A suite of essential biodiversity variables for detecting critical biodiversity change

Ecosystem condition emerges from an ecological equation of state applied to North American tree communities

Ecosystems represent the largest scales of biological organization and shape the ecology and evolution of genes, populations, species, and communities. Yet we lack an understanding of the key properties of ecosystems-the state variables-that must be tracked to predict changes in ecosystem condition through time,1,2,3 instead commonly relying on reference states.4,5 A recently published ecological equation of state demonstrated a strong relationship between biomass, species richness, organism abundance, and productivity, suggesting the untested possibility that this relationship may systematically vary under ecological disturbance (i.e., vary with ecosystem condition).6 To test this idea, we investigate how the performance of the ecological equation of state relates to expected ecosystem condition (derived from protected area data) using satellite-derived proxies for the forests of the conterminous USA. We found that, despite the noise introduced by the use of satellite-derived proxies, the performance of the ecological equation of state in predicting biomass varied systematically with expected ecosystem condition. Moreover, differences in equation performance could be used to identify areas with different expected ecosystem condition. This differential performance was stronger in the equation of state than in correlative models fit to the same data, though similar to patterns seen in the relationship between productivity and biomass. These findings suggest deeper underlying regularities linking ecosystem condition and state variables and the potential to break ecology's dependence on reference states. Further investigation of these relationships may reveal new principles of ecosystem dynamics, which are vital to informing global biodiversity conservation efforts.

Evaluating the feasibility of automating dataset retrieval for biodiversity monitoring

Aim

Effective management strategies for conserving biodiversity and mitigating the impacts of global change rely on access to comprehensive and up-to-date biodiversity data. However, manual search, retrieval, evaluation, and integration of this information into databases present a significant challenge to keeping pace with the rapid influx of large amounts of data, hindering its utility in contemporary decision-making processes. Automating these tasks through advanced algorithms holds immense potential to revolutionize biodiversity monitoring.

Innovation

In this study, we investigate the potential for automating the retrieval and evaluation of biodiversity data from Dryad and Zenodo repositories. We have designed an evaluation system based on various criteria, including the type of data provided and its spatio-temporal range, and applied it to manually assess the relevance for biodiversity monitoring of datasets retrieved through an application programming interface (API). We evaluated a supervised classification to identify potentially relevant datasets and investigate the feasibility of automatically ranking the relevance. Additionally, we applied the same appraoch on a scientific literature source, using data from Semantic Scholar for reference. Our evaluation centers on the database utilized by a national biodiversity monitoring system in Quebec, Canada.

Main conclusions

We retrieved 89 (55%) relevant datasets for our database, showing the value of automated dataset search in repositories. Additionally, we find that scientific publication sources offer broader temporal coverage and can serve as conduits guiding researchers toward other valuable data sources. Our automated classification system showed moderate performance in detecting relevant datasets (with an F-score up to 0.68) and signs of overfitting, emphasizing the need for further refinement. A key challenge identified in our manual evaluation is the scarcity and uneven distribution of metadata in the texts, especially pertaining to spatial and temporal extents. Our evaluative framework, based on predefined criteria, can be adopted by automated algorithms for streamlined prioritization, and we make our manually evaluated data publicly available, serving as a benchmark for improving classification techniques.

Towards a toolkit for global insect biodiversity monitoring

Insects are the most diverse group of animals on Earth, yet our knowledge of their diversity, ecology and population trends remains abysmally poor. Four major technological approaches are coming to fruition for use in insect monitoring and ecological research-molecular methods, computer vision, autonomous acoustic monitoring and radar-based remote sensing-each of which has seen major advances over the past years. Together, they have the potential to revolutionize insect ecology, and to make all-taxa, fine-grained insect monitoring feasible across the globe. So far, advances within and among technologies have largely taken place in isolation, and parallel efforts among projects have led to redundancy and a methodological sprawl; yet, given the commonalities in their goals and approaches, increased collaboration among projects and integration across technologies could provide unprecedented improvements in taxonomic and spatio-temporal resolution and coverage. This theme issue showcases recent developments and state-of-the-art applications of these technologies, and outlines the way forward regarding data processing, cost-effectiveness, meaningful trend analysis, technological integration and open data requirements. Together, these papers set the stage for the future of automated insect monitoring. This article is part of the theme issue 'Towards a toolkit for global insect biodiversity monitoring'.

