Ethics,Narrative, and Agriculture: Transforming Agricultural Practice through Ecological Imagination

The environmental degradation caused by industrial agriculture, as well as the resulting social and health consequences, creates an urgency to rethink food production by expanding the moral imagination to include agricultural practices. Agricultural practices presume human use of the earth and acknowledge human dependence on the biotic community, and these relations mean that agriculture presents a separate set of considerations in the broader field of environmental ethics. Many scholars and activists have argued persuasively that we need new stories to rethink agricultural practice, however, the link—the story that does and can shape agricultural practice—has not yet been fully articulated in environmental discourse. My analysis explores how language has shaped existing agricultural models and, more important, the potential of story to influence agricultural practice. To do this, I draw upon cognitive theory to illustrate how metaphoric and narrative language structures thought and influences practice, beginning with my contention that industrial agriculture relies on a discourse of mechanistic relations between humans and a passive earth, language that has naturalized the chemically intensive monocultures prevalent in much of the American Midwest. However, alternative agricultures, including organic agriculture, agro-ecology, and ecological agriculture, emphasize qualities such as interdependence and reciprocity and do so as a deliberate response to the perceived inadequacies of industrial agriculture and its governing narrative. Exploring the different discourses of agricultural systems can help us think through different modalities for human relations with the biotic community and demonstrate story’s potential role in altering practice.     

Ecosystems emerging. 5: Constraints

Ecosystem constraints are both ontic and epistemic. They limit activity, and as problems to be solved they drive organization, which is our hypothesis:

The driver of organization is constraint.

Solutions proliferate further constraints in an unending spiral of problem (constraint) generation and solution. As constraints proliferate, behavior narrows, and species diversify to compensate (paradox of constraint). Resource enrichment reduces constraints, releases behavior, and reduction of challenges decreases diversity (paradox of enrichment)—high diversity is expressed in low-resource environments and low diversity in high-resource environments. A three-part model of constraints is formulated for non-living systems, and also for goal-directed, problem-solving biota. Mode 1: dynamical means behavior is co-determined by internal states and external inputs. Mode 2: cybernetic employs negative feedback to keep dynamics within goal-oriented operating limits. Mode 3: model-making entails ability to represent (model) physical reality and respond to both phenomenal (modeled) and physical inputs; this property distinguishes living from nonliving systems. Principal sections of the paper elaborate dynamical constraints (three classes), boundary constraints (expressed in edge effects and trophic dynamics), physical constraints (space, time, temperature), chemical constraints (environment fitness, ecological stoichiometry, chemical evolution, limiting factors), coding constraints (environmental vs. genetic coding), network and pathway constraints (connectivity), and natural selection constraints (fitting to the biosphere). Consideration of how the world would look without constraints suggests how fundamental these are in ecosystem emergence, and how the next property in this series, differentiation, would be unmotivated without them. We conclude that constraints as a category are under-studied in ecology, poorly understood in ecological phenomenology, and (our hypothesis) comprise a ubiquitous organizing force in nature.     

Control system approaches to ecological systems analysis: Invariants and frequency response

The steady-state assumption is a mainstay for the analysis of ecological systems with more than three or four states. However, it is well accepted in ecology that inputs to large systems come in pulses assumed to have a reasonably constant magnitude and frequency. Steady pulse inputs and the use of electro-chemical–mechanical control systems methodology enables limited short term dynamic responses of ecological systems of a scale often occurring in systems of potential engineering importance to be analyzed. This paper explores and presents a survey of multi-input–multi-output (MIMO) control systems analysis of ecosystem network models to better understand pulse frequency issues and further develop experimentally verifiable approaches to testing the MIMO concept. The analysis process is demonstrated using two network model exemplars. Two aspects of MIMO analyses appear relevant to understanding ecological systems: (1) Eigenvalue invariant analyses and singular value decomposition (SVD) analyses enable assessment of stability and relative strength of states. Eigenvalues reflect time constants and provide a check on experimentally determined system matrices. (2) Analysis of SVD versus frequency for each output indicates maximum pulse frequencies that allow system components to benefit from pulsing. As a group, MIMO analyses complement other analytical methods and provide a theoretical systems focus convenient for analyzing ecosystems from an engineering perspective.     

