Detecting abundance trends under uncertainty: the influence of budget, observation error and environmental change

ArticleCopyright © 2014 The Authors. Animal Conservation published by John Wiley & Sons Ltd on behalf of The Zoological Society of London.Population monitoring must robustly detect trends over time in a cost-effective manner. However, several underlying ecological changes driving population trends may interact differently with observation uncertainty to produce abundance trends that are more or less detectable for a given budget and over a given time period. Errors in detecting these trends include failing to detect declines when they exist (type II), detecting them when they do not exist (type I), detecting trends in one direction when they are actually in another direction (type III) and incorrectly estimating the shape of the trend. Robust monitoring should be able to avoid each of these error types. Using monitoring of two contrasting ungulate species and multiple scenarios of population change (poaching, climate change and road development) in the Serengeti ecosystem as a case study, we used a ‘virtual ecologist’ approach to investigate monitoring effectiveness under uncertainty. We explored how the prevalence of different types of error varies depending on budgetary, observational and environmental conditions. Higher observation error and conducting surveys less frequently increased the likelihood of not detecting trends and misclassifying the shape of the trend. As monitoring period and frequency increased, observation uncertainty was more important in explaining effectiveness. Types I and III errors had low prevalence for both ungulate species. Greater investment in monitoring considerably decreased the likelihood of failing to detect significant trends (type II errors). Our results suggest that it is important to understand the effects of monitoring conditions on perceived trends before making inferences about underlying processes. The impacts of specific threats on population abundance and structure feed through into monitoring effectiveness; hence, monitoring programmes must be designed with the underlying processes to be detected in mind. Here we provide an integrated modelling framework that can produce advice on robust monitoring strategies under uncertainty.Portuguese Foundation for Science and TechnologyEuropean Commissio

Quantifying the short-term costs of conservation interventions for fishers at Lake Alaotra, Madagascar

Artisanal fisheries are a key source of food and income for millions of people, but if poorly managed, fishing can have declining returns as well as impacts on biodiversity. Management interventions such as spatial and temporal closures can improve fishery sustainability and reduce environmental degradation, but may carry substantial short-term costs for fishers. The Lake Alaotra wetland in Madagascar supports a commercially important artisanal fishery and provides habitat for a Critically Endangered primate and other endemic wildlife of conservation importance. Using detailed data from more than 1,600 fisher catches, we used linear mixed effects models to explore and quantify relationships between catch weight, effort, and spatial and temporal restrictions to identify drivers of fisher behaviour and quantify the potential effect of fishing restrictions on catch. We found that restricted area interventions and fishery closures would generate direct short-term costs through reduced catch and income, and these costs vary between groups of fishers using different gear. Our results show that conservation interventions can have uneven impacts on local people with different fishing strategies. This information can be used to formulate management strategies that minimise the adverse impacts of interventions, increase local support and compliance, and therefore maximise conservation effectiveness

ABC inference of multi-population divergence with admixture from unphased population genomic data

Rapidly developing sequencing technologies and declining costs have made it possible to collect genome-scale data from population-level samples in nonmodel systems. Inferential tools for historical demography given these data sets are, at present, underdeveloped. In particular, approximate Bayesian computation (ABC) has yet to be widely embraced by researchers generating these data. Here, we demonstrate the promise of ABC for analysis of the large data sets that are now attainable from nonmodel taxa through current genomic sequencing technologies. We develop and test an ABC framework for model selection and parameter estimation, given histories of three-population divergence with admixture. We then explore different sampling regimes to illustrate how sampling more loci, longer loci or more individuals affects the quality of model selection and parameter estimation in this ABC framework. Our results show that inferences improved substantially with increases in the number and/or length of sequenced loci, while less benefit was gained by sampling large numbers of individuals. Optimal sampling strategies given our inferential models included at least 2000 loci, each approximately 2 kb in length, sampled from five diploid individuals per population, although specific strategies are model and question dependent. We tested our ABC approach through simulation-based cross-validations and illustrate its application using previously analysed data from the oak gall wasp, Biorhiza pallida

Whole-genome data reveal the complex history of a diverse ecological community

How widespread ecological communities assemble remains a key question in ecology. Trophic interactions between widespread species may reflect a shared population history or ecological fitting of local pools of species with very different population histories. Which scenario applies is central to the stability of trophic associations and the potential for coevolution between species. Here we show how alternative community assembly hypotheses can be discriminated using whole-genome data for component species and provide a likelihood framework that overcomes current limitations in formal comparison of multispecies histories. We illustrate our approach by inferring the assembly history of a Western Palearctic community of insect herbivores and parasitoid natural enemies, trophic groups that together comprise 50% of terrestrial species. We reject models of codispersal from a shared origin and of delayed enemy pursuit of their herbivore hosts, arguing against herbivore attainment of “enemy-free space.” The community-wide distribution of species expansion times is also incompatible with a random, neutral model of assembly. Instead, we reveal a complex assembly history of single- and multispecies range expansions through the Pleistocene from different directions and over a range of timescales. Our results suggest substantial turnover in species associations and argue against tight coevolution in this system. The approach we illustrate is widely applicable to natural communities of nonmodel species and makes it possible to reveal the historical backdrop against which natural selection acts

