Mapping conservation priorities and connectivity pathways under climate change for tropical ecosystems

Abstract

Climate change and land use conversion are global threats to biodiversity. Protected areas and biological corridors have been historically implemented as biodiversity conservation measures and suggested as tools within planning frameworks to respond to climate change. However, few applications to national protected areas systems considering climate change in tropical countries exist. Our goal is to define new priority areas for biodiversity conservation and biological corridors within an existing protected areas network. We aim at preserving samples of all biodiversity under climate change and facilitate species dispersal to reduce the vulnerability of biodiversity. The analysis was based on a three step strategy: i) protect representative samples of various levels of terrestrial biodiversity across protected area systems given future redistributions under climate change, ii) identify and protect areas with reduced climate velocities where populations could persist for relatively longer periods, and iii) ensure species dispersal between conservation areas through climatic connectivity pathways. The study was integrated into a participatory planning approach for biodiversity conservation in Costa Rica. Results showed that there should be an increase of 11 % and 5 % on new conservation areas and biological corridors respectively. Our approach integrates climate change into the design of a network of protected areas for tropical ecosystems and can be applied to other biodiversity rich areas to reduce the vulnerability of biodiversity to global warming.

Full text

Mapping conservation priorities and connectivity
pathways under climate change for tropical ecosystems
Emily Fung
1
&Pablo Imbach
1
&Lenin Corrales
1,2
&
Sergio Vilchez
3
&Nelson Zamora
4
&Freddy Argotty
1
&
Lee Hannah
5
&Zayra Ramos
6,7
Received: 23 September 2015 /Accepted: 26 August 2016 /Published online: 28 September 2016
#The Author(s) 2016. This article is published with open access at Springerlink.com
Abstract Climate change and land use conversion are global threats to biodiversity. Protected
areas and biological corridors have been historically implemented as biodiversity conservation
measures and suggested as tools within planning frameworks to respond to climate change.
However, few applications to national protected areas systems considering climate change in
tropical countries exist. Our goal is to define new priority areas for biodiversity conservation
Climatic Change (2017) 141:77–92
DOI 10.1007/s10584-016-1789-8
This article is part of a Special Issue on BClimate change impacts on ecosystems, agriculture and smallholder
farmers in Central America^edited by Camila I. Donatti and Lee Hannah.
Electronic supplementary material The online version of this article (doi:10.1007/s10584-016-1789-8)
contains supplementary material, which is available to authorized users.
*Emily Fung
efung@catie.ac.cr
Nelson Zamora
zamoravn@gmail.com
Lee Hannah
l.hannah@conservation.org
Zayra Ramos
zramos@catie.ac.cr
1
Environmental Modelling Laboratory, Climate Change Program, CATIE 7170, Turrialba 30501,
Costa Rica
2
Latin University of Costa Rica, Heredia, Costa Rica
3
Biostatistics Unit, Graduate School, CATIE 7170, Turrialba 30501, Costa Rica
4
Botanical Department, National Biodiversity Institute (INBio), Heredia, Costa Rica
5
Center for Applied Biodiversity Science, Conservation International, Washington, DC 20037, USA
6
Climate Change Program, CATIE 7170, Turrialba 30501, Costa Rica
7
Department of Forest, Rangeland, and Fire Sciences, University of Idaho, Moscow, ID, USA
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and biological corridors within an existing protected areas network. We aim at preserving
samples of all biodiversity under climate change and facilitate species dispersal to reduce the
vulnerability of biodiversity. The analysis was based on a three step strategy: i) protect
representative samples of various levels of terrestrial biodiversity across protected area systems
given future redistributions under climate change, ii) identify and protect areas with reduced
climate velocities where populations could persist for relatively longer periods, and iii) ensure
species dispersal between conservation areas through climatic connectivity pathways. The
study was integrated into a participatory planning approach for biodiversity conservation in
Costa Rica. Results showed that there should be an increase of 11 % and 5 % on new
conservation areas and biological corridors respectively. Our approach integrates climate
change into the design of a network of protected areas for tropical ecosystems and can be
applied to other biodiversity rich areas to reduce the vulnerability of biodiversity to global
warming.
