Monitoring change in aquatic invertebrate biodiversity: sample size, faunal elements and analytical methods

Replication is usually regarded as an integral part of biological sampling, yet the cost of extensive within-wetland replication prohibits its use in broad-scale monitoring of trends in aquatic invertebrate biodiversity. In this paper, we report results of testing an alternative protocol, whereby only two samples are collected from a wetland per monitoring event and then analysed using ordination to detect any changes in invertebrate biodiversity over time. Simulated data suggested ordination of combined data from the two samples would detect 20% species turnover and be a cost-effective method of monitoring changes in biodiversity, whereas power analyses showed about 10 samples were required to detect 20% change in species richness using ANOVA. Errors will be higher if years with extreme climatic events (e.g. drought), which often have dramatic short-term effects on invertebrate communities, are included in analyses. We also suggest that protocols for monitoring aquatic invertebrate biodiversity should include microinvertebrates. Almost half the species collected from the wetlands in this study were microinvertebrates and their biodiversity was poorly predicted by macroinvertebrate data.     

Climate change, phenology and species detectability in a monitoring scheme

The knowledge of the state of biodiversity on the globe is based on a large number of monitoring schemes. Quite often the results of these schemes are sensitive to the timing of monitoring due to the phenology of species, which in turn may affect the detectability of species during censuses. As global warming has been shown to cause changes in phenology, there is an increasing risk that species detectability will be altered if the timing of monitoring is not adapted to this change. I tested how sensitive species detectability is to the timing of censuses and whether there are potential climate-driven temporal changes in the detectability of 73 Finnish land bird species monitored using single-visit line-transects in 1987–2010. This was done by investigating seasonal and annual patterns in the proportion of birds in the main belt and those detected by displaying activity. Over 20 of the study species showed significant changes in detectability within the census season. However, only three species showed a significant trend in annual detectability. According to multi-species analyses there was a slight but significant increasing trend in the proportion of displaying birds and a slight decreasing trend in the proportion of birds in the main belt. However, the observed species-specific annual changes in displaying activity or in proportion of birds in main belt were not associated with the observed population trends of species during the same period. Nevertheless, the findings highlight a strong potential risk that species detectability can change if climate change escalates in the future. I recommend researchers to investigate how sensitive their monitoring systems are for phenological changes and prepare tools for taking potential changes in detectability into account.     

Towards meaningful monitoring: A case study of a threatened rodent

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 changes. Here, we demonstrate the use of existing data to support the design of monitoring programmes aimed at detecting declines in species occupancy. We used single‐season occupancy models and baseline data to gain information on variables affecting the occupancy and detectability of the threatened brush‐tailed rabbit‐rat Conilurus penicillatus (Gould 1842) on the Tiwi Islands, Australia. This information was then used to estimate the survey effort required to achieve sufficient power to detect changes in occupancy of different magnitudes. We found that occupancy varied spatially, driven primarily by habitat (canopy height and cover, distance to water) and fire history across the landscape. Detectability varied strongly among seasons, and was three times higher in the late dry season (July–September), compared to the early dry season (April–June). Evaluation of three monitoring scenarios showed that conducting surveys at times when detectability is highest can lead to a substantial improvement in our ability to detect declines, thus reducing the survey effort and costs. Our study highlights the need for careful consideration of survey design related to the ecology of a species, as it can lead to substantial cost savings and improved insight into species population change via monitoring.     

Optimized monitoring sites for detection of biodiversity trends in China

Properly designed monitoring networks can generate data to understand status and trends of biodiversity, and to assess progress towards conservation targets. However, biodiversity monitoring is often affected by poor sampling design. We proposed an approach to choosing optimized monitoring sites among large areas. Based on comprehensive distribution data of 34,284 vertebrates and vascular plants from 2376 counties in China, we selected 564 optimized monitoring sites (counties) through complementarity analysis and pre-existing knowledge of nature reserves. The optimized monitoring sites are complementary to each other and reasonably distributed, to ensure that maximum species are covered while the total number of sites and monitoring costs are minimized. Incongruence of optimized monitoring sites among different taxa indicates that taxa with different ecological features should be selected for large-scale monitoring programmes. The results of this study have been applied in the design and operation of China Biodiversity Observation Network.     

