Jaclyn Hall

Scaling categorical spatial data for earth systems models

Efforts to deduce the appropriate scales of ecosystem functions and how patterns change with scale have a long history in ecology and landscape ecology (Levin, 1992; O’Neill et al., 1996). Ecosystem function models are critical to predicting ecosystem responses to global change, but are limited by the technical challenges of model–data synthesis. Accurately relating phenomena across multiple scales is an important challenge in ecological modeling, as information is lost when converting between scales of analysis. Researchers must determine how much information is necessary to preserve the landscape signature of the ecological processes under study. Zhao & Liu (2014) sought to determine the appropriate spatial resolution for categorical land cover data to use in regional-scale models of carbon dynamics, and compared the use of two common categorical data resampling methods: majority (MR) and nearest neighbor (NNR). Their analysis of the NNR method showed a power-law relationship between study extent and grain, but results from MR method showed a different relationship, suggesting that the resampling method drove the results. Zhao & Liu (2014) concluded the NNR method to be superior and reported the MR approach produced ‘devastatingly deficient’ results. We discuss the lack of robustness of their power-law relationship by analyzing the configuration and composition of simulated landscapes subjected to different resampling methods. The authors stated that NNR is clearly preferential to the MR method because NNR preserves uncommon land cover types. They support their use of NNR by mis-citing Cain et al. (1997). Zhao & Liu (2014) state that the critical spatial resolution in scaling exercises follows a power-law function of the study region extent. We argue that the pattern of the landscape process to be modeled determines the results of the resampling method. We illustrate, using a simple simulated landscape, how the effect of resampling algorithm is related to the proportion of landscape within each land cover class and the spatial configuration (clumpiness)

Towards regional, error-bounded landscape carbon storage estimates for data-deficient areas of the world.

Monitoring landscape carbon storage is critical for supporting and validating climate change mitigation policies. These may be aimed at reducing deforestation and degradation, or increasing terrestrial carbon storage at local, regional and global levels. However, due to data-deficiencies, default global carbon storage values for given land cover types such as ‘lowland tropical forest’ are often used, termed ‘Tier 1 type’ analyses by the Intergovernmental Panel on Climate Change (IPCC). Such estimates may be erroneous when used at regional scales. Furthermore uncertainty assessments are rarely provided leading to estimates of land cover change carbon fluxes of unknown precision which may undermine efforts to properly evaluate land cover policies aimed at altering land cover dynamics. Here, we present a repeatable method to estimate carbon storage values and associated 95% confidence intervals (CI) for all five IPCC carbon pools (aboveground live carbon, litter, coarse woody debris, belowground live carbon and soil carbon) for data-deficient regions, using a combination of existing inventory data and systematic literature searches, weighted to ensure the final values are regionally specific. The method meets the IPCC ‘Tier 2’ reporting standard. We use this method to estimate carbon storage over an area of33.9 million hectares of eastern Tanzania, reporting values for 30 land cover types. We estimate that this area stored 6.33 (5.92–6.74) Pg C in the year 2000. Carbon storage estimates for the same study area extracted from five published Africa-wide or global studies show a mean carbon storage value of ∼50% of that reported using our regional values, with four of the five studies reporting lower carbon storage values. This suggests that carbon storage may have been underestimated for this region of Africa. Our study demonstrates the importance of obtaining regionally appropriate carbon storage estimates, and shows how such values can be produced for a relatively low investment.

Ecological and social outcomes of a new protected area in Tanzania.

Balancing ecological and social outcomes of conservation actions is recognized in global conservation policy but is challenging in practice. Compensation to land owners or users for foregone assets has been proposed by economists as an efficient way to mitigate negative social impacts of human displacement from protected areas. Joint empirical assessments of the conservation and social impacts of protected area establishment involving compensation payments are scarce. We synthesized social and biological studies related to the establishment of the Derema forest corridor in Tanzanias biodiverse East Usambara Mountains. This lengthy conservation process involved the appropriation of approximately 960 ha of native canopy agroforest and steep slopes for the corridor and monetary compensation to more than 1100 claimants in the surrounding villages. The overarching goals from the outset were to conserve ecological processes while doing no harm to the local communities. We evaluated whether these goals were achieved by analyzing 3 indicators of success: enhancement of forest connectivity, improvement of forest condition, and mitigation of negative impacts on local peoples livelihoods. Indicators of forest connectivity and conditions were enhanced through reductions of forest loss and exotic species and increases in native species and canopy closure. Despite great efforts by national and international organizations, the intervention failed to mitigate livelihood losses especially among the poorest people. The Derema case illustrates the challenges of designing and implementing compensation schemes for conservation-related displacement of people.

