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Chapter 1
Introduction to Spatial Ecology and Its
Relevance for Conservation
1.1 What Is Spatial Ecology?
“Space: The final frontier”Kareiva (1994)
All aspects of ecology play out in space. From Darwin’s entangled bank to
Hutchinson’s ecological theater (Hutchinson 1965; Darwin 1859), space is inherent
to all processes and research in ecology. The importance of space has captured the
imagination of biologists interested in a wide variety of topics, such as migration,
species coexistence, deforestation, and the spread of invasive species. Therefore,
how space directly and indirectly affects biodiversity and ecosystem functioning is
implicitly and/or explicitly the focus of several subdisciplines in the life sciences
(Fig. 1.1).
All of these subdisciplines share concepts and analytical methods that stem from the
field of spatial ecology: a field coined by Tilman and Karieva in 1997. Since then, the
term “spatial ecology”has been used in a wide range of ways depending on each
ecological subdiscipline and field. Biogeography focuses on species geographic distri-
butions (Lomolino 2017). Landscape ecology relates spatial heterogeneity to ecological
processes and species distribution (Turner and Gardner 2015). Movement ecology
focuses on organismal dispersal and migration (Nathan et al. 2008). Macroecology
investigates the relation of processes and species at large spatial scales (Gaston and
Blackburn 2000). Metaecology considers dispersal and spatial interactions at different
spatial scales to model ecological processes that affect species distribution and dynam-
ics (i.e., metapopulations, metacommunities, metaecosystems; Massol et al. 2011).
Spatial and landscape genetics relate how landscape features affect gene glow and
local adaptation (Manel et al. 2003; Guillot et al. 2009). Finally, conservation biology
develops and applies spatial solutions to a variety of problems, including mitigating the
effects of roads, protected area networks, and spatial prioritization in conservation
planning (Primack 2014)(Fig.1.1).
Throughout this book, we use the term spatial ecology in a broad sense referring
to the study and modeling of the role(s) of space on ecological processes (e.g.,
©Springer Nature Switzerland AG 2018
R. Fletcher, M.-J. Fortin, Spatial Ecology and Conservation Modeling,
https://doi.org/10.1007/978-3-030-01989-1_1
1
robert.fletcher@ufl.edu
population dynamics, species interactions, dispersal) that in turn affects ecological
patterns, such as species distributions. This definition shares similarities with some
early definitions of landscape ecology (Pickett and Cadenasso 1995; Turner 1989).
Yet over the years, landscape ecology evolved to include socio-economic aspects of
landscapes as well (Wu 2017).
Research in spatial ecology aims to understand the processes that affect species
distributions and dynamics, and how these processes play out across space. Endog-
enous processes are related to the dynamics of each ecological entity (e.g., movement,
dispersal, and migration) and the interactions among entities within and across
species (population demographics, genetic variation, behavior, competition, facilita-
tion, trophic interactions, etc.). Exogenous processes are related to the response of
organisms to environmental factors that are themselves spatially structured (climate,
local habitat features, microhabitat heterogeneity, patch disturbance-succession,
environmental filtering, historical contingencies, etc.). Overall, it is the combined
action and feedback effects of these endogenous and exogenous processes that result
in the spatial patterns observed at different levels of organization though space (e.g.,
metapopulations, metacommunities, and metaecosystems) (Fig. 1.2).
Spatial ecology is increasingly applied to conservation and management to help
deliver more effective ways to conserve biodiversity. The rapid rate at which
landscapes are altered is creating spatially heterogeneous environmental conditions
that affect species ability to disperse and ultimately persist. Yet, even in homoge-
neous environments, endogenous processes alone can shape species spatial distri-
butions (Okubo 1974). This is why many of the core ecological theories and
analytical models used in spatial ecology are process-based ones. Therefore, one
of the most important cornerstones of spatial ecology as a discipline is the way in
Spatial
Ecology
Animal/Plant
Ecology
Animal Movement
Plant Dispersal
Modeling
Population
genetics
Population
dynamics
Community,
Ecosystem
Meta-
popu-
lation
Land-
scape
genetics
Landscape
Ecology
Epidemi-
ology
Spatial
pattern /
process
Meta-
community,
meta-ecosystem
Spatial
epidemi-
ology
Fig. 1.1 Spatial
subdisciplines derived from
ecological disciplines using
a spatial ecology framework
to tackle current
conservation issues
2 1 Introduction to Spatial Ecology and Its Relevance for Conservation
robert.fletcher@ufl.edu
which the challenges of understanding the processes underlying the spatial distribu-
tion of ecological entities are tackled. Spatial ecology offers concepts and tools to
understand, predict, and map how biodiversity responds to environmental change.
