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Landscape Epidemiology of Emerging Infectious Diseases in Natural and Human-Altered Ecosystems

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Landscape Epidemiology of Emerging Infectious Diseases in Natural and Human-Altered Ecosystems PY50CH19-Meentemeyer ARI 25 May 2012 18:6 V I E E W R S I E N C N Landscape Epidemiology A D V A of Emerging Infectious Diseases in Natural and Human-Altered Ecosystems Ross K. Meentemeyer,1,∗ Sarah E. Haas,1 and Toma´sVˇ aclav´ ık´ 2,3 1Center for Applied GIScience, Department of Geography and Earth Sciences, University of North Carolina, Charlotte, North Carolina 28223; email: [email protected]; [email protected] 2Department of Computational Landscape Ecology, Helmholtz Center for Environmental Research UFZ, 04318 Leipzig, Germany; email: [email protected] 3Department of Ecology and Environmental Sciences, Faculty of Science, Palacky´ University, 77146 Olomouc, Czech Republic; email: [email protected] Annu. Rev. Phytopathol. 2012. 50:19.1–19.24 Keywords The Annual Review of Phytopathology is online at connectivity, disease control, dynamic model, invasive species, phyto.annualreviews.org multiscale, species distribution model This article’s doi: 10.1146/annurev-phyto-081211-172938 Abstract Copyright c 2012 by Annual Reviews. A central challenge to studying emerging infectious diseases (EIDs) All rights reserved is a landscape dilemma: Our best empirical understanding of disease 0066-4286/12/0908/0001$20.00 dynamics occurs at local scales, whereas pathogen invasions and ∗Corresponding author management occur over broad spatial extents. The burgeoning field of landscape epidemiology integrates concepts and approaches from disease ecology with the macroscale lens of landscape ecology, en- abling examination of disease across spatiotemporal scales in complex environmental settings. We review the state of the field and describe analytical frontiers that show promise for advancement, focusing on natural and human-altered ecosystems. Concepts fundamental to practicing landscape epidemiology are discussed, including spatial scale, static versus dynamic modeling, spatially implicit versus explicit approaches, selecting ecologically meaningful variables, and inference versus prediction. We highlight studies that have advanced the field by incorporating multiscale analyses, landscape connectivity, and dynamic modeling. Future research directions include understanding disease as a component of interacting ecological disturbances, scaling up the ecological impacts of disease, and examining disease dynamics as a coupled human-natural system. 19.1 PY50CH19-Meentemeyer ARI 25 May 2012 18:6 INTRODUCTION uncertainties associated with human behavior and decision-making processes can further Emerging infectious diseases (EIDs) of plants complicate our understanding of disease Emerging infectious and animals are impacting natural ecosystems systems (84). The field of disease ecology has disease (EID): at unprecedented rates in response to increases made critical strides toward understanding how a disease undergoing in human mobility, climate change, and the range expansion or pathogens interact locally with plant and animal creation of new habitat conditions (4, 18, 51, increased incidence populations in natural systems. However, our 65). The dynamic and inherently spatial nature following introduction knowledge of larger-scale interactions between of an exotic pathogen of epidemiological processes presents unique the spatiotemporal heterogeneity of host and or reemergence of one challenges to studying and managing the spread environmental conditions and the rates at which once in decline of EIDs in natural communities. First, natural pathogens disperse through and among frag- Natural ecosystem: ecosystems often exhibit nonlinear dynamics mented host populations remains limited (39, an ecological system and feedbacks across a wide range of interacting consisting of wild 42, 83). Consequently, the challenge of explic- (and sometimes unknown) ecological variables populations of plants, itly integrating landscape heterogeneity of the (93, 94). Second, the heterogeneous nature of animals, and microbes biophysical environment into epidemiological that is not artificially the biotic and abiotic variables driving disease analyses must be overcome for us to better un- created (i.e., planted, dynamics in natural ecosystems is notoriously derstand the multiple scales at which epidemio- farmed, or intensively difficult to measure, and there is almost never managed) by humans logical processes operate in ecological systems. a single right scale of observation (32, 62) The burgeoning field of landscape epidemi- (Figure 1). In human-altered ecosystems ology examines interactions between landscape (e.g., fragmented suburban forests), additional a b 400 m 300 m 200 m 100 m Sampling site Host Non-host Figure 1 Diagram of two landscape