Spatial Replication Research Articles

Spatiotemporal variation in drivers of parasitism in a wild wood mouse population

Abstract Host–parasite interactions in nature are driven by a range of factors across several ecological scales, so observed relationships are often context‐dependent. Importantly, if these factors vary across space and time, practical sampling limitations can limit or bias inferences, and the relative importance of different drivers can be hard to discern. Here we ask to what degree environmental, host and within‐host influences on parasitism are shaped by spatiotemporal variation. We used a replicated, longitudinal dataset of >1,500 observations for nearly 1000 individual wood mice, Apodemus sylvaticus, encompassing 6 years of sampling across five different woodland sites, and investigated drivers of infection intensity with a highly prevalent gastrointestinal nematode, Heligmosomoides polygyrus. We used a Bayesian modelling approach to further quantify if and how each factor varied in space and time. Finally, we examined the extent to which a lack of spatial or temporal replication (i.e. within single years or single sites) would affect which drivers predict H. polygyrus infection. Season, host body condition, and sex were the three most important determinants of infection intensity; however, the strength and even direction of these effects varied in time, but not in space. Models fit to single years and site replicates in many cases showed weak and variable detection of effects of the factors investigated, highlighting the benefits of long‐term sampling for separating meaningful ecological variation from sampling variation. These results highlight the importance of accounting for spatiotemporal variation in determining what drives disease dynamics and the need to incorporate replication in both time and space when designing sampling regimes. Furthermore, we suggest that embracing, rather than simply controlling for, spatiotemporal variation can reveal meaningful variation for understanding the factors impacting parasitism (e.g. season and host charateristics) which can improve predictions of how wildlife health will respond to change. A free Plain Language Summary can be found within the Supporting Information of this article.

Can eDNA metabarcoding offer a catchment-based approach for biodiversity monitoring?

In previous studies eDNA metabarcoding has been demonstrated as a viable tool for catchment-level biodiversity sampling in rivers (Deiner et al. 2016). However, questions still remain over the appropriate sampling protocol for large spatial scale sampling. River reaches are composed of multiple habitats with species composition varying from one to the next (Costa and Melo 2007). Therefore, how many spatial replicates are needed to reliably represent the river network? Is the previously used approach to sample at every river confluence (Deiner et al. 2016) sufficient or is more needed? These questions were addressed using a case study in the headwaters of the Cound Brook, a tributary to the River Severn in Shropshire, UK. Two sub-catchments of the Cound Brook were used. One sub-catchment had a sample taken at the most downstream point before the confluence. Additionally, a sample at the upstream extent of the same sub-catchment was taken to estimate any correlation between the species found at the beginning of the river reach and at the end. Another sub-catchment also had the same up- and downstream sample design. However, in between was a systemic sampling regime every 500 m. This is to test if increasing the spatial resolution gave significantly different results to the sparser sampling regime. At each sample location, a 1 L water sample was sequentially filtered through membranes of three different mesh sizes: 5µm, 0.45µm and 0.2µm. Sequential filtering was performed because DNA resides in two forms in the environment (Civade et al. 2017), within whole cells (cellular DNA) and outside of cells (extracellular). The theory is that the coarser filters predominantly collect cellular DNA and the finer filters collect predominantly extracellular DNA of increasingly smaller fragment lengths. Consequently, sequential filtering could represent DNA degradation in the environment (Fig. 1). Also, Turner et al. 2014 suggested that the larger particles could determine very recent or local organisms. Therefore, we hypothesised that the DNA collected by the coarser filters would represent local diversity and the DNA collected by the finer filters would reflect biodiversity further upstream. Initial results suggest sequential filtering through the 5µm and 0.45µm filters caught detectable levels of eDNA where the 0.2µm did not catch enough to show up through gel electrophoresis. The relevance of the initial finding suggests that if we only used a 5µm filter the data collected at 0.45µm could have been discarded. Further investigations of any differences in species compositions between filters and the relationships to other sampling locations is still to be determined. This ongoing research is intended to determine the appropriate sampling protocol for a large-scale biodiversity assessment regime combining eDNA metabarcoding and species distribution modelling.

