in temperate forests but near-term research will expand into the high-arctic and eventually tropical systems. The results of this prototype study show that off-the-shelf technology can be used to develop a low-cost alternative for mapping plant traits and three-dimensional structure for ecological research.

Animal diversity and ecosystem functioning in dynamic food webs

NASA Astrophysics Data System (ADS)

Schneider, Florian D.; Brose, Ulrich; Rall, Björn C.; Guill, Christian

2016-10-01

Species diversity is changing globally and locally, but the complexity of ecological communities hampers a general understanding of the consequences of animal species loss on ecosystem functioning. High animal diversity increases complementarity of herbivores but also increases feeding rates within the consumer guild. Depending on the balance of these counteracting mechanisms, species-rich animal communities may put plants under top-down control or may release them from grazing pressure. Using a dynamic food-web model with body-mass constraints, we simulate ecosystem functions of 20,000 communities of varying animal diversity. We show that diverse animal communities accumulate more biomass and are more exploitative on plants, despite their higher rates of intra-guild predation. However, they do not reduce plant biomass because the communities are composed of larger, and thus energetically more efficient, plant and animal species. This plasticity of community body-size structure reconciles the debate on the consequences of animal species loss for primary productivity.

Molecular Ecology of Hypersaline Microbial Mats: Current Insights and New Directions.

PubMed

Wong, Hon Lun; Ahmed-Cox, Aria; Burns, Brendan Paul

2016-01-05

Microbial mats are unique geobiological ecosystems that form as a result of complex communities of microorganisms interacting with each other and their physical environment. Both the microorganisms present and the network of metabolic interactions govern ecosystem function therein. These systems are often found in a range of extreme environments, and those found in elevated salinity have been particularly well studied. The purpose of this review is to briefly describe the molecular ecology of select model hypersaline mat systems (Guerrero Negro, Shark Bay, S'Avall, and Kiritimati Atoll), and any potentially modulating effects caused by salinity to community structure. In addition, we discuss several emerging issues in the field (linking function to newly discovered phyla and microbial dark matter), which illustrate the changing paradigm that is seen as technology has rapidly advanced in the study of these extreme and evolutionally significant ecosystems.

Our evolving conceptual model of the coastal eutrophication problem

USGS Publications Warehouse

Cloern, James E.

2001-01-01

A primary focus of coastal science during the past 3 decades has been the question: How does anthropogenic nutrient enrichment cause change in the structure or function of nearshore coastal ecosystems? This theme of environmental science is recent, so our conceptual model of the coastal eutrophication problem continues to change rapidly. In this review, I suggest that the early (Phase I) conceptual model was strongly influenced by limnologists, who began intense study of lake eutrophication by the 1960s. The Phase I model emphasized changing nutrient input as a signal, and responses to that signal as increased phytoplankton biomass and primary production, decomposition of phytoplankton-derived organic matter, and enhanced depletion of oxygen from bottom waters. Coastal research in recent decades has identified key differences in the responses of lakes and coastal-estuarine ecosystems to nutrient enrichment. The contemporary (Phase II) conceptual model reflects those differences and includes explicit recognition of (1) system-specific attributes that act as a filter to modulate the responses to enrichment (leading to large differences among estuarine-coastal systems in their sensitivity to nutrient enrichment); and (2) a complex suite of direct and indirect responses including linked changes in: water transparency, distribution of vascular plants and biomass of macroalgae, sediment biogeochemistry and nutrient cycling, nutrient ratios and their regulation of phytoplankton community composition, frequency of toxic/harmful algal blooms, habitat quality for metazoans, reproduction/growth/survival of pelagic and benthic invertebrates, and subtle changes such as shifts in the seasonality of ecosystem functions. Each aspect of the Phase II model is illustrated here with examples from coastal ecosystems around the world. In the last section of this review I present one vision of the next (Phase III) stage in the evolution of our conceptual model, organized around 5 questions that will guide coastal science in the early 21st century: (1) How do system-specific attributes constrain or amplify the responses of coastal ecosystems to nutrient enrichment? (2) How does nutrient enrichment interact with other stressors (toxic contaminants, fishing harvest, aquaculture, nonindigenous species, habitat loss, climate change, hydrologic manipulations) to change coastal ecosystems? (3) How are responses to multiple stressors linked? (4) How does human-induced change in the coastal zone impact the Earth system as habitat for humanity and other species? (5) How can a deeper scientific understanding of the coastal eutrophication problem be applied to develop tools for building strategies at ecosystem restoration or rehabilitation?

Harnessing ecosystem models and multi-criteria decision analysis for the support of forest management.

PubMed

Wolfslehner, Bernhard; Seidl, Rupert

2010-12-01

The decision-making environment in forest management (FM) has changed drastically during the last decades. Forest management planning is facing increasing complexity due to a widening portfolio of forest goods and services, a societal demand for a rational, transparent decision process and rising uncertainties concerning future environmental conditions (e.g., climate change). Methodological responses to these challenges include an intensified use of ecosystem models to provide an enriched, quantitative information base for FM planning. Furthermore, multi-criteria methods are increasingly used to amalgamate information, preferences, expert judgments and value expressions, in support of the participatory and communicative dimensions of modern forestry. Although the potential of combining these two approaches has been demonstrated in a number of studies, methodological aspects in interfacing forest ecosystem models (FEM) and multi-criteria decision analysis (MCDA) are scarcely addressed explicitly. In this contribution we review the state of the art in FEM and MCDA in the context of FM planning and highlight some of the crucial issues when combining ecosystem and preference modeling. We discuss issues and requirements in selecting approaches suitable for supporting FM planning problems from the growing body of FEM and MCDA concepts. We furthermore identify two major challenges in a harmonized application of FEM-MCDA: (i) the design and implementation of an indicator-based analysis framework capturing ecological and social aspects and their interactions relevant for the decision process, and (ii) holistic information management that supports consistent use of different information sources, provides meta-information as well as information on uncertainties throughout the planning process.

Harnessing Ecosystem Models and Multi-Criteria Decision Analysis for the Support of Forest Management

NASA Astrophysics Data System (ADS)

Wolfslehner, Bernhard; Seidl, Rupert

2010-12-01

The decision-making environment in forest management (FM) has changed drastically during the last decades. Forest management planning is facing increasing complexity due to a widening portfolio of forest goods and services, a societal demand for a rational, transparent decision process and rising uncertainties concerning future environmental conditions (e.g., climate change). Methodological responses to these challenges include an intensified use of ecosystem models to provide an enriched, quantitative information base for FM planning. Furthermore, multi-criteria methods are increasingly used to amalgamate information, preferences, expert judgments and value expressions, in support of the participatory and communicative dimensions of modern forestry. Although the potential of combining these two approaches has been demonstrated in a number of studies, methodological aspects in interfacing forest ecosystem models (FEM) and multi-criteria decision analysis (MCDA) are scarcely addressed explicitly. In this contribution we review the state of the art in FEM and MCDA in the context of FM planning and highlight some of the crucial issues when combining ecosystem and preference modeling. We discuss issues and requirements in selecting approaches suitable for supporting FM planning problems from the growing body of FEM and MCDA concepts. We furthermore identify two major challenges in a harmonized application of FEM-MCDA: (i) the design and implementation of an indicator-based analysis framework capturing ecological and social aspects and their interactions relevant for the decision process, and (ii) holistic information management that supports consistent use of different information sources, provides meta-information as well as information on uncertainties throughout the planning process.

Mapping wildland fuels for fire management across multiple scales: integrating remote sensing, GIS, and biophysical modeling

USGS Publications Warehouse

Keane, Robert E.; Burgan, Robert E.; Van Wagtendonk, Jan W.

2001-01-01

Fuel maps are essential for computing spatial fire hazard and risk and simulating fire growth and intensity across a landscape. However, fuel mapping is an extremely difficult and complex process requiring expertise in remotely sensed image classification, fire behavior, fuels modeling, ecology, and geographical information systems (GIS). This paper first presents the challenges of mapping fuels: canopy concealment, fuelbed complexity, fuel type diversity, fuel variability, and fuel model generalization. Then, four approaches to mapping fuels are discussed with examples provided from the literature: (1) field reconnaissance; (2) direct mapping methods; (3) indirect mapping methods; and (4) gradient modeling. A fuel mapping method is proposed that uses current remote sensing and image processing technology. Future fuel mapping needs are also discussed which include better field data and fuel models, accurate GIS reference layers, improved satellite imagery, and comprehensive ecosystem models.

Enabling an Open Data Ecosystem for the Neurosciences.

PubMed

Wiener, Martin; Sommer, Friedrich T; Ives, Zachary G; Poldrack, Russell A; Litt, Brian

2016-11-02

As the pace and complexity of neuroscience data grow, an open data ecosystem must develop and grow with it to allow neuroscientists the ability to reach for new heights of discovery. However, the problems and complexities of neuroscience data sharing must first be addressed. Among the challenges facing data sharing in neuroscience, the problem of incentives, discoverability, and sustainability may be the most pressing. We here describe these problems and provide potential future solutions to help cultivate an ecosystem for data sharing. Copyright © 2016 Elsevier Inc. All rights reserved.

Relationships between Plant Diversity and the Abundance and α-Diversity of Predatory Ground Beetles (Coleoptera: Carabidae) in a Mature Asian Temperate Forest Ecosystem

PubMed Central

Zou, Yi; Sang, Weiguo; Bai, Fan; Axmacher, Jan Christoph

2013-01-01

A positive relationship between plant diversity and both abundance and diversity of predatory arthropods is postulated by the Enemies Hypothesis, a central ecological top-down control hypothesis. It has been supported by experimental studies and investigations of agricultural and grassland ecosystems, while evidence from more complex mature forest ecosystems is limited. Our study was conducted on Changbai Mountain in one of the last remaining large pristine temperate forest environments in China. We used predatory ground beetles (Coleoptera: Carabidae) as target taxon to establish the relationship between phytodiversity and their activity abundance and diversity. Results showed that elevation was the only variable included in both models predicting carabid activity abundance and α-diversity. Shrub diversity was negatively and herb diversity positively correlated with beetle abundance, while shrub diversity was positively correlated with beetle α-diversity. Within the different forest types, a negative relationship between plant diversity and carabid activity abundance was observed, which stands in direct contrast to the Enemies Hypothesis. Furthermore, plant species density did not predict carabid α-diversity. In addition, the density of herbs, which is commonly believed to influence carabid movement, had little impact on the beetle activity abundance recorded on Changbai Mountain. Our study indicates that in a relatively large and heterogeneous mature forest area, relationships between plant and carabid diversity are driven by variations in environmental factors linked with altitudinal change. In addition, traditional top-down control theories that are suitable in explaining diversity patterns in ecosystems of low diversity appear to play a much less pronounced role in highly complex forest ecosystems. PMID:24376582

Environmental conditions and prey-switching by a seabird predator impact juvenile salmon survival

USGS Publications Warehouse

Wells, Brian K.; Santora, Jarrod A.; Henderson, Mark J.; Warzybok, Pete; Jahncke, Jaime; Bradley, Russell W.; Huff, David D.; Schroeder, Isaac D.; Nelson, Peter; Field, John C.; Ainley, David G.

2017-01-01

Due to spatio-temporal variability of lower trophic-level productivity along the California Current Ecosystem (CCE), predators must be capable of switching prey or foraging areas in response to changes in environmental conditions and available forage. The Gulf of the Farallones in central California represents a biodiversity hotspot and contains the largest common murre (Uria aalge) colonies along the CCE. During spring, one of the West Coast's most important Chinook salmon (Oncorhynchus tshawytscha) populations out-migrates into the Gulf of the Farallones. We quantify the effect of predation on juvenile Chinook salmon associated with ecosystem-level variability by integrating long-term time series of environmental conditions (upwelling, river discharge), forage species abundance within central CCE, and population size, at-sea distribution, and diet of the common murre. Our results demonstrate common murres typically forage in the vicinity of their offshore breeding sites, but in years in which their primary prey, pelagic young-of-year rockfish (Sebastesspp.), are less available they forage for adult northern anchovies (Engraulis mordax) nearshore. Incidentally, while foraging inshore, common murre consumption of out-migrating juvenile Chinook salmon, which are collocated with northern anchovy, increases and population survival of the salmon is significantly reduced. Results support earlier findings that show timing and strength of upwelling, and the resultant forage fish assemblage, is related to Chinook salmon recruitment variability in the CCE, but we extend those results by demonstrating the significance of top-down impacts associated with these bottom-up dynamics. Our results demonstrate the complexity of ecosystem interactions and impacts between higher trophic-level predators and their prey, complexities necessary to quantify in order to parameterize ecosystem models and evaluate likely outcomes of ecosystem management options.

Environmental conditions and prey-switching by a seabird predator impact juvenile salmon survival

NASA Astrophysics Data System (ADS)

Wells, Brian K.; Santora, Jarrod A.; Henderson, Mark J.; Warzybok, Pete; Jahncke, Jaime; Bradley, Russell W.; Huff, David D.; Schroeder, Isaac D.; Nelson, Peter; Field, John C.; Ainley, David G.

2017-10-01

Due to spatio-temporal variability of lower trophic-level productivity along the California Current Ecosystem (CCE), predators must be capable of switching prey or foraging areas in response to changes in environmental conditions and available forage. The Gulf of the Farallones in central California represents a biodiversity hotspot and contains the largest common murre (Uria aalge) colonies along the CCE. During spring, one of the West Coast's most important Chinook salmon (Oncorhynchus tshawytscha) populations out-migrates into the Gulf of the Farallones. We quantify the effect of predation on juvenile Chinook salmon associated with ecosystem-level variability by integrating long-term time series of environmental conditions (upwelling, river discharge), forage species abundance within central CCE, and population size, at-sea distribution, and diet of the common murre. Our results demonstrate common murres typically forage in the vicinity of their offshore breeding sites, but in years in which their primary prey, pelagic young-of-year rockfish (Sebastes spp.), are less available they forage for adult northern anchovies (Engraulis mordax) nearshore. Incidentally, while foraging inshore, common murre consumption of out-migrating juvenile Chinook salmon, which are collocated with northern anchovy, increases and population survival of the salmon is significantly reduced. Results support earlier findings that show timing and strength of upwelling, and the resultant forage fish assemblage, is related to Chinook salmon recruitment variability in the CCE, but we extend those results by demonstrating the significance of top-down impacts associated with these bottom-up dynamics. Our results demonstrate the complexity of ecosystem interactions and impacts between higher trophic-level predators and their prey, complexities necessary to quantify in order to parameterize ecosystem models and evaluate likely outcomes of ecosystem management options.

Detecting Emergence of Acidification and Warming as Stressors for Coral Reef Regions using Earth System Models

NASA Astrophysics Data System (ADS)

Menendez, A. T.

2015-12-01

Coral reef ecosystems rely on complex interactions between biological, biogeochemical, and physical processes to ensure their survival and resilience. However, both human interaction and anthropogenic climate change have negatively impacted the prosperity of these regions, resulting in a crucial need to understand and predict the future of important biogeochemical and physical stressors. Contemporary changes to these relationships and environmental conditions in coral reef ecosystems are a mixture of anthropogenic contributions and natural variability (e.g. ENSO) of the climate system. To better quantify the uncertainty in future projections, it is exceedingly necessary to differentiate between these two contributors. In this study we look at acidification and warming stressors in the Galapagos, Coral Triangle, and Hawaiian islands regions. We use a suite of hindcast simulations (a 30-member large initial condition ensemble) done with an Earth Systems Model (GFDL-ESM2M) in order quantify the degree to which natural variability alters the emergence time-scales of anthropogenically-induced changes to ecosystem drivers such as pH, ΩArag, and SST. A comparison of output from a suit of CMIP5 models will be used to evaluate model uncertainty for the same regions. Simulated trends and variability in these ecosystem drivers were then compared to observed trends over the three Pacific regions. Evidently the models and observed trends proved invaluable for testing the hypothesis addressing the presence of a temporal hierarchy between emergence, defined by a signal-to-noise ratio, of acidification stressors and temperature as a stressor. Furthermore, challenges in deconvolving anthropogenic and natural contributions to stressor trends will be discussed for each of the three sites.

The Earth's Population Can Reach 14 Billion in the 23rd Century without Significant Adverse Effects on Survivability.

PubMed

Krapivin, Vladimir F; Varotsos, Costas A; Soldatov, Vladimir Yu

2017-08-07

This paper presents the results obtained from the study of the sustainable state between nature and human society on a global scale, focusing on the most critical interactions between the natural and anthropogenic processes. Apart from the conventional global models, the basic tool employed herein is the newly proposed complex model entitled "nature-society system (NSS) model", through which a reliable modeling of the processes taking place in the global climate-nature-society system (CNSS) is achieved. This universal tool is mainly based on the information technology that allows the adaptive conformance of the parametric and functional space of this model. The structure of this model includes the global biogeochemical cycles, the hydrological cycle, the demographic processes and a simple climate model. In this model, the survivability indicator is used as a criterion for the survival of humanity, which defines a trend in the dynamics of the total biomass of the biosphere, taking into account the trends of the biocomplexity dynamics of the land and hydrosphere ecosystems. It should be stressed that there are no other complex global models comparable to those of the CNSS model developed here. The potential of this global model is demonstrated through specific examples in which the classification of the terrestrial ecosystem is accomplished by separating 30 soil-plant formations for geographic pixels 4° × 5°. In addition, humanity is considered to be represented by three groups of economic development status (high, transition, developing) and the World Ocean is parameterized by three latitude zones (low, middle, high). The modelling results obtained show the dynamics of the CNSS at the beginning of the 23rd century, according to which the world population can reach the level of 14 billion without the occurrence of major negative impacts.

