Miguel F. Acevedo

Coupled human and natural systems: A multi-agent-based approach

A major force affecting many forest ecosystems is the encroachment of residential, commercial and industrial development. Analysis of the complex interactions between development decisions and ecosystems, and how the environmental consequences of these decisions influence human values and subsequent decisions will lead to a better understanding of the environmental consequences of private choices and public policies. Determining conditions of the interactions between human decisions and natural systems that lead to long-term sustainability of forest ecosystems is one goal of this work. Interactions between human stakeholders are represented using multi-agent models that act on forest landscape models in the form of land-use change. Feedback on the effects of these actions is received through ecological habitat metrics and hydrological responses. Results are presented on the dynamics of land-use change under different growth management strategies based on an area of the Dallas-Fort Worth (Texas, U.S.A.) region facing intense residential development.

Transition and Gap Models of Forest Dynamics

We describe and apply a correspondence between two major modeling ap- proaches to forest dynamics: transition markovian models and gap models or JABOWA- FORET type simulators. A transition model can be derived from a gap model by defining states on the basis of species, functional roles, vertical structure, or other convenient cover types. A gap-size plot can be assigned to one state according to dominance of one of these cover types. A semi-Markov framework is used for the transition model by considering not only the transition probabilities among the states, but also the holding times in each transition. The holding times are considered to be a combination of distributed and fixed time delays. Spatial extensions are possible by considering collections of gap-size plots and the proportions of these plots occupied by each state. The advantages of this approach include: reducing simulation time, analytica-l guidance to the simulations, direct analytical exploration of hypothesis and the possibility of fast computation from closed-form solutions and formulae. These advantages can be useful in the simulation of landscape dynamics and of species-rich forests, as well as in designing management strategies. A preliminary ap- plication to the H. J. Andrews forest in the Oregon Cascades is presented for demonstration.

Models of forest dynamics based on roles of tree species

Abstract A linkage between the two major modeling approaches to forest dynamics, transition Markovian models and jabowa-foret type simulators, is generated by developing a compact model of forest dynamics. This patch transition model utilizes functional roles instead of species. The roles or types are based on the regeneration and mortality characteristics of tree species; specifically, the requirements of canopy gaps for regeneration and the capacity to create canopy gaps upon death. A gap-size plot can be assigned to each of a set of states defined according to dominance of one of the roles. Transition probabilities among these states and mean holding times in each transition lead to semi-Markovian analytical calculations of the stationary state probabilities. Forest dynamics, as the proportions of total canopy space occupied by each role in a collection of gap-size plots, can be analyzed and simulated using a chain of first-order differential equations to emulate the distributed time-delays. Additional fixed time-delays in the transition of every pair of states is also included to account for long latencies. In addition to simplifying the simulations, the resulting model can also utilize available results of the theory of semi-Markov processes; and therefore, can provide analytical guidance to the simulations, the feasibility of direct exploration of hypothesis and the possibility of fast computation from closed-form solutions and formulae. These advantages can especially be useful in the simulation of landscape dynamics and species-rich tropical forests.

Integration of wireless sensor networks in environmental monitoring cyber infrastructure

Wireless sensor networks (WSNs) have great potential to revolutionize many science and engineering domains. We present a novel environmental monitoring system with a focus on overall system architecture for seamless integration of wired and wireless sensors for long-term, remote, and near-real-time monitoring. We also present a unified framework for sensor data collection, management, visualization, dissemination, and exchange, conforming to the new Sensor Web Enablement standard. Some initial field testing results are also presented. The monitoring system is being integrated into the Texas Environmental Observatory infrastructure for long-term operation. As part of the integrated system, a new WSN-based soil moisture monitoring system is developed and deployed to support hydrologic monitoring and modeling research. This work represents a significant contribution to the empirical study of the emerging WSN technology. We address many practical issues in real-world application scenarios that are often neglected in the existing WSN research.

Biocomplexity of deforestation in the Caparo tropical forest reserve in Venezuela: An integrated multi-agent and cellular automata model

A multi-agent model of social and environmental complexity of deforestation was developed for the Caparo Forest Reserve, Venezuela. It includes three types of agents: settlers, government, and lumber concessionaires. Settlers represent people of limited economic resources that deforest and occupy reserve land to grow crops and eventually claim property rights of this land. Their agricultural practices generate unintended environmental problems. The concessionaires extract lumber using management plans approved and monitored by the government. The agent model links to a cellular automata simulation of the natural system. Representational tools include Galatea (multi-agents), Actilog (rule description), and SpaSim (cellular automata). Three scenarios were explored for government policies: hands-off, pro-forestry and agro-forestry. Results agree qualitatively well with history of land-use change in the area. Old-growth forest is replaced by logged and secondary forest but the rate at which this transformation occurs varies by scenario. These results suggest that some of the agents behaviours and forest management plans should change to promote sustainability of the forest reserve; e.g., broadening governments role to improve management plans and monitoring, and to prevent invasion of reserve land by improving living conditions of potential settlers outside the reserve. These and other alternatives will be modelled in future work.