Standardized Assessment of Biodiversity Trends in Tropical Forest Protected Areas: The End Is Not in Sight

Extinction rates in the Anthropocene are three orders of magnitude higher than background and disproportionately occur in the tropics, home of half the world’s species. Despite global efforts to combat tropical species extinctions, lack of high-quality, objective information on tropical biodiversity has hampered quantitative evaluation of conservation strategies. In particular, the scarcity of population-level monitoring in tropical forests has stymied assessment of biodiversity outcomes, such as the status and trends of animal populations in protected areas. Here, we evaluate occupancy trends for 511 populations of terrestrial mammals and birds, representing 244 species from 15 tropical forest protected areas on three continents. For the first time to our knowledge, we use annual surveys from tropical forests worldwide that employ a standardized camera trapping protocol, and we compute data analytics that correct for imperfect detection. We found that occupancy declined in 22%, increased in 17%, and exhibited no change in 22% of populations during the last 3–8 years, while 39% of populations were detected too infrequently to assess occupancy changes. Despite extensive variability in occupancy trends, these 15 tropical protected areas have not exhibited systematic declines in biodiversity (i.e., occupancy, richness, or evenness) at the community level. Our results differ from reports of widespread biodiversity declines based on aggregated secondary data and expert opinion and suggest less extreme deterioration in tropical forest protected areas. We simultaneously fill an important conservation data gap and demonstrate the value of large-scale monitoring infrastructure and powerful analytics, which can be scaled to incorporate additional sites, ecosystems, and monitoring methods. In an era of catastrophic biodiversity loss, robust indicators produced from standardized monitoring infrastructure are critical to accurately assess population outcomes and identify conservation strategies that can avert biodiversity collapse.     

Aerial Surveys for Estimating Wild Turkey Abundance in the Texas Rolling Plains

Abstract: Aerial surveys have been used to estimate abundance of several wild bird species including wild turkeys (Meleagris gallopavo). We used inflatable turkey decoys at 3 study sites in the Texas Rolling Plains to simulate Rio Grande wild turkey (M. g. intermedia) flocks. We evaluated detectability of flocks and errors in counting flock size during fixed-wing (Cessna 172) aerial surveys using logistic and linear regression models. Flock detectability was primarily influenced by flock size and vegetative cover, and errors in counting flock size were primarily influenced by size of flocks. We conducted computer simulations to evaluate the accuracy and precision of fixed-wing aerial surveys and examined power to detect trends in population change. Our simulations suggested abundance estimates from fixed-wing aerial surveys may be underestimated by 10-15% (2.0-4.8% CV). Power analyses suggested that fixed-wing aerial surveys can provide sufficient power (>0.80) to detect a population change of 10-25% over a 4-5-year period. We concluded fixed-wing aerial surveys are feasible on ecoregion scales.     

Wild turkey (<Emphasis Type="Italic">Meleagris gallopavo</Emphasis>) detectability from helicopters and ramifications for estimating abundance

Aerial surveys have been used to estimate abundance for several wild bird species but its application for wild turkey (Meleagris gallopavo) populations has been limited. We surveyed Rio Grande wild turkey (M. gallopavo intermedia) populations during March 2006 using an R44 helicopter. We used flocks with radio-tagged birds to estimate flock detectability. We also used simulations to evaluate accuracy and precision and examine power to detect trends in population change. We observed that wild turkey flock detectability was 94.7% (74.0–99.9%; 95% CI). Our simulations suggested helicopter surveys would underestimate abundance by about 5.6% (4.6% CV). Surveying 980 to 1,960 km² (requiring 27 to 55 h of flight time) can provide sufficient power (≥0.80) to detect a 10 to 25% change in abundance over a 4- to 5-year period.     

