ALBERT

Description: Remote sensing (RS) is a powerful tool to measure and monitor Essential Biodiversity Variables (EBVs) and their environmental drivers. Despite this potential, stronger integration between remote sensing experts and the ecological community could better support biodiversity initiatives. Here we highlight opportunities to harness remote sensing technology to better understand biodiversity patterns, ecological processes and the consequences for ecosystem services (ESs). We argue that tracking many EBVs using remote sensing should prioritize the monitoring of dominant species, a scalable property across multiple EBV classes, for several reasons. First, a few dominant species in an ecological community disproportionately contribute to the satellite spectral signature. Second, a focus on dominance would enable a stronger links to ecological research, as dominance reflects the ecological community context (i.e. relative abundance of coexisting species). For example dominant species should be especially important contributors to many ecosystem functions and services that rely on abundance or biomass, such as carbon storage or nutrient cycling, because of their greater representation in a community. Furthermore, global change impacts on communities may be reflected in changing dominance structure before the losses of species, thus tracking dominance provides an early-warning sign of community change for EBVs. Finally, focusing on dominant species should improve understanding of spatial and temporal dynamics of dominance-driven ESs through RS mapping. Given the importance of dominant species to ecological communities and ESs, monitoring dominance under changing environmental conditions and human impacts should be a global priority. Remote sensing should play a pivotal role in monitoring Essential Biodiversity Variables (EBVs) across the globe, but this requires thoughtful consideration of how to connect remote sensing metrics with ecologically relevant variables. We argue that monitoring dominant species using remote sensing should be a priority because dominance is an ecologically relevant and scalable measure (of population abundance, community composition, trait representation and contribution to ecosystem function), can provide an early-warning sign of ecological change, and overwhelmingly contributes to biomass-driven ecosystem services (ESs). Furthermore, dominant species largely drive the satellite spectral signature. By identifying dominant species that disproportionately provide ESs, a new research direction for remote sensing is to address how ESs will change through time or across environmental gradients. This direction complements a growing body of work using remote sensing to map and quantify ESs.

Description: Itigi thicket is a spatially restricted ecosystem only present in Zambia and Tanzania. It is thought to be highly threatened and therefore we need to urgently assess the threats to this ecosystem as well as extent and rates of change to derive its true conservation status. In this study we focus on the Itigi-Sumbu thicket surrounding Lake Mweru Wantipa in Zambia, which occurs both inside and outside a National Park (IUCN category II). Earth observation data archives provide the means to assist the conservation assessment process by allowing the monitoring of the ecosystem over time. In particular, the Landsat archive offers over 40 years of imagery at a resolution suited to the distribution of this ecosystem. In this study we exploit this archive and extend it back 50 years using historical aerial photography. The remote-sensing data were classified according to presence of thicket at five dates across a 50-year period and these outputs were combined to produce a deforestation map. Crucially, this map was assessed for accuracy using a novel approach to expert knowledge, which shows that the resultant map is highly accurate (93% overall accuracy). A confusion matrix was used to provide a confidence interval to the deforestation figures. Results indicate that 64% of the Itigi-Sumbu thicket around Lake Mweru Wantipa has been cleared over the last 50 years and that the largest area of remaining thicket is currently situated within the Mweru Wantipa National Park. This deforestation figure provides the means to assess the conservation status of Itigi-Sumbu thicket as part of the Red List of Ecosystem as Endangered (EN). In this study we report on the essential role of Earth Observation data archives in assessing the conservation status of ecosystems. Focusing on Itigi-Sumbu thicket, only found in Zambia and Tanzania, we estimate the extent and rates of change over the last 50 years using historical aerial photography in combination with archived Landsat data and a novel approach to accuracy assessment using expert knowledge.

Description: The use of passive infrared (PIR) triggered camera traps has dramatically increased in recent decades. Unfortunately, technical descriptions of how PIR triggered camera traps operate have not been sufficiently clear. Descriptions have often been ambiguous or misleading and in several cases are demonstrably wrong. Such descriptions have led to erroneous interpretations of camera trapping data. This short communication clarifies how PIR sensors operate. We clarify how infrared radiation is emitted and transmitted, and we describe the parts of the PIR sensor and how they detect infrared radiation and, by extension, fauna. Several problematic descriptions of PIR sensors are drawn on to highlight flawed descriptions and demonstrate where erroneous interpretations of camera trapping data occurred. By clarifying the language and the description of PIR triggered camera traps, this paper ensures that wildlife researchers and managers using camera traps will avoid flawed interpretations of their data. Avoiding flawed interpretations of data should reduce wasted effort and resources that would otherwise come about as researchers attempt to test flawed hypotheses. Furthermore, this paper provides a thorough technical reference for camera trapping practitioners, which is not present elsewhere in the wildlife research literature. Camera traps are a valuable tool for wildlife research. However, understanding how the equipment works is paramount for accurate interpretation of the data. This paper provides a technical explanation of how passive infrared camera traps operate to reduce common misconceptions.