1 Introduction
Biodiversity supports the provision of ecosystem services contributing to human well-being
(MEA 2005). Conserving samples of biodiversity are important for community and ecosys-
tems structure and function and therefore to achieve environmental and development goals.
Climate and land use change have been identified as the main global challenges to biodiversity
conservation (Sala et al. 2000) due to effects on species distribution changes and extinctions,
populations, structure and function of communities and ecosystems (Yang and Rudolf 2010).
Protected areas (PA) and biological corridors (BC) have been proposed as conservation
measures for biodiversity with particular relevance to face the impacts of climate change
(Heller and Zavaleta 2009) accompanied by conservation planning frameworks and tools.
However, few applications to national protected areas systems in tropical countries exist
(Phillips et al. 2008;Gameetal.2011).
With over 50 % of tropical forest already converted into agricultural lands or other uses
(Hansen et al. 2013), the time-window for designing PA that can respond to the threat of
climate change is shortening. The general principle, however, is clear: protection added in
places that conserve species in both their present and future ranges can help meet current and
future conservation targets (Araújo et al. 2004).
PA systems designed based on climate change effects on biodiversity may help respond
to climate stressors. Multiple criteria have been used to identify climate-driven conserva-
tion gaps under the premise that biodiversity viability under future climate change can be
achieved by preserving: i) terrestrial environmental gradients (Game et al. 2011), ii)
climate refugia or holdouts to provide extended time for in-situ adaptation (Hannah
et al. 2014), and iii) connectivity pathways for species dispersal movements (Game
et al. 2011).
Coarse pattern characterization (i.e. ecosystems or biomes) of terrestrial biodiversity as well
as environmental units defined by climatic and topographic variables have been used as
surrogates of all biodiversity levels (communities, populations, species, genes) for conserva-
tion planning (Arponen et al. 2008;Gameetal.2011). Others have proposed the use of land
systems or land facets, defined by a combination of homogeneous topography and soil
variables, which are more stable factors over time (Beier et al. 2015). The assumption is that
by covering a wide range of environmental conditions within a conservation network, the
78 Climatic Change (2017) 141:77–92
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range of suitable living conditions is maximized, and therefore a comprehensive representation
of species is protected (Arponen et al. 2008; Beier et al. 2015). Modeling of terrestrial
vegetation redistribution under climate change has been conducted across the globe (Weltzin
et al. 2003) but has been seldom used in conservation planning of protected areas (Hannah
et al. 2007).
Spatial planning of protected areas for climate change may require to identify areas
in which biodiversity responses to climate change may be minor (Hannah et al. 2014).
The term refugia (or microrefugia) has been used referring to locations where species or
populations survived the last glacial period (Ashcroft 2010; Dobrowski 2011). Recently,
the concept has been applied to select areas that should be protected due to reduced
impacts of climate change on biodiversity (Saxon 2008;Rull2009). Tropical studies
have focused on understanding late quaternary climate fluctuations and refugia dynam-
ics of wet tropical forests (VanDerwal et al. 2009), to support conservation of amphib-
ians (Puschendorf et al. 2009), and the role of riparian forests (Aide and Rivera 1998);
although the Pleistocene refugia hypothesis of Haffer (1969) now seems thoroughly
rejected (Carnaval et al. 2009). In contemporary human-induced climate change, con-
tinual warming will make return to a pre-existing climate rare or nonexistent. Refugia
and microrefugia will therefore become vanishingly rare as climate change progresses
(Hannah et al. 2014). Climate change holdouts refer to populations that may persist for
longer but limited periods in localized areas, for example due to changes in climate that
are smaller than regional trends (Dobrowski 2011;Keppeletal.2012)andcanimprove
the chances of successful species dispersal processes under future climate scenarios
(Hannah et al. 2014).
Increasing landscape connectivity is broadly recommended as a climate change adap-
tation strategy for biodiversity conservation (Heller and Zavaleta 2009). The current
design of the BC network in Mesoamerica is aimed at facilitating connectivity between
protected areas (Mesoamericano 2007). However, species needs for dispersal pathways as
a response to change in climate was not taken into account and current corridors have
limited use for species dispersal under climate change (Imbach et al. 2013). Tropical areas
pose a particular challenge for designing corridors given their species richness and limited
knowledge on their dispersal processes (Rouget et al. 2006), although corridors with large
areas that cover altitudinal gradients have been proposed as general design guidelines
(Imbach et al. 2013).
