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Multi-taxa ecological responses to habitat loss and fragmentation in western Amazonia as revealed by RAPELD biodiversity surveys

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Habitat loss and fragmentation caused by deforestation are important anthropogenic drivers of changes in biodiversity in the Amazon rainforest, and has reached its highest rate in recent decades. However, the magnitude and direction of the effects on species composition and distribution have yet to be fully understood. We evaluated the responses of four taxonomic groups − birds, amphibians, orchid bees, and dung beetles-to habitat loss and fragmentation at both species and assemblage level in the northern Ecuadorian Amazon. We sampled fifteen 250-m long plots in terra-firme forest remnants. We calculated one landscape fragmentation index (fragindex), which considers the proportion of continuous forest cover, edge density and isolation in the landscape, and nine landscape configuration metrics. Logistic regression models and multivariate regression trees were used to analyze species and assemblage responses. Our results revealed that over 80% of birds, amphibians or orchid-bee species, and 60% of dung beetles were negatively affected by habitat loss and fragmentation. Species composition of all taxonomic groups was significantly affected by differences in forest cover and connectivity. Less than 5% of all species were restricted to landscapes with fragindex values higher than 40%. Landscape metrics related to the shape and area of forest patches determined the magnitude and direction of the effect on species responses. Therefore, changes in the landscape configuration of Ecuadorian Amazonia should be minimized to diminish the effects of habitat loss and fragmentation on species occurrence and assemblage composition.
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234 VOL. 513 2021: 234  243
http://dx.doi.org/10.1590/1809-4392202004532
ORIGINAL ARTICLE
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CITE AS: Moulatlet, G.M.; Ambriz, E.; Guevara, J.; López, K.G.; Rodes-Blanco, M.; Guerra-Arévalo, N.; Ortega-Andrade, H.M.; Meneses, P. 2021. Multi-taxa
ecological responses to habitat loss and fragmentation in western Amazonia as revealed by RAPELD biodiversity surveys. Acta Amazonica 51: 234243.
Multi-taxa ecological responses to habitat loss and
fragmentation in western Amazonia as revealed by
RAPELD biodiversity surveys
Gabriel M. MOULATLET1,2* , Emmanuel AMBRIZ1, Jennifer GUEVARA3,4, Karima G. LÓPEZ5,
Marina RODES-BLANCO6, Nereida GUERRA-ARÉVALO6, H. Mauricio ORTEGA-ANDRADE2,6,
Pablo MENESES7
1 Universidad Regional Amazónica Ikiam, Facultad de Ciencias de la Tierra y Agua, Km 7, vía a Muyuna, Tena, Napo, Ecuador
2 Instituto Nacional de Biodiversidad - INABIO, Pje. Rumipamba N. 341 y Av. de los Shyris (Parque La Carolina), Quito, Pichincha, Ecuador
3 Universidad Regional Amazónica Ikiam, Facultad de Ciencias de la Vida, Tropical Ecosystems and Global Change Research Group, Km 7, vía a Muyuna, Tena, Napo, Ecuador
4 McMaster University, Department of Psychology, Neuroscience & Behaviour, Ontario, Canada
5 Universidad de La Laguna, Avenida Astrofísico Francisco Sánchez, s/n. San Cristóbal de La Laguna. S/C de Tenerife, España
6 Universidad Regional Amazónica Ikiam, Facultad de Ciencias de la Vida, Biogeography and Spatial Ecology Research Group, Km 7, vía a Muyuna, Tena, Napo, Ecuador
7 Universidad Regional Amazónica Ikiam, Facultad de Ciencias Socioambientales, Km 7, vía a Muyuna, Tena, Napo, Ecuador
* Corresponding author: gabriel.moulatlet@gmail.com; https://orcid.org/0000-0003-2571-1207
ABSTRACT
Habitat loss and fragmentation caused by deforestation are important anthropogenic drivers of changes in biodiversity in the
Amazon rainforest, and has reached its highest rate in recent decades. However, the magnitude and direction of the eects on
species composition and distribution have yet to be fully understood. We evaluated the responses of four taxonomic groups
− birds, amphibians, orchid bees, and dung beetles – to habitat loss and fragmentation at both species and assemblage level
in the northern Ecuadorian Amazon. We sampled fteen 250-m long plots in terra-rme forest remnants. We calculated
one landscape fragmentation index (fragindex), which considers the proportion of continuous forest cover, edge density and
isolation in the landscape, and nine landscape conguration metrics. Logistic regression models and multivariate regression
trees were used to analyze species and assemblage responses. Our results revealed that over 80% of birds, amphibians or orchid-
bee species, and 60% of dung beetles were negatively aected by habitat loss and fragmentation. Species composition of all
taxonomic groups was signicantly aected by dierences in forest cover and connectivity. Less than 5% of all species were
restricted to landscapes with fragindex values higher than 40%. Landscape metrics related to the shape and area of forest patches
determined the magnitude and direction of the eect on species responses. erefore, changes in the landscape conguration
of Ecuadorian Amazonia should be minimized to diminish the eects of habitat loss and fragmentation on species occurrence
and assemblage composition.