“Anyone Know What Species This Is?” – Twitter Conversations as Embryonic Citizen Science Communities

Social media like blogs, micro-blogs or social networks are increasingly being investigated and employed to detect and predict trends for not only social and physical phenomena, but also to capture environmental information. Here we argue that opportunistic biodiversity observations published through Twitter represent one promising and until now unexplored example of such data mining. As we elaborate, it can contribute to real-time information to traditional ecological monitoring programmes including those sourced via citizen science activities. Using Twitter data collected for a generic assessment of social media data in ecological monitoring we investigated a sample of what we denote biodiversity observations with species determination requests (N = 191). These entail images posted as messages on the micro-blog service Twitter. As we show, these frequently trigger conversations leading to taxonomic determinations of those observations. All analysed Tweets were posted with species determination requests, which generated replies for 64% of Tweets, 86% of those contained at least one suggested determination, of which 76% were assessed as correct. All posted observations included or linked to images with the overall image quality categorised as satisfactory or better for 81% of the sample and leading to taxonomic determinations at the species level in 71% of provided determinations. We claim that the original message authors and conversation participants can be viewed as implicit or embryonic citizen science communities which have to offer valuable contributions both as an opportunistic data source in ecological monitoring as well as potential active contributors to citizen science programmes.     

Road-Based Surveys for Estimating Wild Turkey Density in the Texas Rolling Plains

Abstract: Line-transect-based distance sampling has been used to estimate density of several wild bird species including wild turkeys (Meleagris gallopavo). We used inflatable turkey decoys during autumn (Aug-Nov) and winter (Dec-Mar) 2003-2005 at study sites in the Texas Rolling Plains, USA, to simulate Rio Grande wild turkey (M. g. intermedia) flocks. We evaluated detectability of flocks using logistic regression models. Our modeling effort suggested that distance to a flock and flock size played important roles in flock detectability. We also conducted surveys from roads for wild turkeys during November 2004-January 2006. The detection probability of decoy flocks was similar to wild turkey flocks during winter (decoy flock, 69.3 ± 6.2% [x̄ ± 95% CI]; wild turkey flock, 62.2 ± 18.3%) and autumn (decoy flock, 44.1 ± 5.1%; wild turkey flock, 44.7 ± 25.6%), which suggested that using decoys was appropriate for evaluating detectability of wild turkey flocks from roads. We conducted computer simulations to evaluate the performance of line-transect-based distance sampling and examined the power to detect trends in population change. Simulations suggested that population density may be underestimated by 12% during inter and 29% during autumn. Such bias occurred because of incomplete detectability of flocks near roads. Winter surveys tended to have less bias, lower relative variability, and greater power than did autumn surveys. During winter surveys, power was sufficient (≥0.80) to detect a 10-25% change in population density in 8-12 years using ≥100 16-km transects or ≥80 32-km transects. We concluded line-transect-based distance sampling from roads is an efficient, effective, and inexpensive technique for monitoring Rio Grande wild turkey populations across large scales.     

Cultivation of genetically modified organisms: resource needs for monitoring adverse effects on biodiversity

Genetically modified organisms (GMO) in non-European countries are introduced into the agro-environment on large scale with little knowledge of adverse effects on biodiversity. In the European Union (EU) possible effects of GMOs on biodiversity have to be accurately and precisely monitored. Monitoring biodiversity with a high precision is expensive and may only be achieved in close cooperation between GMO monitoring and general biodiversity monitoring. The EuMon project sampled metadata on biodiversity monitoring in Europe. Basing on the metadata, we estimated resource needs for biodiversity monitoring as needed for detecting potential adverse effects of GMOs on biodiversity. On average the analyzed schemes with a potential to detect at least a 5% change of biodiversity monitor 242.6 ± 105.4 sites at 322.6 ± 172.1 person days employing 63 ± 23 persons per year. The time invested in monitoring, given as person days, however, differed greatly between schemes and species groups, so that real manpower might be considerably higher.     

Should we account for detectability in population trends?

Capsule?Accounting for changes in detectability over time which could invalidate population trends for common and widespread breeding birds in the UK, resulted in little change in trends for the majority of species considered.

Aims?To examine whether detectability has a significant influence on population trends for common and widespread breeding birds in the UK.

Methods?Using data collected over 16 years of the UK Breeding Bird Survey (1994–2009) and focusing on a random sample of 20 common and widespread bird species, we examine the extent to which controlling for temporal change in detectability would influence national population trends.

