Gurutzeta Guillera-Arroita

Gurutzeta Guillera-Arroita
University of Melbourne | MSD · School of BioSciences

PhD Statistics, MSc Conservation Science, Engineer

About

90
Publications
51,926
Reads
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5,975
Citations
Citations since 2017
54 Research Items
5329 Citations
201720182019202020212022202302004006008001,0001,2001,400
201720182019202020212022202302004006008001,0001,2001,400
201720182019202020212022202302004006008001,0001,2001,400
201720182019202020212022202302004006008001,0001,2001,400

Publications

Publications (90)
Article
Full-text available
To assess whether flexible species distribution models that perform well at nearby testing locations still perform strongly when evaluated on spatially separated testing data. Australian Wet Tropics (AWT), Ontario, Canada (CAN), north‐east New South Wales, Australia (NSW), New Zealand (NZ), five countries of South America (SA), and Switzerland (SWI...
Article
The replacement of natural areas with forestry plantations is a worldwide expanding process with direct consequences for biodiversity and ecosystem functionality. In the Mediterranean region, Eucalyptus spp. plantations are widespread, forming monospecific landscapes that in Portugal dominate most of its forested areas. The reduction in the availab...
Article
Full-text available
Species distribution modeling (SDM) is widely used in ecology and conservation. Currently, the most available data for SDM are species presence‐only records (available through digital databases). There have been many studies comparing the performance of alternative algorithms for modeling presence‐only data. Among these, a 2006 paper from Elith and...
Article
Full-text available
The random forest (RF) algorithm is an ensemble of classification or regression trees and is widely used, including for species distribution modelling (SDM). Many researchers use implementations of RF in the R programming language with default parameters to analyse species presence-only data together with ‘background’ samples. However, there is goo...
Article
Open-access occurrence data are useful for studying spatial patterns of fungi, but often have quality issues. These include errors in taxonomy and geo-coordinates, and incomplete coverage across areas and taxonomic groups. We identify 15 quality issues that can lead to incorrect biogeographic inference, and develop a reproducible pipeline that flag...
Article
Predictions of species' current and future ranges are needed to effectively manage species under environmental change. Species ranges are typically estimated using correlative species distribution models (SDMs), which have been criticized for their static nature. In contrast, dynamic occupancy models (DOMs) explicitily describe temporal changes in...
Article
Full-text available
1. The establishment of new botanic gardens in tropical regions highlights a need for weed risk assessment tools suitable for tropical ecosystems. The relevance of plant traits for invasion into tropical rainforests has not been well studied. 2. Working in and around four botanic gardens in Indonesia where 590 alien species have been planted, we es...
Article
Line‐transect distance sampling is widely used to estimate population densities by using distances of observed targets from transect lines to model detectability. When the target taxa are high‐density, the frequent measuring of distances may make the method seem impractical. We present a method that improves the efficiency of distance sampling when...
Article
Full-text available
Species distribution models (SDMs) constitute the most common class of models across ecology, evolution and conservation. The advent of ready‐to‐use software packages and increasing availability of digital geoinformation have considerably assisted the application of SDMs in the past decade, greatly enabling their broader use for informing conservat...
Article
Full-text available
Accurately predicting species ranges is a primary goal of ecology. Demographic distribution models (DDMs), which correlate underlying vital rates (e.g. survival and reproduction) with environmental conditions, can potentially predict species ranges through time and space. However, tests of DDM accuracy across wide ranges of species' life histories...
Preprint
Full-text available
1. The Random Forest (RF) algorithm is an ensemble of classification or regression trees, and is a widely used and high-performing machine learning technique. It is increasingly used for species distribution modelling (SDM). Many researchers use implementations of RF in the R programming language with default parameters to analyse species presence-...
Article
Joint species distribution models (JSDMs) simultaneously model the distributions of multiple species, while accounting for residual co-occurrence patterns. Despite increasing adoption of JSDMs in the literature, the question of how to define and evaluate JSDM predictions has only begun to be explored. We define four different JSDM prediction types...
Article
Full-text available
Significance Forest restoration has become a global conservation priority, particularly in the tropics where a significant proportion of remaining forest ecosystems are degraded. To achieve ambitious restoration targets via limited conservation funds, areas that will deliver the greatest biodiversity value must be prioritized. Here, we combine airb...