KEYWORDS: deforestation, Ecuador, species distribution, tropical forests
Respuesta ecológica multitaxón a la pérdida de hábitat y fragmentación
del paisaje en la Amazonía occidental reveladas por evaluaciones de
biodiversidad RAPELD
RESUMEN
La pérdida y fragmentación del hábitat causada por la deforestación es un importante impulsor antropogénico de cambios sobre
la biodiversidad en la selva amazónica. Sin embargo, la magnitud y dirección de los efectos sobre la composición y distribución
de las especies aún es incomprendida. Evaluamos las respuestas de cuatro grupos taxonómicos - aves, anbios, abejas de
orquídeas y escarabajos peloteros - a la pérdida y fragmentación del hábitat, tanto a nivel de especies como de ensamblaje, en
la Amazonía norte ecuatoriana. Tomamos muestras de quince parcelas de 250 m de largo en remanentes de bosque de tierra
rme. Calculamos un índice de fragmentación del paisaje (fragindex), que considera la cobertura forestal continua, densidad
del borde y el aislamiento en el paisaje, y nueve métricas de conguración del paisaje para analizar las respuestas de especies y
ensamblajes. Más del 80% de las especies de aves, anbios o abejas de orquídeas y el 60% de los escarabajos peloteros se vieron
afectados negativamente por la pérdida y fragmentación del hábitat. La composición por especies se vio signicativamente
afectada por las diferencias en la cobertura forestal y la conectividad, mientras que la forma y el área de los parches de bosque
determinaron la magnitud y la dirección del efecto en las respuestas de las especies. Por lo tanto, los cambios en la conguración
del paisaje de la Amazonía ecuatoriana deben minimizarse para disminuir los efectos de la pérdida y fragmentación del hábitat
sobre la presencia de especies y la composición de los ensambles.
PALABRAS-CLAVE: deforestación, Ecuador, distribución de especies, bosques tropicales
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INTRODUCTION
Between 2000 and 2012, more than 250,000 km2 of
South American tropical forests were replaced by agriculture,
cattle pastures and aected by other economic activities like
mining and oil exploitation (Lewis et al. 2015; Hansen et al.
2020). Consequently, continuous forest areas are reduced
and fragmented into smaller patches among non-native
habitats (Achard et al. 2014; Haddad et al. 2015). Most
land transformation occurs in privately-owned lands, which
are more vulnerable to transformations and degradation
(Laurance et al. 2002, 2009; Zimbres et al. 2018). In the
western portion of the Amazon basin in Ecuador, deforestation
is the main driver of habitat loss and fragmentation, mainly
for cattle pasture and silviculture (Bonilla-Bedoya et al. 2014).
With few protected areas that could guarantee the integrity
and connectivity of large forest areas, the 132,292 km2 of
Ecuadorian Amazonia have been rapidly fragmented since
1970 (Sierra 2000; Hansen et al. 2013). Between 2010 and
2015, 2% of the total deforestation in the Amazon basin
occurred in Ecuador, with an accumulated deforestation of
12,120 km2 (Borja et al. 2017).
Habitat loss and fragmentation are twin processes that
lead to the increase in forest edge, decrease in forest area,
and isolation of fragments (Fischer and Lindenmayer 2007;
Haddad et al. 2015; Hadley and Betts 2016; Fahrig 2019).
At the local scale, forest edges enhance the exposure of
the vegetation to higher temperatures and lower humidity
(Laurance et al. 2002, 2017). Edges aect vertebrates (Pfeifer
et al. 2017) and invertebrates (Fahrig 2017), changing not
only their abundance and local distribution patterns, but also
their phenotypic features (Pfeifer et al. 2017). At the landscape
scale, the reduction in forest area and connectivity among
fragments increases the isolation among populations, restricts
movement and gene ow, leading to local extinctions and
reduced recolonization probability (Fischer and Lindenmayer
2007). e eect of reduced fragment area and increasing
isolation can be enhanced or minimized depending on the
characteristics of the matrix surrounding the fragments
(Lees and Peres 2009). For example, palm oil plantations
and pastures are less permeable dispersal barriers for some
organisms than secondary forests (Mendes-Oliveira et al.
2017; Harada et al. 2020).
e eects of habitat loss and fragmentation can also
greatly vary among and within taxonomic groups. In some
invertebrates, such as dung beetles, species richness and
abundance tend to decrease with forest area and with the
degree of fragment isolation (Vulinec et al. 2008, Carpio et
al. 2009, Cândido et al. 2018). In other invertebrate groups,
such as orchid bees, there is conicting evidence for the eects
of habitat loss and fragmentation on species abundance or
richness, as eects can be positive (Brosi et al. 2008), negative
(Nemésio and Silveira 2010), or neutral (Tonhasca et al.
2002; Storck-Tonon et al. 2013; Botsch et al. 2017). Even
in the absence of eects on species abundance or richness,
fragmentation can still impact community composition
(Botsch et al. 2017). In vertebrates such as amphibians species-
specic responses tend to be negative relative to forest-edge
increase (Schneider-Maunoury et al. 2016). Birds usually
respond negatively to fragmentation, and many species are
aected by habitat isolation (Stouer 2020) and forest edges
(Moura et al. 2016).
Here, we evaluate the ability of ten landscape conguration
metrics (Wang et al. 2014) to detect species ecological
responses in a landscape under deforestation pressure. First,
we quantied the performance of each metric as predictor
of species occurrence and species assemblage composition.
en we asked 1) how dierent landscape metrics modulate
the magnitude and the direction of species individual
ecological responses; and 2) how species responses dier
among taxonomic groups. To address these questions, we
examined the occurrence of four taxonomic groups (birds,
amphibians, orchid bees, and dung beetles) in 15 plots in a
fragmented landscape in the northern Ecuadorian lowland
Amazonia. Our results are aimed at supporting decision-
makers and stakeholders in the implementation of public
policies of the Agenda Nacional de Biodiversidad de Ecuador
(the Ecuadorian National Agenda for Biodiversity).