Our goal was to identify and map potential gaps under the existing protected area
system and design connectivity routes to facilitate species range shifts to reduce the
vulnerability of biodiversity to a changing climate. Site selection was based on results
from workshops with experts and modeling outputs. We modeled impacts on biodiversity
based on a three step strategy: i) protect representative samples of various levels of
terrestrial biodiversity (ecosystems, communities, populations and species) across
protected area systems given future redistributions under climate change, ii) identify and
protect areas with reduced climate velocities where populations could persist for relatively
longer periods (referred as climate holdouts), and iii) ensure species dispersal between
conservation areas through climatic connectivity pathways. Experts input was used to
validate methods and to identify opportunities and constraints for field implementation of
new conservation areas. The methods used here represents a participatory planning
approach for biodiversity conservation under climate change in tropical areas based on
CostaRicaasacasestudy.
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2 Materials and methods
2.1 Study region
Costa Rica is located in the Mesoamerican region near the northern limit of the Neotropical
realm in a zone that begins the transition to the Nearctic realm of North America. Estimations
show than in only 0.0001 % of the earth’s surface, the country holds around 4 % (ca. 500,000)
of all world’s species (including all taxa) (ca. 14,000,000) (SINAC 2007). Costa Rica is part of
the Mesoamerican biodiversity hotspot (Myers et al. 2000) and part of the Mesoamerican
Biological Corridor, a network of PA and biological connectivity aimed at conserving large
mammals and biodiversity along the length of Central America (DeClerck et al. 2010).
In response to rapid land use change during the 1970–1990s (3.7 % deforestation rate
average for the period, Sanchez-Azofeifa et al. (2003)), the country started to consolidate the
National System of Conservation Areas (SINAC) (SINAC 2007), increasing the extent of PA
and BC from 3 to 26.5 % of the country area (Estado de la Nación 2013). However, a few
terrestrial environmental gradients (mountaintops of dry forests in Guanacaste and Osa
peninsula, tropical montane vegetation and middle lowlands of the Nicoya Peninsula) are still
not completely protected (Arias et al. 2008).
The first gap analysis of the PA system in Costa Rica aimed at ensuring that at least 90 % of
its biodiversity was under protection (García 1996). However, this assessment and the second
to come in 2007, did not account for future climate change scenarios (SINAC 2007).
The first gap analysis used macro-types as the biodiversity surrogate, defined as landscape
areas that share uniform physiognomic appearance and flora but did not consider vegetation
associations (examples of macro-types classes include paramo, oak forests, evergreen/
deciduous forests). The classification was based on forest types, dominant species, soil type,
elevation and geomorphology (1:250,000 scale, Gómez (1986)). Results suggested the need to
extend the national conservation areas system to protect nine under-represented macro-types
(García 1996). In 2007, the country repeated the gap analysis using an improved bio-
environmental gradient map describing phytogeographic units (PU) as a surrogate for biodi-
versity. The PU map consisted of 31 categories based on information from the earlier
vegetation macro-types and floristic regions (Zamora 2008). The floristic regions refer to
including floristic associations, based on dominant and indicator species (1:200,000 scale,
Hammel et al. (2003)).
The 2007 gap analysis established to protect 10 to 30 % (conservation targets) of each PU
unit within the current PA system. Results from reserve network selection and expert knowl-
edge, proposed to create 92 new conservation areas with approximately 712,000 ha and 128
new biological corridors between protected areas. The PU representativeness targets and
current conservation network (PA and BC) (SINAC 2009) are used as the basis for the analysis
presented here.