Article
Full-text available
Aim The world's forested area has been declining, especially in developing countries. In contrast, forest plantations are increasing, particularly exotic Eucalyptus plantations, which cover nowadays over 20 million ha worldwide. This global landscape change affects native communities, especially those at higher trophic levels that are affected by b...
Article
Full-text available
Species distribution models (SDMs) constitute the most common class of models across ecology, evolution and conservation. The advent of ready-to-use software packages and increasing availability of digital geoinformation have considerably assisted the application of SDMs in the past decade, greatly enabling their broader use for informing conservat...
Article
Full-text available
As we sit in the vortex of the Covid‐19 outbreak, individual energies are focused on staying safe and juggling the personal, social and financial impacts of the pandemic and political responses to it. These impacts are profoundly re‐shaping our lives, with many commentators suggesting that ‘normality’ will be permanently redefined for all sectors o...
Article
Species distribution models (SDMs) are an emerging tool in the study of fungi, and their use is expanding across species and research topics. To summarise progress to date and to highlight important considerations for future users, we review 283 studies that apply SDMs to fungi. We found that macrofungi, lichens, and pathogenic microfungi are most...
Article
Full-text available
Predictive performance is important to many applications of species distribution models (SDMs). The SDM ‘ensemble’ approach, which combines predictions across different modelling methods, is believed to improve predictive performance, and is used in many recent SDM studies. Here, we aim to compare the predictive performance of ensemble species dist...
Article
Full-text available
Zero‐deforestation commitments seek to decouple agricultural production and forest loss to improve prospects for biodiversity. However, the effectiveness of methods designed to meet these commitments is poorly understood. In a highly fragmented tropical landscape dominated by oil palm, we tested the capacity for the High Carbon Stock (HCS) Approach...
Article
Full-text available
Knowing where species occur is fundamental to many ecological and environmental applications. Species distribution models (SDMs) are typically based on correlations between species occurrence data and environmental predictors, with ecological processes captured only implicitly. However, there is a growing interest in approaches that explicitly mode...
Article
Full-text available
Advancing technology represents an unprecedented opportunity to enhance our capacity to conserve the Earth's biodiversity. However, this great potential is failing to materialize and rarely endures. We contend that unleashing the power of technology for conservation requires an internationally coordinated strategy that connects the conservation com...
Article
Innovation has the potential to enable conservation science and practice to keep pace with the escalating threats to global biodiversity, but this potential will only be realized if such innovations are designed and developed to fulfill specific needs and solve well‐defined conservation problems. We propose that business‐world strategies for assess...
Article
Full-text available
With the expansion in the quantity and types of biodiversity data being collected, there is a need to find ways to combine these different sources to provide cohesive summaries of species' potential and realized distributions in space and time. Recently, model-based data integration has emerged as a means to achieve this by combining datasets in wa...
Article
Full-text available
Aim The idea of combining predictions from different models into an ensemble has gained considerable popularity in species distribution modelling, partly due to free and comprehensive software such as the R package BIOMOD. However, despite proliferation of ensemble models, we lack oversight of how and where they are used for modelling distributions...
Article
Full-text available
Multispecies occupancy models can estimate species richness from spatially replicated multispecies detection/non-detection survey data, while accounting for imperfect detection. A model extension using data augmentation allows inferring the total number of species in the community, including those completely missed by sampling (i.e., not detected i...
Article
Full-text available
Detecting trends in species’ distribution and abundance are essential for conserving threatened species, and depend upon effective monitoring programmes. Despite this, monitoring programmes are often designed without explicit consideration of their ability to deliver the information required by managers, such as their power to detect population cha...
Article
Full-text available
1.When applied to structured data, conventional random cross‐validation techniques can lead to underestimation of prediction error, and may result in inappropriate model selection. 2.We present the R package blockCV, a new toolbox for cross‐validation of species distribution modelling. Although it has been developed with species distribution modell...
Article
1.Joint species distribution models (JSDMs) account for biotic interactions and missing environmental predictors in correlative species distribution models. Several different JSDMs have been proposed in the literature, but the use of different or conflicting nomenclature and statistical notation potentially obscures similarities and differences amo...
Article
Full-text available
Detecting exotic plant species is essential for invasive species management. By accounting for factors likely to affect species’ detection rates (e.g. survey conditions, observer experience), detectability models can help choose search methods and allocate search effort. Integrating information on species’ traits can refine detectability models, an...