MATERIAL AND METHODS
Study area
Our study took place in the municipality of Shushundi,
Sucumbíos province, Ecuador ( Figure 1). Annual precipitation
exceeds 2400 mm and monthly precipitation exceeds 100
mm (INAHMI 2006). is area was chosen due to its high
deforestation rates and increasing anthropogenic impacts.
Annual gross deforestation in Sucumbios between 2014 and
2016 exceeded 9,000 hectares (MAE 2017). Oil extraction is
the root cause of deforestation and environmental degradation
in the province (Lessmann et al. 2016). e direct impact
of road opening across continuous primary forest to access
oil-rich areas is followed by land division and occupation by
settlers. Large areas are occupied by monocultures of African
palm (Elaeis guineensis), cocoa (eobroma cacao), and coee
(Coea spp.). Given its high deforestation rates, this area
was indicated as one of the priority areas for conservation in
Ecuador (Cuesta et al. 2017).
Sampling design
We installed 15 RAPELD plots (standardized plots for
rapid assessment and long-term sampling) (Magnusson et al.
2005) in privately owned remnant forests (Figure 1). All plots
were installed with previous authorization from landowners.
All plots were 250 m long and installed in terra-rme forest
of minimum 1 ha in area. A 1-km2 grid was superimposed to
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the study area and the RAPELD plots were installed in 15 grid
cells containing representative forest remnants. e proportion
of forest cover in the 1-km2 cells containing the plots varied
from 15 % to 100 % (Supplementary Material, Table S1).
Secondary and logged forests were avoided. RAPELD plots
allow for integrated sampling of dierent taxonomic groups
by adjusting plot width, thus making biotic data comparable
among organisms with dierent ecological characteristics.
More details on the concept and structure of RAPELD plots
are available at <https://ppbio.inpa.gov.br/en/methods>.
Biodiversity surveys
We collected occurrence data (presence-absence) of birds
(class Aves), amphibians (order Anura), Euglossine bees
(order Hymenoptera: family Apidae), and dung beetles (order
Coleoptera: family Scarabaeidae) during the month of August
2018 in each of the 15 plots. ese groups were chosen because
they are indicator groups that respond rapidly to landscape
change (Vellend et al. 2008).
Bird surveys were carried out at the starting point of the
250-m transect in each plot. An experienced ornithologist
recorded and identied all birds seen or heard for 30 minutes
within an 80-m radius, an intemendiate distance where
understorey bird species can be visually identifyed (Barlow et
al. 2007; Mestre et al. 2011). Each plot was visited twice in
dierent days, in hours of higher activity of most bird species,
once in the morning from 06:00 to 09:00, and once in the
afternoon, from 16:00 to 18:00, totalling 30 survey days.
Amphibian were surveyed for 90 minutes on two occasions
on dierent days in each plot, once in the morning (09:00 -
12:00) and once at night (19:00 - 22:00), totalling 30 survey
days. Surveys consisted of active search by two observers, one
at each side of the transect, in a 2-m strip from the center of
the transect (total sampling area of 1,000 m2), from the ground
up to 3 m high in the vegetation. All amphibians found were
captured, photographed and released.
The sampling of orchid bees was carried out using
homemade traps installed every 50 m (at 0, 50, 100, 150,
200, and 250 m along the transect), totalling six traps per
plot. e traps consisted of 2-L transparent plastic bottles
containing aromatic baits (Ferreira et al. 2013). e bottom
part of each bottle was lled with an odorless detergent to
trap the bees. Each alternating trap contained a bait made
of cotton soaked with one of two complementary attractants
(eucalyptus essential oil or clove essential oil). ese attractants
are commonly used to attract male orchid bees (Opedal et al.
2020). e traps were suspended 1.5 m above the ground in
shady sites, alternating the left and right side of the transect,
approximately 1 m from its central line, and were checked
every 24 hours between 07:00 and 13:00 for three consecutive
days. We made sure to provision the traps with a fresh amount
of attractant each time they were checked. e collected bees
were preserved in 70% ethanol to be later identied in the
laboratory. e material was deposited in the invertebrate
collection of Instituto Nacional de Biodiversidad – INABIO.
Dung beetles were sampled using pitfall traps with two
types of bait: mixed human feces and decomposed meat. Two
pitfall traps, each with one type of bait, were placed every
50 m, at 0, 50, 100, 150, 200, and 250 m along the central
line of the transect in each plot. e traps were checked after
24 and 48 hours, totalling three sampling days per plot.
Trapped beetles were collected and preserved in 70% ethanol.
Specimens were identied in the laboratory by using specic
dichotomous keys (Génier 1996; Chamorro et al. 2018).
e material was deposited in the invertebrate collection of
Instituto Nacional de Biodiversidad – INABIO.
Raw species data is available in the SINMBIO dataset at
the Ecuadorian National Biodiversity database (https://bndb.
sisbioecuador.bio/bndb/collections/index.php).
Figure 1. Location of the study area in northeastern Ecuador (red dot on the smaller map). Forest/Non Forest classication used to calculated landscape metrics is
indicated. See Table S1 in the Supplementary Matetial for the detailed landscape description. This gure is in color in the electronic version.
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Calculation of landscape metrics
We used one fragmentation index and nine landscape
conguration metrics as indicators of the degree of habitat
loss and fragmentation. For that, we generated a forest/non-
forest land cover layer combining three sources of information:
1) a land use map of the Sigtierras project - MAGAP (www.
sigtierras.gob.ec) for the municipalities of Shushundi, Joya
de los Sachas and Orellana produced from mosaics of aerial
photographs taken between 2010 and 2013 (at 1:25.000);
2) information on human land uses obtained from high-
resolution images in Google Earth of 2014; and 3) global forest
change maps for 2000-2017 (Hansen et al. 2013).
