Factors Influencing the Spatial Ecology of Cheetahs in Fenced Protected Areas

Spatial ecology of soil nematodes: Perspectives from global to micro scales

Spatial ecology focuses on the role of space and time in ecological processes and events from a local to a global scale and is particularly relevant in developing environmental policy and (mandated) monitoring goals. In other words, spatial ecology is where geography and ecology intersect, and high-quality geospatial data and analysis tools are required to address emerging issues in spatial ecology. In this commentary and review for the International Journal of GIS Special Issue on Spatial Ecology, we highlight selected current research priorities in spatial ecology and describe geospatial data and methods for addressing these tasks. Geoinformation research themes are identified in population ecology, community and landscape ecology, and ecosystem ecology, and these themes are further linked to the assessment of ecosystem services. Methods in spatial ecology benefit from explicit consideration of spatial autocorrelation, and applications discussed in this review include species distribution modeling, remote sensing of community and ecosystem properties, and models of climate change. The linkages of the Special Issue papers to these emerging issues are described.

The overlap between spatial and physiological ecology is generally understudied, yet both fields are fundamentally related in assessing how individuals balance limited resources. Herein, we quantified the relationships between spatial ecology using two parameters of home range (annual home range area and number of burrows used in 1 yr) and four measures of physiology that integrate stress and immunity (baseline plasma corticosterone [CORT] concentration, plasma lactate concentration, heterophil-to-lymphocyte [H∶L] ratio, and bactericidal ability [BA]) in a wild free-ranging population of the gopher tortoise (Gopherus polyphemus) to test the hypothesis that space usage is correlated with physiological state. We also used structural equation models (SEMs) to test for causative relationships between the spatial and physiological parameters. We predicted that larger home ranges would be negatively correlated with traditional biomarkers of stress and positively correlated with immunity, consistent with our hypothesis that home ranges are determined based on individual condition. Males had larger home ranges, used more burrows, and had higher baseline CORT than females. We found significant negative correlations between lactate and home range (, , ). CORT was negatively correlated with the number of burrows used in both sexes (, , , adjusted ). No correlations were observed between space use and BA or, notably, H∶L ratio. SEMs suggested that variation in the number of burrows used was a result of variation in baseline CORT. The lack of a relationship between H∶L ratio and home range suggests that home range differences are not associated with differences in chronic stress, despite the pattern between baseline CORT and number of burrows used. Instead, this study indicates that animals balance trade-offs in energetics, likely by way of baseline corticosteroid, in such a way as to maintain function across continuously variable home range strategies.

Trindade Petrels (Pterodroma arminjoniana) are vulnerable gadfly petrels that breed on the remote Trindade Island, located ~1100 km off the Brazilian coast. Little is known about their spatial ecology, and their trophic ecology has only been described for the breeding season. We tagged four Trindade Petrels with global location sensing loggers (GLS) from October 2013 to November 2014 and sampled the blood and feathers (innermost primary and the eighth secondary) of 14 individuals to evaluate their year-round spatial and isotopic ecology. We examined individual distributions, habitat use and suitability, activity, and isotopic values during the breeding, migration, and non-breeding periods. Trindade Petrels used areas in the southwest Atlantic Ocean (between 10°N and 50°S in latitude) during the breeding season. They migrated through pelagic waters of the tropical Atlantic to the northwest Atlantic, where they spent the non-breeding season. Trindade Petrels used mostly tropical to subtropical waters in areas of intermediate to high wind speeds and low marine productivity. Individuals spent more time foraging at night than during the day. During the breeding season, birds in northerly areas had higher carbon-13 values, and birds that used more pelagic areas foraged on prey at a higher trophic level (higher nitrogen-15 values) than those in more southern and coastal areas. Isotopic values during the breeding, migration, and non-breeding periods differed, possibly due to differences among individuals in their at-sea distribution throughout the year. We confirmed the non-breeding distribution of Trindade Petrels, which was previously known only from vessel sightings and stranded birds. Our results also suggest a strong temporal segregation in the at-sea distribution and trophic ecology between two groups of individuals, which might indicate the existence of two separate breeding populations.