Data
Examples of used leaf photos for leaf area and leaf shape calculation of 25 detected exotic species. The photo ordered from smallest to the largest leaf shape (complexity) value. (TIF)
Data
Line transect distance sampling lay out. Black circles represent individuals of exotic species and dashed arrows show their perpendicular distance to the transect. Surveys were conducted from the border of the botanic gardens towards the native rainforest interior. Only detections within 10 m of the transect line were recorded. The number of transe...
Data
List of reference publications used for native species composition information data. (PDF)
Data
Map of sampling locations: Cibodas, Kuningan, Baturraden and Eka Karya Bali. (TIF)
Data
History plot of Markov chain Monte Carlo (MCMC) simulation based on the constructed detectability model. The plots demonstrate the converged chains in the model simulation for all variables (nodes) included (b0, bS, bS2, bH, bA, and bA2) (left part of the graph). The credible interval for all involved variables are not containing zero values except...
Data
R code script for Bayesian analysis of the tested detection model in this study. (PDF)
Preprint
Full-text available
When applied to structured data, conventional random cross-validation techniques can lead to underestimation of prediction error, and may result in inappropriate model selection. We present the R package blockCV , a new toolbox for cross-validation of species distribution modelling. The package can generate spatially or environmentally separated fo...
Preprint
The score test statistic using the observed information is easy to compute numerically. Its large sample distribution under the null hypothesis is well known and is equivalent to that of the score test based on the expected information, the likelihood-ratio test and the Wald test. However, several authors have noted that under the alternative this...
Article
In ecology, the true causal structure for a given problem is often not known, and several plausible models and thus model predictions exist. It has been claimed that using weighted averages of these models can reduce prediction error, as well as better reflect model selection uncertainty. These claims, however, are often demonstrated by isolated ex...
Article
Full-text available
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 wi...
Article
Full-text available
Carbon-based policies provide powerful opportunities to unite tropical forest conservation with climate change mitigation. However, their effectiveness in delivering biodiversity co-benefits is dependent on high levels of biodiversity being found in high carbon areas. Previous studies have focussed solely on the co-benefits associated with Reducing...
Article
1.Accurate knowledge of species occurrence is fundamental to a wide variety of ecological, evolutionary, and conservation applications. Assessing the presence or absence of species at sites is often complicated by imperfect detection, with different mechanisms potentially contributing to false negative and/or false positive errors at different samp...
Article
Full-text available
In a recent paper, Hutto (2016a) challenges the need to account for detectability when interpreting data from point counts. A number of issues with model-based approaches to deal with detectability are presented, and an alternative suggested: surveying an area around each point over which detectability is assumed certain. The article contains a num...
Article
Occupancy-detection models that account for imperfect detection have become widely used in many areas of ecology. As with any modelling exercise, it is important to assess whether the fitted model encapsulates the main sources of variation in the data, yet there have been few methods developed for occupancy-detection models that would allow practit...
Article
Species occupancy, the proportion of sites occupied by a species, is a state variable of interest in ecology. One challenge in its estimation is that detection is often imperfect in wildlife surveys. As a consequence, occupancy models that explicitly describe the observation process are becoming widely used in the discipline. These models require d...
Article
Full-text available
Ecological data often show temporal, spatial, hierarchical (random effects), or phylogenetic structure. Modern statistical approaches are increasingly accounting for such dependencies. However, when performing cross-validation, these structures are regularly ignored, resulting in serious underestimation of predictive error. One cause for the poor p...
Article
Camera-traps are increasingly used to survey threatened mammal species and are an important tool for estimating habitat occupancy. To date, cost-efficient occupancy survey effort allocation studies have focused on trade-offs between number of sample units (SUs) and sampling occasions, with simplistic accounts of associated costs which do not reflec...
Article
Conservation of endangered species increasingly envisages complex strategies that integrate captive and wild management actions. Management decisions in this context must be made in the face of uncertainty, often with limited capacity to collect information. Adaptive management (AM) combines management and monitoring, with the aim of updating knowl...
Article
Building useful models of species distributions requires attention to several important issues, one being imperfect detection of species. Data sets of species detections are likely to suffer from false absence records. Depending on the type of survey, false positive records can also be a problem. Disregarding these observation errors may lead to im...