Results?Population trends were significantly different for only 2 of the 20 species, Common Blackbird and Winter Wren. This difference corresponds to an apparent fall off in detectability of these species between 2005 and 2009. For the remaining species, controlling for detectability resulted in no significant difference in population trends.

Conclusions?The importance of detectability should be examined as part of any long-term monitoring programme. However, currently we do not find sufficient support for routinely incorporating detectability into population trends for widespread and abundant breeding birds in the UK.     

Long-term monitoring at multiple trophic levels suggests heterogeneity in responses to climate change in the Canadian Arctic tundra

Arctic wildlife is often presented as being highly at risk in the face of current climate warming. We use the long-term (up to 24 years) monitoring records available on Bylot Island in the Canadian Arctic to examine temporal trends in population attributes of several terrestrial vertebrates and in primary production. Despite a warming trend (e.g. cumulative annual thawing degree-days increased by 37% and snow-melt date advanced by 4–7 days over a 23-year period), we found little evidence for changes in the phenology, abundance or productivity of several vertebrate species (snow goose, foxes, lemmings, avian predators and one passerine). Only primary production showed a response to warming (annual above-ground biomass of wetland graminoids increased by 123% during this period). We nonetheless found evidence for potential mismatches between herbivores and their food plants in response to warming as snow geese adjusted their laying date by only 3.8 days on average for a change in snow-melt of 10 days, half of the corresponding adjustment shown by the timing of plant growth (7.1 days). We discuss several reasons (duration of time series, large annual variability, amplitude of observed climate change, nonlinear dynamic or constraints imposed by various rate of warming with latitude in migrants) to explain the lack of response by herbivores and predators to climate warming at our study site. We also show how length and intensity of monitoring could affect our ability to detect temporal trends and provide recommendations for future monitoring.     

Towards a global terrestrial species monitoring program

The Convention on Biological Diversity's strategic plan lays out five goals: “(A) address the underlying causes of biodiversity loss by mainstreaming biodiversity across government and society; (B) reduce the direct pressures on biodiversity and promote sustainable use; (C) improve the status of biodiversity by safeguarding ecosystems, species and genetic diversity; (D) enhance the benefits to all from biodiversity and ecosystem services; (E) enhance implementation through participatory planning, knowledge management and capacity building.” To meet and inform on the progress towards these goals, a globally coordinated approach is needed for biodiversity monitoring that is linked to environmental data and covers all biogeographic regions. During a series of workshops and expert discussions, we identified nine requirements that we believe are necessary for developing and implementing such a global terrestrial species monitoring program. The program needs to design and implement an integrated information chain from monitoring to policy reporting, to create and implement minimal data standards and common monitoring protocols to be able to inform Essential Biodiversity Variables (EBVs), and to develop and optimize semantics and ontologies for data interoperability and modelling. In order to achieve this, the program needs to coordinate diverse but complementary local nodes and partnerships. In addition, capacities need to be built for technical tasks, and new monitoring technologies need to be integrated. Finally, a global monitoring program needs to facilitate and secure funding for the collection of long-term data and to detect and fill gaps in under-observed regions and taxa. The accomplishment of these nine requirements is essential in order to ensure data is comprehensive, to develop robust models, and to monitor biodiversity trends over large scales. A global terrestrial species monitoring program will enable researchers and policymakers to better understand the status and trends of biodiversity.     

A Monte Carlo method to account for sampling error in multi-species indicators

The usefulness of biodiversity indicators strongly increases if accompanied by measures of uncertainty. In the case of indicators that combine population indices of species, however, the inclusion of the uncertainty of the species indices has shown to be hard to realize, usually due to imperfections in monitoring programmes. Missing values and time series of different lengths preclude the use of analytical approaches, whereas bootstrapping across sites requires the raw abundance data on the site level, which may not always be available. Sometimes bootstrapping across species rather than sites is opted for, but this approach ignores the uncertainty attached to species indices. We developed a method to account for sampling error of species indices in the calculation of multi-species indicators based on Monte Carlo simulation of annual species indices. The construction of confidence intervals enables various trend assessments, like testing for linear or smooth trends, testing for changes between two time points, testing the significance of a suspected change-point and testing for differences between two multi-species indicators. Here, we compare our method with conventional methods and illustrate the benefits of our approach using Dutch breeding bird indicators.     

