Analysing and mapping species range dynamics using occupancy models

Kéry, Marc; Guillera‐Arroita, Gurutzeta; Lahoz‐Monfort, José J.

doi:10.1111/jbi.12087

Cited by 119 publications

(125 citation statements)

References 49 publications

(65 reference statements)

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“…6). In line with previous studies (De C á ceres and Brotons 2012, Rodhouse et al 2012, K é ry et al 2013, we argue that monitoring data may also be cost-eff ectively collected and used in species distribution models to document the spatial distribution of the species. Th e AUC was only weakly sensitive to sample size and levelled off at smaller sample size in high-prevalence species (MSS ϭ 115 Ϯ 14, MSC ϭ 0.69% Ϯ 0.09%) than in low-prevalence species (MSS ϭ 183 Ϯ 15, MSC ϭ 1.10% Ϯ 0.09%).…”

Section: Discussionsupporting

confidence: 86%

Optimising long‐term monitoring projects for species distribution modelling: how atlas data may help

Aizpurua

Paquet²,

Brotons

et al. 2014

Ecography

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29how they change over time may provide key information to guide eff ective landscape and conservation planning. Dynamic species distribution mapping may, therefore, be considered as an essential component of a biodiversity monitoring project (Brotons et al. 2007(Brotons et al. , K é ry et al. 2013. In any monitoring project, sampling units are, however, sparsely distributed over the region of interest, which is inconvenient for a straightforward mapping of species distributions.Species distribution modelling is an increasingly used technique (Rodr í guez et al. 2007) that can produce distribution maps based on monitoring data (Brotons et al. 2006). With these models, environmental variables describing the habitat conditions in the sampling units are related to records of species presence. Th ese models are used to predict the species distribution beyond the sampling units in areas where species occurrence is unknown (Ara ú jo and Guisan 2006, Elith et al. 2010. Th e use of models to predict species distributions is of key signifi cance for biodiversity conservation (Guisan et al. 2013). Among several applications, models Long-term biodiversity monitoring data are mainly used to estimate changes in species occupancy or abundance over time, but they may also be incorporated into predictive models to document species distributions in space. Although changes in occupancy or abundance may be estimated from a relatively limited number of sampling units, small sample size may lead to inaccurate spatial models and maps of predicted species distributions. We provide a methodological approach to estimate the minimum sample size needed in monitoring projects to produce accurate species distribution models and maps. Th e method assumes that monitoring data are not yet available when sampling strategies are to be designed and is based on external distribution data from atlas projects. Atlas data are typically collected in a large number of sampling units during a restricted timeframe and are often similar in nature to the information gathered from long-term monitoring projects. Th e large number of sampling units in atlas projects makes it possible to simulate a broad gradient of sample sizes in monitoring data and to examine how the number of sampling units infl uences the accuracy of the models. We apply the method to several bird species using data from a regional breeding bird atlas. We explore the eff ect of prevalence, range size and habitat specialization of the species on the sample size needed to generate accurate models. Model accuracy is sensitive to particularly small sample sizes and levels off beyond a suffi ciently large number of sampling units that varies among species depending mainly on their prevalence. Th e integration of spatial modelling techniques into monitoring projects is a cost-eff ective approach as it off ers the possibility to estimate the dynamics of species distributions in space and over time. We believe our innovative method will help in the sampling design of future monitoring projects ai...

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Section: Discussionsupporting

confidence: 86%

Optimising long‐term monitoring projects for species distribution modelling: how atlas data may help

Aizpurua

Paquet²,

Brotons

et al. 2014

Ecography

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“…In addition, the introduction events of these NIS are generally still too recent to properly assess the phase (expansion or persistence) they are experiencing and therefore the corresponding model ('natural fluctuation' or 'boom and bust'): invasion kinetics is often a long-lasting process and, in most cases, only hypotheses can be drawn . Predicting the effects of invasive NIS on native ecosystems (Strayer 2012) and applying occupancy models (Kéry et al 2013) to analyse their kinetics require the sustained collection of series of data by targeted long-term studies, chronosequences, repeated mapping and underwater surveys to gather quantitative information. Only from the spatial patterns of NIS spread we will be able to predicate ecological patterns, which are crucial for setting efficient management actions (Galil et al 2014).…”

