Regional data refine local predictions: modeling the distribution of plant species abundance on a portion of the central plains

Species distribution models are frequently used to predict species occurrences in novel conditions, yet few studies have examined the consequences of extrapolating locally collected data to regional landscapes. Similarly, the process of using regional data to inform local prediction for species distribution models has not been adequately evaluated. Using boosted regression trees, we examined errors associated with extrapolating models developed with locally collected abundance data to regional-scale spatial extents and associated with using regional data for predictions at a local extent for a native and non-native plant species across the northeastern central plains of Colorado. Our objectives were to compare model results and accuracy between those developed locally and extrapolated regionally, those developed regionally and extrapolated locally, and to evaluate extending species distribution modeling from predicting the probability of presence to predicting abundance. We developed models to predict the spatial distribution of plant species abundance using topographic, remotely sensed, land cover and soil taxonomic predictor variables. We compared model predicted mean and range abundance values to observed values between local and regional. We also evaluated model prediction performance based on Pearson's correlation coefficient. We show that: (1) extrapolating local models to regional extents may restrict predictions, (2) regional data can help refine and improve local predictions, and (3) boosted regression trees can be useful to model and predict plant species abundance. Regional sampling designed in concert with large sampling frameworks such as the National Ecological Observatory Network may improve our ability to monitor changes in local species abundance.     

The Effects of Local Ecological Knowledge, Minimum-Impact Knowledge, and Prior Experience on Visitor Perceptions of the Ecological Impacts of Backcountry Recreation

An on-site visitor survey instrument was developed to examine visitor perceptions of resource impacts resulting from backcountry hiking activities. The survey was conducted in the Bear Lake Corridor of Rocky Mountain National Park, CO and examined visitor characteristics that may influence visitor perceptions of specific resource conditions. Findings indicate that visitors are more perceptive of recreation-related resource impacts that are the result of undesirable behavior and, while visitors do perceive resource impacts, visitors tend to be more affected by crowding. Factors such as local ecological knowledge and knowledge of minimal-impact practices positively influence visitor perceptions of resource impacts. These findings support the use of visitor education on ecological knowledge and minimum-impact as a means of increasing visitor awareness of recreation impact issues.     

Bridging research and practice in conservation

Calls for biodiversity conservation practice to be more evidence based are growing, and we agree evidence use in conservation practice needs improvement. However, evidence-based conservation will not be realized without improved access to evidence. In medicine, unlike in conservation, a well-established and well-funded layer of intermediary individuals and organizations engage with medical practitioners, synthesize primary research relevant to decision making, and make evidence easily accessible. These intermediaries prepare targeted evidence summaries and distribute them to practitioners faced with time-sensitive and value-laden decisions. To be effective, these intermediaries, who we refer to as evidence bridges, should identify research topics based on the priorities of practitioners; synthesize evidence; prepare and distribute easy-to-find and easy-to-use evidence summaries; and develop and maintain networks of connections with researchers and practitioners. Based on a review of the literature regarding evidence intermediaries in conservation and environmental management, as well as an anonymous questionnaire searching for such organizations, we found few intermediaries that met all these criteria. Few evidence bridges that do exist are unable to reach most conservation practitioners, which include resource managers in government and industry, conservation organizations, and farmers and other private landowners. We argue that the lack of evidence bridges from research to practitioners contributes to evidence complacency and limits the use of evidence in conservation action. Nevertheless, several existing organizations help reduce the gap between evidence and practice and could serve as a foundation for building additional components of evidence bridges in conservation. Although evidence bridges need expertise in research and evidence synthesis, they also require expertise in identifying and communicating with the community of practitioners most in need of clear and concise syntheses of evidence. Article Impact Statement: Evidence-based conservation will not be realized without improved access to evidence. We call for intermediary evidence bridges.     