Sediment eDNA Metabarcoding for monitoring impacts from offshore oil extraction

Routine biological monitoring of the areas affected by offshore oil drilling and extraction is critical for ensuring proper environmental management. In addition to sufficient knowledge of the ecosystem affected, formalised e.g. as biotic indices of indicator species, adequate temporal and spatial resolution is also required, to provide accurate information. As already demonstrated in several types of environments, environmental DNA (eDNA) metabarcoding offers an attractive alternative to current morphology-based assessments, including for impacts of oil extraction or spills. We have recently studied the influence of different experimental strategies on the accuracy of marine sediment metabarcoding, suggesting minimum criteria for technical and spatial replication (Hestetun et al. 2020). Here, we aim to evaluate the predictive power of this strategy, through agreement with assessments based on physicochemical measurements and current bioindicators. To this end, we targeted the metazoan, and total eukaryotic benthic communities, using COI and 18S V1-V2 markers, respectively. Sampled sites ranged from high to low impacts. The studied areas were located near active production installations and reference sites on the Norwegian continental shelf, in the North Sea and Barents Sea. As a proxy for accumulated impact, we developed a simple physicochemical pressure index (PI) based on total hydrocarbons, PAH16, barium and copper, all of which agreed well with impact reported from recent routine monitoring. Alpha diversity of both molecular datasets, as well as of morphology data, correlated strongly with this PI. However, the correlation was stronger yet with the macroinvertebrate-based Norwegian Sensitivity Index (NSI) derived from COI metabarcoding data, which also agreed well with NSI values derived from morphology-based monitoring. We also identified a set of bioindicator taxa from each of the two metabarcoding datasets, used to develop two novel metabarcoding-based biotic indeces. Using cross-validation, we demonstrated that predictions based on these indeces agreed well with PI. Predictive performance was better, and similar to NSI, for the COI-based index, but also high for the 18S-based version. In conclusion, this study demonstrates how de novo biotic indices can be developed, that perform comparably to existing biotic indices. We are confident that, using a larger set of samples, performance can be improved beyond that of current monitoring practices. Thanks to the reduced costs of eDNA analysis in comparison to morphological identifiation, this would also pave the way for improved spatial and temporal resolution employed in routine environmental monitoring. In doing so, it can also provide valuable raw data for improving our understanding of benthic ecology, biodiversity and its sensitivity to anthropogenic pressures.

Time-for-space substitution in N-mixture models for estimating population trends: a simulation-based evaluation

N-mixture models usually rely on a meta-population design, in which repeated counts of individuals in multiple sampling locations are obtained over time. The time-for-space substitution (TSS) in N-mixture models allows to estimate population abundance and trend of a single population, without spatial replication. This application could be of great interest in ecological studies and conservation programs; however, its reliability has only been evaluated on a single case study. Here we perform a simulation-based evaluation of this particular application of N-mixture modelling. We generated count data, under 144 simulated scenarios, from a single population surveyed several times per year and subject to different dynamics. We compared simulated abundance and trend values with TSS estimates. TSS estimates are overall in good agreement with real abundance. Trend and abundance estimation is mainly affected by detection probability and population size. After evaluating the reliability of TSS, both against real world data, and simulations, we suggest that this particular application of N-mixture model could be reliable for monitoring abundance in single populations of rare or difficult to study species, in particular in cases of species with very narrow geographic ranges, or known only for few localities.

FeatherFlame: An Arduino-Based Thermocouple Datalogging System to Record Wildland Fire Flame Temperatures in Agris

Rangeland scientists have long relied on thermocouples for measuring temperature, especially in agris—in the field, under the extreme conditions of wildland fire. But the electronics required to sense and record thermocouple data remain expensive to both purchase and protect from exposure to heat and flames. Open-source, do-it-yourself (DIY) electronics platforms such as Arduino are increasingly popular among ecologists, and have been shown to perform as well as proprietary commercial systems when recording thermocouple data. The FeatherFlame system is a reliable, low-cost solution to sampling wildland fire, ranging from US$240–490 for 1–6 thermocouple sensors, including all fire protection equipment. The low cost and multi-sensor capacity facilitates spatial replication, which allows fire ecologists to measure and report meaningful data on rate of spread and calculate fire intensity.

