Abstract. Lacking long-term dendrochronological and lake sediment data, little is known regarding the history of fire in southern Appalachian forests through the Holocene. Here we used 82 radiocarbon ages for soil charcoal collected from local depositional sites along a topographic gradient from mixed hardwood (Liriodendron tulipifera and Quercus spp.) to oakpine (Quercus prinus and Pinus rigida) forest to provide a coarse-grained picture of changes in fire frequency within a 10-ha area during the Holocene. Charcoal ages ranged from 0 to 10 570 yr BP, with a single date older than 4000 yr BP. The data indicate that fires occurred regularly across the study area over the past 4000 yr. Further, such fires were not confined to dry oakpine dominated ridges, but extended downslope into areas that are today dominated by mesic hardwood forest. Summed probability analysis taking into account radiometric errors suggests that fires became more frequent ;1000 yr ago, coinciding with the appearance of Woodland Tradition Native Americans in this region. We provide a direct demonstration of relatively frequent fire at the forest stand scale in Appalachian forests over a significant portion of the Holocene. Our results are consistent with the widely held view that fires have become less frequent in this region over the past 250 years. We discuss the difficulties in calculating the inbuilt error associated with estimating actual fire dates from charcoal fragments. But we conclude that such analysis of soil charcoal is a promising approach for reconstructing general trends in fire behavior within forest stands in this region.
Spatial patterning often occurs in ecosystems as a result of a selforganizing process caused by feedback between organisms and the physical environment. Here, we show that the spatial patterns observable in centuries-old Balinese rice terraces are also created by feedback between farmers' decisions and the ecology of the paddies, which triggers a transition from local to globalscale control of water shortages and rice pests. We propose an evolutionary game, based on local farmers' decisions that predicts specific power laws in spatial patterning that are also seen in a multispectral image analysis of Balinese rice terraces. The model shows how feedbacks between human decisions and ecosystem processes can evolve toward an optimal state in which total harvests are maximized and the system approaches Pareto optimality. It helps explain how multiscale cooperation from the community to the watershed scale could persist for centuries, and why the disruption of this self-organizing system by the Green Revolution caused chaos in irrigation and devastating losses from pests. The model shows that adaptation in a coupled human-natural system can trigger self-organized criticality (SOC). In previous exogenously driven SOC models, adaptation plays no role, and no optimization occurs. In contrast, adaptive SOC is a self-organizing process where local adaptations drive the system toward local and global optima.self-organization | criticality | irrigation | evolutionary games | Pareto optimality T he geometric precision of Balinese rice terraces has inspired generations of postcard photographers. Viewed from above, a changing mosaic of colors appears: green when the rice is young, yellow as it nears harvest, silver when the paddies are flooded, and brown when they are drained. These colors are not uniform across the island, because Bali is an equatorial island with only two seasons, wet and dry. Consequently, farmers can plant their crops at any time, although they avoid harvesting in the rainy season. The colored patches that make up the mosaics are visible in Google Earth. Like many natural phenomena, patches show a characteristic power-law distribution of sizes. However, in this case, the patches are created by the farmer's decisions about when to synchronize irrigation schedules with their neighbors: Each patch displays the outcome of these choices. Adjacent patches tend to be correlated. This correlation weakens with distance, a relationship that also follows a specific power law (Fig. 1). To discover why harvests approach a maximum when both the size distribution of patches and the corresponding correlation functions fit power-law distributions, we need a model that relates the decisions of the farmers to the consequences for irrigation flows and rice growth.In Bali, water is regarded as a public good, the gift of the Goddess of the Lakes. Rice is grown in paddy fields fed by irrigation systems dependent on rainfall. Rainfall varies by season and, in combination with groundwater inflow, determines river flow. By virtue of...
Population viability analysis (PVA) uses concepts from theoretical ecology to provide a powerful tool for quantitative estimates of population dynamics and extinction risks. However, conventional statistical PVA requires long‐term data from every population of interest, whereas many species of concern exist in multiple isolated populations that are only monitored occasionally. We present a hierarchical multi‐population viability analysis model that increases inference power from sparse data by sharing information among populations to assess extinction risks while accounting for incomplete detection and sampling biases with explicit observation and sampling sub‐models. We present a case study in which we customized this model for historical population monitoring data (1985–2015) from federally threatened Lahontan cutthroat trout populations in the Great Basin, USA. Data were counts of fish captured during backpack electrofishing surveys from locations associated with 155 isolated populations. Some surveys (25%) included multi‐pass removal sampling, which provided valuable information about capture efficiency. GIS and remote sensing were used to estimate August stream temperatures, peak flows, and riparian vegetation condition in each population each year. Field data were used to derive an annual index of nonnative trout densities. Results indicated that population growth rates were higher in colder streams and that nonnative trout reduced carrying capacities of native trout. Extinction risks increased with more environmental stochasticity and were also related to population extent, water temperatures, and nonnative densities. We developed a graphical user interface to interact with the fitted model results and to simulate future habitat scenarios and management actions to assess their influence on extinction risks in each population. Hierarchical multi‐population viability analysis bridges the gap between site‐level field observations and population‐level processes, making effective use of existing datasets to support management decisions with robust estimates of population dynamics, extinction risks, and uncertainties.
The ranges and abundances of species that depend on freshwater habitats are declining worldwide. Efforts to counteract those trends are often hampered by a lack of information about species distribution and conservation status and are often strongly biased toward a few well-studied groups. We identified the 3,906 vascular plants, macroinvertebrates, and vertebrates native to California, USA, that depend on fresh water for at least one stage of their life history. We evaluated the conservation status for these taxa using existing government and non-governmental organization assessments (e.g., endangered species act, NatureServe), created a spatial database of locality observations or distribution information from ~400 data sources, and mapped patterns of richness, endemism, and vulnerability. Although nearly half of all taxa with conservation status (n = 1,939) are vulnerable to extinction, only 114 (6%) of those vulnerable taxa have a legal mandate for protection in the form of formal inclusion on a state or federal endangered species list. Endemic taxa are at greater risk than non-endemics, with 90% of the 927 endemic taxa vulnerable to extinction. Records with spatial data were available for a total of 2,276 species (61%). The patterns of species richness differ depending on the taxonomic group analyzed, but are similar across taxonomic level. No particular taxonomic group represents an umbrella for all species, but hotspots of high richness for listed species cover 40% of the hotspots for all other species and 58% of the hotspots for vulnerable freshwater species. By mapping freshwater species hotspots we show locations that represent the top priority for conservation action in the state. This study identifies opportunities to fill gaps in the evaluation of conservation status for freshwater taxa in California, to address the lack of occurrence information for nearly 40% of freshwater taxa and nearly 40% of watersheds in the state, and to implement adequate protections for freshwater taxa where they are currently lacking.
Population growth and increasing water-use pressures threaten California's freshwater ecosystems and have led many native fishes to the brink of extinction. To guide fish conservation efforts, we provide the first systematic prioritization of river catchments and identify those that disproportionately contribute to fish taxonomic diversity. Using high-resolution range maps of exceptional quality, we also assess the representation of fish taxa within the state's protected areas and examine the concordance of high-priority catchments with existing reserves and among distinct taxonomic groups. Although most of the state's native fishes are found within protected areas, only a small proportion of their ranges are represented. Few high-priority catchments occur within protected areas, suggesting that fish conservation will require active management and targeted river restoration outside of reserves. These results provide the foundation for systematic freshwater conservation planning in California and for prioritizing where limited resources are allocated for fish recovery and protection.
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