The Reynolds transport theorem: Application to ecological compartment modeling and case study of ecosystem energetics

The Reynolds transport theorem (RTT) from mathematics and engineering has a rich history of success in mass transport dynamics and traditional thermodynamics. This paper introduces RTT as a complementary approach to traditional compartmental methods used in ecological modeling and network analysis. A universal system equation for a generic flow quantity is developed into a generic open-system differential expression for conservation of energy. Nonadiabatic systems are defined and incorporated into control volume (CV) and control surface (CS) perspectives of RTT where reductive assumptions in empirical data are then formally introduced, reviewed, and appropriately implemented. Compartment models are abstract, time-dependent systems of simultaneous differential equations describing storage and flow of conservative quantities between interconnected entities (the compartments). As such, they represent a set of flexible and somewhat informal, assumptions, definitions, algebraic manipulations, and graphical depictions subject to influence and selectively parsed expression by the modeler. In comparison, RTT compartment models are more rigorous and formal integro-differential equations and graphics initiated by the RTT universal system equation, forcing an ordered identification of simplifying assumptions, ending with clearly identified depictions of the transfer and transport of conservative substances in physical space and time. They are less abstract in the rigor of their equation development leaving less ambiguity to modeler discretion. They achieve greater consistency with other RTT compartment style models while possibly generating greater conformity with physical reality. Characteristics of the RTT approach are compared with those of a traditional compartment model of energy flow in an intertidal oyster-reef community.     

Diversity, Seasonality, and Context of Mammalian Roadkills in the Southern Great Plains

Thousands of mammals are killed annually from vehicle collisions, making the issue an important one for conservation biologists and environmental managers. We recorded all readily identifiable kills on or immediately adjacent to roads in the southern Great Plains from March 2004–March 2007. We also recorded distance traveled, whether a road was paved or divided, the number of lanes, and prevailing habitat. Surveys were opportunistic and were conducted by car during conditions of good visibility. Over our 239 surveys and >16,500 km traveled, we recorded 1412 roadkills from 18 different mammal species (size ranged from Sciurus squirrels to the white-tailed deer, Odocolieus virginianus). The overall kill rate was 8.50 / 100 km. Four species were prone to collisions: the Virginia opossum (Didelphis virginiana), nine-banded armadillo (Dasypus novemcinctus), striped skunk (Mephitis mephitis), and northern raccoon (Procyon lotor). Together they accounted for approximately 85% (1198) of all roadkills. Mortality rate differed significantly between 2- and 4-lane roads (8.39 versus 7.79 / 100 km). Kill rates were significantly higher on paved versus unpaved roads (8.60 versus 3.65 / 100 km), but did not depend on whether a road was divided. Roadkills were higher in spring than in fall (1.5×), winter (1.4×), or summer (1.3×). The spring peak (in kills / 100 km) was driven chiefly by the armadillo (2.76 in spring/summer versus 0.73 in autumn/winter) and opossum (2.65 versus 1.47). By contrast, seasonality was dampened by a late winter/early spring peak in skunk mortalities, for which 41% occurred in the 6-week period of mid-February through March. The raccoon did not exhibit a strong seasonal pattern. Our data are consistent with dispersal patterns of these species. Our results underscore the high rate of highway mortality in the southern plains, as well as differences in seasonality and road type that contribute to mortality. Conservation and management efforts should focus on creating underpasses or using other means to reduce roadkill rates.     