Fragmentation of Florida scrub in an urban landscape

The Florida scrub community is considered a biodiversity hotspot due to the high degree of endemism and the number of species restricted to a few counties or fragments. Florida scrub habitat is officially listed as an imperiled ecoregion of global importance because it is a geographically restricted habitat with a high diversity of rare and endemic flora. This study examines landscape metrics and plant species richness of scrub in Pinellas County, which is the most densely populated county in Florida and once contained large areas of Florida scrub. Landscape metrics on scrub area, historic xeric upland area, naturally vegetated upland area within proximity, isolation indices, disturbance, and soils were collected for the 20 largest and best remaining fragments of scrub in Pinellas County from Geographic Information Systems map layers, Digital Ortho Quarter Quadrangles, and field validation. Landscape metrics were compared with three categories of species richness: scrub species richness, obligate scrub species richness, and richness of species listed as threatened or endangered. All categories of species richness in remaining Florida scrub fragments in Pinellas County were significantly associated with area of remaining scrub habitat. Site elevation was associated with obligate scrub species richness and degree of disturbance was associated with higher species richness for listed species. We conclude that large areas of scrub in higher elevated uplands and active management in the form of prescription burning will be needed to ensure the persistence of a number of endemic scrub specific species within remaining fragments.

Hypertension in Florida: Data From the OneFlorida Clinical Data Research Network

Introduction Hypertension is highly prevalent in Florida, but surveillance through the Behavioral Risk Factor Surveillance System (BRFSS) is limited to self-reported hypertension and does not capture data on undiagnosed hypertension or measure blood pressure. We aimed to characterize the hypertensive population in the OneFlorida Clinical Research Consortium by using electronic health records and provide proof-of-concept for using routinely collected clinical data to augment surveillance efforts. Methods We identified patients with hypertension, defined as having at least 1 outpatient visit from January 2012 through June 2016 with an ICD-9-CM or ICD-10-CM diagnosis code for hypertension, or in the absence of a diagnosis, an elevated blood pressure (systolic ≥140 mm Hg or diastolic ≥90 mm Hg) recorded in the electronic health record at the most recent visit. The hypertensive population was characterized and mapped by zip code of patient residence to county prevalence. Results Of 838,469 patients (27.9% prevalence) who met the criteria for hypertension, 68% had received a diagnosis and 61% had elevated blood pressure. The geographic distribution of hypertension differed between diagnosed hypertension (highest prevalence in northern Florida) and undiagnosed hypertension (highest prevalence along eastern coast, in southern Florida, and in some rural western Panhandle counties). Uncontrolled hypertension was concentrated in southern Florida and the western Panhandle. Conclusion Our use of clinical data, representing usual care for Floridians, allows for identifying cases of uncontrolled hypertension and potentially undiagnosed cases, which are not captured by existing surveillance methods. Large-scale pragmatic research networks, like OneFlorida, may be increasingly important for tailoring future health care services, trials, and public health programs.

Outlier in Analysis of Cancer Mortality by US County

In the study by Dr Mokdad and colleagues regarding disparities in cancer mortality among US counties, 1 Florida county repeatedly stands out for highest rates of mortality nationally.1 The authors calculated that Union County, Florida, has 2 to 6 times the national rates of mortality for tracheal, bronchus and lung, kidney, liver, lip and oral cavity, colon and rectum, testicular, and pancreatic cancers.