Some insights on grassland health assessment based on remote sensing.

PubMed

Xu, Dandan; Guo, Xulin

2015-01-29

Grassland ecosystem is one of the largest ecosystems, which naturally occurs on all continents excluding Antarctica and provides both ecological and economic functions. The deterioration of natural grassland has been attracting many grassland researchers to monitor the grassland condition and dynamics for decades. Remote sensing techniques, which are advanced in dealing with the scale constraints of ecological research and provide temporal information, become a powerful approach of grassland ecosystem monitoring. So far, grassland health monitoring studies have mostly focused on different areas, for example, productivity evaluation, classification, vegetation dynamics, livestock carrying capacity, grazing intensity, natural disaster detecting, fire, climate change, coverage assessment and soil erosion. However, the grassland ecosystem is a complex system which is formed by soil, vegetation, wildlife and atmosphere. Thus, it is time to consider the grassland ecosystem as an entity synthetically and establish an integrated grassland health monitoring system to combine different aspects of the complex grassland ecosystem. In this review, current grassland health monitoring methods, including rangeland health assessment, ecosystem health assessment and grassland monitoring by remote sensing from different aspects, are discussed along with the future directions of grassland health assessment.

Some Insights on Grassland Health Assessment Based on Remote Sensing

PubMed Central

Xu, Dandan; Guo, Xulin

2015-01-01

Grassland ecosystem is one of the largest ecosystems, which naturally occurs on all continents excluding Antarctica and provides both ecological and economic functions. The deterioration of natural grassland has been attracting many grassland researchers to monitor the grassland condition and dynamics for decades. Remote sensing techniques, which are advanced in dealing with the scale constraints of ecological research and provide temporal information, become a powerful approach of grassland ecosystem monitoring. So far, grassland health monitoring studies have mostly focused on different areas, for example, productivity evaluation, classification, vegetation dynamics, livestock carrying capacity, grazing intensity, natural disaster detecting, fire, climate change, coverage assessment and soil erosion. However, the grassland ecosystem is a complex system which is formed by soil, vegetation, wildlife and atmosphere. Thus, it is time to consider the grassland ecosystem as an entity synthetically and establish an integrated grassland health monitoring system to combine different aspects of the complex grassland ecosystem. In this review, current grassland health monitoring methods, including rangeland health assessment, ecosystem health assessment and grassland monitoring by remote sensing from different aspects, are discussed along with the future directions of grassland health assessment. PMID:25643060

Surface fuel litterfall and decomposition in the northern Rocky Mountains, U.S.A.

Treesearch

Robert E. Keane

2008-01-01

Surface fuel deposition and decomposition rates are important to fire management and research because they can define the longevity of fuel treatments in time and space and they can be used to design, build, test, and validate complex fire and ecosystem models useful in evaluating management alternatives. We determined rates of surface fuel litterfall and decomposition...

Incorporating food web dynamics into ecological restoration: a modeling approach for river ecosystems

Treesearch

J. Ryan Bellmore; Joseph R. Benjamin; Michael Newsom; Jennifer A. Bountry; Daniel Dombroski

2017-01-01

Restoration is frequently aimed at the recovery of target species, but also influences the larger food web in which these species participate. Effects of restoration on this broader network of organisms can influence target species both directly and indirectly via changes in energy flow through food webs. To help incorporate these complexities into river restoration...

Integrating forest stand projections with wildlife occupancy models to develop a decision support tool

Treesearch

Michelle F. Tacconelli; Edward F. Loewenstein

2012-01-01

Natural resource managers must often balance multiple objectives on a single property. When these objectives are seemingly conflicting, the manager’s job can be extremely difficult and complex. This paper presents a decision support tool, designed to aid land managers in optimizing wildlife habitat needs while accomplishing additional objectives such as ecosystem...

Build your own soil: exploring microfluidics to create microbial habitat structures

PubMed Central

Aleklett, Kristin; Kiers, E Toby; Ohlsson, Pelle; Shimizu, Thomas S; Caldas, Victor EA; Hammer, Edith C

2018-01-01

Soil is likely the most complex ecosystem on earth. Despite the global importance and extraordinary diversity of soils, they have been notoriously challenging to study. We show how pioneering microfluidic techniques provide new ways of studying soil microbial ecology by allowing simulation and manipulation of chemical conditions and physical structures at the microscale in soil model habitats. PMID:29135971

Predicting the spread of sudden oak death in California: spatial-temporal modeling of susceptible-infectious transitions

Treesearch

Richard D. Hunter; Ross K. Meentemeyer; David M. Rizzo; Christopher A. Gilligan

2008-01-01

The number of emerging infectious diseases is thought to be increasing worldwide - many of which are caused by non-native, invasive plant pathogens I n forest ecosystems. As new diseases continue to emerge, the ability to predict disease outbreaks is critical for effective management and prevention of epidemics, especially in complex spatially heterogeneous landscapes...

National Ecosystem Services Classification System (NESCS): Framework Design and Policy Application

EPA Science Inventory

Understanding the ways in which ecosystems provide flows of “services” to humans is critical for decision making in many contexts; however, relationships between natural and human systems are complex. A well-defined framework for classifying ecosystem services is essential for sy...

Book Review: Large-Scale Ecosystem Restoration: Five Case Studies from the United States

EPA Science Inventory

Broad-scale ecosystem restoration efforts involve a very complex set of ecological and societal components, and the success of any ecosystem restoration project rests on an integrated approach to implementation. Editors Mary Doyle and Cynthia Drew have successfully synthesized ma...

Coral identity underpins architectural complexity on Caribbean reefs.

PubMed

Alvarez-Filip, Lorenzo; Dulvy, Nicholas K; Côte, Isabelle M; Watkinson, Andrew R; Gill, Jennifer A

2011-09-01

The architectural complexity of ecosystems can greatly influence their capacity to support biodiversity and deliver ecosystem services. Understanding the components underlying this complexity can aid the development of effective strategies for ecosystem conservation. Caribbean coral reefs support and protect millions of livelihoods, but recent anthropogenic change is shifting communities toward reefs dominated by stress-resistant coral species, which are often less architecturally complex. With the regionwide decline in reef fish abundance, it is becoming increasingly important to understand changes in coral reef community structure and function. We quantify the influence of coral composition, diversity, and morpho-functional traits on the architectural complexity of reefs across 91 sites at Cozumel, Mexico. Although reef architectural complexity increases with coral cover and species richness, it is highest on sites that are low in taxonomic evenness and dominated by morpho-functionally important, reef-building coral genera, particularly Montastraea. Sites with similar coral community composition also tend to occur on reefs with very similar architectural complexity, suggesting that reef structure tends to be determined by the same key species across sites. Our findings provide support for prioritizing and protecting particular reef types, especially those dominated by key reef-building corals, in order to enhance reef complexity.

Sequencing the fungal tree of life

Treesearch

F. Martin; D. Cullen; D. Hibbett; A. Pisabarro; J.W. Spatafora; S.E. Baker; I.V. Grigoriev

2011-01-01

Terrestrial ecosystems host a complex array of interacting communities, with thousands of species of animals, plants, fungi and bacteria. In soils, this complex web of life is responsible for the cycling of carbon (C), for water and nutrients, for soil quality and for plant nutrition and health. To predict future changes of these threatened ecosystems and to fully...

Change in terrestrial ecosystem water-use efficiency over the last three decades.

PubMed

Huang, Mengtian; Piao, Shilong; Sun, Yan; Ciais, Philippe; Cheng, Lei; Mao, Jiafu; Poulter, Ben; Shi, Xiaoying; Zeng, Zhenzhong; Wang, Yingping

2015-06-01

Defined as the ratio between gross primary productivity (GPP) and evapotranspiration (ET), ecosystem-scale water-use efficiency (EWUE) is an indicator of the adjustment of vegetation photosynthesis to water loss. The processes controlling EWUE are complex and reflect both a slow evolution of plants and plant communities as well as fast adjustments of ecosystem functioning to changes of limiting resources. In this study, we investigated EWUE trends from 1982 to 2008 using data-driven models derived from satellite observations and process-oriented carbon cycle models. Our findings suggest positive EWUE trends of 0.0056, 0.0007 and 0.0001 g C m(-2)  mm(-1)  yr(-1) under the single effect of rising CO2 ('CO2 '), climate change ('CLIM') and nitrogen deposition ('NDEP'), respectively. Global patterns of EWUE trends under different scenarios suggest that (i) EWUE-CO2 shows global increases, (ii) EWUE-CLIM increases in mainly high latitudes and decreases at middle and low latitudes, (iii) EWUE-NDEP displays slight increasing trends except in west Siberia, eastern Europe, parts of North America and central Amazonia. The data-driven MTE model, however, shows a slight decline of EWUE during the same period (-0.0005 g C m(-2)  mm(-1)  yr(-1) ), which differs from process-model (0.0064 g C m(-2)  mm(-1)  yr(-1) ) simulations with all drivers taken into account. We attribute this discrepancy to the fact that the nonmodeled physiological effects of elevated CO2 reducing stomatal conductance and transpiration (TR) in the MTE model. Partial correlation analysis between EWUE and climate drivers shows similar responses to climatic variables with the data-driven model and the process-oriented models across different ecosystems. Change in water-use efficiency defined from transpiration-based WUEt (GPP/TR) and inherent water-use efficiency (IWUEt , GPP×VPD/TR) in response to rising CO2 , climate change, and nitrogen deposition are also discussed. Our analyses will facilitate mechanistic understanding of the carbon-water interactions over terrestrial ecosystems under global change. © 2015 John Wiley & Sons Ltd.

The Case Against Charge Transfer Interactions in Dissolved Organic Matter Photophysics.

PubMed

McKay, Garrett; Korak, Julie A; Erickson, Paul R; Latch, Douglas E; McNeill, Kristopher; Rosario-Ortiz, Fernando L

2018-01-16

The optical properties of dissolved organic matter influence chemical and biological processes in all aquatic ecosystems. Dissolved organic matter optical properties have been attributed to a charge-transfer model in which donor-acceptor complexes play a primary role. This model was evaluated by measuring the absorbance and fluorescence response of organic matter isolates to changes in solvent temperature, viscosity, and polarity, which affect the position and intensity of spectra for known donor-acceptor complexes of organic molecules. Absorbance and fluorescence spectral shape were largely unaffected by these changes, indicating that the distribution of absorbing and emitting species was unchanged. Overall, these results call into question the wide applicability of the charge-transfer model for explaining organic matter optical properties and suggest that future research should explore other models for dissolved organic matter photophysics.

An assessment of the impact of climate adaptation measures to reduce flood risk on ecosystem services.

PubMed

Verburg, Peter H; Koomen, Eric; Hilferink, Maarten; Pérez-Soba, Marta; Lesschen, Jan Peter

Measures of climate change adaptation often involve modification of land use and land use planning practices. Such changes in land use affect the provision of various ecosystem goods and services. Therefore, it is likely that adaptation measures may result in synergies and trade-offs between a range of ecosystems goods and services. An integrative land use modelling approach is presented to assess such impacts for the European Union. A reference scenario accounts for current trends in global drivers and includes a number of important policy developments that correspond to on-going changes in European policies. The reference scenario is compared to a policy scenario in which a range of measures is implemented to regulate flood risk and protect soils under conditions of climate change. The impacts of the simulated land use dynamics are assessed for four key indicators of ecosystem service provision: flood risk, carbon sequestration, habitat connectivity and biodiversity. The results indicate a large spatial variation in the consequences of the adaptation measures on the provisioning of ecosystem services. Synergies are frequently observed at the location of the measures itself, whereas trade-offs are found at other locations. Reducing land use intensity in specific parts of the catchment may lead to increased pressure in other regions, resulting in trade-offs. Consequently, when aggregating the results to larger spatial scales the positive and negative impacts may be off-set, indicating the need for detailed spatial assessments. The modelled results indicate that for a careful planning and evaluation of adaptation measures it is needed to consider the trade-offs accounting for the negative effects of a measure at locations distant from the actual measure. Integrated land use modelling can help land use planning in such complex trade-off evaluation by providing evidence on synergies and trade-offs between ecosystem services, different policy fields and societal demands.

Simple rules can guide whether land- or ocean-based conservation will best benefit marine ecosystems.

PubMed

Saunders, Megan I; Bode, Michael; Atkinson, Scott; Klein, Carissa J; Metaxas, Anna; Beher, Jutta; Beger, Maria; Mills, Morena; Giakoumi, Sylvaine; Tulloch, Vivitskaia; Possingham, Hugh P

2017-09-01

Coastal marine ecosystems can be managed by actions undertaken both on the land and in the ocean. Quantifying and comparing the costs and benefits of actions in both realms is therefore necessary for efficient management. Here, we quantify the link between terrestrial sediment runoff and a downstream coastal marine ecosystem and contrast the cost-effectiveness of marine- and land-based conservation actions. We use a dynamic land- and sea-scape model to determine whether limited funds should be directed to 1 of 4 alternative conservation actions-protection on land, protection in the ocean, restoration on land, or restoration in the ocean-to maximise the extent of light-dependent marine benthic habitats across decadal timescales. We apply the model to a case study for a seagrass meadow in Australia. We find that marine restoration is the most cost-effective action over decadal timescales in this system, based on a conservative estimate of the rate at which seagrass can expand into a new habitat. The optimal decision will vary in different social-ecological contexts, but some basic information can guide optimal investments to counteract land- and ocean-based stressors: (1) marine restoration should be prioritised if the rates of marine ecosystem decline and expansion are similar and low; (2) marine protection should take precedence if the rate of marine ecosystem decline is high or if the adjacent catchment is relatively intact and has a low rate of vegetation decline; (3) land-based actions are optimal when the ratio of marine ecosystem expansion to decline is greater than 1:1.4, with terrestrial restoration typically the most cost-effective action; and (4) land protection should be prioritised if the catchment is relatively intact but the rate of vegetation decline is high. These rules of thumb illustrate how cost-effective conservation outcomes for connected land-ocean systems can proceed without complex modelling.

Simple rules can guide whether land- or ocean-based conservation will best benefit marine ecosystems

PubMed Central

Bode, Michael; Atkinson, Scott; Klein, Carissa J.; Metaxas, Anna; Beher, Jutta; Beger, Maria; Mills, Morena; Giakoumi, Sylvaine; Tulloch, Vivitskaia; Possingham, Hugh P.

2017-01-01

Coastal marine ecosystems can be managed by actions undertaken both on the land and in the ocean. Quantifying and comparing the costs and benefits of actions in both realms is therefore necessary for efficient management. Here, we quantify the link between terrestrial sediment runoff and a downstream coastal marine ecosystem and contrast the cost-effectiveness of marine- and land-based conservation actions. We use a dynamic land- and sea-scape model to determine whether limited funds should be directed to 1 of 4 alternative conservation actions—protection on land, protection in the ocean, restoration on land, or restoration in the ocean—to maximise the extent of light-dependent marine benthic habitats across decadal timescales. We apply the model to a case study for a seagrass meadow in Australia. We find that marine restoration is the most cost-effective action over decadal timescales in this system, based on a conservative estimate of the rate at which seagrass can expand into a new habitat. The optimal decision will vary in different social–ecological contexts, but some basic information can guide optimal investments to counteract land- and ocean-based stressors: (1) marine restoration should be prioritised if the rates of marine ecosystem decline and expansion are similar and low; (2) marine protection should take precedence if the rate of marine ecosystem decline is high or if the adjacent catchment is relatively intact and has a low rate of vegetation decline; (3) land-based actions are optimal when the ratio of marine ecosystem expansion to decline is greater than 1:1.4, with terrestrial restoration typically the most cost-effective action; and (4) land protection should be prioritised if the catchment is relatively intact but the rate of vegetation decline is high. These rules of thumb illustrate how cost-effective conservation outcomes for connected land–ocean systems can proceed without complex modelling. PMID:28877168

Trade-offs across space, time, and ecosystem services

USGS Publications Warehouse

Rodriguez, J.P.; Beard, T.D.; Bennett, E.M.; Cumming, Graeme S.; Cork, S.J.; Agard, J.; Dobson, A.P.; Peterson, G.D.

2006-01-01

Ecosystem service (ES) trade-offs arise from management choices made by humans, which can change the type, magnitude, and relative mix of services provided by ecosystems. Trade-offs occur when the provision of one ES is reduced as a consequence of increased use of another ES. In some cases, a trade-off may be an explicit choice; but in others, trade-offs arise without premeditation or even awareness that they are taking place. Trade-offs in ES can be classified along three axes: spatial scale, temporal scale, and reversibility. Spatial scale refers to whether the effects of the trade-off are felt locally or at a distant location. Temporal scale refers to whether the effects take place relatively rapidly or slowly. Reversibility expresses the likelihood that the perturbed ES may return to its original state if the perturbation ceases. Across all four Millennium Ecosystem Assessment scenarios and selected case study examples, trade-off decisions show a preference for provisioning, regulating, or cultural services (in that order). Supporting services are more likely to be "taken for granted." Cultural ES are almost entirely unquantified in scenario modeling; therefore, the calculated model results do not fully capture losses of these services that occur in the scenarios. The quantitative scenario models primarily capture the services that are perceived by society as more important - provisioning and regulating ecosystem services - and thus do not fully capture trade-offs of cultural and supporting services. Successful management policies will be those that incorporate lessons learned from prior decisions into future management actions. Managers should complement their actions with monitoring programs that, in addition to monitoring the short-term provisions of services, also monitor the long-term evolution of slowly changing variables. Policies can then be developed to take into account ES trade-offs at multiple spatial and temporal scales. Successful strategies will recognize the inherent complexities of ecosystem management and will work to develop policies that minimize the effects of ES trade-offs. Copyright ?? 2006 by the author(s).