First, we updated the Sigtierras - MAGAP 2010-2013
map using information on anthropogenic land use obtained
from on-screen scanning techniques applied to high resolution
2014 Google Earth images. Human land-use areas larger than
1 ha were digitized to maintain the original spatial scale of
the Sigtierras cartography and the 30 m x 30 m resolution
from the global forest-change maps. Secondly, we combined
this new layer with the canopy-cover percentage for the year
2000 (i.e., percentage of larger trees higher than 5 m in each
pixel) and the forest loss for 2000-2017 from the global forest-
change map (Hansen et al. 2013). irdly, we classied pixels
as forest (when they had over 80% tree cover until 2000) or
non-forest. e estimated forest area for 2000 was updated
according to the deforested areas between 2001 and 2017 as
well as the human land-use areas obtained from the previously
updated and rasterized map of the Sigtierras-MAGAP project.
Our nal raster was thus a binary layer of forest cover with
pixels classied either as forest or non-forest.
We used this binary layer as input to calculate a
fragmentation index (hereafter fragindex; Butler et al. 2014).
e fragindex is the average value of three metrics: percentage
of intervened areas, i.e., the relative amount of non-forest
cover in each cell; percentage of edge, i.e., the relative amount
of forest with borders adjacent to anthropogenic matrices; and
interspersion, a metric that measures isolation or clumping
of forested areas in each cell. is combination of metrics
allows the estimation and analysis of fragmentation values at
the regional scale (Butler et al. 2004). is index ranges from
0 to 100, where 0 corresponds to cells with continuous forest
and 100 correspond to cells without forest. We applied the
fragindex to 1-km2 cells. Single fragmentation metrics were
associated with each sampling plot through the 1- km2 cells
in which the plots were embedded. Landscape patterns can be
measured at patch, class, or landscape level. We used the class
level, which is a unit between patch and mosaic in landscape
ecology (Wang et al. 2014). We selected landscape units of
1 km x 1 km as adequate for the interpretation of class-level
landscape metrics (Long et al. 2010). e fragindex calculation
and forest cover maps were done using the software Qgis v
2.18.14 (QGIS Development Team 2021).
In addition to the fragindex, we selected nine class-
level landscape metrics based on their relevance for each
taxonomic group (Table 1), as they indicate various aspects
of the landscape conguration, such as area, shape, core,
connectivity, and edges. Metrics were obtained using the
function “classStats” of the R package SDMTools (VanDerWal
et al. 2014), which is based on the FRAGSTAT software
(McGarigal et al. 2012). e R codes are available at https://
github.com/gamamo/FragEcuador.git.
Data analysis
We used the landscape metrics (Table 1) as covariates in
logistic regression models to determine their relative eect
on assemblage pattern and species occurrence. Each of the
15 plots was used as an independent observation unit in the
analysis.
Species-level analysis
To reduce redundancy in the covariates for the logistic
regression models, we pre-selected landscape metrics of
relevance for each taxonomic group by analyzing the
Spearmans Rho correlation between each landscape metric
(Supplementary Material, Figure S1) and by asking experts
in each taxonomic group to list the variables to which
assemblages were expected to respond. e set of landscape
metrics dier for each taxonomic group (Table 1).
To quantify the performance of each landscape metric
in explaining the probability of species occurrence (species-
level approach), logistic regression models of the LASSO
(Least Absolute Shrinkage and Selection Operator) family of
penalized models were implemented. From the pre-selected
set of variables for each assemblage, LASSO models select
covariates as part of the parameter estimation process. e
LASSO model tuning parameter is selected via cross-validation
with the deviance and related to the penalty of the model
(Bühlmann and Geer 2011). e higher the tuning parameter,
the more covariates are left out of the models. e adjustment
of the logistic regression models of the LASSO family requires
both presence and absence data. us, for each species we
simulated the same number of pseudo-absences as presences
to equal weighting presences and absences (Barbet-Massin et
al. 2012). LASSO models were limited to species observed in
at least ve plots, following recommendation of a minimum
of nine observations for LASSO logistic models (i.e., ve
occurrences and ve simulated pseudo-absences; Friedman
et al. 2010). LASSO logistic models were performed using
functions from the R package glmnet (Friedman et al. 2010).
The effect of each landscape metric on each species
probability of occurrence (i.e., the odds ratio) was used to
interpret the logistic models. e eect was dened as the
transformation of the odds ratio of every single selected
metric (Supplementary Material, Table S2). As odds ratios
are always positive, odds values need to be transformed to
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ensure the comparison between negative and positive eects.
Odds ratios higher than 1 indicate a relative positive eect on
the probability of occurrence, i.e., the probability of species
occurrence increases as a given metric increases in one unit.
In this case, we calculated the eect as odds ratio - 1. Odds
ratios lower than 1 indicate a relative negative eect on the
probability of occurrence, i.e., the probability of species
occurrence decreases as a given landscape metric increases
in one unit. In this case, the eect was calculated as 1/odds
ratio - 1.
To detect spatial autocorrelation, we performed Moran’s
analysis with the species richness of each taxonomic group. We
obtained values close to 0 for all taxonomic groups, indicating
the absence of spatial autocorrelation in species composition.
Assemblage-level analysis
To evaluate the hierarchical importance of landscape
metrics in species assemblages, we used distance-based
multivariate regression trees (MRT) (De’Ath 2002). MRTs
are built by repeatedly splitting sampling plots in two sets.