Testing a highly replicable and standardized method to rapidly assess seed removal probabilities

Seed removal can result in either seed predation or dispersal and is therefore an indicator of important ecosystem functions. To better understand how these variable processes are affected by environmental changes, rapid and reliable assessments with high temporal and spatial replication are needed. We address this need by testing the application of a rapid ecosystem function assessment (REFA) method to investigate seed removal in habitats with differing land use intensity. We recorded seed removal hourly over eight hours at 301 sites in five habitat types in three urban regions in Germany. We calculated seed removal rates per sampling period, traditionally used in seed removal studies, as well as instantaneous seed removal probabilities based on hourly sampling. Across regions, seed removal probabilities and rates were lowest in arable fields, a habitat type with high land-use intensity. Except in urban sealed areas, temperature had a negative effect on seed removal. Additional Cox hazard regressions suggest invertebrates as the main seed removing animals in arable fields, whereas vertebrates were likely removers in other habitat types. We confirm that seed removal is strongly negatively affected by human disturbance, indicating that the tested method is appropriate in different settings. We were able to recognize patterns in highly variable data and the method also has the advantages of low cost, high replication and high temporal resolution. However, there is a trade-off between the high temporal-resolution of instantaneous seed removal probabilities and the sampling effort, but adjustments in the standardized setup can be made depending on the study. To further utilize the extensive data collection in the REFA method, we propose to combine instantaneous seed removal probabilities, seed removal rates and Cox hazard regressions of seed removal to provide complementary information on the extent and temporal patterns of seed removal and indications about potential seed removing guilds. Keywords: Seed predation, seed dispersal, seed removal, granivore, REFA

High‐density camera trap grid reveals lack of consistency in detection and capture rates across space and time

AbstractCounts of independent photo events from camera traps are commonly used to make inference about species occupancy, the density of unmarked populations, and the relative abundance of species across time and space. These applications rest on the untested assumption that data collected from individual cameras are representative of the landscape location in which they are placed, and that nearby cameras would record similar data when any additional micro‐site differences are accounted for. We established a high‐density camera trapping grid (100 × 100 m; 27 cameras) in Virginia, USA, to explicitly test these assumptions, investigating variation in capture rates and detection probabilities for a range of terrestrial mammals during four 2‐month seasonal surveys. Despite controlling for numerous habitat and placement factors, we documented, across all 5 focal species, large ranges and coefficients of variation in both capture rate and detection probabilities, which were similar to those seen across 2 sets of independent forest sampling sites from a larger, more typical camera trap sampling design. We also documented a lack of spatial autocorrelation in capture rate at any distance. Measured local covariates relevant to the camera viewshed (stem density, camera height, log presence, effective detection distance [EDD], total dbh of oak trees) rarely explained any significant portion of observed variation in capture rates or detection probabilities across the grid. The influence of EDD, measured here for the first time for individual camera stations, was inconsistently important and varied in direction of effect depending on species and season. Our study indicates single‐camera stations may fail to sample animal presence and frequency of use in a robust and repeatable way, primarily resulting from the influence of both idiosyncrasies in animal movement and measured and unknown micro‐site characteristics. We recommend spatial replication within sites (e.g., small‐scale shifting of cameras or use of multiple stations) should be considered to minimize impacts of relevant micro‐site characteristics, some of which may be difficult to identify.