Combined global change effects on ecosystem processesin nine U.S. topographically complex areas

USGS Publications Warehouse

Hartman, Melannie D.; Baron, Jill S.; Ewing, Holly A.; Weathers, Kathleen

2014-01-01

Concurrent changes in climate, atmospheric nitrogen (N) deposition, and increasing levels of atmospheric carbon dioxide (CO2) affect ecosystems in complex ways. The DayCent-Chem model was used to investigate the combined effects of these human-caused drivers of change over the period 1980–2075 at seven forested montane and two alpine watersheds in the United States. Net ecosystem production (NEP) increased linearly with increasing N deposition for six out of seven forested watersheds; warming directly increased NEP at only two of these sites. Warming reduced soil organic carbon storage at all sites by increasing heterotrophic respiration. At most sites, warming together with high N deposition increased nitrous oxide (N2O) emissions enough to negate the greenhouse benefit of soil carbon sequestration alone, though there was a net greenhouse gas sink across nearly all sites mainly due to the effect of CO2 fertilization and associated sequestration by plants. Over the simulation period, an increase in atmospheric CO2 from 350 to 600 ppm was the main driver of change in net ecosystem greenhouse gas sequestration at all forested sites and one of two alpine sites, but an additional increase in CO2 from 600 to 760 ppm produced smaller effects. Warming either increased or decreased net greenhouse gas sequestration, depending on the site. The N contribution to net ecosystem greenhouse gas sequestration averaged across forest sites was only 5–7 % and was negligible for the alpine. Stream nitrate (NO3−) fluxes increased sharply with N-loading, primarily at three watersheds where initial N deposition values were high relative to terrestrial N uptake capacity. The simulated results displayed fewer synergistic responses to warming, N-loading, and CO2 fertilization than expected. Overall, simulations with DayCent-Chem suggest individual site characteristics and historical patterns of N deposition are important determinants of forest or alpine ecosystem responses to global change.

Influence of Gap-Filling to Generate Continuous Datasets on Process Network Analysis

NASA Astrophysics Data System (ADS)

Yun, J.; Kim, J.; Kim, S.; Chun, J.

2013-12-01

The interplay of environmental conditions, energy, matter, and information defines the context and constraints for the set of processes and structures that may emerge during self-organization in complex ecosystems. Following Ruddell and Kumar (2009), we have evaluated statistical measures of characterizing the organization of the information flow in ecohydrological process networks in a deciduous forest ecosystem. We used the time series data obtained in 2008 (normal year) from the KoFlux forest tower site in central Korea. The 30-minute averages of eddy fluxes of energy, water and CO2 were measured at 40m above an oak-dominated old deciduous forest along with other micrometeorological variables. In this analysis, we selected 13 variables: atmospheric pressure (Pa), net ecosystem CO2 exchange (NEE), gross primary productivity (GPP), ecosystem respiration (RE), latent heat flux (LE), precipitation (Precip), solar radiation (Rg), air temperature (T), vapor pressure deficit (VPD), sensible heat flux (H), canopy temperature (Tc), wind direction (WD), and wind speed (WS). Our results support that a process network approach can be used to formally resolve feedback, time scales, and subsystems that define the complex ecosystem's organization by considering mutual information and transfer entropy simultaneously. We also observed that the turbulent and atmospheric boundary layer subsystems are coupled through feedback loops, and form a regional self-organizing subsystem in August when the forest is in healthy environment. In particular, we noted that the observed feedback loops in the process network disappeared when the time series data were artificially gap-filled for missing data, which is a common practice in post-data processing. In this presentation, we report the influence of gap-filling on the process network analysis by artificially assigning different sizes and periods of missing data and discuss the implication of our results on validation and calibration of ecosystem models. Acknowledgment. This research was supported by the Korea Meteorological Administration Research and Development Program under Grant CATER 2013-3030.

Regional and inter-annual variability in Atlantic zooplankton en route to the Arctic Ocean: potential effects of multi-path Atlantic water advection through Fram Strait and the Barents Sea

NASA Astrophysics Data System (ADS)

Kwasniewski, Slawomir; Gluchowska, Marta; Trudnowska, Emilia; Ormanczyk, Mateusz; Walczowski, Waldemar; Beszczynska-Moeller, Agnieszka

2016-04-01

The Arctic is among the regions where the climate change effects on ecosystem will be the most rapid and consequential, with Arctic amplification recognized as an integral part of the process. Great part of the changes are forced by advection of warm waters from the North Atlantic and the expected modifications of Arctic marine ecosystem will be induced not only by changing environmental conditions but also as a result of introducing Atlantic biota. Thus, the knowledge of physical and biological heterogeneity of Atlantic inflow is requisite for understanding the effects of climate change on biological diversity and ecosystem functioning in the Arctic. The complex and variable two-branched structure of the Atlantic Water flow via Fram Strait and the Barents Sea most likely has a strong influence on the ocean biology in these regions, especially in the pelagic realm. Zooplankton are key components of marine ecosystems which form essential links between primary producers and grazer/predator consumers, thus they are important for functioning of the biological carbon pump. Changes in zooplankton distribution and abundance may have cascading effects on ecosystem functioning, with regulatory effects on climate. Based on data collected in summers of 2012-2014, within the scope of the Polish-Norwegian PAVE research project, we investigate zooplankton distribution, abundance and selected structural characteristics of communities, in relation to water mass properties in the Atlantic Water complex flow to the Arctic Ocean. The main questions addressed here are: what are the differences in zooplankton patterns between the Fram Strait and Barents Sea branches, and how does the inter-annual variability of Atlantic Water advection relate to changes in zooplankton? The results of the investigation are precondition for foreseeing changes in the pelagic realm in the Arctic Ocean and are necessary for constructing and tuning plankton components of ecosystem models.

Systems biology approach to bioremediation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chakraborty, Romy; Wu, Cindy H.; Hazen, Terry C.

2012-06-01

Bioremediation has historically been approached as a ‘black box’ in terms of our fundamental understanding. Thus it succeeds and fails, seldom without a complete understanding of why. Systems biology is an integrated research approach to study complex biological systems, by investigating interactions and networks at the molecular, cellular, community, and ecosystem level. The knowledge of these interactions within individual components is fundamental to understanding the dynamics of the ecosystem under investigation. Finally, understanding and modeling functional microbial community structure and stress responses in environments at all levels have tremendous implications for our fundamental understanding of hydrobiogeochemical processes and the potentialmore » for making bioremediation breakthroughs and illuminating the ‘black box’.« less

Integrated earth system dynamic modeling for life cycle impact assessment of ecosystem services.

PubMed

Arbault, Damien; Rivière, Mylène; Rugani, Benedetto; Benetto, Enrico; Tiruta-Barna, Ligia

2014-02-15

Despite the increasing awareness of our dependence on Ecosystem Services (ES), Life Cycle Impact Assessment (LCIA) does not explicitly and fully assess the damages caused by human activities on ES generation. Recent improvements in LCIA focus on specific cause-effect chains, mainly related to land use changes, leading to Characterization Factors (CFs) at the midpoint assessment level. However, despite the complexity and temporal dynamics of ES, current LCIA approaches consider the environmental mechanisms underneath ES to be independent from each other and devoid of dynamic character, leading to constant CFs whose representativeness is debatable. This paper takes a step forward and is aimed at demonstrating the feasibility of using an integrated earth system dynamic modeling perspective to retrieve time- and scenario-dependent CFs that consider the complex interlinkages between natural processes delivering ES. The GUMBO (Global Unified Metamodel of the Biosphere) model is used to quantify changes in ES production in physical terms - leading to midpoint CFs - and changes in human welfare indicators, which are considered here as endpoint CFs. The interpretation of the obtained results highlights the key methodological challenges to be solved to consider this approach as a robust alternative to the mainstream rationale currently adopted in LCIA. Further research should focus on increasing the granularity of environmental interventions in the modeling tools to match current standards in LCA and on adapting the conceptual approach to a spatially-explicit integrated model. Copyright © 2013 Elsevier B.V. All rights reserved.

Fogwater deposition modeling for terrestrial ecosystems: A review of developments and measurements

NASA Astrophysics Data System (ADS)

Katata, Genki

2014-07-01

Recent progress in modeling fogwater (and low cloud water) deposition over terrestrial ecosystems during fogwater droplet interception by vegetative surfaces is reviewed. Several types of models and parameterizations for fogwater deposition are discussed with comparing assumptions, input parameter requirements, and modeled processes. The relationships among deposition velocity of fogwater (Vd) in model results, wind speed, and plant species structures associated with literature values are gathered for model validation. Quantitative comparisons between model results and observations in forest environments revealed differences as large as 2 orders of magnitude, which are likely caused by uncertainties in measurement techniques over heterogeneous landscapes. Results from the literature review show that Vd values ranged from 2.1 to 8.0 cm s-1 for short vegetation, whereas Vd = 7.7-92 cm s-1 and 0-20 cm s-1 for forests measured by throughfall-based methods and the eddy covariance method, respectively. This review also discusses the current understanding of the impacts of fogwater deposition on atmosphere-land interactions and over complex terrain based on results from numerical studies. Lastly, future research priorities in innovative modeling and observational approaches for model validation are outlined.

Loss of Rare Fish Species from Tropical Floodplain Food Webs Affects Community Structure and Ecosystem Multifunctionality in a Mesocosm Experiment

PubMed Central

Pendleton, Richard M.; Hoeinghaus, David J.; Gomes, Luiz C.; Agostinho, Angelo A.

2014-01-01

Experiments with realistic scenarios of species loss from multitrophic ecosystems may improve insight into how biodiversity affects ecosystem functioning. Using 1000 L mesocoms, we examined effects of nonrandom species loss on community structure and ecosystem functioning of experimental food webs based on multitrophic tropical floodplain lagoon ecosystems. Realistic biodiversity scenarios were developed based on long-term field surveys, and experimental assemblages replicated sequential loss of rare species which occurred across all trophic levels of these complex food webs. Response variables represented multiple components of ecosystem functioning, including nutrient cycling, primary and secondary production, organic matter accumulation and whole ecosystem metabolism. Species richness significantly affected ecosystem function, even after statistically controlling for potentially confounding factors such as total biomass and direct trophic interactions. Overall, loss of rare species was generally associated with lower nutrient concentrations, phytoplankton and zooplankton densities, and whole ecosystem metabolism when compared with more diverse assemblages. This pattern was also observed for overall ecosystem multifunctionality, a combined metric representing the ability of an ecosystem to simultaneously maintain multiple functions. One key exception was attributed to time-dependent effects of intraguild predation, which initially increased values for most ecosystem response variables, but resulted in decreases over time likely due to reduced nutrient remineralization by surviving predators. At the same time, loss of species did not result in strong trophic cascades, possibly a result of compensation and complexity of these multitrophic ecosystems along with a dominance of bottom-up effects. Our results indicate that although rare species may comprise minor components of communities, their loss can have profound ecosystem consequences across multiple trophic levels due to a combination of direct and indirect effects in diverse multitrophic ecosystems. PMID:24416246

Linking definitions, mechanisms, and modeling of drought-induced tree death.

PubMed

Anderegg, William R L; Berry, Joseph A; Field, Christopher B

2012-12-01

Tree death from drought and heat stress is a critical and uncertain component in forest ecosystem responses to a changing climate. Recent research has illuminated how tree mortality is a complex cascade of changes involving interconnected plant systems over multiple timescales. Explicit consideration of the definitions, dynamics, and temporal and biological scales of tree mortality research can guide experimental and modeling approaches. In this review, we draw on the medical literature concerning human death to propose a water resource-based approach to tree mortality that considers the tree as a complex organism with a distinct growth strategy. This approach provides insight into mortality mechanisms at the tree and landscape scales and presents promising avenues into modeling tree death from drought and temperature stress. Copyright © 2012 Elsevier Ltd. All rights reserved.

Ecosystems and the Biosphere as Complex Adaptive Systems

NASA Technical Reports Server (NTRS)

Levin, Simon A.

1998-01-01

Ecosystems are prototypical examples of complex adaptive systems, in which patterns at higher levels emerge from localized interactions and selection processes acting at lower levels. An essential aspect of such systems is nonlinearity, leading to historical dependency and multiple possible outcomes of dynamics. Given this, it is essential to determine the degree to which system features are determined by environmental conditions, and the degree to which they are the result of self-organization. Furthermore, given the multiple levels at which dynamics become apparent and at which selection can act, central issues relate to how evolution shapes ecosystems properties, and whether ecosystems become buffered to changes (more resilient) over their ecological and evolutionary development or proceed to critical states and the edge of chaos.

Social-ecological outcomes in recreational fisheries: The interaction of lakeshore development and stocking

USGS Publications Warehouse

Ziegler, Jacob P.; Golebie, Elizabeth J.; Jones, Stuart E.; Weidel, Brian C.; Solomon, Christopher T.

2017-01-01

Many ecosystems continue to experience rapid transformations due to processes like land use change and resource extraction. A systems approach to maintaining natural resources focuses on how interactions and feedbacks among components of complex social‐ecological systems generate social and ecological outcomes. In recreational fisheries, residential shoreline development and fish stocking are two widespread human behaviors that influence fisheries, yet emergent social‐ecological outcomes from these potentially interacting behaviors remain under explored. We applied a social‐ecological systems framework using a simulation model and empirical data to determine whether lakeshore development is likely to promote stocking through its adverse effects on coarse woody habitat and thereby also on survival of juvenile and adult fish. We demonstrate that high lakeshore development is likely to generate dependency of the ecosystem on the social system, in the form of stocking. Further, lakeshore development can interact with social‐ecological processes to create deficits for state‐level governments, which threatens the ability to fund further ecosystem subsidies. Our results highlight the value of a social‐ecological framework for maintaining ecosystem services like recreational fisheries.

Bringing the ecosystem services concept into marine management decisions, supporting ecosystems-based management.

NASA Astrophysics Data System (ADS)

Tweddle, J. F.; Byg, A.; Davies, I.; Gubbins, M.; Irvine, K.; Kafas, A.; Kenter, J.; MacDonald, A.; Murray, R. B. O.; Potts, T.; Slater, A. M.; Wright, K.; Scott, B. E.

2016-02-01

The marine environment is under increasing use, putting pressure on marine ecosystems and increasing competition for space. New activities (e.g. renewable energy developments), evolving marine policies (e.g. implementation of marine protected areas), and climate change may drive changes in biodiversity and resulting ecosystem services (ES) that society and business utilise from coastal and marine systems. A process is needed that integrates ecological assessment of changes with stakeholder perceptions and valuation of ES, whilst balancing ease of application with the ability to deal with complex social-economic-ecological issues. The project "Cooperative participatory assessment of the impact of renewable technology on ecosystem services: CORPORATES" involved natural and social scientists, law and policy experts, and marine managers, with the aim of promoting more integrated decision making using ES concepts in marine management. CORPORATES developed a process to bring ES concepts into stakeholders' awareness. The interactive process, involving 2 workshops, employs interludes of knowledge exchange by experts on ecological processes underpinning ES and on law and policy. These enable mapping of benefits linked to activities, participatory system modelling, and deliberation of policy impacts on different sectors. The workshops were attended by industry representatives, regulatory/advisory partners, and other stakeholders (NGOs, SMEs, recreationalists, local government). Mixed sector groups produced new insights into links between activities and ES, and highlighted cross-sector concerns. Here we present the aspects of the process that successfully built shared understanding between industry and stakeholders of inter-linkages and interactions between ES, benefits, activities, and economic and cultural values. These methods provide an ES-based decision-support model for exchanging societal-ecological knowledge and providing stakeholder interaction in marine planning, supporting ecosystem-based management.

Bringing the ecosystem services concept into marine management decisions, supporting ecosystems-based management.

NASA Astrophysics Data System (ADS)

Tweddle, J. F.; Byg, A.; Davies, I.; Gubbins, M.; Irvine, K.; Kafas, A.; Kenter, J.; MacDonald, A.; Murray, R. B. O.; Potts, T.; Slater, A. M.; Wright, K.; Scott, B. E.

2016-12-01

The marine environment is under increasing use, putting pressure on marine ecosystems and increasing competition for space. New activities (e.g. renewable energy developments), evolving marine policies (e.g. implementation of marine protected areas), and climate change may drive changes in biodiversity and resulting ecosystem services (ES) that society and business utilise from coastal and marine systems. A process is needed that integrates ecological assessment of changes with stakeholder perceptions and valuation of ES, whilst balancing ease of application with the ability to deal with complex social-economic-ecological issues. The project "Cooperative participatory assessment of the impact of renewable technology on ecosystem services: CORPORATES" involved natural and social scientists, law and policy experts, and marine managers, with the aim of promoting more integrated decision making using ES concepts in marine management. CORPORATES developed a process to bring ES concepts into stakeholders' awareness. The interactive process, involving 2 workshops, employs interludes of knowledge exchange by experts on ecological processes underpinning ES and on law and policy. These enable mapping of benefits linked to activities, participatory system modelling, and deliberation of policy impacts on different sectors. The workshops were attended by industry representatives, regulatory/advisory partners, and other stakeholders (NGOs, SMEs, recreationalists, local government). Mixed sector groups produced new insights into links between activities and ES, and highlighted cross-sector concerns. Here we present the aspects of the process that successfully built shared understanding between industry and stakeholders of inter-linkages and interactions between ES, benefits, activities, and economic and cultural values. These methods provide an ES-based decision-support model for exchanging societal-ecological knowledge and providing stakeholder interaction in marine planning, supporting ecosystem-based management.