A 250-year index of first flowering dates and its response to temperature changes

Widespread concerns about global biodiversity loss have led to a growing demand for indices of biodiversity status. Today, climate change is among the most serious threats to global biodiversity. Although many studies have revealed phenological responses to climate change, no long-term community-level indices have been developed. We derived a 250-year index of first flowering dates for 405 plant species in the UK for assessing the impact of climate change on plant communities. The estimated community-level index in the most recent 25 years was 2.2–12.7 days earlier than any other consecutive 25-year period since 1760. The index was closely correlated with February–April mean Central England Temperature, with flowering 5.0 days earlier for every 1°C increase in temperature. The index was relatively sensitive to the number of species, not records per species, included in the model. Our results demonstrate how multi-species, multiple-site phenological events can be integrated to obtain indices showing trends for each species and across species. This index should play an important role in monitoring the impact of climate change on biodiversity. Furthermore, this approach can be extended to incorporate data from other taxa and countries for evaluating cross-taxa and cross-country phenological responses to climate change.     

Using simple species lists to monitor trends in animal populations: new methods and a comparison with independent data

There is an urgent need to develop simple and inexpensive methods for monitoring wildlife populations in resource-poor countries. List-based methods have been advocated as simple yet potentially useful biodiversity monitoring tools, and systems have recently been launched in a number of countries to collect species lists. We attempt to advance the use of systematic list-based monitoring by (1) suggesting improvements to the way in which list reporting rates are calculated; (2) assessing the extent to which degrading effort-corrected measures of abundance into simple species lists results in loss of information on population trends; (3) comparing long-term trends in list reporting rates with population trends from a wholly independent monitoring scheme. Daily species lists of birds were derived from regular trapping at a nature reserve in southern England. Most species showed a strong correlation across years between the proportion of lists on which they occurred, adjusted for list length (adjusted list reporting rate; ALRR), and an effort-corrected measure of abundance (captures per unit effort; CPUE). ALRR revealed almost as much about annual variation in abundance as CPUE for all but the most frequently captured species. Long-term (>20 years) trends in ALRRs at the nature reserve were positively correlated with UK national population trends recorded over the same period by an independent, labour-intensive monitoring scheme that counted birds at a large number of widely spread sites. Our results support previous claims that simple species lists could generate data useful for monitoring long-term population trends, particularly where such lists are collected systematically. However, further research on the efficiency of list reporting rates relative to more sophisticated methods is necessary, before list-based methods can be advocated for dedicated monitoring schemes in resource-poor regions.     

Evaluating the effectiveness of overstory cover as a surrogate for bird community diversity and population trends

Landscape features are often used as surrogates for biodiversity. While landscape features may perform well as surrogates for coarse metrics of biodiversity such as species richness, their value for monitoring population trends in individual species is virtually unexplored. We compared the performance of a proposed habitat surrogate for birds, percentage cover of vegetation overstory, for two distinct aspects of bird assemblages: community diversity (i.e. species richness) and population trends. We used four different long-term studies of open woodland habitats to test the consistency of the relationship between overstory percentage cover and bird species richness across a large spatial extent (>1000 km) in Australia. We then identified twelve bird species with long-term time-series data to test the relationship between change in overstory cover and populations trends. We found percentage cover performed consistently as a surrogate for species richness in three of the four sites. However, there was no clear pattern in the performance of change in percentage cover as a surrogate for population trends. Four bird species exhibited a significant relationship with change in percentage overstory cover in one study, but this was not found across multiple studies. These results demonstrate a lack of consistency in the relationship between change in overstory cover and population trends among bird species, both within and between geographic regions. Our study demonstrates that biodiversity surrogates representing community-level metrics may be consistent across regions, but provide only limited information about individual species population trends. Understanding the limitations of the information provided by a biodiversity surrogate can inform the appropriate context for its application.     