Spatio-temporal patterns of soil phosphorus enrichment in Everglades water conservation area 2A

The Florida Everglades have undergone significant ecological change resulting from anthropogenic manipulation of historical regimes of hydrology, nutrient loading, and fire. Water Conservation Area 2A (WCA-2A) in the northern Everglades has been a focal point for the study of ecological effects of nutrient loading, especially phosphorus (P), from the nearby Everglades Agricultural Area (EAA). The overall objective of our study was to evaluate recent (1990 to 1998) changes in the spatial extent and patterns of soil P enrichment in Everglades WCA-2A. Surface soil was sampled to a depth of 10 cm at 62 sites within WCA-2A during 1998 for analysis of total phosphorus (TP) content. Geostatistical methods were used to create an interpolated grid of soil TP values across WCA-2A. Comparison of the results of this study with a similar study performed in 1990 showed that the extent of soil P enrichment in surface soil and sediments increased between 1990 and 1998, as evidenced by increased coverage of highly P-enriched soil near the primary surface inflows and a general increase in the concentration of soil TP in the interior regions of WCA-2A. Approximately 73% (31 777 ha) of the total land area of WCA-2A was considered P-enriched (soil total P > 500 mg kg(-1)) in 1998, compared with 48% of the land area (20,829 ha) in 1990, an average increase of 1,327 ha yr(-1). Study results indicate that the soil P enrichment "front" has advanced further into the relatively unimpacted interior of WCA-2A during the past several years.     

LAKE CHAMPLAIN BASIN NONPOINT SOURCE PHOSPHORUS ASSESSMENT1

ABSTRACT: Existing land use data were used to estimate nonpoint source phosphorus loads to Lake Champlain (Vermont/New York/Quebec) in a loading function model that combined P concentration coefficients with regional hydrologic data. The estimates were verified against monitored loading data, then used to assess the relative magnitudes of contributions from major land uses and regions of the Lake Champlain Basin. The Basin is comprised of 62 percent forest, 28 percent agricultural land, 3 percent urban land, and 7 percent water. The best-fit model estimated an annual total P load of 457 mt/year, which did not differ significantly from the 458 metric tons/year measured for an average hydrologic year, and accurately predicted loads from major tributaries. Agriculture contributes 66 percent of the annual nonpoint source P load to Lake Champlain; urban and forest land contribute 18 percent and 16 percent, respectively. Because agricultural land contributes most nonpoint source P to Lake Champlain, load reduction effort must deal with agricultural sources. However, because the urban 3 percent of the basin contributes 18 percent of the estimated load, high load reduction efficiencies might be achieved by addressing urban sources. This assessment clearly demonstrated the relationship between land use and P loads in the Lake Champlain Basin, a prerequisite for policy-makers to endorse a P management strategy requiring changes in land use and management.     

Predicting Invasiveness of Plant Species Based on Biological Information

Abstract: Previous studies suggest that, within particular groups of plant species, biological attributes can be used to predict the potential invasiveness of species that are intentionally introduced for horticultural or agricultural purposes. We examined the broad question of whether commonly available biological information can predict the invasiveness of a wide range of intentionally and accidentally introduced species. We collected information from published floras on 165 pairs of plant species. In each pair, one species originated in Europe and successfully invaded New Brunswick, Canada, and the other was a congeneric species that has not invaded North America. Only three biological characters—lifeform, stem height, and flowering period—and European geographic range were known for all species. We conducted multiple logistic regression analyses using two-thirds (110) of the species pairs and tested the predictive ability of resulting models using the remaining 55 pairs. Although a significant logistic regression model was obtained using the biological attributes, the model could not predict invasiveness of the test species pairs. In contrast, a model using only European range successfully predicted invasiveness in 70% of the test species. The importance of geographic range suggests that prediction of invasiveness on a species-by-species basis is not likely to help stem the flow of accidentally introduced invasive species. Species that are inadvertently picked up and moved to a new location due to their wide distribution are the same species that are likely to succeed in a new environment due to their wide environmental tolerances.     