Article
The deep ocean is the largest and least-explored ecosystem on Earth, and a uniquely energy-poor environment. The distribution, drivers and origins of deep-sea biodiversity remain unknown at global scales. Here we analyse a database of more than 165,000 distribution records of Ophiuroidea (brittle stars), a dominant component of sea-floor fauna, and...
Article
Full-text available
Environmental DNA (eDNA) sampling is prone to both false positive and false negative errors. We review statistical methods to account for such errors in the analysis of eDNA data, and use simulations to compare the performance of different modelling approaches. Our simulations illustrate that even low false positive rates can produce biased estimat...
Article
Full-text available
1.Applied ecologists continually advocate further research, under the assumption that obtaining more information will lead to better decisions. Value of information (VoI) analysis can be used to quantify how additional information may improve management outcomes: despite its potential, this method is still underused in environmental decision-making...
Article
Species distribution models (SDMs) are used to inform a range of ecological, biogeographical and conservation applications. However, users often underestimate the strong links between data type, model output and suitability for end-use. We synthesize current knowledge and provide a simple framework that summarizes how interactions between data type...
Article
AimEnvironmental impact assessments (EIAs) often involve establishing whether a species of concern is present at the site considered for development. When surveys falsely conclude that sites are unoccupied, species prevalence in the region is cumulatively reduced. We argue that setting an acceptable level of induced decline in species occurrence pr...
Article
Auto-logistic and related auto-models, implemented approximately as autocovariate regression, provide simple and direct modelling of spatial dependence. The autologistic model has been widely applied in ecology since Augustin, Mugglestone and Buckland (J. Appl. Ecol., 1996, 33, 339) analysed red deer census data using a hybrid estimation approach,...
Article
The autologistic model and related auto-models, commonly applied as autocovariate regression, offer distinct advantages for analysing spatially autocorrelated ecological data. However, comparative studies by Carl and K\"uhn (Ecol. Model., 2007, 207, 159), Dormann (Ecol. Model., 2007, 207, 234), Dormann et al. (Ecography, 2007, 30, 609) and Beale et...
Article
Full-text available
The management of natural systems often involves periodic interventions that must be decided without a complete understanding of how the system responds to our actions. It is in this situation of recurrent decision-making under uncertainty that adaptive management (AM) has been repeatedly advocated, with each decision round providing an opportunity...
Article
1.Thibaud et al. (2014) present a framework for simulating species and evaluating the relative effects of factors affecting the predictions from species distribution models (SDMs). They demonstrate their approach by generating presence-absence datasets for different simulated species and analysing them using four modelling methods: three presence-a...
Article
Full-text available
In a recent paper, Welsh, Lindenmayer and Donnelly (WLD) question the usefulness of models that estimate species occupancy while accounting for detectability. WLD claim that these models are difficult to fit and argue that disregarding detectability can be better than trying to adjust for it. We think that this conclusion and subsequent recommendat...
Article
A problem of interest for ecology and conservation is that of determining the best allocation of survey effort in studies aimed at estimating the proportion of sites occupied by a species. Many species are difficult to detect and often remain undetected during surveys at sites where they are present. Hence, for the estimator of species occupancy to...
Article
Full-text available
Invasive species are a cause for concern in natural and economic systems and require both monitoring and management. There is a trade-off between the amount of resources spent on surveying for the species and conducting early management of occupied sites, and the resources that are ultimately spent in delayed management at sites where the species w...
Article
Species often remain undetected at sites where they are present. However, the impact of imperfect detection on species distribution models (SDMs) is not fully appreciated. In this paper we evaluate the influence of imperfect detection on the calibration and discrimination capacity of SDMs. We compare the performance of three types of SDMs: (1) a te...
Article
Aim: Our aims are: (1) to highlight the power of dynamic occupancy models for analysing species range dynamics while accounting for imperfect detection; (2) to emphasize the flexibility to model effects of environmental covariates in the dynamics parameters (extinction and colonization probability); and (3) to illustrate the development of predicti...
Article
Full-text available
The loss and fragmentation of substantial areas of forest habitat, in combination with rampant hunting, has pushed many of Southeast Asia’s megafauna species to the verge of extinction. However, the extent of these declines is rarely quantified, thereby weakening lessons learned and species-based management. This need not be the case as a prolifera...