2.2 General approach
To design the PA and BC system for the long-term persistence of biodiversity under a
changing climate, we integrated a spatial component addressing the impacts of climate change
on biodiversity with considerations for field implementation of the proposed conservation
areas. We used modeling tools and climate change scenarios to assess impacts, and participa-
tory methods with experts for site selection. We addressed impacts on biodiversity by
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modeling: i) PU redistribution under future climate scenarios to quantify the ability of the
current network of PA in protecting PUs under climate change, and ii) climate holdouts,
mapped as sites with expected small changes in climate, relatively to its surrounding,assuming
that their populations could then persist under climate change. We also mapped climatic
connectivity routes for species dispersal between conservation areas assuming that dispersal
pathways would follow climates relatively closer to their current ones. Modeling results were
combined with information from experts, gathered during workshops, regarding threats and
opportunities for field implementation of new conservation areas (Supplementary Material 1).
2.2.1 Climate change scenarios
We used climate data to model the current and future (under climate change scenarios)
potential PU distributions, climate connectivity and holdout areas. Historical climate data
was obtained from the WorldClim database at ~1km
2
(30 arc-seconds) spatial resolution for
the 1950–2000 period and used to model the current PU distribution using a statistical
approach. To model future PU distribution, we used future climate scenarios from 19
General Circulation Models (GCMs) under the representative concentration pathway 4.5
(RCP 4.5, corresponding to an intermediate level of global radiative forcing) from CMIP5
(Coupled Model InterComparison Project 5, (IPCC 2013)) for the 2041–2060 period (Hijmans
et al. 2005). To estimate both range distributions (current and future), 19 bioclimatic variables
were derived from temperature and precipitation maps for each GCM run (Hijmans et al.
2005). Downscaling of climate scenarios was estimated by aggregating future anomalies, from
GCM runs, to a high-resolution historical climatology (available at WorldClim.org).
2.2.2 Terrestrial vegetation modeling
We used the national PU map (1:500,000 scale) as a surrogate for biodiversity, defined as
geographic areas sharing particular floristic vegetation patterns characterized by climate
(temperature, precipitation and its seasonality), topography (relief), elevation and geol-
ogy (Zamora 2008). The floristic vegetation pattern was defined as a type of vegetation
were a group of indicator species coexist; given their abundancy, rarity or restricted
distribution. Identification of indicator species was based on Bkeystone species^: organ-
isms controlling potential dominants, resource providers, mutualists and ecosystem
engineers (Payton et al. 2002) based on available occurrence data. To develop the PU
map, a multidisciplinary expert group (comprising biogeography, botany, climate, con-
servation, statistics, ecology, geology, geography, information technology and modeling
scientists) worked on manually delineating each PU using indicator species, climate
maps, contour lines and/or geographical features, such as rivers or basins. The resulting
PU map was used during the 2007 (SINAC 2007) gap analysis and the one presented
here. The PU map provides information suitable for a biodiversity coarse-filter assess-
ment (Powell et al. 2000) that simplified experts and users familiarization, given its use
in previous assessments.
We used a Random Forest algorithm (Liaw and Wiener 2002) to generate classification
rules of the current distribution of the PU (Zamora 2008) using a combination of biophysical
variables as predictors: i) five principal components (PC) capturing 90 % of the variability
from the 19 bioclimatic variables and evapotranspiration (Supplementary Material 2, Table 1)
(Hijmans et al. 2005), ii) relief quantified as the topographic position index (Jenness 2006)
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from a digital elevation model (1 km
2
pixel, Jarvis et al. (2008)) that classifies the landscape
into slope position and landforms (plain, undulating, mountain and valleys and depressions)
and iii) surface lithology describing age and origin of the rocks based on the national
geological map (1:500,000 scale, USGS (1987)). Bioclimatic variables describe regional
precipitation and temperature climatology at the annual, seasonal and monthly scales based
on monthly mean values. Real evapotranspiration was based on Imbach et al. (2012). We used
70/30 % of the pixels to train/validate the model that showed a misclassification rate of 11 %.
The most important variables in the classification according to the Mean Decrease Accuracy
were PC1, PC2, PC3 and surface lithology (Supplementary Material 2,Figure1).Arandom
forest model was used to predict the PU distribution under future climatic scenarios using the
PC maps derived for each one of the 19 GCM’s (Supplementary Material 2,Table1).We
considered future potential ecosystems presence on any given pixel, when >66 % of the future
climate models (>13 out of 19 GCMs) showed agreement indicating a likely presence
(according to IPCC 2013 guidelines).
