ChapterPDF Available

Introduction to Spatial Ecology and Its Relevance for Conservation: Applications with R

Authors:

Abstract and Figures

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.
Content may be subject to copyright.
Chapter 1
Introduction to Spatial Ecology and Its
Relevance for Conservation
1.1 What Is Spatial Ecology?
Space: The nal frontierKareiva (1994)
All aspects of ecology play out in space. From Darwins entangled bank to
Hutchinsons 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
eld of spatial ecology: a eld coined by Tilman and Karieva in 1997. Since then, the
term spatial ecologyhas been used in a wide range of ways depending on each
ecological subdiscipline and eld. 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 denition shares similarities with some
early denitions 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 ltering, 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 ne 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 communitiespatches
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 stateconcept (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 inuential experimental studies highlighted the importance of space for ecol-
ogy. In a seminal experiment, Huffaker (1958) showed how predatorprey 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 reactiondiffusion 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, Skellams 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 speciesarea 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
xycoordinates 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 Inuence of past spatial pattern on current ecological processes and species
current spatial pattern
Spatial
contingency
Inuence 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 inuence current spatial pattern
4 1 Introduction to Spatial Ecology and Its Relevance for Conservation
robert.fletcher@ufl.edu
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
conguration (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 rst emerged in the eld 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 conguration 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 efcient 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 elds 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 eld 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, quantication of their spatial distribution is needed. This is why in
ecology and conservation the rst 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 (intraspecic and interspecic) 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 ows 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 elds, 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 (xy, 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 xycoordinates 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 xycoordinates 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 rst cover topics regarding the quantication of spatial pattern in
ecological data and we then focus more specically 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):660669
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):45084520. 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):21382152. https://doi.org/10.1371/journal.pbio.0040379
Chesson PL (2000) General theory of competitive coexistence in spatially varying environments.
Theor Popul Biol 58:211237
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):326327. 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
ltering
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):129146. 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 inuence of habitat fragmen-
tation on dispersal success: implications for conservation. Theor Popul Biol 41(3):315336.
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):331363. 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, Rayeld B (2012) Spatial statistics, spatial
regression, and graph theory in ecology. Spatial Stat 1:100109. 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):488499. 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):987991. 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):47344756. 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):9931009
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):1432. https://doi.org/10.1016/j.biocon.
2008.10.006
Higgs AJ (1981) Island biogeography theory and nature reserve design. J Biogeogr 8(2):117124.
https://doi.org/10.2307/2844554
Hilborn R (1979) Some long-term dynamics of predator-prey models with diffusion. Ecol Model 6
(1):2330. https://doi.org/10.1016/0304-3800(79)90055-3
Huffaker CB (1958) Experimental studies on predation: dispersion factors and predator-prey
oscillations. Hilgardia 27:343383
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 re on boreal forest age structure. Ecosystems 10
(8):12611277. https://doi.org/10.1007/s10021-007-9095-y
Kareiva P (1982) Experimental and mathematical analyses of herbivore movement: quantifying the
inuence of plant spacing and quality on foraging discrimination. Ecol Monogr 52(3):261282.
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 eld experiments. Oecologia 57(3):322327. https://doi.org/10.1007/
bf00377175
Kareiva P (1994) Space: the nal frontier for ecological theory. Ecology 75(1):11. 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):17311744. 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):601613. 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):909919
Levin SA (1976) Population dynamic models in heterogeneous environments. Annu Rev Ecol Syst
7:287310. https://doi.org/10.1146/annurev.es.07.110176.001443
Levin SA (1992) The problem of pattern and scale in ecology. Ecology 73(6):19431967. https://
doi.org/10.2307/1941447
Levin SA (2000) Multiple scales and the maintenance of biodiversity. Ecosystems 3(6):498506.
https://doi.org/10.1007/s100210000044
Levins R (1969) Some demographic and genetic consequences of environmental heterogeneity for
biological control. Bull Entomol Soc Am 15:237240
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):1276512770. 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):673679. 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):189197. https://doi.org/10.1016/
s0169-5347(03)00008-9
Margules CR, Pressey RL (2000) Systematic conservation planning. Nature 405(6783):243253.
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):313323. 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):14471459. 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):355364.
