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1.
Ecol Appl ; 30(6): e02123, 2020 09.
Article in English | MEDLINE | ID: mdl-32160362

ABSTRACT

Although ecosystems respond to global change at regional to continental scales (i.e., macroscales), model predictions of ecosystem responses often rely on data from targeted monitoring of a small proportion of sampled ecosystems within a particular geographic area. In this study, we examined how the sampling strategy used to collect data for such models influences predictive performance. We subsampled a large and spatially extensive data set to investigate how macroscale sampling strategy affects prediction of ecosystem characteristics in 6,784 lakes across a 1.8-million-km2 area. We estimated model predictive performance for different subsets of the data set to mimic three common sampling strategies for collecting observations of ecosystem characteristics: random sampling design, stratified random sampling design, and targeted sampling. We found that sampling strategy influenced model predictive performance such that (1) stratified random sampling designs did not improve predictive performance compared to simple random sampling designs and (2) although one of the scenarios that mimicked targeted (non-random) sampling had the poorest performing predictive models, the other targeted sampling scenarios resulted in models with similar predictive performance to that of the random sampling scenarios. Our results suggest that although potential biases in data sets from some forms of targeted sampling may limit predictive performance, compiling existing spatially extensive data sets can result in models with good predictive performance that may inform a wide range of science questions and policy goals related to global change.


Subject(s)
Ecosystem , Lakes
2.
Nurse Educ Today ; 84: 104261, 2020 Jan.
Article in English | MEDLINE | ID: mdl-31722281

ABSTRACT

BACKGROUND: Phenomenological empathy and sense of coherence are two researched communication approaches used to improve therapeutic connections with patients in a variety of nurse related settings. The aim of this study is to evaluate students' feedback concerning how this event has enabled that understanding, development and refinement of skill-sets in PE and SoC when managing the acutely ill during simulation. METHODS: 114 third year bachelor degree-nursing students were given the opportunity to complete an evaluation, developed for the specific purpose of this study. The evaluation contained six closed questions on a four point Likert-scale and three open questions, handed out upon completion of the standardised patient simulation of the acutely ill. Comments written in response to the open questions were analysed using manifest content analysis and closed questions using SPSS to produce descriptive frequencies. RESULTS: 100 students completed the evaluation. Student nurses', regardless of previous experience or age, indicated the need for more education and practice in phenomenological empathy and sense of coherence to enhance their ability to build therapeutic connections with the acutely ill. CONCLUSIONS: Teaching phenomenological empathy and sense of coherence, as an integral part of standardised patient simulation is necessary to motivate student nurses ability to build therapeutic relationships with the acutely ill to enhance person centred care.


Subject(s)
Acute Disease/nursing , Communication , Nurse-Patient Relations , Patient Simulation , Students, Nursing , Adult , Education, Nursing, Baccalaureate , Female , Humans , Male , Middle Aged , Surveys and Questionnaires , Young Adult
3.
Ecol Evol ; 7(9): 3046-3058, 2017 05.
Article in English | MEDLINE | ID: mdl-28480004

ABSTRACT

Understanding broad-scale ecological patterns and processes often involves accounting for regional-scale heterogeneity. A common way to do so is to include ecological regions in sampling schemes and empirical models. However, most existing ecological regions were developed for specific purposes, using a limited set of geospatial features and irreproducible methods. Our study purpose was to: (1) describe a method that takes advantage of recent computational advances and increased availability of regional and global data sets to create customizable and reproducible ecological regions, (2) make this algorithm available for use and modification by others studying different ecosystems, variables of interest, study extents, and macroscale ecology research questions, and (3) demonstrate the power of this approach for the research question-How well do these regions capture regional-scale variation in lake water quality? To achieve our purpose we: (1) used a spatially constrained spectral clustering algorithm that balances geospatial homogeneity and region contiguity to create ecological regions using multiple terrestrial, climatic, and freshwater geospatial data for 17 northeastern U.S. states (~1,800,000 km2); (2) identified which of the 52 geospatial features were most influential in creating the resulting 100 regions; and (3) tested the ability of these ecological regions to capture regional variation in water nutrients and clarity for ~6,000 lakes. We found that: (1) a combination of terrestrial, climatic, and freshwater geospatial features influenced region creation, suggesting that the oft-ignored freshwater landscape provides novel information on landscape variability not captured by traditionally used climate and terrestrial metrics; and (2) the delineated regions captured macroscale heterogeneity in ecosystem properties not included in region delineation-approximately 40% of the variation in total phosphorus and water clarity among lakes was at the regional scale. Our results demonstrate the usefulness of this method for creating customizable and reproducible regions for research and management applications.