Description: Paleotropical islands are experiencing extensive land-use change, yet little is known about how such changes are impacting wildlife in these biodiversity hotspots. To address this knowledge gap, we characterized bat responses to forest conversion in a biodiverse, human-threatened coastal rainforest habitat on Makira, Solomon Islands. We analysed ~200 h of acoustic recordings from echolocating bats in the four dominant types of land use on Makira: intact forest, secondary forest, food gardens and cacao plantations. Bat calls were identified to the species level using a supervised classification model (where labelled data are used to train the system). We examined relative activity levels and morphological traits across habitats. Relative activity levels were highest in intermediately disturbed habitats and lowest in the most heavily disturbed habitat, although these differences were not significant. There were significant differences in the mean forearm length of bat assemblages across habitats, with the highest mean forearm length found in the most open habitat (Cacao). Overall, our study constitutes the first detailed exploration of anthropogenic effects on mammalian diversity in the Solomon Islands and includes the first acoustic and morphological information for many bat species in Melanesia. We use our experience to discuss the challenges of acoustic monitoring in such a remote and poorly studied region. Forest conversion is a major threat to biodiversity and is particularly acute on tropical islands, which are home to a high number of endemic species and important sites for conservation. Our work provides interesting information on both the impact of forest conversion on bat assemblages, and the application of acoustic monitoring of bats for a data-deficient area of the Solomon Islands. We found significant differences in the mean forearm length across habitats, and use our experience to discuss the challenges of acoustic monitoring in a remote and poorly studied region.

Description: Although satellite-based variables have for long been expected to be key components to a unified and global biodiversity monitoring strategy, a definitive and agreed list of these variables still remains elusive. The growth of interest in biodiversity variables observable from space has been partly underpinned by the development of the essential biodiversity variable (EBV) framework by the Group on Earth Observations – Biodiversity Observation Network, which itself was guided by the process of identifying essential climate variables. This contribution aims to advance the development of a global biodiversity monitoring strategy by updating the previously published definition of EBV, providing a definition of satellite remote sensing (SRS) EBVs and introducing a set of principles that are believed to be necessary if ecologists and space agencies are to agree on a list of EBVs that can be routinely monitored from space. Progress toward the identification of SRS-EBVs will require a clear understanding of what makes a biodiversity variable essential, as well as agreement on who the users of the SRS-EBVs are. Technological and algorithmic developments are rapidly expanding the set of opportunities for SRS in monitoring biodiversity, and so the list of SRS-EBVs is likely to evolve over time. This means that a clear and common platform for data providers, ecologists, environmental managers, policy makers and remote sensing experts to interact and share ideas needs to be identified to support long-term coordinated actions. This contribution introduces a set of definitions and principles that are believed to be necessary if ecologists and space agencies are to agree on a list of essential biodiversity variables that can be routinely monitored from space. In particular, it argues that progress toward the identification of satellite remote sensing EBVs (SRS-EBVs) will require a clear understanding of what makes a biodiversity variable essential, as well as agreement on who the users of the SRS-EBVs are.

Description: Estimates of animal abundance are essential for understanding animal ecology. Camera traps can be used to estimate the abundance of terrestrial mammals, including elusive species, provided that the sensitivity of the sensor, estimated as the effective detection distance (EDD), is quantified. Here, we show how the EDD can be inferred directly from camera trap images by placing markers at known distances along the midline of the camera field of view, and then fitting distance-sampling functions to the frequency of animal passage between markers. EDD estimates derived from simulated passages using binned detection distances approximated those obtained from continuous detection distance measurements if at least five intervals were used over the maximum detection distance. A field test of the method in two forest types with contrasting vegetation density, with five markers at 2.5 m intervals, produced credible EDD estimates for 13 forest-dwelling mammals. EDD estimates were positively correlated with species body mass, and were shorter for the denser vegetation, as expected. Our findings suggest that this simple method can produce reliable estimates of EDD. These estimates can be used to correct photographic capture rates for difference in sampling effort resulting from differences in sensor sensitivity between species and habitats. Simplifying the estimation of EDD will result in less biased indices of relative abundance, and will also facilitate the use of camera trap data for estimating animal density. We present a simple method to estimate effective detection distance of camera traps, which will enable camera trap data to be corrected for biases in detection probability between species and habitats. The method uses a line of markers in the centre of the camera view, which enables rapid estimation of trigger distances of animals passing the camera view using images taken by the camera trap. These distance estimates can be used to estimate effective detection distance using distance-sampling techniques.