POTENTIAL EFFECTS OF GLOBAL CLIMATIC CHANGE ON THE PHENOLOGY AND YIELD OF MAIZE IN VENEZUELA

Simulated impacts of global and regional climate change, induced by an enhanced greenhouse effect and by Amazonian deforestation, on the phenology and yield of two grain corn cultivars in Venezuela (CENIAP PB-8 and OBREGON) are reported. Three sites were selected:Turén, Barinas andYaritagua, representing two important agricultural regions in the country. The CERES-Maize model, a mechanistic process-based model, in theDecision Support System for Agrotechnology Transfer (DSSAT) was used for the crop simulations. These simulations assume non-limiting nutrients, no pest damage and no damage from excess water; therefore, the results indicate only the difference between baseline and perturbed climatic conditions, when other conditions remain the same. Four greenhouse-induced global climate change scenarios, covering different sensitivity levels, and one deforestation-induced regional climate change scenario were used. The greenhouse scenarios assume increased air temperature, increased rainfall and decreased incoming solar radiation, as derived from atmospheric GCMs for doubled CO2 conditions. The deforestation scenarios assume increased air temperature, increased incoming solar radiation and decreased rainfall, as predicted by coupled atmosphere-biosphere models for extensive deforestation of a portion of the Amazon basin. Two baseline climate years for each site were selected, one year with average precipitation and another with lower than average rainfall. Scenarios associated with the greenhouse effect cause a decrease in yield of both cultivars at all three sites, while the deforestation scenarios produce small changes. Sensitivity tests revealed the reasons for these responses. Increasing temperatures, especially daily maximum temperatures, reduce yield by reducing the duration of the phenological phases of both cultivars, as expected from CERES-Maize. The reduction of the duration of the kernel filling phase has the largest effect on yield. Increases of precipitation associated with greenhouse warming have no effects on yield, because these sites already have adequate precipitation; however, the crop model used here does not simulate potential negative effects of excess water, which could have important consequences in terms of soil erosion and nutrient leaching. Increases in solar radiation increased yields, according to the non-saturating light response of the photosynthesis rate of a C4 plant like corn, compensating for reduced yields from increased temperatures in deforestation scenarios. In the greenhouse scenarios, reduced insolation (due to increased cloud cover) and increased temperatures combine to reduce yields; a combination of temperature increase with a reduction in solar radiation produces fewer and lighter kernels.

Interdisciplinary progress in food production, food security and environment research

SUMMARY This review examines contributions of interdisciplinary (ID) research to understanding interactions between environmental quality, food production and food security. Global patterns of food insecurity and crop production are reviewed in relation to climate, land use and economic changes, as well as potential productivity increases compatible with environmental conservation. Interactions between food production and global processes make food

Biocomplexity and conservation of biodiversity hotspots: three case studies from the Americas

The perspective of ‘biocomplexity’ in the form of ‘coupled natural and human systems’ represents a resource for the future conservation of biodiversity hotspots in three direct ways: (i) modelling the impact on biodiversity of private land-use decisions and public land-use policies, (ii) indicating how the biocultural history of a biodiversity hotspot may be a resource for its future conservation, and (iii) identifying and deploying the nodes of both the material and psycho-spiritual connectivity between human and natural systems in service to conservation goals. Three biocomplexity case studies of areas notable for their biodiversity, selected for their variability along a latitudinal climate gradient and a human-impact gradient, are developed: the Big Thicket in southeast Texas, the Upper Botanamo River Basin in eastern Venezuela, and the Cape Horn Archipelago at the austral tip of Chile. More deeply, the biocomplexity perspective reveals alternative ways of understanding biodiversity itself, because it directs attention to the human concepts through which biodiversity is perceived and understood. The very meaning of biodiversity is contestable and varies according to the cognitive lenses through which it is perceived.

Estimating parameters of forest patch transition models from gap models

Abstract An algorithm to estimate the parameter values of a transition forest landscape model (MOSAIC) from a gap model (FACET) is presented here. MOSAIC is semi-Markov; it includes random distributed holding times and fixed or deterministic delays in addition to transition probabilities. FACET is a terrain-sensitive version of ZELIG, a spatially explicit gap model. For each topographic class, the input to the algorithm consists of gap model tracer files identifying the cover type of each plot through time. These cover types or states are defined a priori. The method, based on individual plots of the FACET model, requires one FACET run initialized from the “gap” cover type and follows the time history of each plot. The algorithm estimates the transition probability by counting the number of transitions between each pair of states and estimates the fixed lags and the parameters of the probability density functions of the distributed delays by recording the times at which these transitions are made. These density functions are assumed to be Erlang; its two parameters, order and rate, are estimated using a nonlinear least squares procedure. Thus, as output, the algorithm produces four matrices at each terrain class: transition probabilities, fixed delays, and the two parameters for the Erlang distributions. The algorithm is illustrated by its application to two sites, high and low elevation, from the H.J. Andrews Forest in the Oregon Cascades. This scaling-up method helps to bridge the conceptual breach between landscape- and stand-scale models. To reflect landscape heterogeneity, the algorithm can be executed repetitively for many different terrain classes. While the method developed here focuses on FACET and MOSAIC, this general approach could be extended to use other fine-scale models or other forms of meta-models.

A Minimally Invasive Technique to Monitor Valve-Movement Behavior in Bivalves

A real time, minimally invasive method to observe valve movement of bivalves using proximity sensors and a personal computer has been developed. The method is being evaluated as a tool to assess both episodic toxicity events and ambient toxicity. The method described minimizes contact with the animal to the anchoring of one valve and the placement of a small aluminum foil disk on the other valve, and allows the measurement of the distance that a clams valves are open. Using proximity sensors and an aluminum foil target, valve movements of the Asiatic clam, Corbicula fluminea were measured and digitally recorded using a data acquisition board and a personal computer. One advantage of this method is its use of readily available stock electronics. In its final form, we envision an in situ biological monitoring system using C. fluminea deployed in aquatic systems in association with automated physical/chemical monitoring systems like those found at USGS gauging stations. A tool such as this could be used as ...