Table 1. Description of class-level landscape metrics (McGarigal et al. 2012) used to evaluate the occurrence of birds, amphibians, orchid bees and dung beetles in
forest fragments in the northern Ecuadorian Amazon. Ten metrics were selected based on their relevance to each taxonomic group according to literature review and
expert knowledge on each group. Metrics that were relevant for each taxonomic group and retained in the modelling process are indicated. The direction of the eects
(i.e., positive or negative) on habitat loss and fragmentation when these landscape metrics increase in one unit are shown in a separate column. Class-level metrics are
calculated for 1-km2 cells containing the sampling plots.
Metrics Type
(Wang et al. 2014) Abbreviation Description Unit
Taxonomic groups
for which the
metric was relevant
Eect
direction
Proportion of
Landscape
AREA/EDGE/
DENSITY prop.land
The proportion of the total landscape represented
by forest cover. It corresponds to the sum of
the areas of all forest patches, divided by total
landscape area.
Proportion
Amphibians,
orchid bees,
dung beetles
+
Landscape
Shape Index
AREA/EDGE/
DENSITY land.shape
Measures the ratio between forest perimeter and
forest area for each landscape. Higher values of the
index correspond to landscapes that are mostly
covered by forest
Unitless
Amphibian,
orchid bees,
birds
+
Largest Patch
Index
AREA/EDGE/
DENSITY largest.patch
Quanties the percentage of total landscape area
composed by the largest forest patch. Higher values
represent landscapes with an entire patch of forest.
Percent Dung beetles +
Minimum
Patch Area
AREA/EDGE/
DENSITY min.patch.area
Calculates the area of the smallest forest patch
relative to the combined area of patches in the
landscape.
Amphibians,
orchid bees +
Mean Patch
Area
AREA/EDGE/
DENSITY mean.patch.area
Measures the average area of the forest patches
in the landscape. Smaller values indicated more
fragmented landscapes.
Amphibian,
orchid bees,
birds,
dung beetles
+
Mean Shape
Index SHAPE mean.shape
Measures the average perimeter-to-area ratio for
a patch. Low values indicate that all patches are
square
Unitless Orchid bees,
birds +
Landscape
Division Index
CONTAGION/
INTERSPERSION land.division Probability that two randomly chosen pixels in the
landscape are not situated in the same forest patch. Proportion –
Proportion
of Like
Adjacencies
CONTAGION/
INTERSPERSION prop.like.adj
It shows the frequency with which dierent pairs
of patch types appear side-by-side on the map.
Measures the degree of aggregation of patch types.
Proportion
Amphibians,
orchid bees,
birds
+
Proportion
of Core
Landscape
COREAREA prop.land.core
Percentage of the landscape comprised within a
patch beyond some specied edge distance or
buer width. Proportional landscape core is equal to
0 when no core is found in the area and approaches
1 when proportion increases.
Proportion
Amphibians,
orchid bees,
birds,
dung beetles
+
FragIndex fragindex
Measures the magnitude of fragmentation.
Combination of three metrics: proportion of
intervened areas, percentage of edge and
interspersion.
Proportion
Amphibians,
orchid bees,
birds,
dung beetles
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At each split, MRT tries to minimize species dissimilarities
between plots when separating plots in two sets. We calculated
dissimilarities using the Bray-Curtis index for presence-
absence data including all the species of each taxonomic group
using the R package vegan (Oksanen et al. 2018). We used
cross-validation to select the MRT tree with the smallest error
(De’Ath 2002). e explained variation of MRT is given by
the residual error of the overall tree. MRTs were calculated
using the functions of the R package mvpart (erneau and
Atkinson 2013).
RESULTS
In birds, 59 out of 138 species (42.5%) were sighted
only once and no species was found in all plots. Psarocolius
angustifrons was the most widespread species. In amphibians,
14 out of 46 species (30.5%) were detected only once and
no species was found in all plots. e most frequent species
was Pristimantis lanthanites, occurring in 12 plots. For orchid
bees, Euglossa intersecta was the only species found in all plots.
In contrast, 12 of 26 species (46.2%) were found only once.
Of 42 species of dung beetles, ve were found only once, and
Deltochium crenulipes was the only species present in all plots.
Habitat loss and fragmentation eects at species-
level
All chosen landscape metrics had some eect on the
probability of individual species presence (Figure 2), albeit
with dierent magnitudes (high, medium, and low). Birds
responded positively to the increment in overall perimeter/
area ratio (land.shape metric) and of the forest patches (mean.
shape metric). Six species also responded positively to the
increment in forest patch area, although two seemed to
benet from the decrease in forest cover (land.prop metric).
Among amphibians, 70% of the species responded positively
to the increment in the min.patch.area metric. Four of these
responded positively to the increment in overall perimeter/
area ratio (land.shape metric). Only Pristimantis lanthanites
responded positively to the fragindex. Similar to birds,
orchid bees responded positively to the increment in overall
perimeter/area ratio (land.shape metric) and of the forest
patches (mean.shape metric). A single species had a positive
response to the fragindex. Most dung beetle species (72%)
responded positively to the increment in the mean area of
forest patches (mean.patch.area metric). In this group, 40%
of the species showed a positive response to the fragindex, a
Figure 2. Eect of landscape metrics on the probability of occurrence of species represented through transformed odds ratio. The magnitude of the eect of each
landscape metric was classied as high, medium, or low based on the odds ratio transformed values (Table S2). Odds higher than 1 (positive eect, increase in the
probability of occurrence) are represented by upside triangles; odds between 0 and 1 (negative eect, decrease in the probability of occurrence) are represented by
downside triangles. Neutral eects are indicated by the absence of symbols. The magnitude of the eect is indicated by the size of the symbol (the larger the symbol, the
higher the eect) and by the color (higher eects are shown in black, medium eects in dark gray and lower eects in gray). See Table 1 for the description of the variables.