Microbial Mat Compositional and Functional Sensitivity to Environmental Disturbance

PubMed Central

Preisner, Eva C.; Fichot, Erin B.; Norman, Robert S.

2016-01-01

The ability of ecosystems to adapt to environmental perturbations depends on the duration and intensity of change and the overall biological diversity of the system. While studies have indicated that rare microbial taxa may provide a biological reservoir that supports long-term ecosystem stability, how this dynamic population is influenced by environmental parameters remains unclear. In this study, a microbial mat ecosystem located on San Salvador Island, The Bahamas was used as a model to examine how environmental disturbance affects the protein synthesis potential (PSP) of rare and abundant archaeal and bacterial communities and how these changes impact potential biogeochemical processes. This ecosystem experienced a large shift in salinity (230 to 65 g kg-1) during 2011–2012 following the landfall of Hurricane Irene on San Salvador Island. High throughput sequencing and analysis of 16S rRNA and rRNA genes from samples before and after the pulse disturbance showed significant changes in the diversity and PSP of abundant and rare taxa, suggesting overall compositional and functional sensitivity to environmental change. In both archaeal and bacterial communities, while the majority of taxa showed low PSP across conditions, the overall community PSP increased post-disturbance, with significant shifts occurring among abundant and rare taxa across and within phyla. Broadly, following the post-disturbance reduction in salinity, taxa within Halobacteria decreased while those within Crenarchaeota, Thaumarchaeota, Thermoplasmata, Cyanobacteria, and Proteobacteria, increased in abundance and PSP. Quantitative PCR of genes and transcripts involved in nitrogen and sulfur cycling showed concomitant shifts in biogeochemical cycling potential. Post-disturbance conditions increased the expression of genes involved in N-fixation, nitrification, denitrification, and sulfate reduction. Together, our findings show complex community adaptation to environmental change and help elucidate factors connecting disturbance, biodiversity, and ecosystem function that may enhance ecosystem models. PMID:27799927

The Influence of Mean Trophic Level on Biomass and Production in Marine Ecosystems

NASA Astrophysics Data System (ADS)

Woodson, C. B.; Schramski, J.

2016-02-01

The oceans have faced rapid removal of top predators causing a reduction in the mean trophic level of many marine ecosystems due to fishing down the food web. However, estimating the pre-exploitation biomass of the ocean has been difficult. Historical population sizes have been estimated using population dynamics models, archaeological or historical records, fisheries data, living memory, ecological monitoring data, genetics, and metabolic theory. In this talk, we expand on the use of metabolic theory by including complex trophic webs to estimate pre-exploitation levels of marine biomass. Our results suggest that historical marine biomass could be as much as 10 times higher than current estimates and that the total carrying capacity of the ocean is sensitive to mean trophic level and trophic web complexity. We further show that the production levels needed to support the added biomass are possible due to biomass accumulation and predator-prey overlap in regions such as fronts. These results have important implications for marine biogeochemical cycling, fisheries management, and conservation efforts.

Progression in Complexity: Contextualizing Sustainable Marine Resources Management in a 10th Grade Classroom

NASA Astrophysics Data System (ADS)

Bravo-Torija, Beatriz; Jiménez-Aleixandre, María-Pilar

2012-01-01

Sustainable management of marine resources raises great challenges. Working with this socio-scientific issue in the classroom requires students to apply complex models about energy flow and trophic pyramids in order to understand that food chains represent transfer of energy, to construct meanings for sustainable resources management through discourse, and to connect them to actions and decisions in a real-life context. In this paper we examine the process of elaboration of plans for resources management in a marine ecosystem by 10th grade students (15-16 year) in the context of solving an authentic task. A complete class ( N = 14) worked in a sequence about ecosystems. Working in small groups, the students made models of energy flow and trophic pyramids, and used them to solve the problem of feeding a small community for a long time. Data collection included videotaping and audiotaping of all of the sessions, and collecting the students' written productions. The research objective is to examine the process of designing a plan for sustainable resources management in terms of the discursive moves of the students across stages in contextualizing practices, or different degrees of complexity (Jiménez-Aleixandre & Reigosa International Journal of Science Education, 14(1): 51-61 2006), understood as transformations from theoretical statements to decisions about the plan. The analysis of students' discursive moves shows how the groups progressed through stages of connecting different models, between them and with the context, in order to solve the task. The challenges related to taking this sustainability issue to the classroom are discussed.

Before the Endless Forms: Embodied Model of Transition from Single Cells to Aggregates to Ecosystem Engineering

PubMed Central

Solé, Ricard V.; Valverde, Sergi

2013-01-01

The emergence of complex multicellular systems and their associated developmental programs is one of the major problems of evolutionary biology. The advantages of cooperation over individuality seem well known but it is not clear yet how such increase of complexity emerged from unicellular life forms. Current multicellular systems display a complex cell-cell communication machinery, often tied to large-scale controls of body size or tissue homeostasis. Some unicellular life forms are simpler and involve groups of cells cooperating in a tissue-like fashion, as it occurs with biofilms. However, before true gene regulatory interactions were widespread and allowed for controlled changes in cell phenotypes, simple cellular colonies displaying adhesion and interacting with their environments were in place. In this context, models often ignore the physical embedding of evolving cells, thus leaving aside a key component. The potential for evolving pre-developmental patterns is a relevant issue: how far a colony of evolving cells can go? Here we study these pre-conditions for morphogenesis by using CHIMERA, a physically embodied computational model of evolving virtual organisms in a pre-Mendelian world. Starting from a population of identical, independent cells moving in a fluid, the system undergoes a series of changes, from spatial segregation, increased adhesion and the development of generalism. Eventually, a major transition occurs where a change in the flow of nutrients is triggered by a sub-population. This ecosystem engineering phenomenon leads to a subsequent separation of the ecological network into two well defined compartments. The relevance of these results for evodevo and its potential ecological triggers is discussed. PMID:23596506

The Naïve Overfitting Index Selection (NOIS): A new method to optimize model complexity for hyperspectral data

NASA Astrophysics Data System (ADS)

Rocha, Alby D.; Groen, Thomas A.; Skidmore, Andrew K.; Darvishzadeh, Roshanak; Willemen, Louise

2017-11-01

The growing number of narrow spectral bands in hyperspectral remote sensing improves the capacity to describe and predict biological processes in ecosystems. But it also poses a challenge to fit empirical models based on such high dimensional data, which often contain correlated and noisy predictors. As sample sizes, to train and validate empirical models, seem not to be increasing at the same rate, overfitting has become a serious concern. Overly complex models lead to overfitting by capturing more than the underlying relationship, and also through fitting random noise in the data. Many regression techniques claim to overcome these problems by using different strategies to constrain complexity, such as limiting the number of terms in the model, by creating latent variables or by shrinking parameter coefficients. This paper is proposing a new method, named Naïve Overfitting Index Selection (NOIS), which makes use of artificially generated spectra, to quantify the relative model overfitting and to select an optimal model complexity supported by the data. The robustness of this new method is assessed by comparing it to a traditional model selection based on cross-validation. The optimal model complexity is determined for seven different regression techniques, such as partial least squares regression, support vector machine, artificial neural network and tree-based regressions using five hyperspectral datasets. The NOIS method selects less complex models, which present accuracies similar to the cross-validation method. The NOIS method reduces the chance of overfitting, thereby avoiding models that present accurate predictions that are only valid for the data used, and too complex to make inferences about the underlying process.

Implementations of back propagation algorithm in ecosystems applications

NASA Astrophysics Data System (ADS)

Ali, Khalda F.; Sulaiman, Riza; Elamir, Amir Mohamed

2015-05-01

Artificial Neural Networks (ANNs) have been applied to an increasing number of real world problems of considerable complexity. Their most important advantage is in solving problems which are too complex for conventional technologies, that do not have an algorithmic solutions or their algorithmic Solutions is too complex to be found. In general, because of their abstraction from the biological brain, ANNs are developed from concept that evolved in the late twentieth century neuro-physiological experiments on the cells of the human brain to overcome the perceived inadequacies with conventional ecological data analysis methods. ANNs have gained increasing attention in ecosystems applications, because of ANN's capacity to detect patterns in data through non-linear relationships, this characteristic confers them a superior predictive ability. In this research, ANNs is applied in an ecological system analysis. The neural networks use the well known Back Propagation (BP) Algorithm with the Delta Rule for adaptation of the system. The Back Propagation (BP) training Algorithm is an effective analytical method for adaptation of the ecosystems applications, the main reason because of their capacity to detect patterns in data through non-linear relationships. This characteristic confers them a superior predicting ability. The BP algorithm uses supervised learning, which means that we provide the algorithm with examples of the inputs and outputs we want the network to compute, and then the error is calculated. The idea of the back propagation algorithm is to reduce this error, until the ANNs learns the training data. The training begins with random weights, and the goal is to adjust them so that the error will be minimal. This research evaluated the use of artificial neural networks (ANNs) techniques in an ecological system analysis and modeling. The experimental results from this research demonstrate that an artificial neural network system can be trained to act as an expert ecosystem analyzer for many applications in ecological fields. The pilot ecosystem analyzer shows promising ability for generalization and requires further tuning and refinement of the basis neural network system for optimal performance.

Trophic flows, ecosystem structure and fishing impacts in the South Catalan Sea, Northwestern Mediterranean

NASA Astrophysics Data System (ADS)

Coll, Marta; Palomera, Isabel; Tudela, Sergi; Sardà, Francesc

2006-01-01

An exploited ecosystem from the continental shelf and upper slope of the Northwestern Mediterranean Sea was described by means of an Ecopath mass-balance model with the aim of characterising its functioning and structure and describing the ecosystem impacts of fishing. This application included some complexities added to the general modelling methodology due to the high biodiversity of the Mediterranean Sea and the multispecific nature of the fishery, and to the difficulties of working with fishing data which are usually irregularly or imprecisely collected. The model comprised 40 functional groups including primary producers, the main species of benthic, demersal and pelagic invertebrates, fishes and non-fish vertebrates and three detritus groups. In addition, trawling, purse seine, longline and troll bait fishing fleets were included. Results showed that the functional groups were organized into four trophic levels with the highest levels corresponding to anglerfish, dolphins, large pelagic fishes and adult hake. The system was dominated by the pelagic fraction, where sardine and anchovy prevailed in terms of fish biomasses and catches. Detritus and detritivorous groups also played key roles in the ecosystem and important coupled pelagic-demersal interactions were described. Considering Odum's theory of ecosystem development, the ecosystem was placed on an intermediate-low developmental stage due, at least partially, to the impact of fishing activity. This highlighted the high intensity of fishing in the ecosystem, in accordance with the general assessment of western Mediterranean marine resources, and fishing fleets were ranked as top predators of the system. The low trophic level of the catch was in line with the long history of exploitation in the area. However, the steady decline of pelagic landings between 1994 and 2003, coupled with a decrease of the pelagic biomass within the system, underlined the low resistance of the system in front of perturbations. This decline was reproduced under Ecosim dynamic simulations combining different scenarios of moderate increase of fishing effort and an environmental forcing affecting the availability of preys to small and medium-sized pelagic fishes under wasp-waist flow control.

Changes in Arctic and Boreal ecosystems of North America: Integrating Recent Results from the Field, Remote Sensing and Ecosystem Models

NASA Astrophysics Data System (ADS)

Goetz, S. J.; Rogers, B. M.; Mack, M. C.; Goulden, M.; Pastick, N. J.; Berner, L. T.; Fisher, J.

2017-12-01

The Arctic and boreal forest biomes have global significance in terms of climate feedbacks associated with land surface interactions with the atmosphere. Changes in Arctic tundra and boreal forest ecosystem productivity and fire disturbance feedbacks have been well documented in recent years, but findings are often only locally relevant and are sometimes inconsistent among research teams. Part of these inconsistencies lie in utilization of different data sets and time periods considered. Integrated approaches are thus needed to adequately address changes in these ecosystems in order to assess consistency and variability of change, as well as ecosystem vulnerability and resiliency across spatial and temporal scales. Ultimately this can best be accomplished via multiple lines of evidence including remote sensing, field measurements and various types of data-constrained models. We will discuss some recent results integrating multiple lines of evidence for directional ecosystem change in the Arctic and boreal forest biomes of North America. There is increasing evidence for widespread spatial and temporal variability in Arctic and boreal ecosystem productivity changes that are strongly influenced by cycles of changing fire disturbance severity and its longer-term implications (i.e legacy effects). Integrated, multi-approach research, like that currently underway as part of the NASA-led Arctic Boreal Vulnerability Experiment (above.nasa.gov), is an effective way to capture the complex mechanisms that drive patterns and directionality of ecosystem structure and function, and ultimately determine feedbacks to environmental change, particularly in the context of global climate change. Additional ongoing ABoVE research will improve our understanding of the consequences of environmental changes underway, as well as increase our confidence in making projections of the ecosystem responses, vulnerability and resilience to change. ABoVE will also build a lasting legacy of collaboration through an expanded knowledge base, provision of key datasets to a broader network of researchers and resource managers, and the development of data products and knowledge designed to foster decision support and applied research partnerships with broad societal relevance.

Stochastic simulations of a synthetic bacteria-yeast ecosystem

PubMed Central

2012-01-01

Background The field of synthetic biology has greatly evolved and numerous functions can now be implemented by artificially engineered cells carrying the appropriate genetic information. However, in order for the cells to robustly perform complex or multiple tasks, co-operation between them may be necessary. Therefore, various synthetic biological systems whose functionality requires cell-cell communication are being designed. These systems, microbial consortia, are composed of engineered cells and exhibit a wide range of behaviors. These include yeast cells whose growth is dependent on one another, or bacteria that kill or rescue each other, synchronize, behave as predator-prey ecosystems or invade cancer cells. Results In this paper, we study a synthetic ecosystem comprising of bacteria and yeast that communicate with and benefit from each other using small diffusible molecules. We explore the behavior of this heterogeneous microbial consortium, composed of Saccharomyces cerevisiae and Escherichia coli cells, using stochastic modeling. The stochastic model captures the relevant intra-cellular and inter-cellular interactions taking place in and between the eukaryotic and prokaryotic cells. Integration of well-characterized molecular regulatory elements into these two microbes allows for communication through quorum sensing. A gene controlling growth in yeast is induced by bacteria via chemical signals and vice versa. Interesting dynamics that are common in natural ecosystems, such as obligatory and facultative mutualism, extinction, commensalism and predator-prey like dynamics are observed. We investigate and report on the conditions under which the two species can successfully communicate and rescue each other. Conclusions This study explores the various behaviors exhibited by the cohabitation of engineered yeast and bacterial cells. The way that the model is built allows for studying the dynamics of any system consisting of two species communicating with one another via chemical signals. Therefore, key information acquired by our model may potentially drive the experimental design of various synthetic heterogeneous ecosystems. PMID:22672814

Linking genes to ecosystem trace gas fluxes in a large-scale model system

NASA Astrophysics Data System (ADS)

Meredith, L. K.; Cueva, A.; Volkmann, T. H. M.; Sengupta, A.; Troch, P. A.

2017-12-01

Soil microorganisms mediate biogeochemical cycles through biosphere-atmosphere gas exchange with significant impact on atmospheric trace gas composition. Improving process-based understanding of these microbial populations and linking their genomic potential to the ecosystem-scale is a challenge, particularly in soil systems, which are heterogeneous in biodiversity, chemistry, and structure. In oligotrophic systems, such as the Landscape Evolution Observatory (LEO) at Biosphere 2, atmospheric trace gas scavenging may supply critical metabolic needs to microbial communities, thereby promoting tight linkages between microbial genomics and trace gas utilization. This large-scale model system of three initially homogenous and highly instrumented hillslopes facilitates high temporal resolution characterization of subsurface trace gas fluxes at hundreds of sampling points, making LEO an ideal location to study microbe-mediated trace gas fluxes from the gene to ecosystem scales. Specifically, we focus on the metabolism of ubiquitous atmospheric reduced trace gases hydrogen (H2), carbon monoxide (CO), and methane (CH4), which may have wide-reaching impacts on microbial community establishment, survival, and function. Additionally, microbial activity on LEO may facilitate weathering of the basalt matrix, which can be studied with trace gas measurements of carbonyl sulfide (COS/OCS) and carbon dioxide (O-isotopes in CO2), and presents an additional opportunity for gene to ecosystem study. This work will present initial measurements of this suite of trace gases to characterize soil microbial metabolic activity, as well as links between spatial and temporal variability of microbe-mediated trace gas fluxes in LEO and their relation to genomic-based characterization of microbial community structure (phylogenetic amplicons) and genetic potential (metagenomics). Results from the LEO model system will help build understanding of the importance of atmospheric inputs to microorganisms pioneering fresh mineral matrix. Additionally, the measurement and modeling techniques that will be developed at LEO will be relevant for other investigators linking microbial genomics to ecosystem function in more well-developed soils with greater complexity.

High-resolution modeling of a marine ecosystem using the FRESCO hydroecological model

NASA Astrophysics Data System (ADS)

Zalesny, V. B.; Tamsalu, R.