Conservation targets were defined as a sub-set of species, communities or ecological
systems that represent biodiversity, established for each PU during the 2007 gap analysis
by expert’s criteria, based on the area of each PU. Conservation targets were set of
>10,000 ha or between 10 and 30 % of the total area of each PU to be conserved to
maintain a representative sample (SINAC 2007). We quantified the likely future area of
each PU within protected areas. For those PU that did not meet conservation targets within
PA, additional sites were selected with the Marxan planning support tool. Marxan is
designed to solve problems when multiple complex solutions exist, by selecting sites that
meet a specific conservation target with the most cost-efficient solution for field imple-
mentation (i.e. lowest cost) (Watts et al. 2009). A 250 ha hexagon was assumed to provide
a minimum area useful for spatial planning and 21,180 planning units covered the country.
In order to account for future uncertainties on PU distribution from climate scenarios, we
estimated the contribution of each hexagon to achieve a PU conservation target as the
product of each PU mean pixel frequency across the 19 scenarios by the total hexagon
area. Therefore, our setup optimized the selection of additional conservation sites that
maximized higher likelihood of PU presence under future climate scenarios. We assumed
that conservation costs of a hexagon depended on its dominant land use (SINAC and
FONAFIFO 2014), with forests having the lower cost for implementation (0) of conser-
vation activities and non-forest areas (agriculture and urban areas) with maximum costs
(100). Pastures, forest plantations and secondary forests were assigned costs of 60, 40 and
20 respectively. We calculated solutions with different clumping levels of planning units
(Balletal.2009). PU without any significant likely future distribution (<10 km
2
), were not
included in the analysis and assumed to disappear.
2.2.3 Climate holdouts: velocity of climate change
We mapped velocity of climate change as a proxy for climate holdouts to identify areas
where populations may persist for longer periods. Velocity of climate change is
calculated as the distance (km) per year that a species would need to travel to maintain
its original climate conditions (Loarie et al. 2009; Ackerly et al. 2010; Dobrowski et al.
2013). We estimated the velocity of climate change based on future changes in mean
annual temperature and total annual precipitation following Loarie et al. (2009)and
Dobrowskietal.(2013). We calculated velocity as the ratio of temporal (year/km) and
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spatialgradient(
°
C/km or mm/km) of changes in climate, as a proxy for the potential
speed at which species would need to disperse in the future. We mapped areas with
minor velocities (arbitrarily selected as <0.01 °C/km) assuming that species would need
to move shorter distances to maintain its current climate and be able to persist for a
relatively longer time. The resulting map was used to select conservation areas by
experts during the participatory workshops.
2.2.4 Climatic connectivity pathways: direction of climate change
Climate change direction was used to identify possible spatial trajectories for species
dispersal pursuing their suitable climate niche. We used the direction of future change in
temperature (year/km), following Burrows et al. (2014) formula, to map the direction of
potential trajectories. Burrows et al. 2014 combined trajectories to map corridor, sink,
source, convergence and divergence areas. Nevertheless, we used a simplified approach
based on each pixel direction of change. We assumed that all species have dispersal
capacities to keep pace with climate change without accounting for species dispersal
capacity nor potential barriers other than climatic. We assumed that continuous areas with
similar direction represented connectivity pathways if the direction followed the shifts in
the PU future redistribution, or a barrier otherwise. Clusters of vectors pointing at each
other were also assumed as barriers. We assumed that the first situation (i.e. opposite
direction) represented a larger barrier than the second (i.e. pointing to each other).
Direction of changes in precipitation was not considered given its inconsistent direction
pattern possibly resulting from uncertainty in future precipitation scenarios over this
region (IPCC 2013).
2.2.5 Conservation site and connectivity network selection: experts inputs
Selection of additional conservation sites and BC resulted from combining results of
experts input and modeling outputs during workshops. We systematized leading biolo-
gists and conservation planners opinion through participatory workshops. The first
workshop focused on validating the methodologies. We started with a description on
climate variability, trends and future climate scenarios as background to the analysis,
followed by an open discussion based on guided questions (Supplementary Material 3)
related to the methods, data availability and limitations. The second workshop aimed at
communicating modeling results and identification of new gaps and connectivity routes.