1.2 The Importance of Space in Ecology
Species dynamics occur over space and time. Space affects species in multiple ways
from how they use resources and occupy space within their home range and
throughout their geographical range, how they move, disperse, and migrate through
heterogeneous landscapes, as well as how they interact with other species
(Table 1.1).
To determine the relative importance of space on ecological patterns and pro-
cesses, both mathematical and statistical models are frequently used (Dale and Fortin
2014; Cantrell et al. 2009; Fortin et al. 2012; Ovaskainen et al. 2016). These two
modeling approaches encompass stark differences from data needs, model assump-
tions, and epistemologies (Fig. 1.2). Both process-based (e.g., mathematical, sto-
chastic simulations and computational models) and phenomenological approaches
(e.g., statistical regression models) have a long history of contributing to our under-
standing of the spatial distribution of ecological entities from fine to broad scales
(Levin 1976; MacArthur and Wilson 1967). Such spatial models aim to improve our
understanding of the underlying processes acting on species distributions (e.g., to
estimate the relative importance of environmental drivers versus dispersal to species
distributions) and to perform ecological forecasting (e.g., to predict species distribu-
tions based on such processes; Pagel and Schurr 2012; Dietze 2017).
The foundation for spatial ecology can be traced largely to the seminal paper of
Watt (1947) on the relationship between spatial pattern and ecological processes.
Watt (1947) emphasized that plants occurred in bounded communities—patches—
that form a dynamic mosaic across the landscape, what has become known as the
SA-sp: Spatial autocorrelation of the species
SA-env: Spatial structure of the environment
SD: Spatial dependence of species response to
spatially structured environment
Space
Environment Species
SD
SA-env SA-sp
Fig. 1.2 How space affects
both the spatial structure of
the environmental
conditions and species
distribution. Species
distribution is also affected
by the spatial structure of the
environmental data (adapted
from Wagner and Fortin
2005)
1.2 The Importance of Space in Ecology 3
robert.fletcher@ufl.edu
“shifting-mosaic steady state”concept (Bormann and Likens 1979). Then, in
the 1950s and 1960s, there were three key areas of research that emphasized the
importance of space for ecological processes and its relevance for conservation. First,
some influential experimental studies highlighted the importance of space for ecol-
ogy. In a seminal experiment, Huffaker (1958) showed how predator–prey dynamics
could be stable when including the potential for spatial refugia of prey, while stability
was not possible in small, homogenous habitats. This result was important because
prior to that time, spatial concepts had not been formally considered in theory and
concepts regarding species coexistence. This experiment emphasized the role of
movement in altering species interactions and community structure, a theme that
has persisted and grown over time.
A second area of conceptual development came from theoretical ecology
(Hastings and Gross 2012), where ecologists investigated how diffusion of organ-
isms through space can alter population and community dynamics (Skellam 1951;
Okubo and Levin 2001; Hilborn 1979). Skellam (1951) pioneered these ideas by
applying reaction–diffusion models originally derived for molecular processes to the
problem of dispersal and population dynamics. In this model, Skellam (1951)
assumed diffusion (or random movement) of organisms. While it is clear that
organisms do not move in a simple random manner, the utility of this approach is
that this simple formulation can go a long way in explaining observed patterns in
ecology (Kareiva 1982,1983), and it can be extended to capture non-random issues
(e.g., advection; Reeve et al. 2008). In addition, Skellam’s work set the stage for
modeling invasive spread, a topic of great importance to conservation biology.
The third area is the application of biogeographic concepts to our understanding
of species–area relationships by Preston (1948,1962) and later MacArthur and
Table 1.1 Examples of how space can be incorporated into spatial analyses and their effects on
ecological processes (adapted from Fortin et al. (2012))
Spatial aspects Effects on ecological processes and data
x–ycoordinates Location of data according to positions of other locations (Euclidean or
relative distance)
Spatial
autocorrelation
The magnitude, spatial scale, and directionality of data values as a function of
distances between data point locations
Spatial
relationship
Locations of abiotic predictors affect the responses of biotic/ecological
variables
Spatial legacy Influence of past spatial pattern on current ecological processes and species
current spatial pattern
Spatial
contingency
Influence of nearby locations (local neighbors) on ecological processes and
species spatial pattern
Spatial
perception
How the intervening landscape features affect daily animal movement and
species dispersal ability
Multiple spatial
scales
Additive spatial scales influence current spatial pattern
4 1 Introduction to Spatial Ecology and Its Relevance for Conservation
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Wilson (1963,1967). This area was particularly crucial in developing the application
of spatial ecology to practical issues of conservation (Higgs 1981). Indeed, many
ecological theories and conservation concepts, including practical solutions, stem
from island biogeography theory, where the size of islands/patches and their spatial
configuration (spacing/isolation) are critical for species persistence through variation
in colonization and extinction events (MacArthur and Wilson 1967; Laurance 2008).