Effects of water temperature on freshwater macroinvertebrates: a systematic review

Water temperature is one of the main abiotic factors affecting the structure and functioning of aquatic ecosystems and its alteration can have important effects on biological communities. Macroinvertebrates are excellent bio-indicators and have been used for decades to assess the status of aquatic ecosystems as a result of environmental stresses; however, their responses to temperature are poorly documented and have not been systematically evaluated. The aims of this review are: (i) to collate and summarize responses of freshwater macroinvertebrates to different temperature conditions, comparing the results of experimental and theoretical studies; (ii) to understand how the focus of research on the effects of temperature on macroinvertebrates has changed during the last 51 years; and (iii) to identify research gaps regarding temperature responses, ecosystem types, organism groups, spatiotemporal scales, and geographical regions to suggest possible research directions. We performed a comparative assessment of 223 publications that specifically consider freshwater macroinvertebrates and address the effects of temperature. Short-term studies performed in the laboratory and focusing on insects exposed to a range of temperatures dominated. Field studies were carried out mainly in Europe, at catchment scale and almost exclusively in rivers; they mainly investigated responses to water thermal regime at the community scale. The most frequent biological responses tested were growth rate, fecundity and the time and length of emergence, whereas ecological responses mainly involved composition, richness, and distribution. Thermal research on freshwater macroinvertebrates has undergone a shift since the 2000s when studies involving extended spatiotemporal scales and investigating the effects of global warming first appeared. In addition, recent studies have considered the effects of temperature at genetic and evolutionary scales. Our review revealed that the effects of temperature on macroinvertebrates are manifold with implications at different levels, from genes to communities. However, community-level physiological, phenological and fitness responses tested on individuals or populations should be studied in more detail given their macroecological effects are likely to be enhanced by climate warming. In addition, most field studies at regional scales have used air temperature as a proxy for water temperature; obtaining accurate water temperature data in future studies will be important to allow proper consideration of the spatial thermal heterogeneity of water bodies and any effects on macroinvertebrate distribution patterns. Finally, we found an uneven number of studies across different ecosystems and geographic areas, with lentic bodies and regions outside the West underrepresented. It will also be crucial to include macroinvertebrates of high-altitude and tropical areas in future work because these groups are most vulnerable to climate warming for multiple reasons. Further studies on temperature-macroinvertebrate relationships are needed to fill the current gaps and facilitate appropriate conservation strategies for freshwater ecosystems in an anthropogenic-driven era.

Global genetic diversity status and trends: towards a suite of Essential Biodiversity Variables (EBVs) for genetic composition