Novel Insights to Be Gained From Applying Metacommunity Theory to Long-Term, Spatially Replicated Biodiversity Data

Global loss of biodiversity and its associated ecosystem services is occurring at an alarming rate and is predicted to accelerate in the future. Metacommunity theory provides a framework to investigate multi-scale processes that drive change in biodiversity across space and time. Short-term ecological studies across space have progressed our understanding of biodiversity through a metacommunity lens, however, such snapshots in time have been limited in their ability to explain which processes, at which scales, generate observed spatial patterns. Temporal dynamics of metacommunities have been understudied, and large gaps in theory and empirical data have hindered progress in our understanding of underlying metacommunity processes that give rise to biodiversity patterns. Fortunately, we are at an important point in the history of ecology, where long-term studies with cross-scale spatial replication provide a means to gain a deeper understanding of the multiscale processes driving biodiversity patterns in time and space to inform metacommunity theory. The maturation of coordinated research and observation networks, such as the United States Long Term Ecological Research (LTER) program, provides an opportunity to advance explanation and prediction of biodiversity change with observational and experimental data at spatial and temporal scales greater than any single research group could accomplish. Synthesis of LTER network community datasets illustrates that long-term studies with spatial replication present an under-utilized resource for advancing spatio-temporal metacommunity research. We identify challenges towards synthesizing these data and present recommendations for addressing these challenges. We conclude with insights about how future monitoring efforts by coordinated research and observation networks could further the development of metacommunity theory and its applications aimed at improving conservation efforts.

Spatial kernel models capturing field heterogeneity for accurate estimation of genetic potential.

According to Fisher’s principles, an experimental field is typically divided into multiple blocks for local control. Although homogeneity is supposed within a block, this assumption may not be practical for large blocks, such as those including hundreds of plots. In line evaluation trials, which are essential in plant breeding, field heterogeneity must be carefully treated, because it can cause bias in the estimation of genetic potential. To more accurately estimate genotypic values in a large field trial, we developed spatial kernel models incorporating genome-wide markers, which consider continuous heterogeneity within a block and over the field. In the simulation study, the spatial kernel models were robust under various conditions. Although heritability, spatial autocorrelation range, replication number, and missing plots directly affected the estimation accuracy of genotypic values, the spatial kernel models always showed superior performance over the classical block model. We also employed these spatial kernel models for quantitative trait locus mapping. Finally, using field experimental data of bioenergy sorghum lines, we validated the performance of the spatial kernel models. The results suggested that a spatial kernel model is effective for evaluating the genetic potential of lines in a heterogeneous field.

94 President Oral Presentation Pick: Grazing diverse combinations of tanniferous and non-tanniferous legumes: Implications for beef cattle performance and environmental impact

Abstract We tested the effect of increasingly diverse combinations of tanniferous legumes (birdsfoot trefoil-BFT, sainfoin-SF) and alfalfa (ALF) on cattle performance, methane (CH4) emissions and nitrogen (N) balance. Pairs of heifers (401 ± 49.6 kg) grazed three spatial replications of 7 treatments (n = 3/treatment): monocultures (BFT, SF, ALF) and all possible 2- and 3-way choices among strips of these legumes in a completely randomized block design of two 15-d periods during 2 consecutive years. Average daily gains (ADG) of heifers grazing the tanniferous legumes (1.05 kg/d) were 40% greater (P < 0.10) than of heifers grazing ALF (0.74 kg/d) during the first year. Heifers grazing the 3-way choice had greater intakes (10.4 vs 7.8 kg/d; P = 0.064) and ADG (1.21 vs. 0.95 kg/d, P = 0.054) than those grazing monocultures, suggesting a nutritional synergism among legumes. The average CH4 emissions for legume monocultures vs. 2- and 3-way choices was 222 vs. 202 and 162 g/kg BW gain (P > 0.10), respectively. For heifers grazing SF and BFT compared with ALF, blood urea N was less (14.3 and 16.8 vs 20.8 mg/dL; P < 0.05) as were urinary N concentrations (3.7 and 3.5 vs 6.0 g/L; P < 0.05), but fecal N concentrations were greater (34.5 and 35.5 vs 30.5 g/kg, respectively; P < 0.05). Combining both tanniferous legumes (SF-BFT) led to the greatest declines in urinary N (2.24 g/L) and urea-N (1.71 g/L) concentration, suggesting that different types of tannins in different legume species result in associative effects that enhance N economy. In addition, heifers grazing 3-way choices partitioned less N into urine (40.7 vs 50.6%; P = 0.037) and retained more N (36.1 vs 25.2%, P = 0.046) than heifers grazing monocultures. In summary, combinations of tanniferous legumes with alfalfa improved animal performance and reduced environmental impacts relative to monocultures, resulting in a more sustainable approach to beef production in pasture-based finishing systems.