The current era of spatial ecology has grown from island biogeography, where
dispersal of individuals is key and can act as a rescue effect or spatial insurance
(Loreau et al. 2003a) that protects a population from local extinction. Here, species
are often considered to act as metapopulations (Hanski 1999; Levins 1969). The
concept of spatial insurance has been extended to dispersal of several species to
maintain species assemblages and communities as metacommunities (Leibold et al.
2017,2004) and to maintain ecosystem functions as metaecosystems (Loreau et al.
2003b; Guichard 2017).
1.3 The Importance of Space in Conservation
Conservation biologists have increasingly embraced the importance of space in the
conservation of biodiversity and ecosystem services (Schagner et al. 2013; Moilanen
et al. 2009). Space is relevant for conservation in four major ways: (1) it is essential
for spatial mapping of biodiversity and ecosystem services; (2) it provides guidance
for mitigating effects of environmental change; (3) it facilitates effective prioritiza-
tion of areas for conservation; and (4) it provides key components of tools and
models used in conservation.
Several biogeography and macroecology theories provide spatial foundations for
understanding and mapping biodiversity across the planet. The emphasis on spatial
components first emerged in the field of biogeography, where there was interest in
identifying and understanding species distributions and geographic gradients in
biodiversity throughout the world. For instance, early on scientists emphasized the
latitudinal gradient of diversity, where diversity was greater in the tropics than in the
temperate zone (Currie and Paquin 1987). Understanding this and other biogeo-
graphic (and macroecological) patterns have been, and continue to be, of interest in
conservation as it helps identify hotspots of biodiversity and endemism of conser-
vation relevance (Myers et al. 2000; Dawson et al. 2017; Orme et al. 2005).
Many approaches to mitigating the effects of environmental change embrace spatial
concepts. For example, the use of corridors in conservation explicitly emphasizes how
the spatial configuration of the environment can promote biodiversity (Crooks and
Sanjayan 2006). Translocations and re-introduction programs require understanding
how potential release locations may inhibit or foster the success of such programs
(Seddon et al. 2014). Adaptation strategies to mitigate the effects of climate change
often emphasize spatial ecological concepts (Heller and Zavaleta 2009).
1.3 The Importance of Space in Conservation 5
robert.fletcher@ufl.edu
Conservation prioritization and planning, one of the major foci for conservation
biology, also emphasizes the importance of spatial ecology. Early rules for conser-
vation planning embraced the need to limit isolation of protected areas and maximize
their area (Diamond 1975). Later work has embraced explicit mapping of conserva-
tion prioritization strategies and how issues such as complementarity of biodiversity
among protected areas is essential for efficient conservation planning (Margules and
Pressey 2000). More recently, conservation planning for climate change emphasizes
how key areas are currently connected and how connectivity may change as climate
and land use continue to change (Pressey et al. 2007; Schmitz et al. 2015; Carroll
et al. 2017). Throughout, spatial concepts are essential for guiding effective strate-
gies for both biodiversity and ecosystem service conservation (Chan et al. 2006;
Moilanen and Wintle 2007).
Ecological concepts and analytical tools developed in the fields of landscape
ecology, geography, and spatial statistics are now commonly used in conservation so
that informed decisions about planning strategies and management can be made
(e.g., Moilanen et al. 2009). Indeed, most conservation planning and management
requires knowledge and the explicit spatial modeling of space and its major conse-
quences on species spatial variation and responses to global change. The inclusion of
space is therefore crucial when modeling species ecology and responses to a
changing world such as (1) species dispersal, (2) species interactions, (3) disturbance
dynamics, and (4) environmental change. Furthermore, as the field of conservation
aims to provide better management recommendations to mitigate threats to biodi-
versity, implicit and explicit aspects of space need to be incorporated into applied
solutions such as restoration, species reintroductions, and maintaining connectivity
among habitat patches. In all these conservation applications the spatial scale of
implementation is key (Wiens 1989; Levin 1992,2000; McGarigal et al. 2016; Doak
et al. 1992; Fletcher et al. 2013; Gering et al. 2003).
1.4 The Growth of Frameworks for Spatial Modeling
Before modeling species dispersal, response to environmental conditions, and species
interactions, quantification of their spatial distribution is needed. This is why in
ecology and conservation the first steps toward a better understanding and manage-
ment of biodiversity often consist of (1) mapping species distributions, and (2) quan-
tifying spatial patterns of both species distributions and environmental conditions
(Ferrier 2002; Gaston and Blackburn 2000; Guisan and Thuiller 2005). Once such
quantitative information is obtained, the next modeling steps frequently aim at relating
and modeling the responses of species to environmental conditions across space and/or
the species (intraspecific and interspecific) spatial interactions (Synes et al. 2017).