Biodiversity underlies ecosystem resilience, ecosystem function, sustainable economies, and human well‐being. Understanding how biodiversity sustains ecosystems under anthropogenic stressors and global environmental change will require new ways of deriving and applying biodiversity data. A major challenge is that biodiversity data and knowledge are scattered, biased, collected with numerous methods, and stored in inconsistent ways. The Group on Earth Observations Biodiversity Observation Network (GEO BON) has developed the Essential Biodiversity Variables (EBVs) as fundamental metrics to help aggregate, harmonize, and interpret biodiversity observation data from diverse sources. Mapping and analyzing EBVs can help to evaluate how aspects of biodiversity are distributed geographically and how they change over time. EBVs are also intended to serve as inputs and validation to forecast the status and trends of biodiversity, and to support policy and decision making. Here, we assess the feasibility of implementing Genetic Composition EBVs (Genetic EBVs), which are metrics of within‐species genetic variation. We review and bring together numerous areas of the field of genetics and evaluate how each contributes to global and regional genetic biodiversity monitoring with respect to theory, sampling logistics, metadata, archiving, data aggregation, modeling, and technological advances. We propose four Genetic EBVs: (i) Genetic Diversity; (ii) Genetic Differentiation; (iii) Inbreeding; and (iv) Effective Population Size (N_e). We rank Genetic EBVs according to their relevance, sensitivity to change, generalizability, scalability, feasibility and data availability. We outline the workflow for generating genetic data underlying the Genetic EBVs, and review advances and needs in archiving genetic composition data and metadata. We discuss how Genetic EBVs can be operationalized by visualizing EBVs in space and time across species and by forecasting Genetic EBVs beyond current observations using various modeling approaches. Our review then explores challenges of aggregation, standardization, and costs of operationalizing the Genetic EBVs, as well as future directions and opportunities to maximize their uptake globally in research and policy. The collection, annotation, and availability of genetic data has made major advances in the past decade, each of which contributes to the practical and standardized framework for large‐scale genetic observation reporting. Rapid advances in DNA sequencing technology present new opportunities, but also challenges for operationalizing Genetic EBVs for biodiversity monitoring regionally and globally. With these advances, genetic composition monitoring is starting to be integrated into global conservation policy, which can help support the foundation of all biodiversity and species' long‐term persistence in the face of environmental change. We conclude with a summary of concrete steps for researchers and policy makers for advancing operationalization of Genetic EBVs. The technical and analytical foundations of Genetic EBVs are well developed, and conservation practitioners should anticipate their increasing application as efforts emerge to scale up genetic biodiversity monitoring regionally and globally.

Supporting in situ conservation of the genetic diversity of crop wild relatives using genomic technologies

The last decade has witnessed huge technological advances in genomics, particularly in DNA sequencing. Here, we review the actual and potential application of genomics in supporting in situ conservation of crop wild relatives (CWRs). In addition to helping in prioritization of protection of CWR taxa and in situ conservation sites, genome analysis is allowing the identification of novel alleles that need to be prioritized for conservation. Genomics is enabling the identification of potential sources of important adaptive traits that can guide the establishment or enrichment of in situ genetic reserves. Genomic tools also have the potential for developing a robust framework for monitoring and reporting genome‐based indicators of genetic diversity changes associated with factors such as land use or climate change. These tools have been demonstrated to have an important role in managing the conservation of populations, supporting sustainable access and utilization of CWR diversity, enhancing accelerated domestication of new crops and forensic genomics thus preventing misappropriation of genetic resources. Despite this great potential, many policy makers and conservation managers have failed to recognize and appreciate the need to accelerate the application of genomics to support the conservation and management of biodiversity in CWRs to underpin global food security. Funding and inadequate genomic expertise among conservation practitioners also remain major hindrances to the widespread application of genomics in conservation.

Recommendations for connecting molecular sequence and biodiversity research infrastructures through ELIXIR

