Neighborhood effects in bird distributions,Navarre, Spain

This study examines the role of neighborhood effects in the spatial distributions of selected bird species in Navarre, Spain. We employed a geographic information system (GIS) to organize the data on bird distributions and relevant environmental variables and to analyze their spatial patterns. Three bird species were selected for analysis: the European honey-buzzard (Pernis apivorus), the Eurasian hobby (Falco subbuteo), and the European pied flycatcher (Ficedula hypoleuca). Selected environmental variables of the study area were digitized to create a comprehensive data base and logistic regression models were used to evaluate the significance of each variable in the spatial distribution. The spatial patterns of bird distributions were used to extract topological relationships and to identify neighborhood effects. Although all the selected species illustrate a pattern of positive spatial autocorrelation in their distributions, the significance of neighborhood effects varies from species to species. Among the selected species, neighborhood effects are most evident in the distribution of the European pied flycatcher and are significant for the Eurasian hobby. The distribution of the European honey-buzzard is not much affected by neighborhood effects. The results suggest that examination of neighborhood effects is a prerequisite for modeling bird distributions.     

A Critical Review of Assumptions About the Prairie Dog as a Keystone Species

Cynomys spp.) have been labeled as keystone species because of their influence on biological diversity and ecosystem function. However, the validity of several assumptions used to support keystone status is questionable. We review the strength of the evidence and the magnitude of the prairie dog's effects on ecosystem structure and function. We use this review to reevaluate the keystone role for prairie dogs. Our goal is to encourage sound management of the prairie dog ecosystem by improving the ecological foundation of their keystone status. Our review confirms that prairie dogs affect a number of ecosystem-level functions but that their influence on prairie vertebrates may be less than previously suggested. Species richness and abundance patterns were variable among plants, mammals, and birds and were not consistently higher on prairie dog colonies compared to uncolonized areas. In addition, only nine of the 208 species listed in the literature as observed on or near prairie dogs colonies had quantitative evidence of dependence on prairie dogs. Abundance data indicated opportunistic use of colonies for an additional 20 species. A total of 117 species may have some relationship with prairie dogs, but we lacked sufficient data to evaluate the strength of this relationship. The remaining 62 species may be accidental or alien to the system. Despite our conclusion that some prairie dog functions may be smaller than previously assumed, collectively these functions are quite large compared to other herbivores in the system. We suggest that prairie dogs also provide some unique functions not duplicated by any other species and that continued decline of prairie dogs may lead to a substantial erosion of biological diversity and landscape heterogeneity across prairie and shrub-steppe landscapes. Thus, we concur that keystone status for prairie dogs is appropriate and may aid conservation efforts that help protect species dependent on prairie dogs and support other important ecosystem functions.     

Assessing state-wide biodiversity in the Florida Gap analysis project

The Florida Gap (Fl-Gap) project provides an assessment of the degree to which native animal species and natural communities are or are not represented in existing conservation lands. Those species and communities not adequately represented in areas being managed for native species constitute 'gaps' in the existing network of conservation lands. The United States Geological Survey Gap Analysis Program is a national effort and so, eventually, all 50 states will have completed it. The objective of Fl-Gap was to provide broad geographic information on the status of terrestrial vertebrates, butterflies, skippers and ants and their respective habitats to address the loss of biological diversity. To model the distributions and potential habitat of all terrestrial species of mammals, breeding birds, reptiles, amphibians, butterflies, skippers and ants in Florida, natural land cover was mapped to the level of dominant or co-dominant plant species. Land cover was classified from Landsat Thematic Mapper (TM) satellite imagery and auxiliary data such as the national wetlands inventory (NWI), soils maps, aerial imagery, existing land use/land cover maps, and on-the-ground surveys. Wildlife distribution models were produced by identifying suitable habitat for each species within that species' range. Mammalian models also assessed a minimum critical area required for sustainability of the species' population. Wildlife species richness was summarized against land stewardship ranked by an area's mandates for conservation protection.     