Long-term monitoring of wildlife populations for protected area management in Southeast Asia

Long-term monitoring of biodiversity in protected areas (PAs) is critical to assess threats, link conservation action to species outcomes, and facilitate improved management. Yet, rigorous longitudinal monitoring within PAs is rare. In Southeast Asia (SEA), there is a paucity of long-term wildlife monitoring within PAs, and many threatened species lack population estimates from anywhere in their range, making global assessments difficult. Here, we present new abundance estimates and population trends for 11 species between 2010 and 2020, and spatial distributions for 7 species, based on long-term line transect distance sampling surveys in Keo Seima Wildlife Sanctuary in Cambodia. These represent the first robust population estimates for four threatened species from anywhere in their range and are among the first long-term wildlife population trend analyses from the entire SEA region. Our study revealed that arboreal primates and green peafowl (Pavo muticus) generally had either stable or increasing population trends, whereas ungulates and semiarboreal primates generally had declining trends. These results suggest that ground-based threats, such as snares and domestic dogs, are having serious negative effects on terrestrial species. These findings have important conservation implications for PAs across SEA that face similar threats yet lack reliable monitoring data

The impacts of landscape structure on the winter movements and habitat selection of female red deer

An area of research that has recently gained more attention is to understand how species respond to environmental change such as the landscape structure and fragmentation. Movement is crucial to select habitats but the landscape structure influences the movement patterns of animals. Characterising the movement characteristics, utilisation distribution (UD) and habitat selection of a single species in different landscapes can provide important insights into species response to changes in the landscape. We investigate these three fields in female red deer (Cervus elaphus) in southern Sweden, in order to understand how landscape structure influences their movement and feeding patterns. Movements are compared between two regions, one dominated by a fragmented agriculture-forest mosaic and the other by managed homogenous forest. Red deer in the agriculture-dominated landscape had larger UDs compared to those in the forest-dominated area, moved larger distances between feeding and resting and left cover later in the day but used a similar duration for their movements, suggesting faster travelling speeds between resting and feeding locations. The habitat selection patterns of red deer indicate a trade-off between forage and cover, selecting for habitats that provide shelter during the day and forage by night. However, the level of trade-off, mediated through movement and space use patterns, is influenced by the landscape structure. Our approach provides further understanding of the link between individual animal space use and changing landscapes and can be applied to many species able to carry tracking devices

Using targeted enrichment of nuclear genes to increase phylogenetic resolution in the neotropical rain forest genus Inga (Leguminosae: Mimosoideae)

Evolutionary radiations are prominent and pervasive across many plant lineages in diverse geographical and ecological settings; in neotropical rainforests there is growing evidence suggesting that a significant fraction of species richness is the result of recent radiations. Understanding the evolutionary trajectories and mechanisms underlying these radiations demands much greater phylogenetic resolution than is currently available for these groups. The neotropical tree genus Inga (Leguminosae) is a good example, with ~300 extant species and a crown age of 2–10 MY, yet over 6 kb of plastid and nuclear DNA sequence data gives only poor phylogenetic resolution among species. Here we explore the use of larger-scale nuclear gene data obtained though targeted enrichment to increase phylogenetic resolution within Inga. Transcriptome data from three Inga species were used to select 264 nuclear loci for targeted enrichment and sequencing. Following quality control to remove probable paralogs from these sequence data, the final dataset comprised 259,313 bases from 194 loci for 24 accessions representing 22 Inga species and an outgroup (Zygia). Bayesian phylogenies reconstructed using either all loci concatenated or a gene-tree/species-tree approach yielded highly resolved phylogenies. We used coalescent approaches to show that the same targeted enrichment data also have significant power to discriminate among alternative within-species population histories within the widespread species I. umbellifera. In either application, targeted enrichment simplifies the informatics challenge of identifying orthologous loci associated with de novo genome sequencing. We conclude that targeted enrichment provides the large volumes of phylogenetically-informative sequence data required to resolve relationships within recent plant species radiations, both at the species level and for within-species phylogeographic studies

The Danger of Having All Your Eggs in One Basket—Winter Crash of the Re-Introduced Przewalski's Horses in the Mongolian Gobi

Large mammals re-introduced into harsh and unpredictable environments are vulnerable to stochastic effects, particularly in times of global climate change. The Mongolian Gobi is home to several rare large ungulates such as re-introduced Przewalski's horses (Equus ferus przewalskii) and Asiatic wild asses (Equus hemionus), but also to a millennium-old semi-nomadic livestock herding culture