BackgroundMovement links the distribution of habitats with the social environment of animals using those habitats. Despite the links between movement, habitat selection, and socioecology, their integration remains a challenge due to lack of shared vocabulary across fields, methodological gaps, and the implicit (rather than explicit) historical development of theory in the fields of social and spatial ecology. Given these challenges can be addressed, opportunity for further study will provide insight about the links between social, spatial, and movement ecology. Here, our objective was to disentangle the roles of habitat selection and social association as drivers of movement in caribou (Rangifer tarandus).MethodsTo accomplish our objective, we modelled the relationship between collective movement and selection of foraging habitats using socially informed integrated step selection function (iSSF). Using iSSF, we modelled the effect of social processes, i.e., nearest neighbour distance and social preference, and movement behaviour on patterns of habitat selection.ResultsBy unifying social network analysis with iSSF, we identified movement-dependent social association, where individuals took shorter steps in lichen habitat and foraged in close proximity to more familiar individuals.ConclusionsOur study demonstrates that social preference is context-dependent based on habitat selection and foraging behaviour. We therefore surmise that habitat selection and social association are drivers of collective movement, such that movement is the glue between habitat selection and social association. Here, we put these concepts into practice to demonstrate that movement is the glue connecting individual habitat selection to the social environment.

How space directly and indirectly affects biodiversity and ecosystem functioning is the focus of several subdisciplines in the life sciences. All of these subdisciplines share concepts and analytical methods that stem from the field of spatial ecology. Spatial ecology focuses on the study and modeling of the role(s) of space on ecological processes that in turn affects ecological patterns. Our goal is to introduce why space is important for ecology and conservation, and how various components of space can inform ecological processes and be modeled. We introduce these issues by tracking the history and development of spatial ecology and conservation, and how different types of modeling frameworks have been advanced over the years to capture spatial problems. Spatial ecology largely arose from key empirical and theoretical developments in the 1950s and 1970s that emphasized how spatial heterogeneity could promote population persistence and how dispersal could have major impacts on populations and communities. With more recent growth in spatial models, the availability of spatial data, computing capacity, and ongoing large-scale environmental change, spatial ecology has matured as a discipline. The maturation has led to spatial ecology becoming integral to the entire fields of ecology and conservation.

Despite the increasing importance of new survey tools such as unmanned aerial vehicles (UAVs), the implications of how their spatial deployment may interact with species detection errors have not yet been assessed. Acknowledging and incorporating these errors are crucial for accurate population estimation and improved management. To address this important gap in our knowledge, and to discover how flight plans should be selected to reduce overall error, we simulated contrasting UAV flight surveys over a range of population densities and dispersion patterns using different detection errors. We found that if a survey is carried out using an individual transect that low and slow flights consistently provide the best estimates of abundance and occupancy. However, the greater sampling area afforded by higher or faster flights resulted in more complex guidelines for estimates of abundance or occupancy over larger study areas. For highly clustered populations, especially those at low densities, a high and fast survey is preferable, as its greater area coverage best enables detection of local occupancy. The performance rankings of flight plans were sensitive to the underlying species detectability and, to a lesser extent, population density and aggregation. This suggests that UAV survey plans need to account for the spatial and movement ecology of target species, and that flight plans should adapt as an invasive species spreads, or a threatened species contracts. We encapsulate our results in a decision tree to guide flight planning for given survey objectives, detectability, and ecological context. Importantly, these findings provide guidance to other fields with transect‐based surveys such as manned aviation and road or ground transects that trade‐off sampling area and precision of estimates. Promising new technologies such as UAVs will be best utilized by ecologists if detection errors, and their interaction with the spatial ecology of the species, are carefully assessed.

Count data arise frequently in ecological analyses, but regularly violate the equi‐dispersion constraint imposed by the most popular distribution for analyzing these data, the Poisson distribution. Several approaches for addressing over‐dispersion have been developed (e.g., negative binomial distribution), but methods for including both under‐dispersion and over‐dispersion have been largely overlooked. We provide three specific examples drawn from life‐history theory, spatial ecology, and community ecology, and illustrate the use of the Conway‐Maxwell‐Poisson (CMP) distribution as compared to other common models for count data. We find that where equi‐dispersion is violated, the CMP distribution performs significantly better than the Poisson distribution, as assessed by information criteria that account for the CMP's additional distribution parameter. The Conway‐Maxwell‐Poisson distribution has seen rapid development in other fields such as risk analysis and linguistics, but is relatively unknown in the ecological literature. In addition to providing a more flexible exponential distribution for count data that is easily integrated into generalized linear models, the CMP allows ecologists to focus on the magnitude of under‐ or over‐dispersion as opposed to the simple rejection of the equi‐dispersion null hypothesis. By demonstrating its suitability in a variety of common ecological applications, we hope to encourage its wider adoption as a flexible alternative to the Poisson.