PSV-11 Grazing diverse combination of tanniferous and non-tanniferous legumes: Implications for foraging behavior, performance and hair cortisol in beef cattle

Abstract We tested the effect of increasingly diverse combinations of tanniferous legumes (birdsfoot trefoil-BFT, sainfoin-SF) and alfalfa (ALF) on cattle foraging behavior, performance and hair cortisol concentration. Pairs of heifers (401 ± 49.6 kg) grazed three spatial replications of seven treatments (n = 3/treatment): monocultures (BFT, SF, ALF) and all possible 2- and 3-way choices among strips of these legumes in a completely randomized block design in two 25-d periods during 2 consecutive years. The fewest grazing events occurred in BFT (42.0% of the total scans recorded; P < 0.10), with other treatments ranging between 47.8 (SF-BFT) and 52.6% (ALF-SF) of the total scans recorded. Heifers selected a varied diet, preferring SF over BFT or ALF in 46:27:27 and 70:30 ratios (3- and 2-way choice, respectively) and preferred BFT over ALF (62:38 ratio). All treatments followed similar daily grazing patterns (P >0.10), with two major grazing events (1 hour after sunrise and 3 hours before sunset). No differences among treatments were observed for the number of steps taken, motion index, or percentage of time spent standing (1,600, 5,356, and 45.3%, respectively; P >0.10), suggesting that heifers in choice treatments did not invest extra time in walking, searching or patch-switching activities relative to monoculture treatments. Heifers in the 3-way choice gained more BW (1.27 Kg/d) than in monocultures (1.00 kg/d; P = 0.014), or 2-way choices (0.97 kg/d; P = 0.007), suggesting nutritional synergism among legumes in the treatment of greatest diversity. No differences in hair cortisol concentration were observed among treatments, with values ranging between 1.40 (BFT) and 2.12 ng/g (3-way choice) (P >0.10). Thus, forage diversity enhanced animal performance, likely driven by interactions among condensed tannins and dietary protein, without affecting hair cortisol levels or grazing efficiency, explained by the spatial arrangement (strips) of the forage species presented.

Accounting for food web dynamics when assessing the impact of mesopredator control on declining prey populations

Abstract Increasing populations of mesopredators are suspected to cause declines in vulnerable wildlife to the extent that mesopredator decimation actions (culling) have become commonplace. Design constraints, especially a lack of spatial replication, often hamper the assessment of the impact of such actions. However, extensive temporal replication (i.e. time series) and accounting for potentially confounding variables may alleviate this problem. In alpine‐arctic tundra, the red fox Vulpes vulpes is increasing, while many bird species are declining, likely due to increased predation. Here, we assessed the impact of a long‐term (12‐year) and spatially extensive (~3,500 km2) red fox culling action on the red‐listed willow ptarmigan Lagopus lagopus in the Norwegian Arctic. Ptarmigan populations were monitored annually in the impact area and in an adjacent no‐action area, including a 5‐year period before the action commenced. While logistical constraints prohibited monitoring of red fox population densities, the number of culled foxes and three influential food web covariates were monitored after the onset of the culling action. A Before‐After‐Control‐Impact‐Paired‐Series (BACIPS) analysis without food web covariates indicated that red fox culling curbed the decline of the population in the impact area, and that ptarmigan population density became ~25% higher than in the reference area. Spatially and temporally variable drivers within the food web confounded the simple BACIPS analysis. Accounting for three food web drivers as covariates in a linear mixed model after the onset of action, yielded a more unbiased impact estimate that amounted to ~40% higher ptarmigan population density (4.3 more ptarmigan/km2) in the red fox impact area. Synthesis and applications. We provide the first evidence of the role of the recent expansion of red fox in the decline of bird populations in tundra. We also show that red fox culling may be able to curb such declines, given that management actions are large scale and long term. As mesopredator culling campaigns are often expensive and controversial, it is important that their impacts are accurately assessed. We demonstrate that the accuracy of impact assessments can be profoundly increased by monitoring drivers of food web dynamics that impinge on the target species so that such drivers can be included as covariates in the analysis. This applies in particular to declining bird populations in boreal and arctic food webs ruled by strong multi‐annual interaction cycles.