Effective Control of Aquatic Invasive Species in Tropical Australia

Often ecologists and natural resource managers can easily access data on invasive species occurrence across a region. Yet, collecting species abundance data over a large area is arguably more important for decision making, but inherently costly, so methods which can provide robust information at low-cost are particularly valuable. Studies of species distribution often use occurrence data to build models of the environmental niche. Environmental suitability derived from such models may be used to predict the potential distributions of species. The ability of such models to predict spatial patterns in abundance have recently been demonstrated. Here we tested the relationship of environmental suitability with local abundance of an aquatic invasive species, olive hymenachne (Hymenachne amplexicaulis) in the Wet Tropics of Australia. Ordinary least squares and quantile regressions revealed a positive relationship between environmental suitability and local abundance of olive hymenachne. We expand on this and use the relationship between environmental suitability and local abundance to quantify the effectiveness of management (reduction in local abundance) under four different management investments. We show that the upper limit of abundance can be used to evaluate management effectiveness based on varying investments, and that ongoing management is the most effective at reducing local abundance. We discuss implications of this in addressing important problems in invasive species management.     

Island biogeographical theory: Can it be used to predict lotic recovery rates?

Classic island biogeographic theory predicts that equilibrium will be reached when immigration and extinction rates are equal. These rates are modified by number of species in source area, number of intermediate islands, distance to recipient island, and size of intermediate islands. This general model has been variously modified and proposed to be a stochastic process with minimal competitive interaction or heavily deterministic. Predictive models of recovery (regardless of the end point chosen) have been based on the appropriateness of the MacArthur-Wilson models. Because disturbance frequency, severity, and intensity vary in their effect on community dynamics, we propose that disturbance levels should first be defined before evaluating the applicability of island biogeographical theory. Thus, we suggest a classification system of four disturbance levels based on recovery patterns by primary and secondary succession and faunal organization by primary (invasion of vacant areas) and secondary (remnant of previous community remains) processes. Level 1A disturbances completely destroy communities with no upstream or downstream sources of colonizers, while some component of near surface interstitial or hyporheic flora and fauna survive level 1B disturbances. Recovery has been reported to take from five years to longer than 25 years, when most invading colonists do not have an aerial form. Level 2 disturbances destroy the communities but leave upstream and downstream colonization sources (level 2A) and, sometimes, a hyporheic pool of colonizers (level 2B). Recovery studies have indicated primary succession and faunal structuring patterns (2A) with recovery times of 90–400 days or secondary succession and faunal structuring patterns (2B) with recovery times of 40–250 days. Level 3 disturbances result in reduction in species abundance and diversity along a stream reach; level 4 disturbances result in reduction of abundance and diversity in discrete patches. Both disturbance types lead to secondary succession and secondary faunal organization. Recovery rates can be quite rapid, varying from less than 10 days to 100 or more days. We suggest that island biogeographical models seem appropriate to recovery by secondary processes after level 3 and 4 disturbances, where competition may be an important organizing factor, while models of numerical abundance and resource tracking are probably of better use where community development is by primary succession (levels 1 and 2). Development of predictive recovery models requires research that addresses a number of fundamental questions. These include the role of hydrologic patterns on colonization dynamics, the role of nonaerial colonizers in recovery from level 1 disturbances, and assessment of the impact of changes in the order of invasion by colonizers of varying energetic efficiencies. Finally, we must be able to assemble these data and determine whether information that guides community organization at one level of disturbance can provide insights into colonization dynamics at other levels.     

An Ecoregional Context for Forest Management on National Wildlife Refuges of the Upper Midwest,USA

To facilitate forest planning and management on National Wildlife Refuges, we synthesized multiple data sources to describe land ownership patterns, land cover, landscape pattern, and changes in forest composition for four ecoregions and their associated refuges of the Upper Midwest. We related observed patterns to ecological processes important for forest conservation and restoration, with specific attention to refuge patterns of importance for forest landbirds of conservation priority. The large amount of public land within the ecoregions (31–80%) suggests that opportunities exist for coarse and meso-scale approaches to conserving and restoring ecological processes affecting the refuges, particularly historical fire regimes. Forests dominate both ecoregions and refuges, but refuge forest patches are generally larger and more aggregated than in associated ecoregions. Broadleaf taxa have increased in dominance in the ecoregions and displaced fire-dependent taxa such as pine (Pinus spp.) and other coniferous species; these changes in forest composition have likely also affected refuge forests. Despite compositional changes, larger forest patches on refuges suggests that they may provide better habitat for area-sensitive forest landbirds of mature, compositionally diverse forests than surrounding lands if management continues to promote increased patch size. We reason that although fine-scale research and monitoring for species of conservation priority is important, broad scale (ecoregional) assessments provide crucial context for effective forest and wildlife management in protected areas.     