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):853858. 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):1905219059. 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, Statterseld 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):10161019. 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
dened by eld measurements: estimation, error analysis and dynamics. Ecol Monogr 66
(1):143. 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):293304. 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):329338. 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):331334
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):583592. https://doi.org/10.1016/j.tree.2007.10.001
Preston FW (1948) The commonness, and rarity, of species. Ecology 29(3):254283. https://doi.
org/10.2307/1930989
Preston FW (1962) The canonical distribution of commonness and rarity: Part I. Ecology 43
(2):185215,431432
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):898904. https://doi.org/10.1111/j.1365-2656.2008.01411.x
Schagner JP, Brander L, Maes J, Hartje V (2013) Mapping ecosystem servicesvalues: current
practice and future prospects. Ecosyst Serv 4:3346. 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):190203
Seddon PJ, Grifths CJ, Soorae PS, Armstrong DP (2014) Reversing defaunation: restoring species
in a changing world. Science 345(6195):406412. https://doi.org/10.1126/science.1251818
Skellam JG (1951) Random dispersal in theoretical populations. Biometrika 28:196218
Synes NW, Brown C, Watts K, White SM, Gilbert MA, Travis JM (2017) Emerging opportuniteis
for landscape ecological modelling. Curr Landsc Ecol Rep 1:146167
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):238249. https://doi.org/10.1111/geb.12395
Tilman D, Kareiva P (1997) Spatial ecology: the role of space in population dynamics and
interspecic 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
20:171197. 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):19962006
Urban D, Keitt T (2001) Landscape connectivity: a graph-theoretic perspective. Ecology 82
(5):12051218
Wagner HH, Fortin MJ (2005) Spatial analysis of landscapes: concepts and statistics. Ecology 86
(8):19751987. 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):569580. https://doi.org/10.
2307/1941958
Watt AS (1947) Pattern and process in the plant community. J Ecol 35(12):122. https://doi.org/
10.2307/2256497
Wiens JA (1989) Spatial scaling in ecology. Funct Ecol 3(4):385397
Wu JG (2017) Thirty years of landscape ecology (19872017): retrospects and prospects. Landsc
Ecol 32(12):22252239. 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):439466. https://doi.org/10.1086/419172
References 13
robert.fletcher@ufl.edu
... To some extent metapopulation theory superseded the refuge design criteria in the 1990s (Hanski and Simberloff 1997), and it remains an active area of research in conservation biology and ecology (Hanski and Gaggiotti 2004;Begon and Townsend 2021). The equilibrium theory and metapopulation theory have together spawned research on metacommunities (e.g., Leibold and Miller 2004;Logue et al. 2011;Massol et al. 2011) and metaecosystems (e.g., Loreau et al. 2003;Gravel et al. 2011;Massol et al. 2011;Leibold and Chase 2017), key components in the rise of spatial ecology Fletcher and Fortin 2018). ...
... One of the most important aspects of animal behavior, particularly as it relates to wildlife ecology and conservation, is the way animals move and use space on a landscape. e eld of spatial ecology has grown rapidly over the last several decades as ecologists increasingly recognize the importance of scale, as well as the relationship between ecological processes and landscape composition and heterogeneity (Fletcher and Fortin 2018). As global environments become increasingly fragmented and dominated by anthropogenic drivers, the interaction between ecological systems and spatial heterogeneity becomes all the more important to understand and incorporate into ecological studies and biodiversity conservation e orts alike. ...
Book
The Wood Turtle has experienced significant population declines across its range in the United States and Canada, where it is a species emblematic of cool, remote, clean rivers from Nova Scotia to Minnesota and south to Virginia. This richly illustrated book is the first solely dedicated to the natural history, ecology, and conservation of the Wood Turtle. More than 20 scientists and managers from across the species' range have collaborated in this volume to explore the Wood Turtle's evolution, landscape ecology, distribution, habitat, biology, and behavior, and to evaluate its conservation needs and outlook.
... Dans ce but, ce travail mobilisera différentes approches de l'écologie spatiale (c. à d., aspect de l'écologie où la dimension spatiale joue un rôle clé ; Fletcher & Fortin, 2018) pour améliorer Introduction les connaissances sur l'utilisation de l'espace d'espèces animales associées à des zoonoses préoccupantes pour la santé et l'économie publique. ...