2009-02-01

The FRESCO (Finnish Russian Estonian Cooperation) mathematical model describing a marine hydroecosystem is presented. The methodology of the numerical solution is based on the method of multicomponent splitting into physical and biological processes, spatial coordinates, etc. The model is used for the reproduction of physical and biological processes proceeding in the Baltic Sea. Numerical experiments are performed with different spatial resolutions for four marine basins that are enclosed into one another: the Baltic Sea, the Gulf of Finland, the Tallinn-Helsinki water area, and Tallinn Bay. Physical processes are described by the equations of nonhydrostatic dynamics, including the k-ω parametrization of turbulence. Biological processes are described by the three-dimensional equations of an aquatic ecosystem with the use of a size-dependent parametrization of biochemical reactions. The main goal of this study is to illustrate the efficiency of the developed numerical technique and to demonstrate the importance of a high spatial resolution for water basins that have complex bottom topography, such as the Baltic Sea. Detailed information about the atmospheric forcing, bottom topography, and coastline is very important for the description of coastal dynamics and specific features of a marine ecosystem. Experiments show that the spatial inhomogeneity of hydroecosystem fields is caused by the combined effect of upwelling, turbulent mixing, surface-wave breaking, and temperature variations, which affect biochemical reactions.

A Data-Driven Assessment of the Sensitivity of Global Ecosystems to Climate Anomalies

NASA Astrophysics Data System (ADS)

Miralles, D. G.; Papagiannopoulou, C.; Demuzere, M.; Decubber, S.; Waegeman, W.; Verhoest, N.; Dorigo, W.

2017-12-01

Vegetation is a central player in the climate system, constraining atmospheric conditions through a series of feedbacks. This fundamental role highlights the importance of understanding regional drivers of ecological sensitivity and the response of vegetation to climatic changes. While nutrient availability and short-term disturbances can be crucial for vegetation at various spatiotemporal scales, natural vegetation dynamics are overall driven by climate. At monthly scales, the interactions between vegetation and climate become complex: some vegetation types react preferentially to specific climatic changes, with different levels of intensity, resilience and lagged response. For our current Earth System Models (ESMs) being able to capture this complexity is crucial but extremely challenging. This adds uncertainty to our projections of future climate and the fate of global ecosystems. Here, following a Granger causality framework based on a non-linear random forest predictive model, we exploit the current wealth of satellite data records to uncover the main climatic drivers of monthly vegetation variability globally. Results based on three decades of satellite data indicate that water availability is the most dominant factor driving vegetation in over 60% of the vegetated land. This overall dependency of ecosystems on water availability is larger than previously reported, partly owed to the ability of our machine-learning framework to disentangle the co-linearites between climatic drivers, and to quantify non-linear impacts of climate on vegetation. Our observation-based results are then used to benchmark ESMs on their representation of vegetation sensitivity to climate and climatic extremes. Our findings indicate that the sensitivity of vegetation to climatic anomalies is ill-reproduced by some widely-used ESMs.

Scaling hyporheic exchange and its influence on biogeochemical reactions in aquatic ecosystems

USGS Publications Warehouse

O'Connor, Ben L.; Harvey, Judson W.

2008-01-01

Hyporheic exchange and biogeochemical reactions are difficult to quantify because of the range in fluid‐flow and sediment conditions inherent to streams, wetlands, and nearshore marine ecosystems. Field measurements of biogeochemical reactions in aquatic systems are impeded by the difficulty of measuring hyporheic flow simultaneously with chemical gradients in sediments. Simplified models of hyporheic exchange have been developed using Darcy's law generated by flow and bed topography at the sediment‐water interface. However, many modes of transport are potentially involved (molecular diffusion, bioturbation, advection, shear, bed mobility, and turbulence) with even simple models being difficult to apply in complex natural systems characterized by variable sediment sizes and irregular bed geometries. In this study, we synthesize information from published hyporheic exchange investigations to develop a scaling relationship for estimating mass transfer in near‐surface sediments across a range in fluid‐flow and sediment conditions. Net hyporheic exchange was quantified using an effective diffusion coefficient (De) that integrates all of the various transport processes that occur simultaneously in sediments, and dimensional analysis was used to scale De to shear stress velocity, roughness height, and permeability that describe fluid‐flow and sediment characteristics. We demonstrated the value of the derived scaling relationship by using it to quantify dissolved oxygen (DO) uptake rates on the basis of DO profiles in sediments and compared them to independent flux measurements. The results support a broad application of the De scaling relationship for quantifying coupled hyporheic exchange and biogeochemical reaction rates in streams and other aquatic ecosystems characterized by complex fluid‐flow and sediment conditions.

Application of in-situ bioassays with macrophytes in aquatic mesocosm studies.

PubMed

Coors, Anja; Kuckelkorn, Jochen; Hammers-Wirtz, Monika; Strauss, Tido

2006-10-01

Aquatic mesocosm studies assess ecotoxicological effects of chemicals by using small artificial ponds as models of lentic ecosystems. In this study, methods of controlled insertion of macrophytes within an outdoor mesocosm study were explored. Although analytically confirmed concentrations of the model herbicide terbuthylazine were high enough to expect direct effects on phytoplankton, functional parameters and dominant taxa abundance indicated only minor and transient effects. In-situ assays with Lemna minor, Myriophyllum spicatum, Potamogeton lucens and Chara globularis revealed adverse effects at concentrations in accordance with literature data. Complex interactions such as nutrient limitation and competition were possible reasons for the observed growth promotion at the lower concentration of about 5 microg/l terbuthylazine. The approach of macrophyte in-situ bioassays within a mesocosm study proved to be applicable. Presumed advantages are simultaneous acquisition of toxicity data for several species of aquatic plants under more realistic conditions compared to laboratory tests and inclusion of macrophytes as important structural and functional components in mesocosms while limiting their domination of the model ecosystem.

Spatial Patterns in Herbivory on a Coral Reef Are Influenced by Structural Complexity but Not by Algal Traits

PubMed Central

Vergés, Adriana; Vanderklift, Mathew A.; Doropoulos, Christopher; Hyndes, Glenn A.

2011-01-01

Background Patterns of herbivory can alter the spatial structure of ecosystems, with important consequences for ecosystem functions and biodiversity. While the factors that drive spatial patterns in herbivory in terrestrial systems are well established, comparatively less is known about what influences the distribution of herbivory in coral reefs. Methodology and Principal Findings We quantified spatial patterns of macroalgal consumption in a cross-section of Ningaloo Reef (Western Australia). We used a combination of descriptive and experimental approaches to assess the influence of multiple macroalgal traits and structural complexity in establishing the observed spatial patterns in macroalgal herbivory, and to identify potential feedback mechanisms between herbivory and macroalgal nutritional quality. Spatial patterns in macroalgal consumption were best explained by differences in structural complexity among habitats. The biomass of herbivorous fish, and rates of herbivory were always greater in the structurally-complex coral-dominated outer reef and reef flat habitats, which were also characterised by high biomass of herbivorous fish, low cover and biomass of macroalgae and the presence of unpalatable algae species. Macroalgal consumption decreased to undetectable levels within 75 m of structurally-complex reef habitat, and algae were most abundant in the structurally-simple lagoon habitats, which were also characterised by the presence of the most palatable algae species. In contrast to terrestrial ecosystems, herbivory patterns were not influenced by the distribution, productivity or nutritional quality of resources (macroalgae), and we found no evidence of a positive feedback between macroalgal consumption and the nitrogen content of algae. Significance This study highlights the importance of seascape-scale patterns in structural complexity in determining spatial patterns of macroalgal consumption by fish. Given the importance of herbivory in maintaining the ability of coral reefs to reorganise and retain ecosystem functions following disturbance, structural complexity emerges as a critical feature that is essential for the healthy functioning of these ecosystems. PMID:21347254

Understanding the structure and functioning of polar pelagic ecosystems to predict the impacts of change

PubMed Central

Drinkwater, K. F.; Grant, S. M.; Heymans, J. J.; Hofmann, E. E.; Hunt, G. L.; Johnston, N. M.

2016-01-01

The determinants of the structure, functioning and resilience of pelagic ecosystems across most of the polar regions are not well known. Improved understanding is essential for assessing the value of biodiversity and predicting the effects of change (including in biodiversity) on these ecosystems and the services they maintain. Here we focus on the trophic interactions that underpin ecosystem structure, developing comparative analyses of how polar pelagic food webs vary in relation to the environment. We highlight that there is not a singular, generic Arctic or Antarctic pelagic food web, and, although there are characteristic pathways of energy flow dominated by a small number of species, alternative routes are important for maintaining energy transfer and resilience. These more complex routes cannot, however, provide the same rate of energy flow to highest trophic-level species. Food-web structure may be similar in different regions, but the individual species that dominate mid-trophic levels vary across polar regions. The characteristics (traits) of these species are also different and these differences influence a range of food-web processes. Low functional redundancy at key trophic levels makes these ecosystems particularly sensitive to change. To develop models for projecting responses of polar ecosystems to future environmental change, we propose a conceptual framework that links the life histories of pelagic species and the structure of polar food webs. PMID:27928038

Understanding the structure and functioning of polar pelagic ecosystems to predict the impacts of change.

PubMed

Murphy, E J; Cavanagh, R D; Drinkwater, K F; Grant, S M; Heymans, J J; Hofmann, E E; Hunt, G L; Johnston, N M

2016-12-14

The determinants of the structure, functioning and resilience of pelagic ecosystems across most of the polar regions are not well known. Improved understanding is essential for assessing the value of biodiversity and predicting the effects of change (including in biodiversity) on these ecosystems and the services they maintain. Here we focus on the trophic interactions that underpin ecosystem structure, developing comparative analyses of how polar pelagic food webs vary in relation to the environment. We highlight that there is not a singular, generic Arctic or Antarctic pelagic food web, and, although there are characteristic pathways of energy flow dominated by a small number of species, alternative routes are important for maintaining energy transfer and resilience. These more complex routes cannot, however, provide the same rate of energy flow to highest trophic-level species. Food-web structure may be similar in different regions, but the individual species that dominate mid-trophic levels vary across polar regions. The characteristics (traits) of these species are also different and these differences influence a range of food-web processes. Low functional redundancy at key trophic levels makes these ecosystems particularly sensitive to change. To develop models for projecting responses of polar ecosystems to future environmental change, we propose a conceptual framework that links the life histories of pelagic species and the structure of polar food webs. © 2016 The Authors.

Potential effects of climate change on aquatic ecosystems of the Great Plains of North America

USGS Publications Warehouse

Covich, A.P.; Fritz, S.C.; Lamb, P.J.; Marzolf, R.D.; Matthews, W.J.; Poiani, K.A.; Prepas, E.E.; Richman, M.B.; Winter, T.C.

1997-01-01

The Great Plains landscape is less topographically complex than most other regions within North America, but diverse aquatic ecosystems, such as playas, pothole lakes, ox-bow lakes, springs, groundwater aquifers, intermittent and ephemeral streams, as well as large rivers and wetlands, are highly dynamic and responsive to extreme climatic fluctuations. We review the evidence for climatic change that demonstrates the historical importance of extremes in north-south differences in summer temperatures and east-west differences in aridity across four large subregions. These physical driving forces alter density stratification, deoxygenation, decomposition and salinity. Biotic community composition and associated ecosystem processes of productivity and nutrient cycling respond rapidly to these climatically driven dynamics. Ecosystem processes also respond to cultural effects such as dams and diversions of water for irrigation, waste dilution and urban demands for drinking water and industrial uses. Distinguishing climatic from cultural effects in future models of aquatic ecosystem functioning will require more refinement in both climatic and economic forecasting. There is a need, for example, to predict how long-term climatic forecasts (based on both ENSO and global warming simulations) relate to the permanence and productivity of shallow water ecosystems. Aquatic ecologists, hydrologists, climatologists and geographers have much to discuss regarding the synthesis of available data and the design of future interdisciplinary research. ?? 1997 by John Wiley & Sons, Ltd.

Low functional richness and redundancy of a predator assemblage in native forest fragments of Chiloe island, Chile.

PubMed

Farias, Ariel A; Jaksic, Fabian M

2011-07-01

1. Changes in land use and habitat fragmentation are major drivers of global change, and studying their effects on biodiversity constitutes a major research programme. However, biodiversity is a multifaceted concept, with a functional component linking species richness to ecosystem function. Currently, the interaction between functional and taxonomic components of biodiversity under realistic scenarios of habitat degradation is poorly understood. 2. The expected functional richness (FR)-species richness relationship (FRSR) is positive, and attenuated for functional redundancy in species-rich assemblages. Further, environmental filters are expected to flatten that association by sorting species with similar traits. Thus, analysing FRSR can inform about the response of biodiversity to environmental gradients and habitat fragmentation, and its expected functional consequences. 3. Top predators affect ecosystem functioning through prey consumption and are particularly vulnerable to changes in land use and habitat fragmentation, being good indicators of ecosystem health and suitable models for assessing the effects of habitat fragmentation on their FR. 4. Thus, this study analyses the functional redundancy of a vertebrate predator assemblage at temperate forest fragments in a rural landscape of Chiloe island (Chile), testing the existence of environmental filters by contrasting an empirically derived FRSR against those predicted from null models, and testing the association between biodiversity components and the structure of forest fragments. 5. Overall, contrasts against null models indicate that regional factors determine low levels of FR and redundancy for the vertebrate predator assemblage studied, while recorded linear FRSR indicates proportional responses of the two biodiversity components to the structure of forest fragments. Further, most species were positively associated with either fragment size or shape complexity, which are highly correlated. This, and the absence of ecological filters at the single-fragment scale, rendered taxonomically and functionally richer predator assemblages at large complex-shaped fragments. 6. These results predict strong effects of deforestation on both components of biodiversity, potentially affecting the functioning of remnants of native temperate forest ecosystems. Thus, the present study assesses general responses of functional and taxonomic components of biodiversity to a specific human-driven process. © 2011 The Authors. Journal of Animal Ecology © 2011 British Ecological Society.

Integrated multisystem analysis in a mental health and criminal justice ecosystem.

PubMed

Falconer, Erin; El-Hay, Tal; Alevras, Dimitris; Docherty, John; Yanover, Chen; Kalton, Alan; Goldschmidt, Yaara; Rosen-Zvi, Michal

2014-01-01

Patients with a serious mental illness often receive care that is fragmented due to reduced availability of or access to resources, and inadequate, discontinuous, and uncoordinated care across health, social services, and criminal justice organizations. These gaps in care may lead to increased mental health disease burden and relapse, as well as repeated incarcerations. Further, the complex health, social service, and criminal justice ecosystem within which the patient may be embedded makes it difficult to examine the role of modifiable risk factors and delivered services on patient outcomes, particularly given that agencies often maintain isolated sets of relevant data. Here we describe an approach to creating a multisystem analysis that derives insights from an integrated data set including patient access to case management services, medical services, and interactions with the criminal justice system. We combined data from electronic systems within a US mental health ecosystem that included mental health and substance abuse services, as well as data from the criminal justice system. We applied Cox models to test the associations between delivery of services and re-incarceration. Using this approach, we found an association between arrests and crisis stabilization services in this population. We also found that delivery of case management or medical services provided after release from jail was associated with a reduced risk for re-arrest. Additionally, we used machine learning to train and validate a predictive model linking non-modifiable and modifiable risk factors and outcomes. A predictive model, constructed using elastic net regularized logistic regression, and considering age, past arrests, mental health diagnosis, as well as use of a jail diversion program, outpatient, medical and case management services predicted the probability of re-arrests with fair accuracy (AUC=.67). By modeling the complex interactions between risk factors, service delivery and outcomes, we may better enable systems of care to meet patient needs and improve outcomes.

Balancing the (carbon) budget: Using linear inverse models to estimate carbon flows and mass-balance 13C:15N labelling experiments in low oxygen sediments.

NASA Astrophysics Data System (ADS)

Hunter, William Ross; Van Oevelen, Dick; Witte, Ursula

2013-04-01

Over 1 million km2 of seafloor experience permanent low-oxygen conditions within oxygen minimum zones (OMZs). OMZs are predicted to grow as a consequence of climate change, potentially affecting oceanic biogeochemical cycles. The Arabian Sea OMZ impinges upon the western Indian continental margin at bathyal depths (150 - 1500m) producing a strong depth dependent oxygen gradient at the sea floor. The influence of the OMZ upon the short term processing of organic matter by sediment ecosystems was investigated using in situ stable isotope pulse chase experiments. These deployed doses of 13C:15N labeled organic matter onto the sediment surface at four stations from across the OMZ (water depth 540 - 1100 m; [O2] = 0.35 - 15 μM). In order to prevent experimentally anoxia, the mesocosms were not sealed. 13C and 15N labels were traced into sediment, bacteria, fauna and 13C into sediment porewater DIC and DOC. However, the DIC and DOC flux to the water column could not be measured, limiting our capacity to obtain mass-balance for C in each experimental mesocosm. Linear Inverse Modeling (LIM) provides a method to obtain a mass-balanced model of carbon flow that integrates stable-isotope tracer data with community biomass and biogeochemical flux data from a range of sources. Here we present an adaptation of the LIM methodology used to investigate how ecosystem structure influenced carbon flow across the Indian margin OMZ. We demonstrate how oxygen conditions affect food-web complexity, affecting the linkages between the bacteria, foraminifera and metazoan fauna, and their contributions to benthic respiration. The food-web models demonstrate how changes in ecosystem complexity are associated with oxygen availability across the OMZ and allow us to obtain a complete carbon budget for the stationa where stable-isotope labelling experiments were conducted.