Evaluation of Current Approaches to Stream Classification and a Heuristic Guide to Developing Classifications of Integrated Aquatic Networks

Conservation and management of fresh flowing waters involves evaluating and managing effects of cumulative impacts on the aquatic environment from disturbances such as: land use change, point and nonpoint source pollution, the creation of dams and reservoirs, mining, and fishing. To assess effects of these changes on associated biotic communities it is necessary to monitor and report on the status of lotic ecosystems. A variety of stream classification methods are available to assist with these tasks, and such methods attempt to provide a systematic approach to modeling and understanding complex aquatic systems at various spatial and temporal scales. Of the vast number of approaches that exist, it is useful to group them into three main types. The first involves modeling longitudinal species turnover patterns within large drainage basins and relating these patterns to environmental predictors collected at reach and upstream catchment scales; the second uses regionalized hierarchical classification to create multi-scale, spatially homogenous aquatic ecoregions by grouping adjacent catchments together based on environmental similarities; and the third approach groups sites together on the basis of similarities in their environmental conditions both within and between catchments, independent of their geographic location. We review the literature with a focus on more recent classifications to examine the strengths and weaknesses of the different approaches. We identify gaps or problems with the current approaches, and we propose an eight-step heuristic process that may assist with development of more flexible and integrated aquatic classifications based on the current understanding, network thinking, and theoretical underpinnings.     

Resource scarcity,energy use and environmental impact: A case study of the New Bedford,Massachusetts, USA,fisheries

The commercial fishing fleet in New Bedford, Massachusetts, USA, harvests seafood on George’s Bank, home of one of the nation’s most productive fisheries. We calculated the energy return on investment (EROI) and carbon intensity of protein harvest in the New Bedford fisheries from 1968 to 1988. EROI is the ratio of the energy content of the edible fish protein harvested to the quantity of fossil fuel energy used directly in the harvesting process. Carbon intensity is the quantity of carbon dioxide (CO₂) released (from the burning of fossil fuels) per calorie of edible fish protein harvested. The results show that the EROI of protein harvest declined from 0.18 to 0.028 from 1968 to 1988, indicating that the energy used to harvest seafood increased from about 6 to 36 kcal of fuel for each kilocalorie of protein harvested. The quantity of CO₂ released per calorie of edible fish protein is a linear function of energy use and therefore increased in a similar manner. During this period there was a large increase in fishing effort (caused by the increase in the real price of seafood products, favorable tax treatment for new vessel construction, and low interest loans from the government), and a decline in several important species of fish. The results suggest that fishing pressure could be managed effectively by the regulation of fuel use by the fleet. Despite the increase in the price of many seafood products, fishermen absorbed many of the costs of increasing scarcity in the form of longer working hours and fewer men per vessel.     

Indigenous community-based fisheries in Australia

The commercial sea cucumber species known as Sandfish (Holothuria scabra) occurs intertidally and subtidally in the Northern Territory of Australia, on or adjacent to Aboriginal land. A 4-yr program of community-based fisheries research with Aboriginal Australians was implemented to assess the viability of indigenous Australians' involvement in the wild-stock fishery. The research involved extensive and intensive indigenous participation, unusual in Australian biophysical sciences research, during field survey and habitat mapping, complemented by commercial catch data modelling and discussion of its implications. Field surveys produced Sandfish distribution and site-specific density, and revealed some areas that were not commercially fished. Catch data modelling results suggested that no additional effort could be sustained, however commercial fishers increased their effort, expanding their operations into the newly mapped areas. These actions effectively precluded indigenous peoples' aspirations of entry into the commercial fishery. The efficacy and outcomes of participatory program design with indigenous Australians need critique in the absence of the political will and statutory backing to provide equitable access to resources.     

Identifying Conservation and Restoration Priorities for Saproxylic and Old-Growth Forest Species: A Case Study in Switzerland

Saproxylic (dead-wood-associated) and old-growth species are among the most threatened species in European forest ecosystems, as they are susceptible to intensive forest management. Identifying areas with particular relevant features of biodiversity is of prime concern when developing species conservation and habitat restoration strategies and in optimizing resource investments. We present an approach to identify regional conservation and restoration priorities even if knowledge on species distribution is weak, such as for saproxylic and old-growth species in Switzerland. Habitat suitability maps were modeled for an expert-based selection of 55 focal species, using an ecological niche factor analyses (ENFA). All the maps were then overlaid, in order to identify potential species’ hotspots for different species groups of the 55 focal species (e.g., birds, fungi, red-listed species). We found that hotspots for various species groups did not correspond. Our results indicate that an approach based on “richness hotspots” may fail to conserve specific species groups. We hence recommend defining a biodiversity conservation strategy prior to implementing conservation/restoration efforts in specific regions. The conservation priority setting of the five biogeographical regions in Switzerland, however, did not differ when different hotspot definitions were applied. This observation emphasizes that the chosen method is robust. Since the ENFA needs only presence data, this species prediction method seems to be useful for any situation where the species distribution is poorly known and/or absence data are lacking. In order to identify priorities for either conservation or restoration efforts, we recommend a method based on presence data only, because absence data may reflect factors unrelated to species presence.     