Thesis
Prévenir les risques d’épidémies est devenu un enjeu sanitaire et économique mondial, comme en témoigne l’émergence récente du SARS-COV-2. Cette Thèse vise à améliorer les connaissances sur l’utilisation de l’espace des chauves-souris frugivores (Pteropodidae) dans des environnements modifiés par l’homme. Ce travail mobilise des données de télémétrie satellitaire chez (i) la roussette de Lyle (Pteropus lylei), espèce réservoir du virus Nipah en Asie, et (ii) la chauve-souris à tête de marteau (Hypsignathus monstrosus), impliquée dans la circulation du virus Ebola en Afrique. La population étudiée de roussette de Lyle était déjà connue pour se nourrir préférentiellement dans les zones résidentielles d’un environnement fragmenté au Cambodge. La chauve-souris à tête de marteau, dont l’utilisation des habitats était méconnue, a été étudiée dans une région forestière en République du Congo – épicentre d’épidémies humaine d’Ebola en 2001–2005. De plus, des données de captures directes de chauves-souris ont été collectées dans cette dernière région. Il ressort de ces travaux que la chauve-souris à tête de marteau se nourrit préférentiellement dans les terres agricoles qui entourent les petits villages forestiers. Les individus de roussette de Lyle visitent davantage d’aires d’alimentation dans l’habitat préférentiel durant la nuit, tandis que les chauves-souris à tête de marteau y passent plus de temps sans multiplier le nombre d’aires visitées. Ces deux espèces bénéficient ainsi des ressources anthropiques à l’échelle de la population selon deux stratégies de déplacements individuels, qui sont possiblement ajustées selon le degré de fragmentation de l’environnement. Chez la chauve-souris à tête de marteau, les aires d’alimentation dans la forêt sont délaissées par les individus qui restent longtemps dans le site d’accouplement durant la nuit, ce qui suggère un rôle des terres agricoles dans l’établissement et le maintien des sites d’accouplement. Au cours de nuits successives, les deux espèces revisitent davantage une aire d’alimentation lorsqu’elles y ont passé beaucoup de temps lors de leur dernière visite. Par ailleurs, une communauté de sept espèces de chauves-souris frugivores a été identifiée dans la région étudiée en Afrique. La probabilité d’occurrence de quatre espèces était plus importante dans les villages, tandis que les autres espèces n’étaient pas influencées par l’habitat. L’ensemble de ces travaux fournit de nouvelles informations sur l’utilisation de l’espace des chauves-souris frugivores dans le cadre de leurs activités nocturnes d’alimentation et de reproduction. Ces données pourraient être intégrées dans des modélisations épidémiologiques visant à mieux comprendre les interactions entre les chauves-souris frugivores, les humains ou les animaux domestiques, ainsi que les voies de transmission de pathogènes.
... The combination of ecological exogenous and endogenous processes determines spatial characteristics of a species or population, such as, movement and dispersal, resource acquisition, and intra and interspecies interactions (Fletcher and Fortin 2018). Aided by advanced technology and data analysis methodologies, research on the spatial ecology of jaguars has already yielded valuable information on movement and spatial patterns, which are key to arresting habitat loss and, therefore the fragmentation and subsequent decline in biodiversity. ...
Preprint
Full-text available
ContextMovement ecology contributes valuable information about animal interactions with the environment, and their responses to landscape-level anthropogenic impacts. Big cats are vulnerable to such changes, but the current deficit of information about home range movements, limits the scope of conservation initiatives. Objectives Describe the home range size, interactions, and differences between jaguar populations across its distribution in MexicoMethods We used 41,008 GPS-generated data points obtained from 28 tagged jaguars ( Panthera onca ) in five different states of Mexico over an 18-year period to describe home range size, differences between male and female territories, interactions in overlapping territories, and territory differences among populations. ResultsOur data shows that jaguar home range is smaller than tiger’s but larger than leopard’s. Male mean home range size (285.28 km ² , n=13) tends to be larger than that of females (152.2 km ² , n = 15), the difference was not statistically significant. While the home range for at least one male was 633.44 km ² , contrasted with the much smaller 48.89 km ² for some female jaguars. Data of overlapping ranges showed 34.71% of female territory overlaps male territory, 32.46% of female territory is shared with other females, 18.97% of male territory is shared with other males, and only 16.89% male territory overlaps with female territory. Conclusions The absence of significant differences in home range sizes among the habitats suggest jaguar territory is not highly dependent on the type of habitat it occupies. Our findings of the spatial parameters of jaguar movements can be applied to identifying ecological corridors and the design of protected areas for this species.