MOULATLET et al. Eect of habitat loss and fragmentation in Ecuadorian Amazonia
240 VOL. 513 2021: 234  243
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number higher than for birds (10%), amphibians (10%), and
orchid bees (14%).
Habitat loss and fragmentation eects at
assemblage-level
Multivariate distance-based regression trees (Figure 3)
showed that the composition of bird assemblages was mainly
separated by prop.like.adj, which indicates the degree of
aggregation of forest patches within the landscape (MRT
residual error = 0.71). For amphibians, land.division, which
measures the degree of division of forest patches, caused
the main split in the MRT, followed by prop.like.adj and
the fragindex (MRT residual error = 0.56). For orchid bees,
mean.shape (i.e. perimeter-to-area ratio for a patch) explained
about 20% of the variation of MRT, followed by prop.
land (proportion of forest cover) and prop.like.adj (MRT
residual error = 0.61). For dung beetles, prop.like.adj was the
metric that caused the main split in the composition of the
assemblage (MRT residual error = 0.65).
DISCUSSION
Our results revealed that over 80% of birds, amphibians,
or orchid bee species were negatively aected by habitat loss
and fragmentation, with a lower proportion for dung beetles
(60%). More vagile taxonomic groups, such as birds were
more aected than the invertebrate groups, which can make
better use of the adjacent matrix (Filgueiras et al. 2015).
However, despite the dierences among taxonomic groups,
our results indicate that the landscape metrics related to the
shape and area of forest patches determined the magnitude and
direction of the eect on species occurrences and assemblage
composition.
Species-level responses
Some bird species were negatively aected by decreasing
shape complexity of forest patches, suggesting that they
may benet from a potential variety of resources available
at forest edges. The probability of occurrence of those
species increased in areas with high values for mean.shape
and land.shape, suggesting that there is a complex trade-o
between the occupation of available disturbed areas and their
ecological requirement of continuous forests. e occupation
of disturbed areas depends on the type of matrix, as some
matrices can provide resources for some species (Ewers and
Didham 2006). Square forest patches (with low values of
mean.shape and land.shape) are common in Amazonian
landscapes where dynamic agricultural activities predominate
with extensive road development (Rosa et al. 2017). e
increase of road openings in the study area may be specially
harmful to local bird populations.
Orchid bees were positively affected by the shape
complexity of forest patches (mean.shape and land.shape),
indicating that fragments of complex shape may provide more
resources and refuges. Orchid bees can be sensitive to forest
edges in Amazonian landscapes (Nemésio and Silveira 2010;
Storck-Tonon et al. 2013), but there is still a lack of consensus
regarding their ecological responses (Brosi et al. 2008). Only
two species in our study seemed to benet from diminishing
forest cover (metric prop.land). e probability of occurrence
of Euglossa intersecta decreased with increasing forest
cover and areas with high fragmentation values (fragindex)
Figure 3. Eects of landscape metrics on species composition. The variables with higher importance value in explaining dierences in species composition are
hierarchically indicated at the upper nodes of each regression tree. The values of each variable used to separate communities are shown in front of variable names.
Each tree node indicates the number of plots (n) that share similar species composition based on Bray-Curtis similarity index.
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241 VOL. 513 2021: 234  243
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positively aected the occurrence of Exaerete smaragdina.
Euglossa intersecta occurred in all plots, while E. smaragdina
occurred only in plots with high or low, but not intermediate
fragindex values. ese bees most likely use matrix habitat as
steppingstones when moving between forest areas. So, with the
current landscape conguration in our study area, orchid bees
seem to use forest edges and move across non-forested habitats,
as observed in other parts of Amazonia (Rosa et al. 2015).
e probability of occurrence of some amphibian species
signicantly decreased in areas with lower edge density (land.
shape), suggesting low tolerance of amphibians to habitat
loss and fragmentation, as was also reported by Schneider-
Maunoury et al. (2016). ree species were particularly
sensitive to fragmentation (Oreobates quixensis, Ameerga
bilinguis, and Pristimantis variabilis). Amphibians may be
less vagile than the other studied organisms because of their
dependence on humidity and micro-habitats within forests,
which would explain why the positive response to the
increment of metrics related to forest area (i.e., min.patch.
area and mean.patch.area), contrary to birds or orchid bees,
whose responded more to shape metrics.
Dung beetles were the group with higher proportion
of species that responded positively to the increment in
fragmentation (fragindex), suggesting that habitat loss and
fragmentation is not as detrimental for dung beetles as for
the other taxonomic groups. Dung-beetle assemblages may
not respond immediately to modications in land use. More
commonly, rare species tend to disappear from impacted
areas, while several species may persist in the landscape after
a disturbance, such as a road opening (Carpio et al. 2009).
Species responses were predominantly negative in
landscapes with smaller forest patches of homogeneous shape
and with less forest coverage (metric prop.land). Only a few
species responded positively to the increment in the degree
of fragmentation. Changes in landscape structure driven by
deforestation determined species occurrence. However, our
study design does not allow to discern whether the negative
responses are primarily due to the amount of forest cover or
how the forest cover is subdivided. Only species that were
found in ve or more plots were included in our explanatory
species-specic models. By excluding rare species, we may
have biased our results towards those species that are, to some
extent, more resilient to habitat disturbance. Given that our
study area has been intensively modied in the last decades,
it is likely that species with higher frequencies of occurrence
are those which managed to persist in the long-term due to
environmental ltering (Ewers and Didham 2006). In any
case, the predominantly negative responses to the changes
in landscape conguration in our study area indicate overall
detrimental eects on the surveyed taxonomic groups.