Threats to global biodiversity are increasingly recognised by scientists and the public as a critical challenge. Molecular sequencing technologies offer means to catalogue, explore, and monitor the richness and biogeography of life on Earth. However, exploiting their full potential requires tools that connect biodiversity infrastructures and resources. As a research infrastructure developing services and technical solutions that help integrate and coordinate life science resources across Europe, ELIXIR is a key player. To identify opportunities, highlight priorities, and aid strategic thinking, here we survey approaches by which molecular technologies help inform understanding of biodiversity. We detail example use cases to highlight how DNA sequencing is: resolving taxonomic issues; Increasing knowledge of marine biodiversity; helping understand how agriculture and biodiversity are critically linked; and playing an essential role in ecological studies. Together with examples of national biodiversity programmes, the use cases show where progress is being made but also highlight common challenges and opportunities for future enhancement of underlying technologies and services that connect molecular and wider biodiversity domains. Based on emerging themes, we propose key recommendations to guide future funding for biodiversity research: biodiversity and bioinformatic infrastructures need to collaborate closely and strategically; taxonomic efforts need to be aligned and harmonised across domains; metadata needs to be standardised and common data management approaches widely adopted; current approaches need to be scaled up dramatically to address the anticipated explosion of molecular data; bioinformatics support for biodiversity research needs to be enabled and sustained; training for end users of biodiversity research infrastructures needs to be prioritised; and community initiatives need to be proactive and focused on enabling solutions. For sequencing data to deliver their full potential they must be connected to knowledge: together, molecular sequence data collection initiatives and biodiversity research infrastructures can advance global efforts to prevent further decline of Earth's biodiversity.

Recommendations for connecting molecular sequence and biodiversity research infrastructures through ELIXIR

Threats to global biodiversity are increasingly recognised by scientists and the public as a critical challenge. Molecular sequencing technologies offer means to catalogue, explore, and monitor the richness and biogeography of life on Earth. However, exploiting their full potential requires tools that connect biodiversity infrastructures and resources. As a research infrastructure developing services and technical solutions that help integrate and coordinate life science resources across Europe, ELIXIR is a key player. To identify opportunities, highlight priorities, and aid strategic thinking, here we survey approaches by which molecular technologies help inform understanding of biodiversity. We detail example use cases to highlight how DNA sequencing is: resolving taxonomic issues; Increasing knowledge of marine biodiversity; helping understand how agriculture and biodiversity are critically linked; and playing an essential role in ecological studies. Together with examples of national biodiversity programmes, the use cases show where progress is being made but also highlight common challenges and opportunities for future enhancement of underlying technologies and services that connect molecular and wider biodiversity domains. Based on emerging themes, we propose key recommendations to guide future funding for biodiversity research: biodiversity and bioinformatic infrastructures need to collaborate closely and strategically; taxonomic efforts need to be aligned and harmonised across domains; metadata needs to be standardised and common data management approaches widely adopted; current approaches need to be scaled up dramatically to address the anticipated explosion of molecular data; bioinformatics support for biodiversity research needs to be enabled and sustained; training for end users of biodiversity research infrastructures needs to be prioritised; and community initiatives need to be proactive and focused on enabling solutions. For sequencing data to deliver their full potential they must be connected to knowledge: together, molecular sequence data collection initiatives and biodiversity research infrastructures can advance global efforts to prevent further decline of Earth's biodiversity.

Using Airborne Laser Scanning to Characterize Land-Use Systems in a Tropical Landscape Based on Vegetation Structural Metrics

Many Indonesian forests have been cleared and replaced by fast-growing cash crops (e.g., oil palm and rubber plantations), altering the vegetation structure of entire regions. Complex vegetation structure provides habitat niches to a large number of native species. Airborne laser scanning (ALS) can provide detailed three-dimensional information on vegetation structure. Here, we investigate the potential of ALS metrics to highlight differences across a gradient of land-use management intensities in Sumatra, Indonesia. We focused on tropical rainforests, jungle rubber, rubber plantations, oil palm plantations and transitional lands. Twenty-two ALS metrics were extracted from 183 plots. Analysis included a principal component analysis (PCA), analysis of variance (ANOVAs) and random forest (RF) characterization of the land use/land cover (LULC). Results from the PCA indicated that a greater number of canopy gaps are associated with oil palm plantations, while a taller stand height and higher vegetation structural metrics were linked with rainforest and jungle rubber. A clear separation in metrics performance between forest (including rainforest and jungle rubber) and oil palm was evident from the metrics pairwise comparison, with rubber plantations and transitional land behaving similar to forests (rainforest and jungle rubber) and oil palm plantations, according to different metrics. Lastly, two RF models were carried out: one using all five land uses (5LU), and one using four, merging jungle rubber with rainforest (4LU). The 5LU model resulted in a lower overall accuracy (51.1%) due to mismatches between jungle rubber and forest, while the 4LU model resulted in a higher accuracy (72.2%). Our results show the potential of ALS metrics to characterize different LULCs, which can be used to track changes in land use and their effect on ecosystem functioning, biodiversity and climate.