Projecting Cumulative Benefits of Multiple River Restoration Projects: An Example from the Sacramento-San Joaquin River System in California

Despite increasingly large investments, the potential ecological effects of river restoration programs are still small compared to the degree of human alterations to physical and ecological function. Thus, it is rarely possible to “restore” pre-disturbance conditions; rather restoration programs (even large, well-funded ones) will nearly always involve multiple small projects, each of which can make some modest change to selected ecosystem processes and habitats. At present, such projects are typically selected based on their attributes as individual projects (e.g., consistency with programmatic goals of the funders, scientific soundness, and acceptance by local communities), and ease of implementation. Projects are rarely prioritized (at least explicitly) based on how they will cumulatively affect ecosystem function over coming decades. Such projections require an understanding of the form of the restoration response curve, or at least that we assume some plausible relations and estimate cumulative effects based thereon. Drawing on our experience with the CALFED Bay-Delta Ecosystem Restoration Program in California, we consider potential cumulative system-wide benefits of a restoration activity extensively implemented in the region: isolating/filling abandoned floodplain gravel pits captured by rivers to reduce predation of outmigrating juvenile salmon by exotic warmwater species inhabiting the pits. We present a simple spreadsheet model to show how different assumptions about gravel pit bathymetry and predator behavior would affect the cumulative benefits of multiple pit-filling and isolation projects, and how these insights could help managers prioritize which pits to fill.     

Implications of network particle tracking (NPT) for ecological model interpretation

Network particle tracking (NPT), building on the foundation of network environ analysis (NEA), is a new development in the definition of coherence relations within and between connected systems. This paper evaluates three ecosystem models in a comparison of throughflow- and storage-based NEA and NPT. Compartments in models with high indirect effects and Finn cycling showed low correlation of NEA storage and throughflow with particle repeat visits and numbers of particles in compartments at steady state. Conversely, the correlation between NEA and NPT results was high with two models having lower indirect effects and Finn cycling. Analysis of ecological orientors associated with NEA showed NPT to fully support conventional NEA results when the common conditions of donor control and steady state are satisfied. Particle trajectories are recorded in the new concept of a particle “passport”. Ability to track and record particle in-system histories enables views of multiple scales and opens the possibility of making pathway-dependent modeling decisions. NPT may also enable modeling of time, allowing integration of Newtonian, organismal and stochastic modeling perspectives in a single comprehensive analysis.     

Predictors of specialist avifaunal decline in coastal marshes

Coastal marshes are one of the world's most productive ecosystems. Consequently, they have been heavily used by humans for centuries, resulting in ecosystem loss. Direct human modifications such as road crossings and ditches and climatic stressors such as sea‐level rise and extreme storm events have the potential to further degrade the quantity and quality of marsh along coastlines. We used an 18‐year marsh‐bird database to generate population trends for 5 avian species (Rallus crepitans, Tringa semipalmata semipalmata, Ammodramus nelsonii subvirgatus, Ammodramus caudacutus, and Ammodramus maritimus) that breed almost exclusively in tidal marshes, and are potentially vulnerable to marsh degradation and loss as a result of anthropogenic change. We generated community and species trends across 3 spatial scales and explored possible drivers of the changes we observed, including marsh ditching, tidal restriction through road crossings, local rates of sea‐level rise, and potential for extreme flooding events. The specialist community showed negative trends in tidally restricted marshes (?2.4% annually from 1998 to 2012) but was stable in unrestricted marshes across the same period. At the species level, we found negative population trends in 3 of the 5 specialist species, ranging from ?4.2% to 9.0% annually. We suggest that tidal restriction may accelerate degradation of tidal marsh resilience to sea‐level rise by limiting sediment supply necessary for marsh accretion, resulting in specialist habitat loss in tidally restricted marshes. Based on our findings, we predict a collapse of the global population of Saltmarsh Sparrows (A. caudacutus) within the next 50 years and suggest that immediate conservation action is needed to prevent extinction of this species. We also suggest mitigation actions to restore sediment supply to coastal marshes to help sustain this ecosystem into the future.