Working groups, comprising experts across regions of the country, were provided with
base maps (of PA, BC, current conservation gaps and forest cover) and model outputs
(PU future distribution, Marxan selected areas and climate holdouts). The climate change
direction map was also used to design connectivity networks (Section 2.2.3). Maps were
provided in transparent format allowing overlays to facilitate discussion. Experts pro-
vided criteria for site selection related to land use change threats (i.e., urban or cash crop
developments, local community conflicts, other barriers for species -i.e., hydro-power
reservoirs, stream contaminants) and opportunities for field implementation of new
conservation areas (i.e., resources for implementation and community involvement).
Site selection resulted from expert’s consensus for each group while a rapporteur
systematized implementation issues for each site discussed. The third workshop was
oriented towards a broader audience (including previous workshops participants) to
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validate the final portfolio of new conservation areas and BC. Workshops attendance
ranged between 15 and 31 experts.
3Results
3.1 Terrestrial vegetation modeling
Future PUs distribution indicated that most will experience decrease in their likely distribution
range (Fig. 1). The northern dry region, the humid southeast Caribbean slope and Talamanca’s
mountainside towards the Pacific lowlands did not present likely future distributions of any PU
(grey areas of the map, Fig. 1). PU across the central mountain range (brown), Talamanca’s
Caribbean mountain range (green) and Pacific southernmost areas (light blue and orange)
showed the greatest persistence areas under future scenarios (Fig. 1). PU from dryer north-
western areas (purple PU) experienced an increase in their future distribution range indicating
an expansion into currently more humid areas. North Caribbean lowland plains (dark blue),
Central Pacific lower slopes (red) and Talamanca’s Caribbean mountain range (green) undergo
a reduction of their current distribution combined with newly colonized areas (Fig. 1).
Fig. 1 Potential redistribution of phytogeographic units (PU) under future climate scenarios. Black lines
delineate current PU distribution areas. Within the limits of each PU, light and dark color tones indicate the
future loss and persistence areas respectively. Dark tones outside current PU boundaries indicate colonization
areas
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3.2 Climate holdouts: velocity of climate change
The mean velocity for mean temperature and total precipitation for 2041–2060 across the
country was 0.17 C°/km and 0.88 mm/km respectively. The highest velocity rates were
observed in regions with low topographic relief, primarily found in the north and northeastern
areas (Guanacaste and Alajuela provinces) for precipitation, in addition to the northwestern
region (Caribbean floodplains in Tortuguero) for temperature. The lowest velocity rates were
found in mountainous regions of the country. These potential holdouts were found in the
central volcanic mountain range, central south mountains (La Amistad National Park) and
mountains near the Pacific coast (Fig. 2).
3.3 Climatic connectivity pathways
Directional patterns appeared as i) continuous areas following the same direction demonstrat-
ing clear pathways for species dispersal and ii) undistinguishable pathways due to vectors
pointing at each other. The country’s complex topography resulted in pathways usually having
a few arrows with opposite direction. Figure 3shows examples of regional directional analysis
from two sites in Costa Rica. Arrows indicate the direction of change in climate. Figure 3a-i
shows the potential location of corridors (routes following the blue arrows) in areas with
arrows pointing in the same direction as the range shift of a PU. Figure 3a-ii indicates a climate
Fig. 2 Climate holdouts (red), estimated as the lowest temperature (°C/km) and precipitation (mm/km) velocities
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barrier for species dispersal, as future re-distribution of the PU follows the opposite direction
of climate change. Figure 3a-iii shows arrows in all directions exemplifying no clear pathways.
Connectivity pathways were also identified to facilitate the contraction of PU. Figure 3b-iv
shows the location of corridors that could favor PU range contractions (towards PU persistence
over dark red pixels) and facilitate species dispersal towards persistence areas. We selected
pathways benefiting the connectivity between biological corridors, protected areas and current
conservation gaps (not shown in the figure).