Estimation of breeding probability can make monitoring data more revealing: a case study of amphibians

Monitoring programs serve to detect trends in the distribution and abundance of species. To do so, monitoring programs often use static state variables. Dynamic state variables that describe population dynamics might be more valuable because they allow for a mechanistic understanding of the processes that lead to population trends. We fit multistate occupancy models to data from a country-wide multispecies amphibian occupancy monitoring program and estimated occupancy and breeding probabilities. If breeding probabilities are determinants of occupancy dynamics, then they may serve in monitoring programs as state variables that describe dynamic processes. The results showed that breeding probabilities were low and that a large proportion of the populations had to be considered to be non-breeding populations (i.e., populations where adults are present but no breeding occurs). For some species, the majority of populations were non-breeding populations. We found that non-breeding populations have lower persistence probabilities than populations where breeding occurs. Breeding probabilities may thus explain trends in occupancy but they might also explain other ecological phenomena, such as the success of invasive species, which had high breeding probabilities. Signs of breeding, i.e., the presence of eggs and larvae, were often hard to detect. Importantly, non-breeding populations also had low detection probabilities, perhaps because they had lower abundances. We suggest that monitoring programs should invest more in the detection of life history stages indicative of breeding, and also into the detection of non-breeding populations. We conclude that breeding probability should be used as a state variable in monitoring programs because it can lead to deeper insights into the processes driving occupancy dynamics.

Declines in rodent abundance and diversity track regional climate variability in North American drylands

Regional long-term monitoring can enhance the detection of biodiversity declines associated with climate change, improving future projections by reducing reliance on space-for-time substitution and increasing scalability. Rodents are diverse and important consumers in drylands, regions defined by the scarcity of water that cover 45% of Earth's land surface and face increasingly drier and more variable climates. We analyzed abundance data for 22 rodent species across grassland, shrubland, ecotone, and woodland ecosystems in the southwestern USA. Two time series (1995-2006 and 2004-2013) coincided with phases of the Pacific Decadal Oscillation (PDO), which influences drought in southwestern North America. Regionally, rodent species diversity declined 20%-35%, with greater losses during the later time period. Abundance also declined regionally, but only during 2004-2013, with losses of 5% of animals captured. During the first time series (wetter climate), plant productivity outranked climate variables as the best regional predictor of rodent abundance for 70% of taxa, whereas during the second period (drier climate), climate best explained variation in abundance for 60% of taxa. Temporal dynamics in diversity and abundance differed spatially among ecosystems, with the largest declines in woodlands and shrublands of central New Mexico and Colorado. Which species were winners or losers under increasing drought and amplified interannual variability in drought depended on ecosystem type and the phase of the PDO. Fewer taxa were significant winners (18%) than losers (30%) under drought, but the identities of winners and losers differed among ecosystems for 70% of taxa. Our results suggest that the sensitivities of rodent species to climate contributed to regional declines in diversity and abundance during 1995-2013. Whether these changes portend future declines in drought-sensitive consumers in the southwestern USA will depend on the climate during the next major PDO cycle.

Latitudinal variation in long-term stability of North American rocky intertidal communities

Although long‐term ecological stability is often discussed as a community attribute, it is typically investigated at the species level (e.g. density, biomass), or as a univariate metric (e.g. species diversity). To provide a more comprehensive assessment of long‐term community stability, we used a multivariate similarity approach that included all species and their relative abundances.