Use of fuzzy logic models for prediction of taste and odor compounds in algal bloom-affected inland water bodies

Mechanistic modeling of how algal species produce metabolites (e.g., taste and odor compounds geosmin and 2-methyl isoborneol (2-MIB)) as a biological response is currently not well understood. However, water managers and water utilities using these reservoirs often need methods for predicting metabolite production, so that appropriate water treatment procedures can be implemented. In this research, a heuristic approach using Adaptive Network-based Fuzzy Inference System (ANFIS) was developed to determine the underlying nonlinear and uncertain quantitative relationship between observed cyanobacterial metabolites (2-MIB and geosmin), various algal species, and physical and chemical variables. The model is proposed to be used in conjunction with numerical water quality models that can predict spatial–temporal distribution of flows, velocities, water quality parameters, and algal functional groups. The coupling of the proposed metabolite model with the numerical water quality models would assist various utilities which use mechanistic water quality models to also be able to predict distribution of taste and odor metabolites, especially when monitoring of metabolites is limited. The proposed metabolite model was developed and tested for the Eagle Creek Reservoir in Indiana (USA) using observations over a 3-year period (2008–2010). Results show that the developed models performed well for geosmin (R ²?=?0.83 for all training data and R ²?=?0.78 for validation of all 10 data points in the validation dataset) and reasonably well for the 2-MIB (R ²?=?0.82 for all training data and R ²?=?0.70 for 7 out of 10 data points in the validation dataset).     

The development of a novel process planning algorithm for an unconstrained hybrid manufacturing process

The application of state of the art manufacturing processes has always been constrained by the capabilities either from technical limitations such as limited materials and complex part geometries or production costs. As a result, hybrid manufacturing processes – where varied manufacturing operations are carried out – are emerging as a potential evolution for current manufacturing technologies. However, process planning methods capable of effectively utilising manufacturing resources for hybrid processes are currently limited. In this paper, a hybrid process, entitled iAtractive, combining additive, subtractive and inspection processes, along with part specific process planning is proposed. The iAtractive process aims to accurately manufacture complex geometries without being constrained by the capability of individual additive and subtractive processes. This process planning algorithm enables a part to be manufactured taking into consideration, process capabilities, production time and material consumption. This approach is also adapted for the remanufacture of existing parts. Four test parts have been manufactured from zero and existing parts, demonstrating the efficacy of the proposed hybrid process and the process planning algorithm.     

The Hyper-Envelope Modeling Interface (HEMI): A Novel Approach Illustrated Through Predicting Tamarisk (Tamarix spp.) Habitat in the Western USA

Habitat suitability maps are commonly created by modeling a species’ environmental niche from occurrences and environmental characteristics. Here, we introduce the hyper-envelope modeling interface (HEMI), providing a new method for creating habitat suitability models using Bezier surfaces to model a species niche in environmental space. HEMI allows modeled surfaces to be visualized and edited in environmental space based on expert knowledge and does not require absence points for model development. The modeled surfaces require relatively few parameters compared to similar modeling approaches and may produce models that better match ecological niche theory. As a case study, we modeled the invasive species tamarisk (Tamarix spp.) in the western USA. We compare results from HEMI with those from existing similar modeling approaches (including BioClim, BioMapper, and Maxent). We used synthetic surfaces to create visualizations of the various models in environmental space and used modified area under the curve (AUC) statistic and akaike information criterion (AIC) as measures of model performance. We show that HEMI produced slightly better AUC values, except for Maxent and better AIC values overall. HEMI created a model with only ten parameters while Maxent produced a model with over 100 and BioClim used only eight. Additionally, HEMI allowed visualization and editing of the model in environmental space to develop alternative potential habitat scenarios. The use of Bezier surfaces can provide simple models that match our expectations of biological niche models and, at least in some cases, out-perform more complex approaches.