Impingement losses of white perch at Hudson River power plants: Magnitude and biological significance

We performed a quantitative assessment of the impact of impingement at power plants on the Hudson River white perch population We estimated that impingement reduces the abundance of each white perch year class by at least 10% and probably by 15–20% or more after 2–3 years of vulnerability to power plants We attempted to detect effects of impingement on average year-class abundance of white perch from a time series of abundance indices derived from impingement data We found, however, that neither impingement collection rates observed at Hudson River power plants nor beach seine data provide a reliable index of year-class strength in white perch. Even if a reliable index were developed, natural fluctuations in year-class strength are great enough that a short-term monitoring program would be inadequate for detecting even a large reduction in average year-class strength. We performed a multipopulation analysis using simple food chain and food web models The results suggest that any long-term decline in white perch abundance caused by impingement should be accompanied by an increase in the abundance of one or more competing fish species and by an increase in the biomass of adult white perch relative to young-of-the-year.We conclude that 1) at present, assessments of population-level impact of impingement should focus on short-term effects, 2) research is needed to develop a reliable index of year-class strength for use in long-term monitoring programs, 3) identification and quantification of natural environmental factors influencing year-class strength are needed to improve our ability to predict and detect changes in abundance, and 4) it would be useful in designing monitoring programs to focus on detecting patterns of change among populations and age groups rather than solely on declines in abundance of individual populationsResearch sponsored by the Office of Nuclear Regulatory Research, US Nuclear Regulatory Commission under Interagency Agreement No. 40-550-75 with the US Department of Energy under Contract W-7405-eng-26 with Union Carbide Corporation. Publication No. 2030, Environmental Sciences Division, ORNL.     

Valuing improvements to threatened and endangered marine species: an application of stated preference choice experiments

Non-market valuation research has produced value estimates for over forty threatened and endangered (T&E) species, including mammals, fish, birds, and crustaceans. Increasingly, Stated Preference Choice Experiments (SPCE) are utilized for valuation, as the format offers flexibility for policy analysis and may reduce certain types of response biases relative to the more traditional Contingent Valuation method. Additionally, SPCE formats can allow respondents to make trade-offs among multiple species, providing information on the distinctiveness of preferences for different T&E species. In this paper we present results of an SPCE involving three U.S. Endangered Species Act (ESA)-listed species: the Puget Sound Chinook salmon, the Hawaiian monk seal, and the smalltooth sawfish. We estimate willingness-to-pay (WTP) values for improving each species' ESA listing status and statistically compare these values between the three species using a method of convolutions approach. Our results suggest that respondents have distinct preferences for the three species, and that WTP estimates differ depending on the species and the level of improvement to their ESA status. Our results should be of interest to researchers and policy-makers, as we provide value estimates for three species that have limited, if any, estimates available in the economics literature, as well as new information about the way respondents make trade-offs among three taxonomically different species.     

Ants: Bio-indicators of minesite rehabilitation,land-use,and land conservation

In terms of their numerical abundance, size, and species richness, ants are a prominent taxonomic group in many terrestrial ecosystems This, and the fact that ants occupy higher trophic levels and often specialised niches, suggests that they may be good bio-indicators of various environmental parameters This paper develops the rationale for using ants as bio-indicators and reviews examples of their use Parameters which are considered include ant species richness, species density, Shannon's diversity index, evenness index, and Mountford's similarity index The possible use of indicator species or groups is also discussed although, in Australia, this is still in its exploratory stage The examples given in this paper suggest that a consideration of ant species richness and evenness and also the Mountford's similarity index provides significant insight into the composition of a habitat and of the degree of disturbance Some applications of the ant bio-indicator concept include providing of base-line data in pre-development situations; monitoring ecosystem recovery following land rehabilitation, monitoring degree of ecosystem degradation, and the understanding of faunal composition and status of conservation areas     