4.
PLoS One ; 10(8): e0135454, 2015.
Article in English | MEDLINE | ID: mdl-26267813

ABSTRACT

Catchment land uses, particularly agriculture and urban uses, have long been recognized as major drivers of nutrient concentrations in surface waters. However, few simple models have been developed that relate the amount of catchment land use to downstream freshwater nutrients. Nor are existing models applicable to large numbers of freshwaters across broad spatial extents such as regions or continents. This research aims to increase model performance by exploring three factors that affect the relationship between land use and downstream nutrients in freshwater: the spatial extent for measuring land use, hydrologic connectivity, and the regional differences in both the amount of nutrients and effects of land use on them. We quantified the effects of these three factors that relate land use to lake total phosphorus (TP) and total nitrogen (TN) in 346 north temperate lakes in 7 regions in Michigan, USA. We used a linear mixed modeling framework to examine the importance of spatial extent, lake hydrologic class, and region on models with individual lake nutrients as the response variable, and individual land use types as the predictor variables. Our modeling approach was chosen to avoid problems of multi-collinearity among predictor variables and a lack of independence of lakes within regions, both of which are common problems in broad-scale analyses of freshwaters. We found that all three factors influence land use-lake nutrient relationships. The strongest evidence was for the effect of lake hydrologic connectivity, followed by region, and finally, the spatial extent of land use measurements. Incorporating these three factors into relatively simple models of land use effects on lake nutrients should help to improve predictions and understanding of land use-lake nutrient interactions at broad scales.


Subject(s)
Lakes/analysis , Lakes/chemistry , Geography , Hydrology , Michigan , Nitrogen/analysis , Phosphorus/analysis
5.
Gigascience ; 4: 28, 2015.
Article in English | MEDLINE | ID: mdl-26140212

ABSTRACT

Although there are considerable site-based data for individual or groups of ecosystems, these datasets are widely scattered, have different data formats and conventions, and often have limited accessibility. At the broader scale, national datasets exist for a large number of geospatial features of land, water, and air that are needed to fully understand variation among these ecosystems. However, such datasets originate from different sources and have different spatial and temporal resolutions. By taking an open-science perspective and by combining site-based ecosystem datasets and national geospatial datasets, science gains the ability to ask important research questions related to grand environmental challenges that operate at broad scales. Documentation of such complicated database integration efforts, through peer-reviewed papers, is recommended to foster reproducibility and future use of the integrated database. Here, we describe the major steps, challenges, and considerations in building an integrated database of lake ecosystems, called LAGOS (LAke multi-scaled GeOSpatial and temporal database), that was developed at the sub-continental study extent of 17 US states (1,800,000 km(2)). LAGOS includes two modules: LAGOSGEO, with geospatial data on every lake with surface area larger than 4 ha in the study extent (~50,000 lakes), including climate, atmospheric deposition, land use/cover, hydrology, geology, and topography measured across a range of spatial and temporal extents; and LAGOSLIMNO, with lake water quality data compiled from ~100 individual datasets for a subset of lakes in the study extent (~10,000 lakes). Procedures for the integration of datasets included: creating a flexible database design; authoring and integrating metadata; documenting data provenance; quantifying spatial measures of geographic data; quality-controlling integrated and derived data; and extensively documenting the database. Our procedures make a large, complex, and integrated database reproducible and extensible, allowing users to ask new research questions with the existing database or through the addition of new data. The largest challenge of this task was the heterogeneity of the data, formats, and metadata. Many steps of data integration need manual input from experts in diverse fields, requiring close collaboration.