scenarios illustrating scale-dependent effects of host (showningreen) and nonhost (showninwhite) habitat abundance and configuration across nested scales of increasing radii (100-m increments) around a sampling site (black square). The amount of host habitat surrounding each site in conjunction with the structural connectivity of habitat may influence the global infection pressure on a site. If a single-scale analysis was conducted at 100 m, scenarios a and b would be identical in the amount and configuration of habitat conditions. At 200 m, however, scenario a would appear to be connected to a greater amount of contiguous host habitat. A multiscale examination, or an analysis that was conducted at a larger spatial extent (e.g., 400 m), would further reveal that scenario b is surrounded by a larger area of contiguous host habitat and thus may exhibit higher infection pressure from the surrounding landscape. 19.2 Meentemeyer · Haas · Vaclav´ ´ık PY50CH19-Meentemeyer ARI 25 May 2012 18:6 1500 m a a 2000 m 1500 m b b 2500 m Figure 2 The spread and persistence of diseases across heterogeneous landscapes depend on spatial heterogeneity and functional connectivity of landscape conditions. (a) Connectivity is greater between the blue sites than it is between the blue and yellow sites and the red site, despite their greater Euclidean distance separation, because the red site is located on the other side of a mountain range, which may function as a geographic barrier to inoculum, host, and/or vector dispersal. (b) In a waterborne pathosystem in which inoculum is dispersed in streams, the two yellow sites (separated by the greatest Euclidean distance) could actually be the most connected because the lower yellow site is located downstream from the upper yellow site. heterogeneity and the underlying ecological and water). For example, rivers and streams Human-altered processes that drive the spread and persistence may act as dispersal corridors that foster the ecosystem: a natural of disease (42, 58, 83, 88). By definition, spread of infection across a heterogeneous ecosystem harboring landscape epidemiology integrates concepts landscape for waterborne plant pathogens (53), wild populations of plants, animals, and and approaches from disease ecology with the yet in other systems, such as zoonotic diseases microbes that is macroscale lens of landscape ecology. The of terrestrial mammals, these same water heavily influenced by intersection of these perspectives enables us to bodies might function as geographic barriers human activities, such understand how the spatial configuration and by impeding host or vector movement (97). as urbanization or composition of landscape features influence Implementing a landscape approach is typ- selective harvesting; does not include epidemiological processes across broad geo- ically not a trivial task. Landscape approaches agroecosystems with graphical areas that extend beyond processes that incorporate spatiotemporal complexity in intensive farming operating locally within a single community. epidemiological systems require careful spatial Landscape Thus, landscape epidemiology is more than linking of molecular and microbial observa- heterogeneity: simply establishing plots in the field and ex- tions of disease distribution with measurements spatial variability of amining differences in local biotic and abiotic of corresponding (and surrounding) biotic and biotic and abiotic conditions among sites; the key is to gain insight abiotic conditions (7). Most landscape epidemi- conditions over a specified geographic into the geographical distribution of disease ological studies utilize geographic information area and to understand how landscape connectivity systems (GIS) and other geospatial technolo- Landscape ecology: influences spatial interactions between sus- gies (e.g., remote sensing) to assimilate the the science of studying ceptible and infected individuals (Figure 2). large, spatial data sets that enable analysis the reciprocal The environmental conditions that determine of relationships between the distribution of interactions between landscape connectivity for dispersal may vary disease and landscape heterogeneity. However, spatial patterns of by region and depend on whether a pathogen despite the many ways GIS has helped advance landscape heterogeneity and disperses biotically (e.g., vector-borne insect landscape epidemiology, GIS software is no- ecological processes movement) or abiotically (e.g., flows of wind toriously limited to providing static snapshots www.annualreviews.org • Landscape Epidemiology 19.3 PY50CH19-Meentemeyer ARI 25 May 2012 18:6 on landscape approaches in epidemiological LEVERAGING GEOSPATIAL ANALYSIS AND studies in order to describe the current state COMPUTATIONAL MODELING of the field. We classified papers based on six categories: (a) research design, (b) static versus Understanding
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