Modeling the processes that affect species distribution can be done using different
degrees of complexity in the analytical tools used. The level of complexity depends on
the processes modeled and ecological theories considered. Then, knowledge gaps about
6 1 Introduction to Spatial Ecology and Its Relevance for Conservation
robert.fletcher@ufl.edu
species distribution can be gained by combining data on species behavior from empir-
ical studies and theoretical models of dispersal and related flows across space. Early
dispersal models set the stage for the development of ecological theories that embrace
space (Fig. 1.3), such as island biogeography (MacArthur and Wilson 1967), patch
dynamics (Pickett and White 1984), hierarchical theory (Wu and Loucks 1995;Allen
and Starr 1982), species coexistence (Chesson 2000), metapopulation (Hanski 1999),
metacommunity (Leibold and Chase 2017), and metaecosystem theory (Guichard
2017). Although these disciplines can be seen as separate fields, spatial ecology brings
them together through theory, models, and data analysis (Massol et al. 2011).
The emergence of modeling frameworks for spatial ecology was also fostered by
several technological advances ranging from the availability of aerial photographs,
remote sensing captors, and computing power. This allowed for conceptual and
modeling developments in spatial ecology to advance more realistic ways to repre-
sent and incorporate space into statistical and modeling approaches (Fig. 1.3).
Indeed, the ability to explicitly include the effects of space in ecological models
was also pivotal in the explosion of novel ecological questions and analytical ways
to address them over the last few decades.
Implicitly: Relative positions (i, j)
in a regular grid
Explicitly: x-y coordinates; Euclidean distance
between patches (black lines); effective
functional distance based on network topology
(grey lines)
Incorporating Space
i, j
x-y
Abiotic factors
generating spatial
autocorrelation
in environmental
gradients,
landscape
heterogeneity,
and human impacts,
such as habitat loss
and spread of invasives
Biotic processes
creating spatial
autocorrelation
in distributions,
dynamics,
interactions,
and
movement
Ecological responses Environmental covariates
Spatial structure of
one species
Spatial structure of
several species
Fig. 1.3 How spatial processes affect species (response variables) and covariates (predictors), and
how space can be incorporated into models
1.4 The Growth of Frameworks for Spatial Modeling 7
robert.fletcher@ufl.edu
The quantum leap in spatial ecology modeling frameworks involved considering
and incorporating space into modeling: implicitly (kernels, moving windows, rela-
tive topological position, etc.), explicitly (x–y, diffusion, spread, individual/agent-
based models, etc.), and realistically (explicit network structure, spatial weights,
multiple spatial scales, etc.) (Fig. 1.3). It started by considering space as discrete
units. Such discretization of space opened a multitude of novel ways to model
ecological systems either in a spatially implicit fashion, where species occupancy
and abundance are modeled considering the effects of relative neighbors based on
grid topology (e.g., cellular automata models), or in a spatially explicit way, where
the actual Euclidean distances among cells (quadrats, pixels, sampling locations) are
used to model the spread of disturbance, disease, or species using dispersal kernels.
Then space was represented by the exact x–ycoordinates of each individual in a
given area such that the spatially explicit movement of individuals could be modeled
using individual/agent-based modeling approaches (Grimm et al. 2005; Matthews
et al. 2007). For example, this approach enabled modeling the dynamics and
succession of tree species at the tree-level using SORTIE (Pacala et al. 1996).
Using x–ycoordinates of individuals or sampling locations also allowed the spatially
explicit modeling of movement and connectivity while accounting for species
dispersal ability through spatially heterogeneous landscapes (Urban and Keitt
2001). Lastly, the spatially explicit representation of space permits us to model
processes acting over several spatial scales using meta-models (Urban 2005; Talluto
et al. 2016). The ability to model species and their responses to global change
explicitly in space opens the door to investigate the effects of the spatial legacy
(Wallin et al. 1994; James et al. 2007; Peterson 2002) of heterogeneity on ecological
processes and species persistence.
1.5 The Path Ahead
Spatial ecology and conservation has rapidly advanced over the past 20 years. With
an increasing emphasis on the use of spatial data and modeling to address both
fundamental and applied problems, the topic has matured. Spatial ecology embraces
spatial modeling and analysis, which is often applied to conservation issues.
In the remainder of this book, our path will be to provide an introduction to
several issues in spatial ecology and conservation, with an emphasis on spatial
modeling of applied ecological problems. We emphasize learning-by-doing, where
we illustrate these topics with real data and the application of spatial modeling to
these topics. We first cover topics regarding the quantification of spatial pattern in
ecological data and we then focus more specifically on topics regarding how species
respond to spatial pattern and its relevance for conservation (Table 1.2). We hope
that this coverage will deliver a strong foundation for students and professionals
alike to begin tackling ongoing issues of ecological and conservation importance.