Choice of stakeholder groups and members in multicriteria decision models

Simplistic economic objectives such as maximisation of producer profits are of little relevance in generating information to assist in the management of natural resources beyond the individual firm level. To provide data and information to support decision-making in natural resource management, it is necessary to take into account the views of various stakeholder groups and the multiple objectives of each group, through the use of some form of multicriteria analysis (MCA). Important decisions arise in the choice of stakeholder, since this will influence the management advice generated. Many groups and individuals can be affected by resource management decisions, but it would be impractical to attempt to identify the objectives and estimate their importance for each group. Also, questions arise concerning whether or not to include government agencies (which represent the broader community) and researchers as stakeholders. A further issue concerns choosing representative samples of stakeholder groups, from which to obtain preference data. Discussions with modellers and a reading of the literature would suggest that the choice of stakeholder groups and representatives is conducted haphazardly and is perhaps biased, and that a more systematic approach is needed. This article explores the above issues with reference to a number of multicriteria analyses, including local studies.     

Effects of Mowing and Prescribed Fire on Plant Community Structure and Function in Rare Coastal Sandplains,Nantucket Island,MA, USA

Coastal sandplains provide habitat for a suite of rare and endangered plant and wildlife species in the northeastern United States. These early successional plant communities were maintained by natural and anthropogenic disturbances including salt spray, fire, and livestock grazing, but over the last 150 years, a decrease in anthropogenic disturbance frequency and intensity has resulted in a shift towards woody shrub dominance at the expense of herbaceous taxa. This study quantified the effects of more than a decade of dormant season disturbance-based vegetation management (mowing and prescribed fire) on coastal sandplain plant community composition on Nantucket Island, Massachusetts, USA. We used time-series plant cover data from two similar sites to evaluate the effectiveness of disturbance management for restoring herbaceous species cover and reducing woody shrub dominance. Our results indicate that applying management outside of the peak of the growing season has not been effective in maintaining or increasing the cover of herbaceous species. While management activities resulted in significant (P < 0.01) increases in herbaceous species immediately after treatment, woody species recolonized and dominated treated sites within 3-years post treatment at the expense of graminoids and forbs. These results highlight the difficulties associated with directing ecological succession using disturbance-based management to maintain rare, herbaceous species in coastal sandplain systems that were once a prevalent landscape component under historically chronic anthropogenic disturbance. Further experimentation with growing season disturbance-based management and different combinations of management techniques could provide insights into management alternatives for maintaining herbaceous conservation targets in coastal sandplains.     

Patterns of selectiveness in the Amazonian freshwater fisheries: implications for management

Tropical fisheries, which are considered multi-species, may show selectiveness. We analyzed the degree of selectivity of fish catches in 46 sites along the Amazon basin through the percentage of biomass corresponding to the most caught fish species. Amazonian fisheries were considered moderately selective, as 54% of the sites directed more than a quarter of fishing effort to one fish species and in 87% of the sites more than half the fishing effort was directed to five fish species. Commercial fisheries were more selective than subsistence fisheries. Eleven fish species (nine of them migratory) have received more fishing pressure in the studied Amazonian regions and the catch composition differed among regions. We thus recommend that fisheries management in the Amazon basin should distribute fishing effort among more fish species; incorporate the particularities of commercial and subsistence fisheries; evaluate fishing effects on ecosystem services; and consider the biological characteristics of preferred fish.     

An Ecology of Prestige in New York City: Examining the Relationships Among Population Density,Socio-economic Status,Group Identity,and Residential Canopy Cover

Several social theories have been proposed to explain the uneven distribution of vegetation in urban residential areas: population density, social stratification, luxury effect, and ecology of prestige. We evaluate these theories using a combination of demographic and socio-economic predictors of vegetative cover on all residential lands in New York City. We use diverse data sources including the City’s property database, time-series demographic and socio-economic data from the US Census, and land cover data from the University of Vermont’s Spatial Analysis Lab (SAL). These data are analyzed using a multi-model inferential, spatial econometrics approach. We also examine the distribution of vegetation within distinct market categories using Claritas’ Potential Rating Index for Zipcode Markets (PRIZM?) database. These categories can be disaggregated, corresponding to the four social theories. We compare the econometric and categorical results for validation. Models associated with ecology of prestige theory are more effective for predicting the distribution of vegetation. This suggests that private, residential patterns of vegetation, reflecting the consumption of environmentally relevant goods and services, are associated with different lifestyles and lifestages. Further, our spatial and temporal analyses suggest that there are significant spatial and temporal dependencies that have theoretical and methodological implications for understanding urban ecological systems. These findings may have policy implications. Decision makers may need to consider how to most effectively reach different social groups in terms of messages and messengers in order to advance land management practices and achieve urban sustainability.     