Assemblage-level responses
Species composition of birds, amphibians and dung
beetles were significantly determined by metrics related
to landscape connectivity. Species that occur in areas with
lower connectivity are probably those that could use matrix
habitats (Antongiovanni and Metzger 2005). Specic traits,
like tolerance to desiccation (Watling and Braga 2015)
could explain why some amphibian species would benet
by making use of matrix habitats. Species composition of
orchid bees diered mostly in plots located in landscapes
with contrasting shapes, which may be due to the capacity
of some species to make use of edge habitat. Dierences in
species composition indicate that deforestation has altered the
landscape conguration to a detectable level that determines
how species assemblages are structured, a process that could
increase overtime. In this case, without the inuence of areas
that serve as population sources, species composition may
get more homogeneous until assemblages are dominated by
persistent species that are able to use matrix habitats.
CONCLUSIONS
We showed that species individual responses can be
aected by habitat loss and fragmentation and how species
composition can dier along fragmentation gradients for
birds, amphibians, orchid bees, and dung beetles. At species-
level, the eect was predominantly negative, with a decrease
in species occurrence probability, although some species
presented positive responses to landscape fragmentation. At
the community level, landscape metrics determined the main
dierentiation in species composition. e negative response
of most species to habitat fragmentation indicates that eorts
to conserve continuous forests, or at least to maintain low
levels of fragmentation, must be increased. Monitoring
species responses, as disposed in the Agenda Nacional de
Biodiversidad de Ecuador, is a fundamental part of the
conservation actions. Changes in landscape conguration in
Ecuadorian Amazonia should be minimized to diminish the
negative eects of habitat loss and fragmentation on species
occurrences and assemblage composition.
ACKNOWLEDGMENTS
We thank Ana Caluña, Jesús Toro, Esteban Calvache
Palacios, Olger Licuy, Salomón Ramirez, Don Mauricio,
Augusto Pauta, Otorino Coquinche, Blanca Andi, Pakiri,
Marcelo, Javier Yánez, Juan Neira, Jorge Celi, Alexandra
Durán, Mario Yánez, Diego Inclán and Lizbeth Andi for their
support in this study. We are thankful to the INABIO for legal,
technical, and institutional support. Collection permits were
issued and granted by Ministério del Ambiente de Ecuador
(001-19-IC-FAU-DNB/MA). is study was funded by the
consortium KFW - INABIO (grant to HMOA).
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ASSOCIATE EDITOR: Paulo D. Bobrowiec
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SUPPLEMENTARY MATERIAL (only available in the electronic version)
Moulatlet et al. Multi-taxa ecological responses to habitat loss and fragmentation in western Amazonia as revealed by
RAPELD biodiversity surveys
Table S1. Description of the landscape around each of 15 RAPELD sampling plots in the northern Ecuadorian Amazon and the associated values of ten landscape
conguration metrics of the 1-km2 cell where plots are inserted. Coordinates are in WGS84 datum. See Table 1 for landscape metrics description and Figure S2 for the
landscape details around each plot.
Plot
code Landscape description Latitude Longitude prop.
land land.shape largest.
patch
min.
patch.
area
mean.
patch.
area
mean.
shape
land.
division
prop.like.
adj
prop.
land.
core
fragindex
1
Adjacent to a cocoa
plantation. Flood prone
area. Dominated by
herbaceous plants and
palm trees
-0.31555 -76.6044 0.1559 3.316456 0.074 3300 31180 1.535814 0.991657 0.84497 0.1066 40.183
2
Adjacent to a pasture.
Primary forest with edge
inuence
-0.32549 -76.6013 0.5087 2.181818 0.4386 12000 127175 1.506375 0.805788 0.940492 0.4479 20.387
3Primary forest 2 km far
from the closest road -0.33245 -76.6054 0.8522 1.362162 0.8522 852200 852200 1.362162 0.273755 0.97086 0.8025 5.837
4Primary forest 2 km far
from the closest road -0.34051 -76.6025 1 1 1 1000000 1000000 1 0 1 1 0
5
Small primary forest patch
adjacent to a banana
plantation
-0.40798 -76.6296 0.844 1.918478 0.844 844000 844000 1.918478 0.287664 0.959032 0.7734 7.273
6
Primary forest close to
Limoncocha lagoon,
within the Limoncocha
reserve
-0.39762 -76.6176 0.5077 2.06993 0.4618 1800 126925 1.309357 0.785016 0.943349 0.4501 19.7
7Primary forest; adjacent to
a cocoa plantation -0.39291 -76.6333 1 1 1 1000000 1000000 1 0 1 1 0
8
Adjacent close to a
channeled river for
aquaculture (tilapias) and
a cocoa plantation
-0.38145 -76.6421 0.1831 2.232558 0.1317 2700 36620 1.19679 0.981435 0.900363 0.147 34.027
9Adjacent to a cocoa
plantation -0.36781 -76.5956 0.4231 3.099237 0.3757 12000 141033.3 1.87233 0.857452 0.908435 0.3427 25.21
10 Adjacent to a cocoa
plantation -0.36627 -76.6129 0.8482 1.578378 0.8482 848200 848200 1.578378 0.280557 0.966157 0.7902 6.51
11
Primary forest on the
northern side of the
Limoncocha lagoon
-0.37476 -76.6105 0.562991 2.766667 0.558462 4500 279750 1.942713 0.688099 0.928479 0.47907 19.937
12
Near to the road. Primary
forest with signs of
disturbance
-0.4164 -76.4902 0.6762 2.048485 0.6762 676200 676200 2.048485 0.542754 0.951234 0.6096 13.913
13
Adjacent to a farm with
pasture, cattle, cocoa
and African oil palm tree
plantation
-0.43865 -76.4782 0.8023 1.555556 0.8023 802300 802300 1.555556 0.356315 0.965699 0.7467 8.173
14 Adjacent to an African oil
palm tree plantation. -0.42865 -76.4535 0.816 1.80663 0.816 816000 816000 1.80663 0.334144 0.960714 0.7517 8.257
15 Primary forest dominated
by palm trees -0.43777 -76.4492 0.6868 1.608434 0.6868 686800 686800 1.608434 0.528306 0.961865 0.6338 12.257
MOULATLET et al. Eect of habitat loss and fragmentation in Ecuadorian Amazonia
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Table S2. Occurrence frequency of species of four taxonomic groups in 15 RAPELD plots in the northern Ecuadorian Amazon and transformed odds ratio from explanatory
logistic models (species-level responses) for associated landscape metrics (calculated for 1-km2 cells) used as co-variable. Blank cells indicate the variable was not used
in the specie’s models. When the odds ratio was higher than 1, odd ratio -1 transformation was applied; When the odds ratio was between 0 and 1, 1/odd ratio - 1
transformation was applied (see Material and Methods). See Table 1 for variable descriptions. Freq = frequency (number of plots where each species was recorded).