Subject(s)
Database Management Systems , Ecology , Geographic Information Systems
6.
PLoS One ; 9(4): e95769, 2014.
Article in English | MEDLINE | ID: mdl-24788722

ABSTRACT

We compiled a lake-water clarity database using publically available, citizen volunteer observations made between 1938 and 2012 across eight states in the Upper Midwest, USA. Our objectives were to determine (1) whether temporal trends in lake-water clarity existed across this large geographic area and (2) whether trends were related to the lake-specific characteristics of latitude, lake size, or time period the lake was monitored. Our database consisted of >140,000 individual Secchi observations from 3,251 lakes that we summarized per lake-year, resulting in 21,020 summer averages. Using Bayesian hierarchical modeling, we found approximately a 1% per year increase in water clarity (quantified as Secchi depth) for the entire population of lakes. On an individual lake basis, 7% of lakes showed increased water clarity and 4% showed decreased clarity. Trend direction and strength were related to latitude and median sample date. Lakes in the southern part of our study-region had lower average annual summer water clarity, more negative long-term trends, and greater inter-annual variability in water clarity compared to northern lakes. Increasing trends were strongest for lakes with median sample dates earlier in the period of record (1938-2012). Our ability to identify specific mechanisms for these trends is currently hampered by the lack of a large, multi-thematic database of variables that drive water clarity (e.g., climate, land use/cover). Our results demonstrate, however, that citizen science can provide the critical monitoring data needed to address environmental questions at large spatial and long temporal scales. Collaborations among citizens, research scientists, and government agencies may be important for developing the data sources and analytical tools necessary to move toward an understanding of the factors influencing macro-scale patterns such as those shown here for lake water clarity.


Subject(s)
Data Collection/methods , Geography , Lakes , Water Quality , Midwestern United States
7.
Environ Monit Assess ; 141(1-3): 131-47, 2008 Jun.
Article in English | MEDLINE | ID: mdl-17724567

ABSTRACT

We quantified potential biases associated with lakes monitored using non-probability based sampling by six state agencies in the USA (Michigan, Wisconsin, Iowa, Ohio, Maine, and New Hampshire). To identify biases, we compared state-monitored lakes to a census population of lakes derived from the National Hydrography Dataset. We then estimated the probability of lakes being sampled using generalized linear mixed models. Our two research questions were: (1) are there systematic differences in lake area and land use/land cover (LULC) surrounding lakes monitored by state agencies when compared to the entire population of lakes? and (2) after controlling for the effects of lake size, does the probability of sampling vary depending on the surrounding LULC features? We examined the biases associated with surrounding LULC because of the established links between LULC and lake water quality. For all states, we found that larger lakes had a higher probability of being sampled compared to smaller lakes. Significant interactions between lake size and LULC prohibit us from drawing conclusions about the main effects of LULC; however, in general lakes that are most likely to be sampled have either high urban use, high agricultural use, high forest cover, or low wetland cover. Our analyses support the assertion that data derived from non-probability-based surveys must be used with caution when attempting to make generalizations to the entire population of interest, and that probability-based surveys are needed to ensure unbiased, accurate estimates of lake status and trends at regional to national scales.


Subject(s)
Environmental Monitoring , Fresh Water , Probability , United States
8.
Environ Sci Technol ; 41(22): 7688-93, 2007 Nov 15.
Article in English | MEDLINE | ID: mdl-18075075

ABSTRACT

Declines in Ca and Mg in low ANC lakes recovering from acidic deposition are widespread across the northern hemisphere. We report overall increases between 1984 and 2004 in the concentrations of Ca + Mg and Cl in lakes representing the statistical population of nearly 4000 low ANC lakes in the northeast U.S. Increases in Cl occurred in nearly all lakes in urbanized southern New England, but only 18% of lakes in more remote Maine had Cl increases. This spatial pattern implicates road salt application as the major source of the increased Cl salts. Among the 48% of the lake population classified as salt-affected, the median changes in Cl (+133 microeq/L) and Ca + Mg (+47 microeq/ L) were large and positive in direction over the 20 years. However, in the unaffected lakes, Cl remained stable and Ca + Mg decreased (-3 microeq/L), consistent with reported long-term trends in base cations of acid-sensitive lakes. This discrepancy between the Cl groups suggests that changes in ion exchange processes in salt-affected watersheds have altered the geochemical cycling of Ca and Mg. One policy-relevant implication is that waters influenced by Cl salts complicate regional assessments of surface water recovery from "acid rain" related to the passage of the Clean Air Act.


Subject(s)
Cations , Chlorides/analysis , Environmental Monitoring/methods , Water Pollutants, Chemical/analysis , Acids , Anions , Calcium/chemistry , Chlorine/analysis , Environment , Environmental Pollutants/analysis , Magnesium/chemistry , Models, Theoretical , Salts/pharmacology , Water/analysis , Water Supply
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