3.4 Conservation targets and gap analysis
Future biodiversity distribution showed that: (i) 7 PUs had likely future areas in current
protected areas that meet conservation targets, (ii) 10 PUs future distribution did not meet
conservation targets, (iii) 4 PUs did not have any likely distribution area in the future and (iii)
10 PUs disappear under future climates. For the 10 PUs not achieving their conservation
targets, we proposed 11 new conservation areas to maximize their representativeness under
future scenarios. These PUs are located in the north and northwestern lowlands of the country
(including one PU in the Pacific coast) and on the southern foothills of the Central Mountain
Range.
Our results show an increase of 151,000 ha (11 % of the current extent) of new conservation
areas and 237, 000 ha (5 % area increase from its current extent) in 15 new BC for Costa Rica,
in order to increase biodiversity representativeness under climate change (Supplementary
Material 4).
4 Discussion
Future expansions and contractions of PUs over the dry northwestern, Caribbean and
central southern areas agree with other studies indicating redistribution of potential life
zones (Bertrand et al. 2011; Khatun et al. 2013) and increased coverage of drier PU types
(Imbach et al. 2012). These redistributions will result from migration of species or
communities to track ideal climate conditions, with a range shift that generates coloniza-
tion and contraction areas; persistence over current distribution through adaptation or
extinction (Breshears et al. 2008). Resulting shifts in individual species responses will
ultimately define the future composition of the PUs, requiring studies on species range
redistributions, population and community dynamics.

Fig. 3 Direction of annual temperature change under future climate scenarios. Purple,blue,yellow and green
arrows indicate northeast, southeast, southwest and northwest directions of change respectively. Light and dark
red areas indicate the current and future (persistence and colonization areas) distribution of a phytogeographic
unit (PU). Black arrows indicate areas for proposed new climatic corridors and black circles show barriers. aThe
PU will likely experience a range reduction (dark red within its current distribution) and colonization areas (dark
red pixels to the right outside its current distribution): i) blue arrows specify the climate direction that species
might need to follow to colonize newly suitable areas, ii) yellow arrows exemplifies a climatic barrier for species
dispersal with climate change in opposite direction as the course that follows the future distribution of the PU
and, iii) all colored arrows cluster showing a barrier for dispersal. bthe PU suffers a range reduction to smaller
persistence areas within its current range (dark red) that require climate pathways to benefit species movement
towards the persistence core (iv). The country topography is highly complex resulting in pathways usually having
afewarrows contradicting the general landscape direction, therefore, we had to neglect single arrows barriers
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The Caribbean lowlands PUs (dark blue in Fig. 1), suggests new colonization areas over
flatlands (towards the south) while the center south and pacific PUs (Green and red PU in
Fig. 1) shift over mountain areas. Range shifts are expected to occur through pioneer species
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that disperse long distances and colonize by exponential population growth in less favorable
climate conditions (Hampe and Petit 2005). Areas of the country without likely distribution of
any PU (grey areas in Fig. 1), mostly resulting from GCM uncertainty or arrangement of novel
climates, could lead to novel species assemblages (Bertrand et al. 2011).
Persistence areas were found in the central region of the country (brown and green PU,
Fig. 1). The literature suggest that these PUs will retain species covering the inner part of the
range distribution, as the margins suffer greater climate stress and experience a contraction
(Hannah et al. 2014).
Mean annual temperature velocity estimates found in this study (0.17 km/yr) are lower than
those presented by Imbach et al. (2013) (0.25 km/yr), Loarie et al. (0.33 km/yr) and Burrows
et al. (2014)(0.1–5 km/yr) for the Central American region, probably due to different emission
scenarios, future time frames and finer spatial resolution of the approach. Dobrowski et al.
(2013) calculated climate velocities at five different resolutions (between 30 arc-seconds and 1
degree) and found that at coarser spatial resolution climate velocity increased due to an
underestimation on the terrain capacity to buffer changes in climate. We found no reports on
precipitation velocities for this region. However, there is a general agreement pattern of higher
temperature velocities in flatter areas and lower estimates over mountainous regions. Relatively
small temperature changes over flat areas will require a species to disperse farther distances to
track its ideal climate under changing conditions, while in mountainous regions, a short
movement upslope or downslope will result in larger compensations, allowing the species to
rapidly keep pace with changes in climate (Loarie et al. 2009;Imbachetal.2013). Precipitation
holdouts were also found in mountainous areas (over high slope areas). However, the relatively
small anomalies of mean precipitation found might result from GCM positive and negative
signals canceling each other, given the uncertainty on trends of future precipitation (Imbach
et al. 2012). Its usefulness as a proxy for holdouts should be further explored.