Large-scale grid-based detection in occupancy surveys of a threatened small mammal: A comparison of two non-invasive methods

Monitoring the status and trends of wildlife is key to understand how species respond to natural and human-derived threats, and to evaluate and improve conservation planning and management. Large-scale, grid-based assessment of species distribution, abundance, and population trends over time is an important component of biodiversity monitoring. However, such assessments still present important challenges related, for instance, to how the choice of the sampling method may affect species detectability and thus, overall data accuracy. Here, we address this issue, focusing on the Cabrera vole (Microtus cabrerae), a threatened small mammal, listed in the Habitats Directive (Annexes II and IV), hence requiring regular evaluation of its population status and trends. We used occupancy modelling to estimate method-specific detection probability of the species over large-scale, grid-based (10 × 10 km²) surveys relying on two non-invasive sampling techniques: sign surveys and owl pellet analysis. Results provided evidence for a greater cost-effectiveness of sign surveys compared to owl pellet analysis for detecting the species in occupancy surveys, suggesting that large-scale population monitoring of Cabrera voles (or other species also producing easily identifiable signs of their presence) may fairly rely on sign-surveys. Overall, our study supported the view that while owl pellet analysis provides a valuable option when the aim is to assess small mammal assemblages (i.e. multiple species) in a region, other complementary methods may be required to increase the detection probability of certain species that because of their secretive behaviour or rarity remain less predated by owls. We thus argue that the choice of the sampling method should be context-dependent and evaluated based on the study aims, the surveyed area (i.e. local factors), the target species (i.e. life history traits) and the available resources. Based on our results we recommend that researchers and managers explore survey-design trade-offs to ensure the proposed designs have sufficient power to detect real population trends.     

Optimizing ultrasonic sampling effort for monitoring forest bats

Landscape‐scale monitoring is a key approach for assessing changes in indicators. However, great care needs to be taken to collect rigorous data and avoid wasting resources in long‐term programmes. Insect‐eating bats are diverse, functionally important and are often proposed as indicator species of environmental health. We used acoustic (ultrasonic) data from pilot bat surveys undertaken in forests and woodlands to optimize sampling effort to produce precise estimates of bat activity and occupancy. We also carried out simulations to evaluate the statistical power of different sampling designs to detect changes in activity and occupancy levels of individual bat species. There was little gain in precision for estimates of bat activity by sampling beyond five to six detector nights. To ensure spatial heterogeneity was sampled around a monitoring point, three detectors for two nights or two detectors for three nights would be required. This level of sampling was also sufficient to be 90% certain of recording occupancy for 11 of 12 taxa. Power simulations revealed that a sampling design using two detectors per monitoring point for two nights could detect a 30% decline within 10 years with 90% power for all species, except the white‐striped free tail bat (Tadarida australis), using either changes in activity levels or occupancy. However, fewer years were required when using occupancy. Setting detectors either on‐flyways or off‐flyways contributed only minor differences to the time taken to reach 90% power for both occupancy and activity levels, though sampling both locations has major implications for interpreting trends in bats. We suggest that bat activity levels are more sensitive for detecting change than occupancy because one pass or 1000 passes can be recorded per night by an acoustic detector, and this is not differentiated by occupancy. Bats can be monitored cost‐effectively and should be included in monitoring programmes.     

Effects of physico-chemistry, land use and hydromorphology on three riverine organism groups: a comparative analysis with monitoring data from Germany and Austria

The majority of studies comparing the response of biotic metrics to environmental stress in rivers are based on relatively small, homogeneous datasets resulting from research projects. Here, we used a large dataset from Austrian and German national river monitoring programmes (2,302 sites) to analyse the response of fish, diatom and macroinvertebrate metrics to four stressors acting at different scales (hydromorphology, physico-chemistry, riparian and catchment land use). Nutrient enrichment and catchment land use were the main discriminating stressors for all organism groups, over-ruling the effects of hydromorphological stress on the site scale. The response of fish metrics to stress was generally low, while macroinvertebrate metrics performed best. The Trophic Diatom Index (TDI) responded most strongly to all stressors in the mountain streams, while different metrics were responsive in the lowlands. Our results suggest that many rivers are still considerably affected by nutrient enrichment (eutrophication), which might directly point at implications of catchment land use. We conclude that monitoring datasets are well-suited to detect major broad-scale trends of degradation and their impact on riverine assemblages, while the more subtle effects of local-scale stressors require stream type-specific approaches.