Climate-driven range shifts of the king penguin in a fragmented ecosystem

NASA Astrophysics Data System (ADS)

Cristofari, Robin; Liu, Xiaoming; Bonadonna, Francesco; Cherel, Yves; Pistorius, Pierre; Le Maho, Yvon; Raybaud, Virginie; Stenseth, Nils Christian; Le Bohec, Céline; Trucchi, Emiliano

2018-03-01

Range shift is the primary short-term species response to rapid climate change, but it is often hampered by natural or anthropogenic habitat fragmentation. Different critical areas of a species' niche may be exposed to heterogeneous environmental changes and modelling species response under such complex spatial and ecological scenarios presents well-known challenges. Here, we use a biophysical ecological niche model validated through population genomics and palaeodemography to reconstruct past range shifts and identify future vulnerable areas and potential refugia of the king penguin in the Southern Ocean. Integrating genomic and demographic data at the whole-species level with specific biophysical constraints, we present a refined framework for predicting the effect of climate change on species relying on spatially and ecologically distinct areas to complete their life cycle (for example, migratory animals, marine pelagic organisms and central-place foragers) and, in general, on species living in fragmented ecosystems.

Predicting Consumer Biomass, Size-Structure, Production, Catch Potential, Responses to Fishing and Associated Uncertainties in the World's Marine Ecosystems.

PubMed

Jennings, Simon; Collingridge, Kate

2015-01-01

Existing estimates of fish and consumer biomass in the world's oceans are disparate. This creates uncertainty about the roles of fish and other consumers in biogeochemical cycles and ecosystem processes, the extent of human and environmental impacts and fishery potential. We develop and use a size-based macroecological model to assess the effects of parameter uncertainty on predicted consumer biomass, production and distribution. Resulting uncertainty is large (e.g. median global biomass 4.9 billion tonnes for consumers weighing 1 g to 1000 kg; 50% uncertainty intervals of 2 to 10.4 billion tonnes; 90% uncertainty intervals of 0.3 to 26.1 billion tonnes) and driven primarily by uncertainty in trophic transfer efficiency and its relationship with predator-prey body mass ratios. Even the upper uncertainty intervals for global predictions of consumer biomass demonstrate the remarkable scarcity of marine consumers, with less than one part in 30 million by volume of the global oceans comprising tissue of macroscopic animals. Thus the apparently high densities of marine life seen in surface and coastal waters and frequently visited abundance hotspots will likely give many in society a false impression of the abundance of marine animals. Unexploited baseline biomass predictions from the simple macroecological model were used to calibrate a more complex size- and trait-based model to estimate fisheries yield and impacts. Yields are highly dependent on baseline biomass and fisheries selectivity. Predicted global sustainable fisheries yield increases ≈4 fold when smaller individuals (< 20 cm from species of maximum mass < 1 kg) are targeted in all oceans, but the predicted yields would rarely be accessible in practice and this fishing strategy leads to the collapse of larger species if fishing mortality rates on different size classes cannot be decoupled. Our analyses show that models with minimal parameter demands that are based on a few established ecological principles can support equitable analysis and comparison of diverse ecosystems. The analyses provide insights into the effects of parameter uncertainty on global biomass and production estimates, which have yet to be achieved with complex models, and will therefore help to highlight priorities for future research and data collection. However, the focus on simple model structures and global processes means that non-phytoplankton primary production and several groups, structures and processes of ecological and conservation interest are not represented. Consequently, our simple models become increasingly less useful than more complex alternatives when addressing questions about food web structure and function, biodiversity, resilience and human impacts at smaller scales and for areas closer to coasts.

Simulating Forest Dynamics of Lowland Rainforests in Eastern Madagascar

NASA Technical Reports Server (NTRS)

Armstrong, Amanda; Fischer, Rico; Huth, Andreas; Shugart, Herman; Fatoyinbo, Temilola

2018-01-01

Ecological modeling and forecasting are essential tools for the understanding of complex vegetation dynamics. The parametric demands of some of these models are often lacking or scant for threatened ecosystems, particularly in diverse tropical ecosystems. One such ecosystem and also one of the world's biodiversity hotspots, Madagascar's lowland rainforests, have disappeared at an alarming rate. The processes that drive tree species growth and distribution remain as poorly understood as the species themselves. We investigated the application of the process-based individual-based FORMIND model to successfully simulate a Madagascar lowland rainforest using previously collected multi-year forest inventory plot data. We inspected the model's ability to characterize growth and species abundance distributions over the study site, and then validated the model with an independently collected forest-inventory dataset from another lowland rainforest in eastern Madagascar. Following a comparative analysis using inventory data from the two study sites, we found that FORMIND accurately captures the structure and biomass of the study forest, with r(squared) values of 0.976, 0.895, and 0.995 for 1:1 lines comparing observed and simulated values across all plant functional types for aboveground biomass (tonnes/ha), stem numbers, and basal area (m(squared)/ha), respectively. Further, in validation with a second study forest site, FORMIND also compared well, only slightly over-estimating shade-intermediate species as compared to the study site, and slightly under-representing shade-tolerant species in percentage of total aboveground biomass. As an important application of the FORMIND model, we measured the net ecosystem exchange (NEE, in tons of carbon per hectare per year) for 50 ha of simulated forest over a 1000-year run from bare ground. We found that NEE values ranged between 1 and -1 t Cha(exp -1)year(exp -1), consequently the study forest can be considered as a net neutral or a very slight carbon sink ecosystem, after the initial 130 years of growth. Our study found that FORMIND represents a valuable tool toward simulating forest dynamics in the immensely diverse Madagascar rainforests.

A Participatory Assessment of Ecosystem Services and Human Wellbeing in Rural Costa Rica Using Photo-Voice

NASA Astrophysics Data System (ADS)

Berbés-Blázquez, Marta

2012-04-01

Human well-being is intricately connected to ecosystem services. A keystone contribution to the ecosystem service literature has been the Millennium Ecosystem Assessment, MA, (Ecosystems and human well-being: a framework for assessment, Island Press, Washington, DC; 2003, 2005). Much of the work on ecosystem services to date has focused on the assessment and classification of environmental functions. The need for inclusion of community perspectives in ecosystem assessments has been widely recognized in order to better understand the distribution of impacts and benefits resulting from natural resource use. Communities can offer a direct route to understanding the complex relationships between ecosystems and human well-being and how environmental management affects their livelihoods. Photovoice has been made popular as a tool for participatory needs assessment but it has had limited use in ecosystem assessments to date. The purpose of this paper is twofold: (1) to present the results of a community-level assessment of environmental services in a watershed dominated by pineapple monoculture in Costa Rica; and (2) to evaluate the strengths and the limitations of photovoice as a tool for mapping the relationship between ecosystems and people. I argue that photovoice is an underutilized methodology that has the potential to complement biophysical ecosystem service assessments in the context of impoverished and resource-dependent communities, particularly, since assessing ecosystem services and acting upon that information requires integrating the knowledges of diverse stakeholders, recognizing power imbalances, and grappling with the complexity of social-ecological systems. Processes such as photovoice have the potential to catalyze community self-organization, which is a critical component for empowerment.

Ecosystem services classification: A systems ecology perspective of the cascade framework.

PubMed

La Notte, Alessandra; D'Amato, Dalia; Mäkinen, Hanna; Paracchini, Maria Luisa; Liquete, Camino; Egoh, Benis; Geneletti, Davide; Crossman, Neville D

2017-03-01

Ecosystem services research faces several challenges stemming from the plurality of interpretations of classifications and terminologies. In this paper we identify two main challenges with current ecosystem services classification systems: i) the inconsistency across concepts, terminology and definitions, and; ii) the mix up of processes and end-state benefits, or flows and assets. Although different ecosystem service definitions and interpretations can be valuable for enriching the research landscape, it is necessary to address the existing ambiguity to improve comparability among ecosystem-service-based approaches. Using the cascade framework as a reference, and Systems Ecology as a theoretical underpinning, we aim to address the ambiguity across typologies. The cascade framework links ecological processes with elements of human well-being following a pattern similar to a production chain. Systems Ecology is a long-established discipline which provides insight into complex relationships between people and the environment. We present a refreshed conceptualization of ecosystem services which can support ecosystem service assessment techniques and measurement. We combine the notions of biomass, information and interaction from system ecology, with the ecosystem services conceptualization to improve definitions and clarify terminology. We argue that ecosystem services should be defined as the interactions (i.e. processes) of the ecosystem that produce a change in human well-being, while ecosystem components or goods, i.e. countable as biomass units, are only proxies in the assessment of such changes. Furthermore, Systems Ecology can support a re-interpretation of the ecosystem services conceptualization and related applied research, where more emphasis is needed on the underpinning complexity of the ecological system.

A participatory assessment of ecosystem services and human wellbeing in rural Costa Rica using photo-voice.

PubMed

Berbés-Blázquez, Marta

2012-04-01

Human well-being is intricately connected to ecosystem services. A keystone contribution to the ecosystem service literature has been the Millennium Ecosystem Assessment, MA, (Ecosystems and human well-being: a framework for assessment, Island Press, Washington, DC; 2003, 2005). Much of the work on ecosystem services to date has focused on the assessment and classification of environmental functions. The need for inclusion of community perspectives in ecosystem assessments has been widely recognized in order to better understand the distribution of impacts and benefits resulting from natural resource use. Communities can offer a direct route to understanding the complex relationships between ecosystems and human well-being and how environmental management affects their livelihoods. Photovoice has been made popular as a tool for participatory needs assessment but it has had limited use in ecosystem assessments to date. The purpose of this paper is twofold: (1) to present the results of a community-level assessment of environmental services in a watershed dominated by pineapple monoculture in Costa Rica; and (2) to evaluate the strengths and the limitations of photovoice as a tool for mapping the relationship between ecosystems and people. I argue that photovoice is an underutilized methodology that has the potential to complement biophysical ecosystem service assessments in the context of impoverished and resource-dependent communities, particularly, since assessing ecosystem services and acting upon that information requires integrating the knowledges of diverse stakeholders, recognizing power imbalances, and grappling with the complexity of social-ecological systems. Processes such as photovoice have the potential to catalyze community self-organization, which is a critical component for empowerment.

Introduced and invasive species in novel rangeland ecosystems: friends or foes?

USGS Publications Warehouse

Belnap, Jayne; Ludwig, John A.; Wilcox, Bradford P.; Betancourt, Julio L.; Dean, W. Richard J.; Hoffmann, Benjamin D.; Milton, Sue J.

2012-01-01

Globally, new combinations of introduced and native plant and animal species have changed rangelands into novel ecosystems. Whereas many rangeland stakeholders (people who use or have an interest in rangelands) view intentional species introductions to improve forage and control erosion as beneficial, others focus on unintended costs, such as increased fire risk, loss of rangeland biodiversity, and threats to conservation efforts, specifically in nature reserves and parks. These conflicting views challenge all rangeland stakeholders, especially those making decisions on how best to manage novel ecosystems. To formulate a conceptual framework for decision making, we examined a wide range of novel ecosystems, created by intentional and unintentional introductions of nonnative species and land-use–facilitated spread of native ones. This framework simply divides decision making into two types: 1) straightforward–certain, and 2) complex–uncertain. We argue that management decisions to retain novel ecosystems are certain when goods and services provided by the system far outweigh the costs of restoration, for example in the case of intensively managed Cenchrus pastures. Decisions to return novel ecosystems to natural systems are also certain when the value of the system is low and restoration is easy and inexpensive as in the case of biocontrol of Opuntia infestations. In contrast, decisions whether to retain or restore novel ecosystems become complex and uncertain in cases where benefits are low and costs of control are high as, for example, in the case of stopping the expansion of Prosopis and Juniperus into semiarid rangelands. Decisions to retain or restore novel ecosystems are also complex and uncertain when, for example, nonnative Eucalyptus trees expand along natural streams, negatively affecting biodiversity, but also providing timber and honey. When decision making is complex and uncertain, we suggest that rangeland managers utilize cost–benefit analyses and hold stakeholder workshops to resolve conflicts.

Emerging concepts for management of river ecosystems and challenges to applied integration of physical and biological sciences in the Pacific Northwest, USA

Treesearch

Bruce E. Rieman; Jason B. Dunham; James L. Clayton

2006-01-01

Integration of biological and physical concepts is necessary to understand and conserve the ecological integrity of river systems. Past attempts at integration have often focused at relatively small scales and on mechanistic models that may not capture the complexity of natural systems leaving substantial uncertainty about ecological responses to management actions....

Effects of different types of moderate severity disturbance on forest structural complexity and ecosystem functioning: A story of ice and fire

NASA Astrophysics Data System (ADS)

Fahey, R. T.; Atkins, J.; Gough, C. M.; Hardiman, B. S.; Haber, L.; Stuart-Haentjens, E.; David, O.; Campbell, J. L.; Rustad, L.; Duffy, M.

2017-12-01

Disturbances that alter the structure and function of forest ecosystems occur along a continuum of severity. In contrast to the extremes of the disturbance gradient (i.e., stand-replacing disturbance and small gap formation), moderate severity disturbances are poorly understood, even though they make up the majority of the gradient and their spatial extent (and likely overall importance to regional disturbance regimes) often exceeds that of more severe disturbances. Moderate severity disturbances originate from a variety of causes, such as fires, ice storms, or pest and pathogen outbreaks, and each of these could reshape structure and function in different ways. Observational data from a limited number of sites shows that moderate disturbance can increase ecosystem complexity, but the generality of this effect has not been tested across a broad range of disturbance types and severities. Here, we utilize data from a set of five case studies of experimental or natural moderate disturbance to assess the effects of different types and severities of disturbance on forest canopy structural complexity (CSC) and the relationship of canopy structure with ecosystem functioning. Using pre- and post-disturbance measures of CSC derived from aerial and terrestrial LiDAR, UAV imagery, and Landsat data we quantified changes in CSC following an experimental ice storm, a low-severity surface fire, Beech Bark Disease and Hemlock Wooly Adelgid outbreaks, and experimental accelerated succession. Our initial findings indicate that different disturbance types have highly variable effects on CSC, and also that progressive increases in disturbance severity alter CSC differently among disturbance types. Differential effects of variable disturbance types on CSC has implications for the carbon cycle, as forest structure is strongly linked with both growth-limiting resource (e.g., nutrients and light) acquisition and net primary productivity. Understanding how different types and severities of moderate disturbance affect canopy structural complexity is thus crucial to informing and improving modeling the earth system and predicting how global shifts in moderate disturbance type, frequency, and severity will alter the land carbon sink.

The EBM-DPSER Conceptual Model: Integrating Ecosystem Services into the DPSIR Framework

PubMed Central

Kelble, Christopher R.; Loomis, Dave K.; Lovelace, Susan; Nuttle, William K.; Ortner, Peter B.; Fletcher, Pamela; Cook, Geoffrey S.; Lorenz, Jerry J.; Boyer, Joseph N.

2013-01-01

There is a pressing need to integrate biophysical and human dimensions science to better inform holistic ecosystem management supporting the transition from single species or single-sector management to multi-sector ecosystem-based management. Ecosystem-based management should focus upon ecosystem services, since they reflect societal goals, values, desires, and benefits. The inclusion of ecosystem services into holistic management strategies improves management by better capturing the diversity of positive and negative human-natural interactions and making explicit the benefits to society. To facilitate this inclusion, we propose a conceptual model that merges the broadly applied Driver, Pressure, State, Impact, and Response (DPSIR) conceptual model with ecosystem services yielding a Driver, Pressure, State, Ecosystem service, and Response (EBM-DPSER) conceptual model. The impact module in traditional DPSIR models focuses attention upon negative anthropomorphic impacts on the ecosystem; by replacing impacts with ecosystem services the EBM-DPSER model incorporates not only negative, but also positive changes in the ecosystem. Responses occur as a result of changes in ecosystem services and include inter alia management actions directed at proactively altering human population or individual behavior and infrastructure to meet societal goals. The EBM-DPSER conceptual model was applied to the Florida Keys and Dry Tortugas marine ecosystem as a case study to illustrate how it can inform management decisions. This case study captures our system-level understanding and results in a more holistic representation of ecosystem and human society interactions, thus improving our ability to identify trade-offs. The EBM-DPSER model should be a useful operational tool for implementing EBM, in that it fully integrates our knowledge of all ecosystem components while focusing management attention upon those aspects of the ecosystem most important to human society and does so within a framework already familiar to resource managers. PMID:23951002

The EBM-DPSER conceptual model: integrating ecosystem services into the DPSIR framework.

PubMed

Kelble, Christopher R; Loomis, Dave K; Lovelace, Susan; Nuttle, William K; Ortner, Peter B; Fletcher, Pamela; Cook, Geoffrey S; Lorenz, Jerry J; Boyer, Joseph N

2013-01-01

There is a pressing need to integrate biophysical and human dimensions science to better inform holistic ecosystem management supporting the transition from single species or single-sector management to multi-sector ecosystem-based management. Ecosystem-based management should focus upon ecosystem services, since they reflect societal goals, values, desires, and benefits. The inclusion of ecosystem services into holistic management strategies improves management by better capturing the diversity of positive and negative human-natural interactions and making explicit the benefits to society. To facilitate this inclusion, we propose a conceptual model that merges the broadly applied Driver, Pressure, State, Impact, and Response (DPSIR) conceptual model with ecosystem services yielding a Driver, Pressure, State, Ecosystem service, and Response (EBM-DPSER) conceptual model. The impact module in traditional DPSIR models focuses attention upon negative anthropomorphic impacts on the ecosystem; by replacing impacts with ecosystem services the EBM-DPSER model incorporates not only negative, but also positive changes in the ecosystem. Responses occur as a result of changes in ecosystem services and include inter alia management actions directed at proactively altering human population or individual behavior and infrastructure to meet societal goals. The EBM-DPSER conceptual model was applied to the Florida Keys and Dry Tortugas marine ecosystem as a case study to illustrate how it can inform management decisions. This case study captures our system-level understanding and results in a more holistic representation of ecosystem and human society interactions, thus improving our ability to identify trade-offs. The EBM-DPSER model should be a useful operational tool for implementing EBM, in that it fully integrates our knowledge of all ecosystem components while focusing management attention upon those aspects of the ecosystem most important to human society and does so within a framework already familiar to resource managers.