Researchers on conservation planning and practice have increasingly recognized and adopted the pivotal role of landscape attributes in shaping the effectiveness of protected areas. However, the degree to which these concepts have been integrated into habitat restoration projects has not been quantified. We reviewed the global literature and found that landscape context was considered in fewer than one in eight restoration projects in the selection of restoration sites (11% of 472 projects). This figure was remarkably similar across terrestrial (10% of 243 projects), marine (13% of 89), and freshwater (13% of 164) ecosystems. Of the 54 restoration projects in which landscape context was considered in site selection, in just over half (56%), animal populations were reported to be larger or more diverse than in control areas. Tighter integration of concepts from spatial ecology and systematic conservation planning into restoration practice could improve the design, optimize placement, and enhance the ecological effectiveness of restoration projects in all ecosystems.

Under which ecological conditions should individuals help their neighbours? We investigate the effect of habitat saturation on the evolution of helping behaviours in a spatially structured population. We combine the formalisms of population genetics and spatial moment equations to tease out the effects of various physiological (direct benefits and costs of helping) and ecological parameters (such as the density of empty sites) on the selection gradient on helping. Our analysis highlights the crucial importance of demography for the evolution of helping behaviours. It shows that habitat saturation can have contrasting effects, depending on the form of competition (direct vs. indirect competition) and on the conditionality of helping. In our attempt to bridge the gap between spatial ecology and population genetics, we derive an expression for relatedness that takes into account both habitat saturation and the spatial structure of genetic variation. This analysis helps clarify discrepancies in the results obtained by previous theoretical studies. It also provides a theoretical framework taking into account the interplay between demography and kin selection, in which new biological questions can be explored.

Two fundamental axes - space and time - shape ecological systems. Over the last 30 years spatial ecology has developed as an integrative, multidisciplinary science that has improved our understanding of the ecological consequences of habitat fragmentation and loss. We argue that accelerating climate change - the effective manipulation of time by humans - has generated a current need to build an equivalent framework for temporal ecology. Climate change has at once pressed ecologists to understand and predict ecological dynamics in non-stationary environments, while also challenged fundamental assumptions of many concepts, models and approaches. However, similarities between space and time, especially related issues of scaling, provide an outline for improving ecological models and forecasting of temporal dynamics, while the unique attributes of time, particularly its emphasis on events and its singular direction, highlight where new approaches are needed. We emphasise how a renewed, interdisciplinary focus on time would coalesce related concepts, help develop new theories and methods and guide further data collection. The next challenge will be to unite predictive frameworks from spatial and temporal ecology to build robust forecasts of when and where environmental change will pose the largest threats to species and ecosystems, as well as identifying the best opportunities for conservation.

The field of spatial ecology has expanded dramatically in the past few years. This volume, written by world experts in the field, gives detailed coverage of the main areas of development in spatial ecological theory. Integrating a perspective from field ecology with novel methods for simplifying spatial complexity, it offers a didactical treatment with a gradual increase in mathematical sophistication. In addition, the volume features introductions to those fundamental phenomena in spatial ecology where emerging spatial patterns influence ecological outcomes qualitatively as well as quantitatively. An appreciation and understanding of such systematic departures from standard, nonspatial models is required if ecological theory is to move on in the 21st century. Written for graduate students and researchers in theoretical, evolutionary, and spatial ecology, applied mathematics, and spatial statistics, this book is a ground-breaking treatment of modern spatial ecological theory.

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The international conference 'Models in population dynamics and ecology 2010: animal movement, dispersal and spatial ecology' took place at the University of Leicester, UK, on 1-3 September 2010, focusing on mathematical approaches to spatial population dynamics and emphasizing cross-scale issues. Exciting new developments in scaling up from individual level movement to descriptions of this movement at the macroscopic level highlighted the importance of mechanistic approaches, with different descriptions at the microscopic level leading to different ecological outcomes. At higher levels of organization, different macroscopic descriptions of movement also led to different properties at the ecosystem and larger scales. New developments from Levy flight descriptions to the incorporation of new methods from physics and elsewhere are revitalizing research in spatial ecology, which will both increase understanding of fundamental ecological processes and lead to tools for better management.

Understanding why, how, and when animals move is essential to many areas of ecology and related fields. Indeed, key aspects of animal behavior, population genetics, biological control, predator–prey dynamics, ecosystem engineering, and conservation biology all hinge upon knowing what critters are moving from where to where in a landscape, including information on how quickly, how regularly, and by what route they travel. The complexities involved in such processes have spawned tremendous efforts in both field research (where goals include measuring and characterizing such movements) and theoretical research (where goals include exploring the nature and potential consequences of movement). Ecologists today routinely receive some training in both empirical and theoretical research, and in the role of statistical analyses and model fitting as a way of linking the two perspectives. However, that has not always been the case. Spatial questions in ecology were long an area where the gulf between theory and reality was particularly wide. In part, this was due to the additional mathematical challenges of spatial models, but it also due to the perhaps greater technological challenges of measuring and contextualizing animal movements.