Article
Full-text available
Climate change has led to an increase in global temperature and frequent intense precipitation, resulting in a rise in severe and intense urban flooding worldwide. This growing threat is exacerbated by rapid urbanization, impervious surface expansion, and overwhelmed drainage systems, particularly in urban regions. As urban flooding becomes more catastrophic and causes significant environmental and property damage, there is an urgent need to understand and address urban flood susceptibility to mitigate future damage. This review aims to evaluate remote sensing datasets and key parameters influencing urban flood susceptibility and provide a comprehensive overview of the flood causative factors utilized in urban flood susceptibility mapping. This review also highlights the evolution of traditional, data-driven, big data, GISs (geographic information systems), and machine learning approaches and discusses the advantages and limitations of different urban flood mapping approaches. By evaluating the challenges associated with current flood mapping practices, this paper offers insights into future directions for improving urban flood management strategies. Understanding urban flood mapping approaches and identifying a foundation for developing more effective and resilient urban flood management practices will be beneficial for mitigating future urban flood damage.
Article
Full-text available
Populations of the threatened Baird’s tapir (Tapirus bairdii) and the white-lipped peccary (Tayassu pecari) face increasing isolation due to rampant deforestation and forest fragmentation across the Greater Maya Forest shared by southeastern Mexico, northern Guatemala, and Belize. We identified (1) the critical areas to ensure the persistence of Baird’s tapir and the white-lipped peccary in the Maya Forest; (2) the corridors and sites with the best conditions to maintain connectivity among core habitats, and (3) the nodes with higher risk of habitat loss compromising landscape connectivity. We used a methodological framework combining circuit theory and species distribution modeling to estimate landscape resistance, land use, and the effect of roads and trails on the current distribution of the two focal species in the Maya Forest. We detected that major roads associated with agricultural landscapes are the primary barriers to the movements of tapirs and white-lipped peccaries in the study area. Conserving corridors that link the forests of the Lacandon and the Calakmul regions, along with the protected area network of northern Belize and establishing nodes between remaining forest fragments, are critical measures to mitigate the impact of habitat fragmentation and loss for both species. The critical constriction areas (pinch points) and the corridors identified in this study support our prediction of the least-cost paths. Our assessment of threats to landscape connectivity provides useful information to inform effective decision-making for conserving Baird’s tapir and white-lipped peccary populations in the Greater Maya Forest.
Article
Full-text available
The study of spatial (paleo)ecology in mammals is critical to understand how animals adapt to and exploit their environment. In this work we analysed the ⁸⁷Sr/⁸⁶Sr, δ¹⁸O and δ¹³C isotope composition of 65 moose bone and antler samples from Sweden from wild-shot individuals dated between 1800 and 1994 to study moose mobility and feeding behaviour for (paleo)ecological applications. Sr data were compared with isoscapes of the Scandinavian region, built ad-hoc during this study, to understand how moose utilise the landscape in Northern Europe. The ⁸⁷Sr/⁸⁶Sr isoscape was developed using a machine-learning approach with external geo-environmental predictors and literature data. Similarly, a δ¹⁸O isoscape, obtained from average annual precipitation δ¹⁸O values, was employed to highlight differences in the isotope composition of the local environment vs. bone/antler. Overall, 82% of the moose samples were compatible with the likely local isotope composition (n = 53), suggesting that they were shot not far from their year-round dwelling area. ‘Local’ samples were used to calibrate the two isoscapes, to improve the prediction of provenance for the presumably ‘non-local’ individuals. For the latter (n = 12, of which two are antlers and ten are bones), the probability of geographic origin was estimated using a Bayesian approach by combining the two isoscapes. Interestingly, two of these samples (one antler and one bone) seem to come from areas more than 250 km away from the place where the animals were hunted, indicating a possible remarkable intra-annual mobility. Finally, the δ¹³C data were compared with the forest cover of Sweden and ultimately used to understand the dietary preference of moose. We interpreted a difference in δ¹³C values of antlers (¹³C-enriched) and bones (¹³C-depleted) as a joint effect of seasonal variations in moose diet and, possibly, physiological stresses during winter-time, i.e., increased consumption of endogenous ¹³C-depleted lipids.