Improving Lidar-based Aboveground Biomass Estimation with Site Productivity for Central Hardwood Forests, USA

NASA Astrophysics Data System (ADS)

Shao, G.; Gallion, J.; Fei, S.

2016-12-01

Sound forest aboveground biomass estimation is required to monitor diverse forest ecosystems and their impacts on the changing climate. Lidar-based regression models provided promised biomass estimations in most forest ecosystems. However, considerable uncertainties of biomass estimations have been reported in the temperate hardwood and hardwood-dominated mixed forests. Varied site productivities in temperate hardwood forests largely diversified height and diameter growth rates, which significantly reduced the correlation between tree height and diameter at breast height (DBH) in mature and complex forests. It is, therefore, difficult to utilize height-based lidar metrics to predict DBH-based field-measured biomass through a simple regression model regardless the variation of site productivity. In this study, we established a multi-dimension nonlinear regression model incorporating lidar metrics and site productivity classes derived from soil features. In the regression model, lidar metrics provided horizontal and vertical structural information and productivity classes differentiated good and poor forest sites. The selection and combination of lidar metrics were discussed. Multiple regression models were employed and compared. Uncertainty analysis was applied to the best fit model. The effects of site productivity on the lidar-based biomass model were addressed.

Soil Carbon Inputs and Ecosystem Respiration: a Field Priming Experiment in Arctic Coastal Tundra

NASA Astrophysics Data System (ADS)

Vaughn, L. S.; Zhu, B.; Bimueller, C.; Curtis, J. B.; Chafe, O.; Bill, M.; Abramoff, R. Z.; Torn, M. S.

2016-12-01

In Arctic ecosystems, climate change is expected to influence soil carbon stocks through changes in both plant carbon inputs and organic matter decomposition. This study addresses the potential for a priming effect, an interaction between these changes in which root-derived carbon inputs alter SOM decomposition rates via microbial biomass increases, co-metabolism of substrates, induced nitrogen limitation, or other possible mechanisms. The priming effect has been observed in numerous laboratory and greenhouse experiments, and is increasingly included in ecosystem models. Few studies, however, have evaluated the priming effect with in situ field manipulations. In a two-year field experiment in Barrow, Alaska, we tested for a priming effect under natural environmental variability. In September 2014 and August 2015, we added 6.1g of 13C-labeled glucose to 25cm diameter mesocosms, 15cm below the soil surface in the mineral soil layer. Over the following month, we quantified effects on the rate and temperature sensitivity of native (non-glucose) ecosystem respiration and GPP. Following the 2014 treatment, soil samples were collected at 1 and 3 weeks for microbial biomass carbon and 13C/12C analysis, and ion exchange membranes were buried for one week to assess nitrate and ammonium availability. In contrast with many laboratory incubation studies using soils from a broad range of ecosystems, we observed no significant priming effect. In spite of a clear signal of 13C-glucose decomposition in respired CO2 and microbial biomass, we detected no treatment effect on background ecosystem respiration or total microbial biomass carbon. Our findings suggest that glucose taken up by microbes was not used for production of additional SOM-decomposing enzymes, possibly due to stoichiometric limitations on enzyme production. To best inform models representing complex and dynamic ecosystems, this study calls for further research relating theory, laboratory findings, and field experimentation.

Coupled hydrological, ecological, decision and economic models for monetary valuation of riparian ecosystem services

NASA Astrophysics Data System (ADS)

Goodrich, D. C.; Brookshire, D.; Broadbent, C.; Dixon, M. D.; Brand, L. A.; Thacher, J.; Benedict, K. K.; Lansey, K. E.; Stromberg, J. C.; Stewart, S.; McIntosh, M.

2011-12-01

Water is a critical component for sustaining both natural and human systems. Yet the value of water for sustaining ecosystem services is not well quantified in monetary terms. Ideally decisions involving water resource management would include an apples-to-apples comparison of the costs and benefits in dollars of both market and non-market goods and services - human and ecosystem. To quantify the value of non-market ecosystem services, scientifically defensible relationships must be developed that link the effect of a decision (e.g. human growth) to the change in ecosystem attributes from current conditions. It is this linkage that requires the "poly-disciplinary" coupling of knowledge and models from the behavioral, physical, and ecological sciences. In our experience another key component of making this successful linkage is development of a strong poly-disciplinary scientific team that can readily communicate complex disciplinary knowledge to non-specialists outside their own discipline. The time to build such a team that communicates well and has a strong sense of trust should not be underestimated. The research described in the presentation incorporated hydrologic, vegetation, avian, economic, and decision models into an integrated framework to determine the value of changes in ecological systems that result from changes in human water use. We developed a hydro-bio-economic framework for the San Pedro River Region in Arizona that considers groundwater, stream flow, and riparian vegetation, as well as abundance, diversity, and distribution of birds. In addition, we developed a similar framework for the Middle Rio Grande of New Mexico. There are six research components for this project: (1) decision support and scenario specification, (2) regional groundwater model, (3) the riparian vegetation model, (4) the avian model, (5) methods for displaying the information gradients in the valuation survey instruments (Choice Modeling and Contingent Valuation), and (6) the economic framework. Our modeling framework began with the identification of factors that influence spatial and temporal changes in riparian vegetation on the two rivers. The linked modeling framework was then employed for making spatial predictions of the changes in presence of surface water, vegetation change, and avian populations in both river systems. An overview of the overall project will be provided, with lessons learned, and initial valuation survey results.

Analysis of Business Connections Utilizing Theory of Topology of Random Graphs

NASA Astrophysics Data System (ADS)

Trelewicz, Jennifer Q.; Volovich, Igor V.

2006-03-01

A business ecosystem is a system that describes interactions between organizations. In this paper, we build a theoretical framework that defines a model which can be used to analyze the business ecosystem. The basic concepts within the framework are organizations, business connections, and market, that are all defined in the paper. Many researchers analyze the performance and structure of business using the workflow of the business. Our work in business connections answers a different set of questions, concerning the monetary value in the business ecosystem, rather than the task-interaction view that is provided by workflow analysis. We apply methods for analysis of the topology of complex networks, characterized by the concepts of small path length, clustering, and scale-free degree distributions. To model the dynamics of the business ecosystem we analyze the notion of the state of an organization at a given instant of time. We point out that the notion of state in this case is fundamentally different from the concept of state of the system which is used in classical or quantum physics. To describe the state of the organization at a given time one has to know the probability of payments to contracts which in fact depend on the future behavior of the agents on the market. Therefore methods of p-adic analysis are appropriate to explore such a behavior. Microeconomic and macroeconomic factors are indivisible and moreover the actual state of the organization depends on the future. In this framework some simple models are analyzed in detail. Company strategy can be influenced by analysis of models, which can provide a probabilistic understanding of the market, giving degrees of predictability.

An index of floodplain surface complexity

USGS Publications Warehouse

Scown, Murray W.; Thoms, Martin C.; DeJager, Nathan R.

2016-01-01

Floodplain surface topography is an important component of floodplain ecosystems. It is the primary physical template upon which ecosystem processes are acted out, and complexity in this template can contribute to the high biodiversity and productivity of floodplain ecosystems. There has been a limited appreciation of floodplain surface complexity because of the traditional focus on temporal variability in floodplains as well as limitations to quantifying spatial complexity. An index of floodplain surface complexity (FSC) is developed in this paper and applied to eight floodplains from different geographic settings. The index is based on two key indicators of complexity, variability in surface geometry (VSG) and the spatial organisation of surface conditions (SPO), and was determined at three sampling scales. FSC, VSG, and SPO varied between the eight floodplains and these differences depended upon sampling scale. Relationships between these measures of spatial complexity and seven geomorphological and hydrological drivers were investigated. There was a significant decline in all complexity measures with increasing floodplain width, which was explained by either a power, logarithmic, or exponential function. There was an initial rapid decline in surface complexity as floodplain width increased from 1.5 to 5 km, followed by little change in floodplains wider than 10 km. VSG also increased significantly with increasing sediment yield. No significant relationships were determined between any of the four hydrological variables and floodplain surface complexity.

Quantifying Hydroperiod, Fire and Nutrient Effects on the Composition of Plant Communities in Marl Prairie of the Everglades: a Joint Probability Method Based Model

NASA Astrophysics Data System (ADS)

Zhai, L.

2017-12-01

Plant community can be simultaneously affected by human activities and climate changes, and quantifying and predicting this combined effect on plant community by appropriate model framework which is validated by field data is complex, but very useful to conservation management. Plant communities in the Everglades provide an unique set of conditions to develop and validate this model framework, because they are both experiencing intensive effects of human activities (such as changing hydroperiod by drainage and restoration projects, nutrients from upstream agriculture, prescribed fire, etc.) and climate changes (such as warming, changing precipitation patter, sea level rise, etc.). More importantly, previous research attention focuses on plant communities in slough ecosystem (including ridge, slough and their tree islands), very few studies consider the marl prairie ecosystem. Comparing with slough ecosystem featured by remaining consistently flooded almost year-round, marl prairie has relatively shorter hydroperiod (just in wet-season of one year). Therefore, plant communities of marl prairie may receive more impacts from hydroperiod change. In addition to hydroperiod, fire and nutrients also affect the plant communities in the marl prairie. Therefore, to quantify the combined effects of water level, fire, and nutrients on the composition of the plant communities, we are developing a joint probability method based vegetation dynamic model. Further, the model is being validated by field data about changes of vegetation assemblage along environmental gradients in the marl prairie. Our poster showed preliminary data from our current project.

Understanding the Ecoydrology of Mangroves: A Simple SPAC Model for Avicennia Marina

NASA Astrophysics Data System (ADS)

Perri, Saverio; Viola, Francesco; Valerio Noto, Leonardo; Molini, Annalisa

2015-04-01

Mangroves represent one of the most carbon-rich ecosystems in the Tropics, noticeably impacting ecosystem services and the economy of these regions. Whether the ability of mangroves to exclude and tolerate salt has been extensively investigated in the literature - both from the structural and functional point of view - their eco-hydrological characteristics remains largely understudied, despite the crucial link with productivity, efficient carbon storage and fluxes. In this contribution we develop a "first-order" Soil Plant Atmosphere Continuum model for Avicennia Marina, a mangrove able to adapt to hyper-arid intertidal zones and characterized by complex morphological and eco-physiological traits. Among mangroves, Avicennia marina is one of the most tolerant to salinity and arid climatic conditions. Our model, based on a simple macroscopic approach, takes into account the specific characteristics of the mangrove ecosystem and in particular, the salinity of the water in the soil and the levels of salt stress to which the plant may be subjected. Mangrove transpiration is hence obtained by solving the plant and leaf water balance and the leaf energy balance, taking explicitly into account the role of osmotic water potential and salinity in governing plant resistance to water fluxes. The SPAC model of Avicennia is hence tested against experimental data obtained from the literature, showing the reliability and effectiveness of this minimalist model in reproducing observed transpiration fluxes. Finally, sensitivity analysis is used to assess whether uncertainty on the adopted parameters could lead to significant errors in the transpiration assessment.

Taking off the training wheels: the properties of a dynamic vegetation model without climate envelopes

DOE PAGES

Fisher, R. A.; Muszala, S.; Verteinstein, M.; ...

2015-04-29

We describe an implementation of the Ecosystem Demography (ED) concept in the Community Land Model. The structure of CLM(ED) and the physiological and structural modifications applied to the CLM are presented. A major motivation of this development is to allow the prediction of biome boundaries directly from plant physiological traits via their competitive interactions. Here we investigate the performance of the model for an example biome boundary in Eastern North America. We explore the sensitivity of the predicted biome boundaries and ecosystem properties to the variation of leaf properties determined by the parameter space defined by the GLOPNET global leafmore » trait database. Further, we investigate the impact of four sequential alterations to the structural assumptions in the model governing the relative carbon economy of deciduous and evergreen plants. The default assumption is that the costs and benefits of deciduous vs. evergreen leaf strategies, in terms of carbon assimilation and expenditure, can reproduce the geographical structure of biome boundaries and ecosystem functioning. We find some support for this assumption, but only under particular combinations of model traits and structural assumptions. Many questions remain regarding the preferred methods for deployment of plant trait information in land surface models. In some cases, plant traits might best be closely linked with each other, but we also find support for direct linkages to environmental conditions. We advocate for intensified study of the costs and benefits of plant life history strategies in different environments, and for the increased use of parametric and structural ensembles in the development and analysis of complex vegetation models.« less

Taking off the training wheels: the properties of a dynamic vegetation model without climate envelopes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fisher, R. A.; Muszala, S.; Verteinstein, M.

We describe an implementation of the Ecosystem Demography (ED) concept in the Community Land Model. The structure of CLM(ED) and the physiological and structural modifications applied to the CLM are presented. A major motivation of this development is to allow the prediction of biome boundaries directly from plant physiological traits via their competitive interactions. Here we investigate the performance of the model for an example biome boundary in Eastern North America. We explore the sensitivity of the predicted biome boundaries and ecosystem properties to the variation of leaf properties determined by the parameter space defined by the GLOPNET global leafmore » trait database. Further, we investigate the impact of four sequential alterations to the structural assumptions in the model governing the relative carbon economy of deciduous and evergreen plants. The default assumption is that the costs and benefits of deciduous vs. evergreen leaf strategies, in terms of carbon assimilation and expenditure, can reproduce the geographical structure of biome boundaries and ecosystem functioning. We find some support for this assumption, but only under particular combinations of model traits and structural assumptions. Many questions remain regarding the preferred methods for deployment of plant trait information in land surface models. In some cases, plant traits might best be closely linked with each other, but we also find support for direct linkages to environmental conditions. We advocate for intensified study of the costs and benefits of plant life history strategies in different environments, and for the increased use of parametric and structural ensembles in the development and analysis of complex vegetation models.« less

Scenarios reveal pathways to sustain future ecosystem services in an agricultural landscape.

PubMed

Qiu, Jiangxiao; Carpenter, Stephen R; Booth, Eric G; Motew, Melissa; Zipper, Samuel C; Kucharik, Christopher J; Chen, Xi; Loheide, Steven P; Seifert, Jenny; Turner, Monica G

2018-01-01

Sustaining food production, water quality, soil retention, flood, and climate regulation in agricultural landscapes is a pressing global challenge given accelerating environmental changes. Scenarios are stories about plausible futures, and scenarios can be integrated with biophysical simulation models to explore quantitatively how the future might unfold. However, few studies have incorporated a wide range of drivers (e.g., climate, land-use, management, population, human diet) in spatially explicit, process-based models to investigate spatial-temporal dynamics and relationships of a portfolio of ecosystem services. Here, we simulated nine ecosystem services (three provisioning and six regulating services) at 220 × 220 m from 2010 to 2070 under four contrasting scenarios in the 1,345-km 2 Yahara Watershed (Wisconsin, USA) using Agro-IBIS, a dynamic model of terrestrial ecosystem processes, biogeochemistry, water, and energy balance. We asked (1) How does ecosystem service supply vary among alternative future scenarios? (2) Where on the landscape is the provision of ecosystem services most susceptible to future social-ecological changes? (3) Among alternative future scenarios, are relationships (i.e., trade-offs, synergies) among food production, water, and biogeochemical services consistent over time? Our results showed that food production varied substantially with future land-use choices and management, and its trade-offs with water quality and soil retention persisted under most scenarios. However, pathways to mitigate or even reverse such trade-offs through technological advances and sustainable agricultural practices were apparent. Consistent relationships among regulating services were identified across scenarios (e.g., trade-offs of freshwater supply vs. flood and climate regulation, and synergies among water quality, soil retention, and climate regulation), suggesting opportunities and challenges to sustaining these services. In particular, proactive land-use changes and management may buffer water quality against undesirable future climate changes, but changing climate may overwhelm management efforts to sustain freshwater supply and flood regulation. Spatially, changes in ecosystem services were heterogeneous across the landscape, underscoring the power of local actions and fine-scale management. Our research highlights the value of embracing spatial and temporal perspectives in managing ecosystem services and their complex interactions, and provides a system-level understanding for achieving sustainability of the food-water-climate nexus in agricultural landscapes. © 2017 by the Ecological Society of America.

Ecosystem engineering varies spatially: a test of the vegetation modification paradigm for prairie dogs

USGS Publications Warehouse

Baker, Bruce W.; Augustine, David J.; Sedgwick, James A.; Lubow, Bruce C.