Leveraging spatial information to forecast nonlinear ecological dynamics

Abstract There has been a recent demand for forecasting in ecology, particularly in the field of ecosystem management. Empirical dynamic modelling (EDM), an equation‐free nonlinear forecasting method, is receiving growing attention, but it requires long time series to produce accurate predictions. Though most ecological time series are short, spatial replicates are often available. Here we explore how utilizing available spatial data can improve our ability to forecast ecological dynamics. There are several ways to incorporate spatial information into EDM and not all have been applied in ecology. We compare spatial EDM approaches used in ecology and physics and introduce a flexible Bayesian model that makes use of prior movement information. We test these methods on simulated data generated with three population dynamics models with varying levels of complexity, time series length, spatial symmetry and heterogeneity. Adding spatial data generally improves accuracy, though the best method depends on the spatial process. We applied the methods to empirical fisheries data, highlighting the complexity of real population dynamics. Leveraging spatial data is an effective way to overcome the problem of short ecological time series. Since the best forecasting method depends on the underlying dynamics, we suggest that users apply several in concert and that this may be useful in identifying spatial heterogeneity in dynamics.

A learning network approach to resolve conservation challenges in the Ngorongoro Conservation Area

The Ngorongoro Conservation Area (NCA) is a protected area and UNESCO World Heritage Site and part of the Serengeti‐Ngorongoro Biosphere reserve in northern Tanzania. It is famous for its large volcanic caldera, unique cultural heritage, early hominid fossils and significant wildlife populations. NCA has been managed as a multiple land‐use area since 1959, a designation intended to foster a harmonious coexistence between indigenous residents and wildlife (Goldstein, 2004).

Ecoimmunology at spatial scales.

Becker, D. J., Albery, G. F., Kessler, M. K., Lunn, T. J., Falvo, C. A., Czirják, G. Á., Martin, L. B., & Plowright, R. K. (2020). Macroimmunology: The drivers and consequences of spatial patterns in wildlife immune defence. Journal of Animal Ecology, 89, 972-995. Ecoimmunology seeks to identify and explain natural variation in immune function. Most research so far has focused on differences among individuals within populations, which are often driven by trade-offs in resource allocation between energetically costly immunity and competing processes such as reproduction. In their review article, Becker et al. (2020) have proposed a framework to explicitly address habitat- and population-level differences in wildlife immune phenotypes. Termed macroimmunology, this concept integrates principles from ecoimmunology and macroecology. Becker et al. (2020) have highlighted three non-mutually exclusive habitat features that are likely to vary at spatial scales and influence immune function: (a) parasite pressure, (b) abiotic and biotic factors and (c) anthropogenic changes. However, a large and robust body of literature suitable for synthesis to detect macroimmunology patterns and effect sizes is not yet available. Through their systematic review and critical assessment, Becker et al. (2020) identified common problems in existing research that hinders spatial inferences, such as a need for spatial replication in study design and statistical analyses that account for spatial dependence. Overall, macroimmunology has the potential to identify and even predict spatial patterns in immune phenotypes that form the mechanistic underpinnings of important wildlife disease processes, and this review represents an important step to realizing these goals.

Designing monitoring protocols to measure population trends of threatened insects: A case study of the cryptic, flightless grasshopper Brachaspis robustus.