8 1 Introduction to Spatial Ecology and Its Relevance for Conservation
robert.fletcher@ufl.edu
References
Allen TFH, Starr TB (1982) Hierarchy: perspectives for ecological complexity. University of
Chicago Press, Chicago
Bormann FH, Likens GE (1979) Catastrophic disturbance and the steady-state in northern hard-
wood forests. Am Sci 67(6):660–669
Cantrell S, Cosner C, Ruan S (2009) Spatial ecology. Chapman & Hall/CRC, Boca Raton, FL
Carroll C, Roberts DR, Michalak JL, Lawler JJ, Nielsen SE, Stralberg D, Hamann A, McRae BH,
Wang TL (2017) Scale-dependent complementarity of climatic velocity and environmental
diversity for identifying priority areas for conservation under climate change. Glob Chang
Biol 23(11):4508–4520. https://doi.org/10.1111/gcb.13679
Chan KMA, Shaw MR, Cameron DR, Underwood EC, Daily GC (2006) Conservation planning for
ecosystem services. PLoS Biol 4(11):2138–2152. https://doi.org/10.1371/journal.pbio.0040379
Chesson PL (2000) General theory of competitive coexistence in spatially varying environments.
Theor Popul Biol 58:211–237
Crooks KR, Sanjayan M (eds) (2006) Connectivity conservation. Cambridge University Press,
New York
Currie DJ, Paquin V (1987) Large-scale biogeographical patterns of species richness of trees.
Nature 329(6137):326–327. https://doi.org/10.1038/329326a0
Dale MRT, Fortin MJ (2014) Spatial analysis: a guide for ecologists, 2nd edn. Cambridge
University Press, Cambridge
Darwin C (1859) On the origin of species by means of natural selection, or preservation of favoured
races in the struggle for life. John Murray, London
Table 1.2 Examples of spatial analytical methods (and book chapter(s) where they are presented)
used in spatial ecology and the quantitative components that they are estimating
Spatial analytical methods Spatial components addressed
Multiscale analysis (Chap. 2) Determine key spatial scales affecting the response variables
Categorical pattern analysis
(Chap. 3)
Quantify land-use and land-cover patterns
Spatial point processes
(Chap. 4)
Identifying the spatial pattern of points (events) and understand
the potential processes generating those patterns
Spatial-, geo-statistics
(Chap. 5)
Magnitude, range, and directionality of spatial variance
Spatial regressions (Chap. 6) Accounting for spatial structure of the response (spatial nuisance)
and independent variables (spatial contingency) in estimating
relationships
Species distribution models
(Chap. 7)
Interpolation, projections, and forecasting
Animal movement models
(Chaps. 8and 9)
Accounting for spatial heterogeneity and quantifying trajectories
Spatial network analysis
(Chap. 9)
Topological network, Euclidean, and functional distances
Spatial population dynamics
(Chap. 10)
Population dynamics accounting for spatial heterogeneity
Beta diversity (Chap. 11) Spatial species turnover
Spatial community analysis
(Chap. 11)
Spatial components of species interactions and environmental
filtering
References 9
robert.fletcher@ufl.edu
Dawson W, Moser D, van Kleunen M, Kreft H, Pergl J, Pysek P, Weigelt P, Winter M, Lenzner B,
Blackburn TM, Dyer EE, Cassey P, Scrivens SL, Economo EP, Guenard B, Capinha C,
Seebens H, Garcia-Diaz P, Nentwig W, Garcia-Berthou E, Casal C, Mandrak NE, Fuller P,
Meyer C, Essl F (2017) Global hotspots and correlates of alien species richness across
taxonomic groups. Nat Ecol Evol 1(7):0186. https://doi.org/10.1038/s41559-017-0186
Diamond JM (1975) The island dilemma: lessons of modern biogeographic studies for the design of
natural reserves. Biol Conserv 7(2):129–146. https://doi.org/10.1016/0006-3207(75)90052-x
Dietze M (2017) Ecological forcasting. Princeton University Press, Princeton
Doak DF, Marino PC, Kareiva PM (1992) Spatial scale mediates the influence of habitat fragmen-
tation on dispersal success: implications for conservation. Theor Popul Biol 41(3):315–336.
https://doi.org/10.1016/0040-5809(92)90032-o
Ferrier S (2002) Mapping spatial pattern in biodiversity for regional conservation planning: where
to from here? Syst Biol 51(2):331–363. https://doi.org/10.1080/10635150252899806
Fletcher RJ Jr, Revell A, Reichert BE, Kitchens WM, Dixon JD, Austin JD (2013) Network
modularity reveals critical scales for connectivity in ecology and evolution. Nat Commun
4:2572. https://doi.org/10.1038/ncomms3572
Fortin MJ, James PMA, MacKenzie A, Melles SJ, Rayfield B (2012) Spatial statistics, spatial
regression, and graph theory in ecology. Spatial Stat 1:100–109. https://doi.org/10.1016/j.