Assisting Australian indigenous resource management and sustainable utilization of species through the use of GIS and environmental modeling techniques

Information on distribution and relative abundance of species is integral to sustainable management, especially if they are to be harvested for subsistence or commerce. In northern Australia, natural landscapes are vast, centers of population few, access is difficult, and Aboriginal resource centers and communities have limited funds and infrastructure. Consequently defining distribution and relative abundance by comprehensive ground survey is difficult and expensive. This highlights the need for simple, cheap, automated methodologies to predict the distribution of species in use, or having potential for use, in commercial enterprise. The technique applied here uses a Geographic Information System (GIS) to make predictions of probability of occurrence using an inductive modeling technique based on Bayes' theorem. The study area is in the Maningrida region, central Arnhem Land, in the Northern Territory, Australia. The species examined, Cycas arnhemica and Brachychiton diversifolius, are currently being 'wild harvested' in commercial trials, involving sale of decorative plants and use as carving wood, respectively. This study involved limited and relatively simple ground surveys requiring approximately 7 days of effort for each species. The overall model performance was evaluated using Cohen's kappa statistics. The predictive ability of the model for C. arnhemica was classified as moderate and for B. diversifolius as fair. The difference in model performance can be attributed to the pattern of distribution of these species. C. arnhemica tends to occur in a clumped distribution due to relatively short distance dispersal of its large seeds and vegetative growth from long-lived rhizomes, while B. diversifolius seeds are smaller and more widely dispersed across the landscape. The output from analysis predicts trends in species distribution that are consistent with independent on-site sampling for each species and therefore should prove useful in gauging the extent of resource availability. However, some caution needs to be applied as the models tend to over predict presence which is a function of distribution patterns and of other variables operating in the landscape such as fire histories which were not included in the model due to limited availability of data.     

A GIS-based approach for assessing the regional conservation status of genetic diversity: an example from the southern Appalachians

Conserving genetic diversity requires an assessment of the distribution of genetic variants in relation to patterns of land use and environmental variation at a regional scale. This assessment requires a novel approach to integrating and analyzing the genetic and environmental data across spatial scales. To explore the integration of genetic data with other geospatial data sets, we developed a GIS-based approach for examining patterns of genetic diversity for several species of salamanders in southern Appalachians. The genetic data, from allozyme surveys in the genetics literature, were integrated into a GIS database along with related attributes including population identifications and spatial locations. Using existing geospatial data, we classified sample locations as being either protected from anthropogenic disturbance (e.g., National Parks, Wilderness Areas) or as unprotected (e.g., private lands, multiple-use lands in National Forests). We used multidimensional scaling of allelic frequencies and contributions of populations to interpopulation differences in allelic richness to determine which populations had genetic characteristics most different from other populations in the sample. Measures of genetic differentiation were integrated into the GIS database to facilitate spatial analysis and visualization of the indices in relation to land use. This approach was useful for both identification of populations with components of genetic variation that were not well represented at protected sites and for identifying areas of species distributions where more genetic sampling would be necessary to make informed management decisions. Our approach could be readily adapted for use by managers and geneticists working with other species and types of genetic markers.     

Improving Predictive Models of In‐Stream Phosphorus Concentration Based on Nationally‐Available Spatial Data Coverages

Spatial data are playing an increasingly important role in watershed science and management. Large investments have been made by government agencies to provide nationally‐available spatial databases; however, their relevance and suitability for local watershed applications is largely unscrutinized. We investigated how goodness of fit and predictive accuracy of total phosphorus (TP) concentration models developed from nationally‐available spatial data could be improved by including local watershed‐specific data in the East Fork of the Little Miami River, Ohio, a 1,290 km² watershed. We also determined whether a spatial stream network (SSN) modeling approach improved on multiple linear regression (nonspatial) models. Goodness of fit and predictive accuracy were highest for the SSN model that included local covariates, and lowest for the nonspatial model developed from national data. Septic systems and point source TP loads were significant covariates in the local models. These local data not only improved the models but enabled a more explicit interpretation of the processes affecting TP concentrations than more generic national covariates. The results suggest SSN modeling greatly improves prediction and should be applied when using national covariates. Including local covariates further increases the accuracy of TP predictions throughout the studied watershed; such variables should be included in future national databases, particularly the locations of septic systems.