Article
Full-text available
Home range and spatiotemporal activity are often lacking for small vertebrates that are difficult to mark individually and to monitor over sufficiently long-time scales to collect reliable information. This is particularly the case for the Edward’s Sand Racer Psammodromus edwarsianus, a small Mediterranean lizard that is almost threatened with extinction in France. In order to fill these gaps, we conducted a four-year mark-recapture survey (2019-2022) carried out on a 0.5ha quadrat composed of two distinct habitats of equivalent surface area (open rocky area and Aleppo pine forest). We estimated the 95% and 50% (core area) spring home ranges for 10 adult individuals (5 males and 5 females) using the Autocorrelated Kernel Density Estimation method. We assessed daily activity patterns of P. edwardsianus and tested whether these differed between the two habitat types using a Generalized Linear Mixed Model. The surface of spring home range varied greatly between individuals (for females, 95% AKDE range from 733 m2 to 3340 m2 and 50% AKDE range from 158 m2 to 546 m2 . For males, 95% AKDE range from 4556 m2 to 7434 m2 and 50% AKDE range from 779 m2 to 1658 m2), and reached up to 290 times the value formerly reported in the literature with significantly larger spring home ranges for males than females. The activity of P. edwardsianus did not vary significantly between the two habitats, and regardless of habitat type, activity was highest in the morning and late afternoon. The data collected have enabled us to gain a better understanding of the displacement potential and the spatiotemporal activity patterns of P. edwardsianus. This study also provide methodological elements and advice for optimizing the monitoring of this species.
Article
Full-text available
The Cerro de la Tortuga State Park (PECT) as a herpetofauna reservoir in the central region of Morelos. The PECT in the south–central region of the state of Morelos in Mexico is an important reservoir of amphibian and reptile diversity. The objective of this study is to update the inventory of amphibians and reptiles and to determine the composition, species richness, species–area relationship and similarity of the herpetofauna between reserves with different types of administration. The herpetofauna within the PECT was composed of 28 species, equivalent to 20 % of the herpetofauna of Morelos and 1.97 % of the herpetofauna of Mexico.The Squamata order was the best represented group, with 17 species (60.71 %), followed by Anura with 10 species (35.71 %) and Testudines with one species (3.57 %). The agreement with the analysis of the species/area relationship, Biósfera Sierra de Huautla Reserve (REBIOSH: 3 spp.) and PECT (1 spp.) harbor a greater number of species than expected with respect to Chichinautzin Biological Corridor (CBCH: 3 spp.), which harbors a lower number of species than expected. The similarity of the herpetofaunistic composition of the PECT result is greater between the State Reserve Sierra de Montenegro (RESM: 50 %) and the REBIOSH (34 %), compared to the CBCH (12 %). Our results indicate that the PECT acts as an important reservoir for the herpetofauna of the south–central region of Morelos, which could structurally be part of the so–called conservation archipelagos. However, in addition to evidence of composition and similarity between reserves, we suggest developers consider habitat quality for corridor identifiers and genetic studies that demonstrate gene flow for species shared between reserves.
Chapter
Nowadays the process of global urbanization is unstoppable, leading to a serious threat to local biodiversity. Urbanization may result in biodiversity decline or even species extinction, while sometimes help maintain species abundance in some developed countries. Different land-cover and land-use types affect species diversity in different aspects and directions, so it’s important to understand the pattern of species distribution across different characteristics of urban landscape, which helps city-designers and decision-makers to mitigate detrimental influences of urbanization on local biodiversity by rational urban planning and effective conservation protection. This study uses bird, which are highly sensitive to environmental changes, as the ecological indicators.This paper studies the differences of species richness, abundance and community composition from five urban land-cover and seven land-use types, and analyses patterns of bird distribution in different land use purposes on the same land cover landscape. This study used bird species richness, Shannon and Simpson diversity index across Greater Manchester to evaluate bird diversity. This study also used Generalized Linear Model to model the relationship between bird species richness and land-cover or land-use density, and used Redundancy Analysis (RDA) to interpret the response of bird communities to land-cover and land-use density. Green spaces (especially for public parks land use) and water bodies have relatively higher bird species richness. Built areas have the lowest species richness, especially the institutional land use (including religious grounds, school grounds, and institutional grounds). Considering different land-use purposes, public parks and recreation have the highest bird diversity in green spaces land-cover, followed by amenity land and domestic gardens. In built-up areas, species diversity in institutional land use is higher than previously developed land use. Clear understanding the relationships between land-cover and land-use types and bird species diversity and communities composition will help better policy making for potential future land-cover and land-use planning.KeywordsSpatial ecologyAvianGreater ManchesterSpecies richnessLand coverLand use
Article
Full-text available
Human-mediated transport beyond biogeographic barriers has led to the introduction and establishment of alien species in new regions worldwide. However, we lack a global picture of established alien species richness for multiple taxonomic groups. Here, we assess global patterns and potential drivers of established alien species richness across eight taxonomic groups (amphibians, ants, birds, freshwater fishes, mammals, vascular plants, reptiles and spiders) for 186 islands and 423 mainland regions. Hotspots of established alien species richness are predominantly island and coastal mainland regions. Regions with greater gross domestic product per capita, human population density, and area have higher established alien richness, with strongest effects emerging for islands. Ants and reptiles, birds and mammals, and vascular plants and spiders form pairs of taxonomic groups with the highest spatial congruence in established alien richness, but drivers explaining richness differ between the taxa in each pair. Across all taxonomic groups, our results highlight the need to prioritize prevention of further alien species introductions to island and coastal mainland regions globally.