Section: Discussionmentioning

confidence: 99%

A tale of two invaders: divergent spreading kinetics of the alien green algae Caulerpa taxifolia and Caulerpa cylindracea

et al. 2015

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International audienceThe two alien green algae Caulerpa taxifolia and Caulerpa cylindracea (formerly Caulerpa racemosa var. cylindracea) are among the most notorious and threatening invasive species in the Mediterranean Sea. From the beginning of their introduction, C. taxifolia aroused a great concern due to its initial exponential spread and impacts on native ecosystems, whilst C. cylindracea received lower attention. In this paper, the distribution of the two aliens over the last 30 years in the Italian side of the Ligurian Sea (NW Mediterranean Sea) is reviewed and the kinetics of their spreading is compared. We combined available data on habitat occupancy with data on substratum cover obtained during underwater surveys to compute the average annual spreading rates for both aliens. C. taxifolia had an impressive expansion phase from 1984 to 2000 but then, its dispersal rate showed lower than that predicted and the species did not persist in areas formerly colonized. Today, abundance of this species is strongly declined as it disappeared from most of the attained areas. On the contrary, C. cylindracea exhibited an impressive and constant expansion from the beginning of its first appearance in the Ligurian Sea and, today, it is still increasing its range and habitat occupancy. Its abundance results 1.5-times greater than that reached by C. taxifolia during the period of its maximum expansion. The divergent kinetics of spreading of the two aliens prevents any possibility of generalization of the future behaviour of invasive species in the Mediterranean Sea: continuous and periodic surveys are thus mandatory to understand the kinetics of expansion and to define species-specific models

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“…Models that were within <2 ∆AIC were considered to have substantial support (Burnham & Anderson, ), and thus, these predictors were selected and used in the next step in a forward manner (e.g. Kéry, Guillera‐Arroita, & Lahoz‐Monfort, ). To prevent over fitting (Burnham & Anderson, ), we kept models with only one predictor per parameter, with the exception of one model which evaluated the additive effect of shrub and forest cover (shrub is a marginal habitat for the study species; Dunstone et al., ).…”

Section: Methodsmentioning

confidence: 99%

“…However, we assume that colonisation between seasons is primarily influenced by habitat configuration/quality variables, rather than human–predator relations. To explore the candidate model space, we worked on the structure for extinction probability followed by colonisation and then repeated the process vice versa (Kéry et al., ). A constant or null model was included in all candidate model sets.…”

Section: Methodsmentioning

confidence: 99%

A spatially integrated framework for assessing socioecological drivers of carnivore decline

Galvéz

Guillera‐Arroita

John

et al. 2018

Journal of Applied Ecology

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Habitat loss, fragmentation and degradation are key threats to the long‐term persistence of carnivores, which are also susceptible to direct persecution by people. Integrating natural and social science methods to examine how habitat configuration/quality and human–predator relations may interact in space and time to effect carnivore populations within human‐dominated landscapes will help prioritise conservation investment and action effectively.We propose a socioecological modelling framework to evaluate drivers of carnivore decline in landscapes where predators and people coexist. By collecting social and ecological data at the same spatial scale, candidate models can be used to quantify and tease apart the relative importance of different threats.We apply our methodological framework to an empirical case study, the threatened güiña (Leopardus guigna) in the temperate forest ecoregion of southern Chile, to illustrate its use. Existing literature suggests that the species is declining due to habitat loss, fragmentation and persecution in response to livestock predation. Data used in modelling were derived from four seasons of camera‐trap surveys, remote‐sensed images and household questionnaires.Occupancy dynamics were explained by habitat configuration/quality covariates rather than by human–predator relations. Güiñas can tolerate a high degree of habitat loss (>80% within a home range). They are primarily impacted by fragmentation and land subdivision (larger farms being divided into smaller ones). Ten per cent of surveyed farmers (N = 233) reported illegally killing the species over the past decade. Synthesis and applications. By integrating ecological and social data, collected at the same spatial scale, within a single modelling framework, our study demonstrates the value of an interdisciplinary approach to assessing the potential threats to a carnivore. It has allowed us to tease apart effectively the relative importance of different potential extinction pressures for the güiña (Leopardus guigna), make informed conservation recommendations and prioritise where future interventions should be targeted. We have identified that human‐dominated landscapes with large intensive farms can be of conservation value, as long as an appropriate network of habitat patches is maintained within the matrix. Conservation efforts to secure the long‐term persistence of the species should focus on reducing habitat fragmentation rather than human persecution.

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Analysing and mapping species range dynamics using occupancy models

Cited by 119 publications

References 49 publications

Optimising long‐term monitoring projects for species distribution modelling: how atlas data may help

Optimising long‐term monitoring projects for species distribution modelling: how atlas data may help

A tale of two invaders: divergent spreading kinetics of the alien green algae Caulerpa taxifolia and Caulerpa cylindracea

A spatially integrated framework for assessing socioecological drivers of carnivore decline

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