Statistically robust monitoring of threatened populations is essential for effective conservation management because the population trend data that monitoring generates is often used to make decisions about when and how to take action. Despite representing the highest proportion of threatened animals globally, the development of best practice methods for monitoring populations of threatened insects is relatively uncommon. Traditionally, population trend data for the Nationally Endangered New Zealand grasshopper Brachaspis robustus has been determined by counting all adults and nymphs seen on a single ~1.5 km transect searched once annually. This method lacks spatial and temporal replication, both of which are essential to overcome detection errors in highly cryptic species like B. robustus. It also provides no information about changes in the grasshopper’s distribution throughout its range. Here, we design and test new population density and site occupancy monitoring protocols by comparing a) comprehensive plot and transect searches at one site and b) transect searches at two sites representing two different habitats (gravel road and natural riverbed) occupied by the species across its remaining range. Using power analyses, we determined a) the number of transects, b) the number of repeated visits and c) the grasshopper demographic to count to accurately detect long term change in relative population density. To inform a monitoring protocol design to track trends in grasshopper distribution, we estimated the probability of detecting an individual with respect to a) search area, b) weather and c) the grasshopper demographic counted at each of the two sites. Density estimates from plots and transects did not differ significantly. Population density monitoring was found to be most informative when large adult females present in early summer were used to index population size. To detect a significant change in relative density with power > 0.8 at the gravel road habitat, at least seventeen spatial replicates (transects) and four temporal replicates (visits) were required. Density estimates at the natural braided river site performed poorly and likely require a much higher survey effort. Detection of grasshopper presence was highest (pg > 0.6) using a 100 m x 1 m transect at both sites in February under optimal (no cloud) conditions. At least three visits to a transect should be conducted per season for distribution monitoring. Monitoring protocols that inform the management of threatened species are crucial for better understanding and mitigation of the current global trends of insect decline. This study provides an exemplar of how appropriate monitoring protocols can be developed for threatened insect species.

Character displacement in the midst of background evolution in island populations of Anolis lizards: A spatiotemporal perspective

Negative interactions between species can generate divergent selection that causes character displacement. However, other processes cause similar divergence. We use spatial and temporal replication across island populations of Anolis lizards to assess the importance of negative interactions in driving trait shifts. Previous work showed that the establishment of Anolis sagrei on islands drove resident Anolis carolinensis to perch higher and evolve larger toepads. To further test the interaction's causality and predictability, we resurveyed a subset of islands nine years later. Anolis sagrei had established on one island between surveys. We found that A. carolinensis on this island now perch higher and have larger toepads. However, toepad morphology change on this island was not distinct from shifts on six other islands whose Anolis community composition had not changed. Thus, the presence of A. sagrei only partly explains A. carolinensis trait variation across space and time. We also found that A. carolinensis on islands with previously established A. sagrei now perch higher than a decade ago, and that current A. carolinensis perch height is correlated with A. sagrei density. Our results suggest that character displacement likely interacts with other evolutionary processes in this system, and that temporal data are key to detecting such interactions.

Spatial replication and habitat context matters for assessments of tropical biodiversity using acoustic indices

Approaches to characterise and monitor biodiversity based on the sound signals of ecosystems have become popular in landscape ecology and biodiversity conservation. However, to date, validation studies of how well acoustic indices reflect observed biodiversity patterns have often relied on low levels of either spatial or temporal replication, while focussing on habitats with similar underlying anthropological and geophysical sound characteristics. For acoustic indices to be broadly applicable to biodiversity monitoring, their capacity to measure the ecological facets of soundscapes must be robust to these potential sources of bias. Using two contrasting recording approaches, we examined the efficacy of four commonly used acoustic indices to reflect patterns of observed bird species richness across a tropical forest degradation gradient in Northeast Borneo. The gradient comprised intact and logged forests, riparian forests, remnants, and oil palm plantations, thus providing a highly variable anthrophonic and geophonic soundscape. We compared the degree to which acoustic indices derived from automated versus point count recording methods detected variation in inter-habitat species richness, as well as their capacity to capture changes in species diversity as a consequence of forest degradation quantified by high-resolution LiDAR derived forest canopy heights. We found Acoustic Diversity Index was associated with forest canopy height as measured by both automated recorders and recordings from point counts, whereas the association between canopy height and Acoustic Complexity Index was only detected using point count recordings. For both types of recordings, Acoustic Complexity Index exhibited the strongest relationship with observed bird richness in old growth and logged forest, whereas Acoustic Diversity was not linked, suggesting avian richness does not drive its association with canopy height. No acoustic indices were associated with observed bird richness in oil palm riparian areas. Our findings underscore the potential utility of soundscape approaches to characterise biodiversity patterns in degraded tropical landscapes, and may be used as a proxy for human inventories of bird communities. However, we also show that for acoustic indices to be effective on landscape-wide studies of environmental gradients, adequate spatial replication is required, and care must be taken to control for non-target elements of soundscapes in different habitats.