spasta.2012.02.004
Gaston KJ, Blackburn TM (2000) Pattern and process in macroecology. Blackwell Science, Oxford,
UK
Gering JC, Crist TO, Veech JA (2003) Additive partitioning of species diversity across multiple
spatial scales: implications for regional conservation of biodiversity. Conserv Biol 17
(2):488–499. https://doi.org/10.1046/j.1523-1739.2003.01465.x
Grimm V, Revilla E, Berger U, Jeltsch F, Mooij WM, Railsback SF, Thulke HH, Weiner J,
Wiegand T, DeAngelis DL (2005) Pattern-oriented modeling of agent-based complex systems:
lessons from ecology. Science 310(5750):987–991. https://doi.org/10.1126/science.1116681
Guichard F (2017) Recent advances in metacommunities and meta-ecosystem theories. F1000
Research 6:610
Guillot G, Leblois R, Coulon A, Frantz AC (2009) Statistical methods in spatial genetics. Mol Ecol
18(23):4734–4756. https://doi.org/10.1111/j.1365-294X.2009.04410.x
Guisan A, Thuiller W (2005) Predicting species distribution: offering more than simple habitat
models. Ecol Lett 8(9):993–1009
Hanski I (1999) Metapopulation ecology. Oxford University Press, Oxford
Hastings A, Gross L (eds) (2012) Encyclopedia of theoretical ecology. UC Press, Berkeley, CA
Heller NE, Zavaleta ES (2009) Biodiversity management in the face of climate change: a review of
22 years of recommendations. Biol Conserv 142(1):14–32. https://doi.org/10.1016/j.biocon.
2008.10.006
Higgs AJ (1981) Island biogeography theory and nature reserve design. J Biogeogr 8(2):117–124.
https://doi.org/10.2307/2844554
Hilborn R (1979) Some long-term dynamics of predator-prey models with diffusion. Ecol Model 6
(1):23–30. https://doi.org/10.1016/0304-3800(79)90055-3
Huffaker CB (1958) Experimental studies on predation: dispersion factors and predator-prey
oscillations. Hilgardia 27:343–383
Hutchinson GE (1965) The ecological theater and the evolutionary play. Yale University Press,
New Haven
James PMA, Fortin MJ, Fall A, Kneeshaw D, Messier C (2007) The effects of spatial legacies
following shifting management practices and fire on boreal forest age structure. Ecosystems 10
(8):1261–1277. https://doi.org/10.1007/s10021-007-9095-y
Kareiva P (1982) Experimental and mathematical analyses of herbivore movement: quantifying the
influence of plant spacing and quality on foraging discrimination. Ecol Monogr 52(3):261–282.
https://doi.org/10.2307/2937331
10 1 Introduction to Spatial Ecology and Its Relevance for Conservation
robert.fletcher@ufl.edu
Kareiva PM (1983) Local movement in herbivorous insects - applying a passive diffusion-model to
mark-recapture field experiments. Oecologia 57(3):322–327. https://doi.org/10.1007/
bf00377175
Kareiva P (1994) Space: the final frontier for ecological theory. Ecology 75(1):1–1. https://doi.org/
10.2307/1939376
Laurance WF (2008) Theory meets reality: how habitat fragmentation research has transcended
island biogeographic theory. Biol Conserv 141(7):1731–1744. https://doi.org/10.1016/j.biocon.
2008.05.011
Leibold MA, Chase JM (2017) Metacommunity ecology. Princeton University Press, Princeton, NJ
Leibold MA, Holyoak M, Mouquet N, Amarasekare P, Chase JM, Hoopes MF, Holt RD, Shurin JB,
Law R, Tilman D, Loreau M, Gonzalez A (2004) The metacommunity concept: a framework for
multi-scale community ecology. Ecol Lett 7(7):601–613. https://doi.org/10.1111/j.1461-0248.