2013-01-01

Colonial, burrowing herbivores can be engineers of grassland and shrubland ecosystems worldwide. Spatial variation in landscapes suggests caution when extrapolating single-place studies of single species, but lack of data and the need to generalize often leads to ‘model system’ thinking and application of results beyond appropriate statistical inference. Generalizations about the engineering effects of prairie dogs (Cynomys sp.) developed largely from intensive study at a single complex of black-tailed prairie dogs C. ludovicianus in northern mixed prairie, but have been extrapolated to other ecoregions and prairie dog species in North America, and other colonial, burrowing herbivores. We tested the paradigm that prairie dogs decrease vegetation volume and the cover of grasses and tall shrubs, and increase bare ground and forb cover. We sampled vegetation on and off 279 colonies at 13 complexes of 3 prairie dog species widely distributed across 5 ecoregions in North America. The paradigm was generally supported at 7 black-tailed prairie dog complexes in northern mixed prairie, where vegetation volume, grass cover, and tall shrub cover were lower, and bare ground and forb cover were higher, on colonies than at paired off-colony sites. Outside the northern mixed prairie, all 3 prairie dog species consistently reduced vegetation volume, but their effects on cover of plant functional groups varied with prairie dog species and the grazing tolerance of dominant perennial grasses. White-tailed prairie dogs C. leucurus in sagebrush steppe did not reduce shrub cover, whereas black-tailed prairie dogs suppressed shrub cover at all complexes with tall shrubs in the surrounding habitat matrix. Black-tailed prairie dogs in shortgrass steppe and Gunnison's prairie dogs C. gunnisoni in Colorado Plateau grassland both had relatively minor effects on grass cover, which may reflect the dominance of grazing-tolerant shortgrasses at both complexes. Variation in modification of vegetation structure may be understood in terms of the responses of different dominant perennial grasses to intense defoliation and differences in foraging behavior among prairie dog species. Spatial variation in the engineering role of prairie dogs suggests spatial variation in their keystone role, and spatial variation in the roles of other ecosystem engineers. Thus, ecosystem engineering can have a spatial component not evident from single-place studies.

The ecological risks of genetically engineered organisms

NASA Astrophysics Data System (ADS)

Wolfenbarger, Lareesa

2001-03-01

Highly publicized studies have suggested environmental risks of releasing genetically engineered organisms (GEOs) and have renewed concerns over the evaluation and regulation of these products in domestic and international arenas. I present an overview of the risks of GEOs and the available evidence addressing these and discuss the challenges for risk assessment. Main categories of risk include non-target effects from GEOs, emergence of new viral diseases, and the spread of invasive (weedy) characteristics. Studies have detected non-target effects in some cases but not all; however, much less information exists on other risks, in part due to a lack of conceptual knowledge. For example, general models for predicting invasiveness are not well developed for any introduced organism. The risks of GEOs appear comparable to those for any introduced species or organism, but the magnitude of the risk or the pathway of exposure to the risk can differ among introduced organisms. Therefore, assessing the risks requires a case-by-case analysis so that any differences can be identified. Challenges to assessing risks to valued ecosystems include variability in effects and ecosystem complexity. Ecosystems are a dynamic and complex network of biological and physical interactions. Introducing a new biological entity, such as a GEO, may potentially alter any of these interactions, but evaluating all of these is unrealistic. Effects on a valued ecosystem could vary greatly depending on the geographical location of the experimental site, the GEO used, the plot size of the experiment (scaling effects), and the biological and physical parameters used in the experiment. Experiments that address these sources of variability will provide the most useful information for risk assessments.

Cold air drainage flows subsidize montane valley ecosystem productivity

Treesearch

Kimberly A. Novick; Andrew C. Oishi; Chelcy Ford Miniat

2016-01-01

In mountainous areas, cold air drainage from high to low elevations has pronounced effects on local temperature, which is a critical driver of many ecosystem processes, including carbon uptake and storage. Here, we leverage new approaches for interpreting ecosystem carbon flux observations in complex terrain to quantify the links between macro-climate...

TEMPERATURE SENSITIVITY OF SOIL RESPIRATION AND ITS EFFECTS ON ECOSYSTEM CARBON BUDGET: NONLINEARITY BEGETS SURPRISES. (R827676)

EPA Science Inventory

Nonlinearity is a salient feature in all complex systems, and it certainly characterizes biogeochemical cycles in ecosystems across a wide range of scales. Soil carbon emission is a major source of uncertainty in estimating the terrestrial carbon budget at the ecosystem level ...

Analyzing the complexity of cone production in longleaf pine by multiscale entropy

Treesearch

Xiongwen Chen; Qinfeng Guo; Dale G. Brockway

2016-01-01

The longleaf pine (Pinus palustris Mill.) forests are important ecosystems in the southeastern USA because of their ecological and economic value. Since European settlement, longleaf pine ecosystems have dramatically declined in extent, to the degree that they are now listed as endangered ecosystems. Its sporadic seed production, which...

Evaluating Productivity Predictions Under Elevated CO2 Conditions: Multi-Model Benchmarking Across FACE Experiments

NASA Astrophysics Data System (ADS)

Cowdery, E.; Dietze, M.

2016-12-01

As atmospheric levels of carbon dioxide levels continue to increase, it is critical that terrestrial ecosystem models can accurately predict ecological responses to the changing environment. Current predictions of net primary productivity (NPP) in response to elevated atmospheric CO2 concentration are highly variable and contain a considerable amount of uncertainty.The Predictive Ecosystem Analyzer (PEcAn) is an informatics toolbox that wraps around an ecosystem model and can be used to help identify which factors drive uncertainty. We tested a suite of models (LPJ-GUESS, MAESPA, GDAY, CLM5, DALEC, ED2), which represent a range from low to high structural complexity, across a range of Free-Air CO2 Enrichment (FACE) experiments: the Kennedy Space Center Open Top Chamber Experiment, the Rhinelander FACE experiment, the Duke Forest FACE experiment and the Oak Ridge Experiment on CO2 Enrichment. These tests were implemented in a novel benchmarking workflow that is automated, repeatable, and generalized to incorporate different sites and ecological models. Observational data from the FACE experiments represent a first test of this flexible, extensible approach aimed at providing repeatable tests of model process representation.To identify and evaluate the assumptions causing inter-model differences we used PEcAn to perform model sensitivity and uncertainty analysis, not only to assess the components of NPP, but also to examine system processes such nutrient uptake and and water use. Combining the observed patterns of uncertainty between multiple models with results of the recent FACE-model data synthesis project (FACE-MDS) can help identify which processes need further study and additional data constraints. These findings can be used to inform future experimental design and in turn can provide informative starting point for data assimilation.

Understanding the biological underpinnings of ecohydrological processes

NASA Astrophysics Data System (ADS)

Huxman, T. E.; Scott, R. L.; Barron-Gafford, G. A.; Hamerlynck, E. P.; Jenerette, D.; Tissue, D. T.; Breshears, D. D.; Saleska, S. R.

2012-12-01

Climate change presents a challenge for predicting ecosystem response, as multiple factors drive both the physical and life processes happening on the land surface and their interactions result in a complex, evolving coupled system. For example, changes in surface temperature and precipitation influence near-surface hydrology through impacts on system energy balance, affecting a range of physical processes. These changes in the salient features of the environment affect biological processes and elicit responses along the hierarchy of life (biochemistry to community composition). Many of these structural or process changes can alter patterns of soil water-use and influence land surface characteristics that affect local climate. Of the many features that affect our ability to predict the future dynamics of ecosystems, it is this hierarchical response of life that creates substantial complexity. Advances in the ability to predict or understand aspects of demography help describe thresholds in coupled ecohydrological system. Disentangling the physical and biological features that underlie land surface dynamics following disturbance are allowing a better understanding of the partitioning of water in the time-course of recovery. Better predicting the timing of phenology and key seasonal events allow for a more accurate description of the full functional response of the land surface to climate. In addition, explicitly considering the hierarchical structural features of life are helping to describe complex time-dependent behavior in ecosystems. However, despite this progress, we have yet to build an ability to fully account for the generalization of the main features of living systems into models that can describe ecohydrological processes, especially acclimation, assembly and adaptation. This is unfortunate, given that many key ecosystem services are functions of these coupled co-evolutionary processes. To date, both the lack of controlled measurements and experimentation has precluded determination of sufficient theoretical development. Understanding the land-surface response and feedback to climate change requires a mechanistic understanding of the coupling of ecological and hydrological processes and an expansion of theory from the life sciences to appropriately contribute to the broader Earth system science goal.

Towards an integrated flood management approach to address trade-offs between ecosystem services: Insights from the Dutch and German Rhine, Hungarian Tisza, and Chinese Yangtze basins

NASA Astrophysics Data System (ADS)

Halbe, Johannes; Knüppe, Kathrin; Knieper, Christian; Pahl-Wostl, Claudia

2018-04-01

The utilization of ecosystem services in flood management is challenged by the complexity of human-nature interactions and practical implementation barriers towards more ecosystem-based solutions, such as riverine urban areas or technical infrastructure. This paper analyses how flood management has dealt with trade-offs between ecosystem services and practical constrains towards more ecosystem-based solutions. To this end, we study the evolution of flood management in four case studies in the Dutch and German Rhine, the Hungarian Tisza, and the Chinese Yangtze basins during the last decades, focusing on the development and implementation of institutions and their link to ecosystem services. The complexity of human-nature interactions is addressed by exploring the impacts on ecosystem services through the lens of three management paradigms: (1) the control paradigm, (2) the ecosystem-based paradigm, and (3) the stakeholder involvement paradigm. Case study data from expert interviews and a literature search were structured using a database approach prior to qualitative interpretation. Results show the growing importance of the ecosystem-based and stakeholder involvement paradigms which has led to the consideration of a range of regulating and cultural ecosystem services that had previously been neglected. We detected a trend in flood management practice towards the combination of the different paradigms under the umbrella of integrated flood management, which aims at finding the most suitable solution depending on the respective regional conditions.

Combining Costs and Benefits of Animal Activities to Assess Net Yield Outcomes in Apple Orchards

PubMed Central

Luck, Gary W.

2016-01-01

Diverse animal communities influence ecosystem function in agroecosystems through positive and negative plant-animal interactions. Yet, past research has largely failed to examine multiple interactions that can have opposing impacts on agricultural production in a given context. We collected data on arthropod communities and yield quality and quantity parameters (fruit set, yield loss and net outcomes) in three major apple-growing regions in south-eastern Australia. We quantified the net yield outcome (accounting for positive and negative interactions) of multiple animal activities (pollination, fruit damage, biological control) across the entire growing season on netted branches, which excluded vertebrate predators of arthropods, and open branches. Net outcome was calculated as the number of undamaged fruit at harvest as a proportion of the number of blossoms (i.e., potential fruit yield). Vertebrate exclusion resulted in lower levels of fruit set and higher levels of arthropod damage to apples, but did not affect net outcomes. Yield quality and quantity parameters (fruit set, yield loss, net outcomes) were not directly associated with arthropod functional groups. Model variance and significant differences between the ratio of pest to beneficial arthropods between regions indicated that complex relationships between environmental factors and multiple animal interactions have a combined effect on yield. Our results show that focusing on a single crop stage, species group or ecosystem function/service can overlook important complexity in ecological processes within the system. Accounting for this complexity and quantifying the net outcome of ecological interactions within the system, is more informative for research and management of biodiversity and ecosystem services in agricultural landscapes. PMID:27391022

Combining Costs and Benefits of Animal Activities to Assess Net Yield Outcomes in Apple Orchards.

PubMed

Saunders, Manu E; Luck, Gary W

2016-01-01

Diverse animal communities influence ecosystem function in agroecosystems through positive and negative plant-animal interactions. Yet, past research has largely failed to examine multiple interactions that can have opposing impacts on agricultural production in a given context. We collected data on arthropod communities and yield quality and quantity parameters (fruit set, yield loss and net outcomes) in three major apple-growing regions in south-eastern Australia. We quantified the net yield outcome (accounting for positive and negative interactions) of multiple animal activities (pollination, fruit damage, biological control) across the entire growing season on netted branches, which excluded vertebrate predators of arthropods, and open branches. Net outcome was calculated as the number of undamaged fruit at harvest as a proportion of the number of blossoms (i.e., potential fruit yield). Vertebrate exclusion resulted in lower levels of fruit set and higher levels of arthropod damage to apples, but did not affect net outcomes. Yield quality and quantity parameters (fruit set, yield loss, net outcomes) were not directly associated with arthropod functional groups. Model variance and significant differences between the ratio of pest to beneficial arthropods between regions indicated that complex relationships between environmental factors and multiple animal interactions have a combined effect on yield. Our results show that focusing on a single crop stage, species group or ecosystem function/service can overlook important complexity in ecological processes within the system. Accounting for this complexity and quantifying the net outcome of ecological interactions within the system, is more informative for research and management of biodiversity and ecosystem services in agricultural landscapes.

Benchmarking Terrestrial Ecosystem Models in the South Central US

NASA Astrophysics Data System (ADS)

Kc, M.; Winton, K.; Langston, M. A.; Luo, Y.

2016-12-01

Ecosystem services and products are the foundation of sustainability for regional and global economy since we are directly or indirectly dependent on the ecosystem services like food, livestock, water, air, wildlife etc. It has been increasingly recognized that for sustainability concerns, the conservation problems need to be addressed in the context of entire ecosystems. This approach is even more vital in the 21st century with formidable increasing human population and rapid changes in global environment. This study was conducted to find the state of the science of ecosystem models in the South-Central region of US. The ecosystem models were benchmarked using ILAMB diagnostic package developed as a result of International Land Model Benchmarking (ILAMB) project on four main categories; viz, Ecosystem and Carbon Cycle, Hydrology Cycle, Radiation and Energy Cycle and Climate forcings. A cumulative assessment was generated with weighted seven different skill assessment metrics for the ecosystem models. This synthesis on the current state of the science of ecosystem modeling in the South-Central region of US will be highly useful towards coupling these models with climate, agronomic, hydrologic, economic or management models to better represent ecosystem dynamics as affected by climate change and human activities; and hence gain more reliable predictions of future ecosystem functions and service in the region. Better understandings of such processes will increase our ability to predict the ecosystem responses and feedbacks to environmental and human induced change in the region so that decision makers can make an informed management decisions of the ecosystem.

Early warning signals of regime shifts in coupled human–environment systems

PubMed Central

Bauch, Chris T.; Sigdel, Ram; Pharaon, Joe; Anand, Madhur

2016-01-01

In complex systems, a critical transition is a shift in a system’s dynamical regime from its current state to a strongly contrasting state as external conditions move beyond a tipping point. These transitions are often preceded by characteristic early warning signals such as increased system variability. However, early warning signals in complex, coupled human–environment systems (HESs) remain little studied. Here, we compare critical transitions and their early warning signals in a coupled HES model to an equivalent environment model uncoupled from the human system. We parameterize the HES model, using social and ecological data from old-growth forests in Oregon. We find that the coupled HES exhibits a richer variety of dynamics and regime shifts than the uncoupled environment system. Moreover, the early warning signals in the coupled HES can be ambiguous, heralding either an era of ecosystem conservationism or collapse of both forest ecosystems and conservationism. The presence of human feedback in the coupled HES can also mitigate the early warning signal, making it more difficult to detect the oncoming regime shift. We furthermore show how the coupled HES can be “doomed to criticality”: Strategic human interactions cause the system to remain perpetually in the vicinity of a collapse threshold, as humans become complacent when the resource seems protected but respond rapidly when it is under immediate threat. We conclude that the opportunities, benefits, and challenges of modeling regime shifts and early warning signals in coupled HESs merit further research. PMID:27815533

Assessing Ecosystem Model Performance in Semiarid Systems

NASA Astrophysics Data System (ADS)

Thomas, A.; Dietze, M.; Scott, R. L.; Biederman, J. A.

2017-12-01

In ecosystem process modelling, comparing outputs to benchmark datasets observed in the field is an important way to validate models, allowing the modelling community to track model performance over time and compare models at specific sites. Multi-model comparison projects as well as models themselves have largely been focused on temperate forests and similar biomes. Semiarid regions, on the other hand, are underrepresented in land surface and ecosystem modelling efforts, and yet will be disproportionately impacted by disturbances such as climate change due to their sensitivity to changes in the water balance. Benchmarking models at semiarid sites is an important step in assessing and improving models' suitability for predicting the impact of disturbance on semiarid ecosystems. In this study, several ecosystem models were compared at a semiarid grassland in southwestern Arizona using PEcAn, or the Predictive Ecosystem Analyzer, an open-source eco-informatics toolbox ideal for creating the repeatable model workflows necessary for benchmarking. Models included SIPNET, DALEC, JULES, ED2, GDAY, LPJ-GUESS, MAESPA, CLM, CABLE, and FATES. Comparison between model output and benchmarks such as net ecosystem exchange (NEE) tended to produce high root mean square error and low correlation coefficients, reflecting poor simulation of seasonality and the tendency for models to create much higher carbon sources than observed. These results indicate that ecosystem models do not currently adequately represent semiarid ecosystem processes.

State of research: environmental pathways and food chain transfer.

PubMed Central

Vaughan, B E

1984-01-01

Data on the chemistry of biologically active components of petroleum, synthetic fuel oils, certain metal elements and pesticides provide valuable generic information needed for predicting the long-term fate of buried waste constituents and their likelihood of entering food chains. Components of such complex mixtures partition between solid and solution phases, influencing their mobility, volatility and susceptibility to microbial transformation. Estimating health hazards from indirect exposures to organic chemicals involves an ecosystem's approach to understanding the unique behavior of complex mixtures. Metabolism by microbial organisms fundamentally alters these complex mixtures as they move through food chains. Pathway modeling of organic chemicals must consider the nature and magnitude of food chain transfers to predict biological risk where metabolites may become more toxic than the parent compound. To obtain predictions, major areas are identified where data acquisition is essential to extend our radiological modeling experience to the field of organic chemical contamination. PMID:6428875