Description: A new wave of terrestrial lidar scanners, optimized for rapid scanning and portability, such as the Compact Biomass Lidar (CBL), enable and improve observations of structure across a range of important ecosystems. We performed studies with the CBL in temperate and tropical forests, caves, salt marshes and coastal areas subject to erosion. By facilitating additional scanning points, and therefore view angles, this new class of terrestrial lidar alters observation coverage within samples, potentially reducing uncertainty in estimates of ecosystem properties. The CBL has proved competent at reconstructing trees and mangrove roots using the same cylinder-based Quantitative Structure Models commonly utilized for data from more capable instruments (Raumonen et al. 2013). For tropical trees with morphologies that challenge standard reconstruction techniques, such as the buttressed roots of Ceiba trees and the multiple stems of strangler figs, the CBL was able to provide the versatility and the speed of deployment needed to fully characterize their unique features. For geomorphological features, the deployment flexibility of the CBL enabled sampling from optimal view-angles, including from a novel suspension system for sampling salt marsh creeks. Overall, the practical aspects of these instruments, which improve deployment logistics, and therefore data acquisition rate, are shown to be emerging capabilities, greatly increasing the potential for observation, particularly in highly temporally dynamic, inaccessible and geometrically complex ecosystems. In order to better analyze information quality across these diverse and challenging ecosystems, we also provide a novel and much-needed conceptual framework, the microstate model, to characterize and mitigate uncertainties in terrestrial lidar observations. This paper represents a data-driven exploration of the applications of newly emerging rapid-scanning, highly portable terrestrial lidar to the extraction of properties of interest in a range of important ecosystems. These studies are contextualized by a novel framework for characterizing and mitigating the instrument and ecosystem sources of uncertainty in lidar observations of structure. The necessity of quantitative information requirements and dynamic sampling for terrestrial lidar observations of ecosystem properties is established.

Description: Camera traps are used to estimate densities or abundances using capture-recapture and, more recently, random encounter models (REMs). We deploy REMs to describe an invasive-native species replacement process, and to demonstrate their wider application beyond abundance estimation. The Irish hare Lepus timidus hibernicus is a high priority endemic of conservation concern. It is threatened by an expanding population of nonnative, European hares L. europaeus , an invasive species of global importance. Camera traps were deployed in thirteen 1 km squares, wherein the ratio of invader to native densities were corroborated by night-driven line transect distance sampling throughout the study area of 1652 km 2 . Spatial patterns of invasive and native densities between the invader's core and peripheral ranges, and native allopatry, were comparable between methods. Native densities in the peripheral range were comparable to those in native allopatry using REM, or marginally depressed using Distance Sampling. Numbers of the invader were substantially higher than the native in the core range, irrespective of method, with a 5:1 invader-to-native ratio indicating species replacement. We also describe a post hoc optimization protocol for REM which will inform subsequent (re-)surveys, allowing survey effort (camera hours) to be reduced by up to 57% without compromising the width of confidence intervals associated with density estimates. This approach will form the basis of a more cost-effective means of surveillance and monitoring for both the endemic and invasive species. The European hare undoubtedly represents a significant threat to the endemic Irish hare. We deployed camera trap random encounter models (REMs) to capture and describe an invasive-native species replacement process between the native Irish hare and the invasive European hare in Northern Ireland, and used line transect Distance Sampling to corroborate spatial patterns of invasive and native densities. Native densities outside the invasive core range were comparable or slightly depressed, while numbers of the invader were substantially higher than the native in the core range, irrespective of method, with 5:1 invader-to-native ratio indicating species replacement. By using a post hoc optimization protocol for REM, future (re-)survey effort may be reduced by up to 57%, forming the basis of a more cost-effective means of surveillance and monitoring for both the endemic and invasive species.