2004.00608.x
Leibold MA, Chase JM, Ernest SKM (2017) Community assembly and the functioning of ecosys-
tems: how metacommunity processes alter ecosystems attributes. Ecology 98(4):909–919
Levin SA (1976) Population dynamic models in heterogeneous environments. Annu Rev Ecol Syst
7:287–310. https://doi.org/10.1146/annurev.es.07.110176.001443
Levin SA (1992) The problem of pattern and scale in ecology. Ecology 73(6):1943–1967. https://
doi.org/10.2307/1941447
Levin SA (2000) Multiple scales and the maintenance of biodiversity. Ecosystems 3(6):498–506.
https://doi.org/10.1007/s100210000044
Levins R (1969) Some demographic and genetic consequences of environmental heterogeneity for
biological control. Bull Entomol Soc Am 15:237–240
Lomolino MV (2017) Biogeography: biological diversity across space and time, 5th edn. Sinauer,
Sunderland, MA
Loreau M, Mouquet N, Gonzalez A (2003a) Biodiversity as spatial insurance in heterogeneous
landscapes. Proc Natl Acad Sci U S A 100(22):12765–12770. https://doi.org/10.1073/pnas.
2235465100
Loreau M, Mouquet N, Holt RD (2003b) Meta-ecosystems: a theoretical framework for a spatial
ecosystem ecology. Ecol Lett 6(8):673–679. https://doi.org/10.1046/j.1461-0248.2003.00483.x
MacArthur RH, Wilson EO (1963) Equilibrium theory of insular zoogeography. Evolution
17(4):373. https://doi.org/10.2307/2407089
MacArthur RH, Wilson EO (1967) The theory of island biogeography. Princeton University Press,
Princeton, NJ
Manel S, Schwartz MK, Luikart G, Taberlet P (2003) Landscape genetics: combining landscape
ecology and population genetics. Trends Ecol Evol 18(4):189–197. https://doi.org/10.1016/
s0169-5347(03)00008-9
Margules CR, Pressey RL (2000) Systematic conservation planning. Nature 405(6783):243–253.
https://doi.org/10.1038/35012251
Massol F, Gravel D, Mouquet N, Cadotte MW, Fukami T, Leibold MA (2011) Linking community
and ecosystem dynamics through spatial ecology. Ecol Lett 14(3):313–323. https://doi.org/10.
1111/j.1461-0248.2011.01588.x
Matthews RB, Gilbert NG, Roach A, Polhill JG, Gotts NM (2007) Agent-based land-use models: a
review of applications. Landsc Ecol 22(10):1447–1459. https://doi.org/10.1007/s10980-007-
9135-1
McGarigal K, Wan HY, Zeller KA, Timm BC, Cushman SA (2016) Multi-scale habitat selection
modeling: a review and outlook. Landsc Ecol. https://doi.org/10.1007/s10980-016-0374-x
Moilanen A, Wintle BA (2007) The boundary-quality penalty: a quantitative method for approx-
imating species responses to fragmentation in reserve selection. Conserv Biol 21(2):355–364.
https://doi.org/10.1111/j.1523-1739.2006.00625.x
Moilanen A, Wilson KA, Possingham H (eds) (2009) Spatial conservation prioritization: quantita-
tive methods and computational tools. Oxford University Press, Oxford
References 11
robert.fletcher@ufl.edu
Myers N, Mittermeier RA, Mittermeier CG, da Fonseca GAB, Kent J (2000) Biodiversity hotspots
for conservation priorities. Nature 403(6772):853–858. https://doi.org/10.1038/35002501
Nathan R, Getz WM, Revilla E, Holyoak M, Kadmon R, Saltz D, Smouse PE (2008) A movement
ecology paradigm for unifying organismal movement research. Proc Natl Acad Sci U S A 105
(49):19052–19059. https://doi.org/10.1073/pnas.0800375105
Okubo A (1974) Diffusion-induced instability in model ecosystems, another possible explanation
of patchiness. Technical Report 86. Chesapeake Bay Institute, MD
Okubo A, Levin SA (2001) Diffusion and ecological problems: modern perspectives. Springer,
New York
Orme CDL, Davies RG, Burgess M, Eigenbrod F, Pickup N, Olson VA, Webster AJ, Ding TS,
Rasmussen PC, Ridgely RS, Stattersfield AJ, Bennett PM, Blackburn TM, Gaston KJ, Owens
IPF (2005) Global hotspots of species richness are not congruent with endemism or threat.
Nature 436(7053):1016–1019. https://doi.org/10.1038/nature03850
Ovaskainen O, De Knegt HJ, del Mar Delgado M (2016) Quantitative ecology and evolutionary
biology: integrating models with data. Oxford University Press, Oxford
Pacala SW, Canham CD, Saponara J, Silander JA, Kobe RK, Ribbens E (1996) Forest models
defined by field measurements: estimation, error analysis and dynamics. Ecol Monogr 66
(1):1–43. https://doi.org/10.2307/2963479
Pagel J, Schurr FM (2012) Forecasting species ranges by statistical estimation of ecological niches
and spatial population dynamics. Glob Ecol Biogeogr 21(2):293–304. https://doi.org/10.1111/j.