The proposed BC should facilitate contractions or expansion of PU by allowing species to
disperse to a suitable climate and rescue small populations from local extinction (due to
demographic or environmental stochasticity) (Bull et al. 2007). Identification of holdout areas
to support the design of BC provides for places where species may persist for longer periods
and support species flow between the expansion and contraction areas. (Hannah et al. 2014).
Temperature directions are dominated by the altitudinal gradient, since altitude is the main
temperature controller over the region (Ackerly et al. 2010). Direction of precipitation showed
no clear patterns, with contradicting directions at very small scales, limiting its use to define
connectivity pathways.
Our conservation targets (10 to 30 % of the PU area) are similar to those used for other
studies (Langhammer et al. 2007), however, it would be valuable to explore the effect of
different values or inclusion species level conservation targets. Furthermore, the methodology
could benefit from improved representation of local species ecological characteristics includ-
ing dispersal capacities and effects of landscape barriers to identify climate pathways or their
sensitivity to changes in climate for improved holdouts mapping.
Experts and conservation managers were involved during all stages of the process to
complement the systematic planning approach (Cowling et al. 2003). Their feedback, contrib-
uted to the selection of new biodiversity conservation sites and validation of the final portfolio.
We found that expert knowledge provided for updated local level information hardly available
on maps at national scale. Information referred to opportunities and barriers for implementation,
socioeconomic aspects of the target area or micro areas of high endemism. Furthermore, their
involvement potentially enhanced user’s legitimacy of the conservation portfolio.
88 Climatic Change (2017) 141:77–92
Content courtesy of Springer Nature, terms of use apply. Rights reserved.

Our results define new areas that could require landscape management for biodiversity
conservation depending on their current vegetation cover and connectivity needs. These
management activities can range from conservation or restoration of forests, agroforestry
systems and live fences to removing barriers for dispersal, among others (Heller and
Zavaleta 2009). Monitoring programs could prove useful to detect changes in areas of
PU expansions and contractions in response to climate fluctuations, therefore strength-
ening our understanding on biodiversity response rates (Plattner 2009) and affected
components (biomes, communities, populations, species and genes) (Bellard et al.
2012). Finally monitoring results could support future research and updates on the
conservation portfolio.
5 Conclusions
We presented a multi-criteria approach for redesigning a network of conservation areas for
enhancing long-term biodiversity viability under changing climate. The approach was based on
integrating information on biodiversity distribution patterns, climate holdouts and connectivity
pathways under future climate scenarios. A participatory planning process also accounted for
expert knowledge on local context, potentially facilitating future implementation and improving
legitimacy to the process. Results indicate the need for conservation activities on sites currently
outside protected areas and for improved landscape connectivity across selected landscapes.
However, assumptions regarding the use of phytogeographic units as surrogates for impacts on
biodiversity or disregarding species dispersal capacity could have important implications for our
findings. Future research and monitoring of changes in species, populations, communities
and ecosystems should help fill these gaps. Finally, the resulting portfolio can support
biodiversity conservation policies and the development of national adaptation strategies
coherent with cross-country conservation efforts (Hannah et al. 2002). This multi-criteria
approach, can be used in other regions to identify areas to ensure biodiversity conser-
vation in face of climate change.
Acknowledgments This work was done to support BCosta Rica’s adaptation of the biodiversity sector to
climate change^project CR-T1081 ATN/OC-13260-CR coordinated by SINAC and partially financed by the
Inter-American Development Bank (IDB). We acknowledge SINAC for their support during the process and all
experts who provided their valuable input during workshops. We thank The Betty and Gordon Moore Center for
Science at Conservation International for providing funds for open access. We thank Peter Läderach for his
review of early versions of this manuscript.
Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International
License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and repro-
duction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a
link to the Creative Commons license, and indicate if changes were made.
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