Freq prop.
land
land.
shape
largest.
patch
min.patch.
area
mean.patch.
area
mean.
shape
land.
division
prop.
like.adj
prop.
land.core fragindex
Birds
Psarocolius angustifrons 14 1.05 2.54 1.16 1.15 994.15
Psarocolius decumanus 13 1.06
Campylorhynchus turdinus 12 1.05
Capito auratus 12 1.03
Cacicus cela 11 1.19 1.10
Xiphorhynchus guttatus 11 1.53 1.05 0.81
Momotus momota 10 1.18
Crypturellus undulatus 9 1.16
Cyanocorax violaceus 9 1.08
Aratinga weddellii 7 1.01 1.02
Leptotila rufaxilla 7 0.81
Brotegoris cyanoptera 6 1.83
Melanerpes cruentatus 6 1.33 1.08 0.98
Piaya cayana 6 1.08 1.04
Pteroglossus pluricinctus 6 1.19 1.03
Campephilus melanoleucos 5 1.50 1.15 3.04
Glaucidium brasilianum 5 1.18
Henicorhina leucosticta 5 1.21 1.03 1.01
Megarynchus pitangua 5 1.05
Orchid bees
Euglossa intersecta 15 0.98 1.04 1.13
Euglossa ammea 12 1.15 1.02
Exaerete smaragdina 10 1.45 1.22 3.71
Eulaema cingulata 7 1.39
Euglossa ignita 6 1.53 0.89 1.11
Eulaema bombiformis 6 1.20 1.03
Euglossa viridifrons 5 1.08 1.09
Amphibians
Pristimantis lanthanites 12 2.10 6.04 0.57 1.14 979.36
Rhinella margaritifera 11 1.15
Oreobates quixensis 10 1.99 1.74 1.69 0.93
Pristimantis kichwarum 9 1.07 1.25
Ameerega bilinguis 8 1.67 0.97
Pristimantis variabilis 8 0.92 1.09 1.71 0.99
Pristimantis croceoinguinis 7 0.27
Adenomera hylaedactyla 6 1.28
Dendropsophus parviceps 5
Pristimantis brevicrus 5 1.07
Pristimantis conspicillatus 5 0.95 3.27 1.30 1.12
MOULATLET et al. Eect of habitat loss and fragmentation in Ecuadorian Amazonia
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VOL. 513 2021: 234  243
Freq prop.
land
land.
shape
largest.
patch
min.patch.
area
mean.patch.
area
mean.
shape
land.
division
prop.
like.adj
prop.
land.core fragindex
Dung beetles
Deltochilum crenulipes 15 1.00
Coprophanaeus telamon 14 0.96 1.42
Eurysternus caribaeus 13 0.79 1.13 1.40
Onthophagus rubrescens 13 0.84 1.05 1.96
Canthon proseni 12 1.54 4.49
Deltochilum batesi 12 1.52 4.52
Deltochilum orbignyi amazonicum 12 1.10 1.24
Onthophagus lojanus 12 1.04 1.30 8.73
Sylvicanthon bridarolli 12 1.54 4.49
Canthon luteicollis 11 1.19 1.42 0.91 7.20
Deltochilum carinatum 11 1.34 0.79
Eurysternus plebejus 11 1.32 0.79
Phanaeus chalcomelas 11 1.33 1.20 0.77
Dichotomius podalirius 9 1.54 5.00
Onthophagus osculatii 9 1.83 7.07
Deltochilum barbipes 8 2.03 0.91
Dichotomius mamillatus 8 2.34 0.90 1.10
Dichotomius ohausi 8 2.00 0.91
Eurysternus lanuginosus 7 0.93 1.15
Uroxys sp. 7 1.07
Canthidium cupreum 6 0.77 0.95
Dichotomius sp. 5 0.95 1.49
Table S2. Continued
MOULATLET et al. Eect of habitat loss and fragmentation in Ecuadorian Amazonia
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AMAZONICA
VOL. 513 2021: 234  243
Figure S1. Spearman correlations between landscape metrics for 15 1-km2 landscape units in the northern Ecuadorian Amazon. See Table 1 for a detailed variable
description.
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