Article
Full-text available
Metacommunity theory has provided many insights into the general problem of local versus regional control of species diversity and relative abundance. The metacommunity framework has been extended from competitive interactions to whole food webs that can be described as spatial networks of interaction networks. Trophic metacommunity theory greatly contributed to resolving the community complexity-stability debate by predicting its dependence on the regional spatial context. The meta-ecosystem framework has since been suggested as a useful simplification of complex ecosystems to apply this spatial context to spatial flows of both individuals and matter. Reviewing the recent literature on metacommunity and meta-ecosystem theories suggests the importance of unifying theories of interaction strength into a meta-ecosystem framework that captures how the strength of spatial, species, and ecosystem fluxes are distributed across location and trophic levels. Such integration predicts important feedback between local and regional processes that drive the assembly of species, the stability of community, and the emergence of ecosystem functions, from limited spatial fluxes of individuals and (in)organic matter. These predictions are often mediated by the maintenance of environmental or endogenous fluctuations from local to regional scales that create important challenges and opportunities for the validation of metacommunity and meta-ecosystem theories and their application to conservation.
Article
Full-text available
As most regions of the earth transition to altered climatic conditions, new methods are needed to identify refugia and other areas whose conservation would facilitate persistence of biodiversity under climate change. We compared several common approaches to conservation planning focused on climate resilience over a broad range of ecological settings across North America and evaluated how commonalities in the priority areas identified by different methods varied with regional context and spatial scale. Our results indicate that priority areas based on different environmental diversity metrics differed substantially from each other and from priorities based on spatiotemporal metrics such as climatic velocity. Refugia identified by diversity or velocity metrics were not strongly associated with the current protected area system, suggesting the need for additional conservation measures including protection of refugia. Despite the inherent uncertainties in predicting future climate, we found that variation among climatic velocities derived from different general circulation models and emissions pathways was less than the variation among the suite of environmental diversity metrics. To address uncertainty created by this variation, planners can combine priorities identified by alternative metrics at a single resolution and downweight areas of high variation between metrics. Alternately, coarse-resolution velocity metrics can be combined with fine-resolution diversity metrics in order to leverage the respective strengths of the two groups of metrics as tools for identification of potential macro- and micro-refugia that in combination maximize both transient and long-term resilience to climate change. Planners should compare and integrate approaches that span a range of model complexity and spatial scale to match the range of ecological and physical processes influencing persistence of biodiversity and identify a conservation network resilient to threats operating at multiple scales. This article is protected by copyright. All rights reserved.
Chapter
Introduction When on board H.M.S. ‘Beagle,’ as naturalist, I was much struck with certain facts in the distribution of the inhabitants of South America, and in the geological relations of the present to the past inhabitants of that continent. These facts seemed to me...
Book
Ecologists are aware of the importance of natural dynamics in ecosystems. Historically, the focus has been on the development in succession of equilibrium communities, which has generated an understanding of the composition and functioning of ecosystems. Recently, many have focused on the processes of disturbances and the evolutionary significance of such events. This shifted emphasis has inspired studies in diverse systems. The phrase "patch dynamics" (Thompson, 1978) describes their common focus. The Ecology of Natural Disturbance and Patch Dynamics brings together the findings and ideas of those studying varied systems, presenting a synthesis of diverse individual contributions.