1466-8238.2011.00663.x
Peterson GD (2002) Contagious disturbance, ecological memory, and the emergence of landscape
pattern. Ecosystems 5(4):329–338. https://doi.org/10.1007/s10021-001-0077-1
Pickett STA, Cadenasso ML (1995) Landscape ecology: spatial heterogeneity in ecological sys-
tems. Science 269(5222):331–334
Pickett STA, White PS (1984) The ecology of natural disturbance and patch dynamics. Academic
Press, New York
Pressey RL, Cabeza M, Watts ME, Cowling RM, Wilson KA (2007) Conservation planning in a
changing world. Trends Ecol Evol 22(11):583–592. https://doi.org/10.1016/j.tree.2007.10.001
Preston FW (1948) The commonness, and rarity, of species. Ecology 29(3):254–283. https://doi.
org/10.2307/1930989
Preston FW (1962) The canonical distribution of commonness and rarity: Part I. Ecology 43
(2):185–215,431–432
Primack RB (2014) Essentials of conservation biology, 6th edn. Sinauer Associates, Sunderland,
MA
Reeve JD, Cronin JT, Haynes KJ (2008) Diffusion models for animals in complex landscapes:
incorporating heterogeneity among substrates, individuals and edge behaviours. J Anim Ecol 77
(5):898–904. https://doi.org/10.1111/j.1365-2656.2008.01411.x
Schagner JP, Brander L, Maes J, Hartje V (2013) Mapping ecosystem services’values: current
practice and future prospects. Ecosyst Serv 4:33–46. https://doi.org/10.1016/j.ecoser.2013.02.003
Schmitz OJ, Lawler JJ, Beier P, Groves C, Knight G, Boyce DA, Bulluck J, Johnston KM, Klein
ML, Muller K, Pierce DJ, Singleton WR, Strittholt JR, Theobald DM, Trombulak SC, Trainor A
(2015) Conserving biodiversity: practical guidance about climate change adaptation approaches
in support of land-use planning. Nat Areas J 35(1):190–203
Seddon PJ, Griffiths CJ, Soorae PS, Armstrong DP (2014) Reversing defaunation: restoring species
in a changing world. Science 345(6195):406–412. https://doi.org/10.1126/science.1251818
Skellam JG (1951) Random dispersal in theoretical populations. Biometrika 28:196–218
Synes NW, Brown C, Watts K, White SM, Gilbert MA, Travis JM (2017) Emerging opportuniteis
for landscape ecological modelling. Curr Landsc Ecol Rep 1:146–167
Talluto MV, Boulangeat I, Ameztegui A, Aubin I, Berteaux D, Butler A, Doyon F, Drever CR,
Fortin MJ, Franceschini T, Lienard J, McKenney D, Solarik KA, Strigul N, Thuiller W, Gravel
D (2016) Cross-scale integration of knowledge for predicting species ranges: a metamodelling
framework. Glob Ecol Biogeogr 25(2):238–249. https://doi.org/10.1111/geb.12395
Tilman D, Kareiva P (1997) Spatial ecology: the role of space in population dynamics and
interspecific interactions. Princeton University Press, Princeton, NJ
12 1 Introduction to Spatial Ecology and Its Relevance for Conservation
robert.fletcher@ufl.edu
Turner MG (1989) Landscape ecology: the effect of pattern on process. Annu Rev Ecol Syst
20:171–197. https://doi.org/10.1146/annurev.ecolsys.20.1.171
Turner MG, Gardner RH (2015) Landscape ecology in theory and practice, 2nd edn. Springer,
New York
Urban DL (2005) Modeling ecological processes across scales. Ecology 86(8):1996–2006
Urban D, Keitt T (2001) Landscape connectivity: a graph-theoretic perspective. Ecology 82
(5):1205–1218
Wagner HH, Fortin MJ (2005) Spatial analysis of landscapes: concepts and statistics. Ecology 86
(8):1975–1987. https://doi.org/10.1890/04-0914
Wallin DO, Swanson FJ, Marks B (1994) Landscape pattern response to changes in pattern
generation rules: land-use legacies in forestry. Ecol Appl 4(3):569–580. https://doi.org/10.
2307/1941958
Watt AS (1947) Pattern and process in the plant community. J Ecol 35(1–2):1–22. https://doi.org/
10.2307/2256497
Wiens JA (1989) Spatial scaling in ecology. Funct Ecol 3(4):385–397
Wu JG (2017) Thirty years of landscape ecology (1987–2017): retrospects and prospects. Landsc
Ecol 32(12):2225–2239. https://doi.org/10.1007/s10980-017-0594-8
Wu JG, Loucks OL (1995) From balance of nature to hierarchical patch dynamics: a paradigm shift
in ecology. Q Rev Biol 70(4):439–466. https://doi.org/10.1086/419172
References 13
robert.fletcher@ufl.edu