We used data from 74 sites sampled annually from 2006 to 2017 to examine broad temporal and spatial patterns of change within rocky intertidal communities along the west coast of North America. We explored relationships between community change (inverse of stability) and the following potential drivers of change/stability: (a) marine heatwave events; (b) three attributes of biodiversity: richness, diversity and evenness and (c) presence of the mussel, Mytilus californianus, a dominant space holder and foundation species in this system.

At a broad scale, we found an inverse relationship between community stability and elevated water temperatures. In addition, we found substantial differences in stability among regions, with lower stability in the south, which may provide a glimpse into the patterns expected with a changing climate. At the site level, community stability was linked to high species richness and, perhaps counterintuitively, to low evenness, which could be a consequence of the dominance of mussels in this system.

Synthesis. Assessments of long‐term stability at the whole‐community level are rarely done but are key to a comprehensive understanding of the impacts of climate change. In communities structured around a spatially dominant species, long‐term stability can be linked to the stability of this ‘foundation species’, as well as to traditional predictors, such as species richness.

Measuring diversity from space: a global view of the free and open source rasterdiv R package under a coding perspective

The variation of species diversity over space and time has been widely recognised as a key challenge in ecology. However, measuring species diversity over large areas might be difficult for logistic reasons related to both time and cost savings for sampling, as well as accessibility of remote ecosystems. In this paper, we present a new package - - to calculate diversity indices based on remotely sensed data, by discussing the theory behind the developed algorithms. Obviously, measures of diversity from space should not be viewed as a replacement of in situ data on biological diversity, but they are rather complementary to existing data and approaches. In practice, they integrate available information of Earth surface properties, including aspects of functional (structural, biophysical and biochemical), taxonomic, phylogenetic and genetic diversity. Making use of the package can result useful in making multiple calculations based on reproducible open source algorithms, robustly rooted in Information Theory.

Quantifying the impact of vegetation-based metrics on species persistence when choosing offsets for habitat destruction

Developers are often required by law to offset environmental impacts through targeted conservation actions. Most offset policies specify metrics for calculating offset requirements, usually by assessing vegetation condition. Despite widespread use, there is little evidence to support the effectiveness of vegetation-based metrics for ensuring biodiversity persistence. We compared long-term impacts of biodiversity offsetting based on area only; vegetation condition only; area × habitat suitability; and condition × habitat suitability in development and restoration simulations for the Hunter Region of New South Wales, Australia. We simulated development and subsequent offsetting through restoration within a virtual landscape, linking simulations to population viability models for 3 species. Habitat gains did not ensure species persistence. No net loss was achieved when performance of offsetting was assessed in terms of amount of habitat restored, but not when outcomes were assessed in terms of persistence. Maintenance of persistence occurred more often when impacts were avoided, giving further support to better enforce the avoidance stage of the mitigation hierarchy. When development affected areas of high habitat quality for species, persistence could not be guaranteed. Therefore, species must be more explicitly accounted for in offsets, rather than just vegetation or habitat alone. Declines due to a failure to account directly for species population dynamics and connectivity overshadowed the benefits delivered by producing large areas of high-quality habitat. Our modeling framework showed that the benefits delivered by offsets are species specific and that simple vegetation-based metrics can give misguided impressions on how well biodiversity offsets achieve no net loss.

Monitoring social–ecological networks for biodiversity and ecosystem services in human-dominated landscapes

The demand the human population is placing on the environment has triggered accelerated rates of biodiversity change and created trade-offs among the ecosystem services we depend upon. Decisions designed to reverse these trends require the best possible information obtained by monitoring ecological and social dimensions of change. Here, we conceptualize a network framework to monitor change in social–ecological systems. We contextualize our framework within Ostrom’s social–ecological system framework and use it to discuss the challenges of monitoring biodiversity and ecosystem services across spatial and temporal scales. We propose that spatially explicit multilayer and multiscale monitoring can help estimate the range of variability seen in social–ecological systems with varying levels of human modification across the landscape. We illustrate our framework using a conceptual case study on the ecosystem service of maple syrup production. We argue for the use of analytical tools capable of integrating qualitative and quantitative knowledge of social–ecological systems to provide a causal understanding of change across a network. Altogether, our conceptual framework provides a foundation for establishing monitoring systems. Operationalizing our framework will allow for the detection of ecosystem service change and assessment of its drivers across several scales, informing the long-term sustainability of biodiversity and ecosystem services.