Using a participatory impact assessment framework to evaluate a community‐led mangrove and fisheries conservation approach in West Kalimantan, Indonesia

Abstract Community‐based conservation has been identified as a solution to biodiversity loss, climate change and the reduction of rural poverty. The heterogeneity in social and economic inequalities often acts as a barrier to community engagement in resource management and further inhibits the distributional equity of social and ecological outcomes. This study presents a participatory impact assessment (PIA) framework that evaluated the outcomes of a cross‐sector community‐led conservation initiative. Community members involved in the programme identified activities and outcomes for the conservation cooperative (CC), ranking the influence of the former on the latter as well as their daily life through multiple focus group discussions (FGDs). Participants were asked to rank the impact of activities on outcomes and the scale of the outcome which was totalled to identify the most impactful programme activities and outcomes during the project period. Community members reported improved income, health, education and the creation of a locally led natural resource management system. Members also reported improved crab harvest rates and reduced mangrove deforestation. Environmental outcomes identified by community members through the PIA were verified through a secondary spatial analysis and mud crab independent fisheries monitoring. The results support the hypothesis that environmental non‐governmental organizations (NGOs) need to consider a multi‐dimensional view of human well‐being, and that cross‐sector integrated interventions may be effective at improving multiple outcomes. Future steps should focus on spatial replication of the CC programme which will provide further insights by testing for differences in outcomes between villages, how those are impacted by pre‐existing social and ecological systems and comparing outcomes between control sites that did not receive interventions. A free Plain Language Summary can be found within the Supporting Information of this article.

A novel experimental approach to investigate the potential for behavioural change in sharks in the context of depredation

Baited video systems have been widely used to assess the relative abundance and diversity of sharks in locations around the world, however they provide limited information on behaviour. We developed and pilot tested a novel experimental approach to investigate whether repeated deployments of baited video systems in the same location could generate quantitative data on shark behavioural patterns, in the context of shark depredation (where sharks consume hooked fish). Specifically, we sought to test whether repeated exposure to boats and food in the same location would lead to a change in the arrival time and first feeding time of sharks, over a short timescale. We used the Ningaloo Marine Park (NMP) in Western Australia, a location where higher shark depredation rates have been identified in consistently fished areas, as a case study. A modified Baited Remote Underwater Video (BRUV) system was repeatedly deployed at two fished sites and two sites within a no-take marine reserve in the NMP, over six consecutive days, to mimic repeated recreational fishing and the availability of hooked fish for sharks to depredate. This approach was designed to investigate and disentangle the potential role of changes in behaviour versus variation in shark abundance, as a mechanism for how and why shark depredation can occur. Here, we report preliminary results from this methodological approach, where time of arrival and time of first feeding declined markedly in the fished site over 6 days of BRUV deployments, compared to the control site in the no-take marine reserve. A greater number of individuals from four carcharhinid species were observed at the fished site, compared to only three individuals from two species in the no-take marine reserve. The preliminary results from pilot testing of this novel experimental approach suggest that, with further modifications to identify individual sharks, and a greater spatial and temporal replication of sampling, it may be possible to identify behavioural changes occurring in sharks in the context of shark depredation. Understanding this mechanism can bring important benefits for fishers and managers, as it can lead to modifications in fishing methods designed at reducing the occurrence of behavioural changes in sharks, and thus mitigating shark depredation.