Regional-scale management maps for forested areas of the Southeastern United States and the US Pacific Northwest

Forests in the United States are managed by multiple public and private entities making harmonization of available data and subsequent mapping of management challenging. We mapped four important types of forest management, production, ecological, passive, and preservation, at 250-meter spatial resolution in the Southeastern (SEUS) and Pacific Northwest (PNW) USA. Both ecologically and socio-economically dynamic regions, the SEUS and PNW forests represent, respectively, 22.0% and 10.4% of forests in the coterminous US. We built a random forest classifier using seasonal time-series analysis of 16 years of MODIS 16-day composite Enhanced Vegetation Index, and ancillary data containing forest ownership, roads, US Forest Service wilderness and forestry areas, proportion conifer and proportion riparian. The map accuracies for SEUS are 89% (10-fold cross-validation) and 67% (external validation) and PNW are 91% and 70% respectively with the same validation. The now publicly available forest management maps, probability surfaces for each management class and uncertainty layer for each region can be viewed and analysed in commercial and open-source GIS and remote sensing software.

Rural-urban and racial-ethnic differences in awareness of direct-to-consumer genetic testing

BackgroundAccess to direct-to-consumer genetic testing services has increased in recent years. However, disparities in knowledge and awareness of these services are not well documented. We examined awareness of genetic testing services by rural/urban and racial/ethnic status.MethodsAnalyses were conducted using pooled cross-sectional data from 4 waves (2011–2014) of the Health Information National Trends Survey (HINTS). Descriptive statistics compared sample characteristics and information sources by rural/urban residence. Logistic regression was used to examine the relationship between geography, racial/ethnic status, and awareness of genetic testing, controlling for sociodemographic characteristics.ResultsOf 13,749 respondents, 16.7% resided in rural areas, 13.8% were Hispanic, and 10.1% were non-Hispanic black. Rural residents were less likely than urban residents to report awareness of genetic testing (OR = 0.74, 95% CI = 0.63–0.87). Compared with non-Hispanic whites, racial/ethnic minorities were less likely to be aware of genetic testing: Hispanic (OR = 0.68, 95% CI = 0.56–0.82); and non-Hispanic black (OR = 0.74, 95% CI = 0.61–0.90).ConclusionsRural-urban and racial-ethnic differences exist in awareness of direct-to-consumer genetic testing. These differences may translate into disparities in the uptake of genetic testing, health behavior change, and disease prevention through precision and personalized medicine.

Environmental Protection and Affection in East Africa

This article questions the degree to which ecological theory can be used as justification for protection of ‘natural environments’ as well as in determining which portions or features of those environments should be protected. As have others, Mark Sagoff points to a range of uncertainties and difficulties involved in the use of ecological theory ‘either to conceptualize what to preserve in the natural world or to understand the reasons to preserve it.’ Rather than the use of ecologic concepts (‘scientization of the environment’ in his terms), he suggests that ‘the nature that should be counted as “environmental” comprises wild places that—because of their beauty, history, intricacy, and majesty— people care about,’ and that nature should be defined more on the basis of ‘personal affection’ than scientific analysis. Sagoff does not, however, critically examine or provide actual or hypothetical examples of the application of such ‘affective criteria’ to formulating a conservation strategy. Nor does the article discuss the history or current state of affective responses to nature, including, for example, such contrary trends as the history of dissent in the US and elsewhere over the establishment and management of national parks, or more broadly, the history of commitment to ‘taming’ rather than protecting nature. Moreover, the paper is strongly premised on objective and subjective conditions in the US and other wealthy nations and does not consider how very different conditions in the developing world may affect its perspectives and conclusions. We suggest that the article’s premises and prescriptions are not well suited to the conditions and challenges in most developing countries. This is particularly true in subSaharan Africa, where we conduct research on the social and ecological impacts of protected areas. We will briefly cite features and cases from East Africa that indicate difficulties with the paper’s arguments and point to a more pragmatic approach to justifying and identifying the objectives for protection of natural environments. In many respects we agree with Sagoff’s critiques, and agree that in East Africa and elsewhere, the relevant criteria for protection of natural environments should not—and mostly cannot—invoke ‘primeval nature’ or ecologic processes undisturbed by human