Model-Assisted Bird Monitoring Based on Remotely Sensed Ecosystem Functioning and Atlas Data

Urgent action needs to be taken to halt global biodiversity crisis. To be effective in the implementation of such action, managers and policy-makers need updated information on the status and trends of biodiversity. Here, we test the ability of remotely sensed ecosystem functioning attributes (EFAs) to predict the distribution of 73 bird species with different life-history traits. We run ensemble species distribution models (SDMs) trained with bird atlas data and 12 EFAs describing different dimensions of carbon cycle and surface energy balance. Our ensemble SDMs—exclusively based on EFAs—hold a high predictive capacity across 71 target species (up to 0.94 and 0.79 of Area Under the ROC curve and true skill statistic (TSS)). Our results showed the life-history traits did not significantly affect SDM performance. Overall, minimum Enhanced Vegetation Index (EVI) and maximum Albedo values (descriptors of primary productivity and energy balance) were the most important predictors across our bird community. Our approach leverages the existing atlas data and provides an alternative method to monitor inter-annual bird habitat dynamics from space in the absence of long-term biodiversity monitoring schemes. This study illustrates the great potential that satellite remote sensing can contribute to the Aichi Biodiversity Targets and to the Essential Biodiversity Variables framework (EBV class “Species distribution”).

Ecosystem antifragility: beyond integrity and resilience

We review the concept of ecosystem resilience in its relation to ecosystem integrity from an information theory approach. We summarize the literature on the subject identifying three main narratives: ecosystem properties that enable them to be more resilient; ecosystem response to perturbations; and complexity. We also include original ideas with theoretical and quantitative developments with application examples. The main contribution is a new way to rethink resilience, that is mathematically formal and easy to evaluate heuristically in real-world applications: ecosystem antifragility. An ecosystem is antifragile if it benefits from environmental variability. Antifragility therefore goes beyond robustness or resilience because while resilient/robust systems are merely perturbation-resistant, antifragile structures not only withstand stress but also benefit from it.

Community-based wildlife management area supports similar mammal species richness and densities compared to a national park

Community-based conservation models have been widely implemented across Africa to improve wildlife conservation and livelihoods of rural communities. In Tanzania, communities can set aside land and formally register it as Wildlife Management Area (WMA), which allows them to generate revenue via consumptive or nonconsumptive utilization of wildlife. The key, yet often untested, assumption of this model is that economic benefits accrued from wildlife motivate sustainable management of wildlife. To test the ecological effectiveness (here defined as persistence of wildlife populations) of Burunge Wildlife Management Area (BWMA), we employed a participatory monitoring approach involving WMA personnel. At intermittent intervals between 2011 and 2018, we estimated mammal species richness and population densities of ten mammal species (African elephant, giraffe, buffalo, zebra, wildebeest, waterbuck, warthog, impala, Kirk's dik-dik, and vervet monkey) along line transects. We compared mammal species accumulation curves and density estimates with those of time-matched road transect surveys conducted in adjacent Tarangire National Park (TNP). Mammal species richness estimates were similar in both areas, yet observed species richness per transect was greater in TNP compared to BWMA. Species-specific density estimates of time-matched surveys were mostly not significantly different between BWMA and TNP, but elephants occasionally reached greater densities in TNP compared to BWMA. In BWMA, elephant, wildebeest, and impala populations showed significant increases from 2011 to 2018. These results suggest that community-based conservation models can support mammal communities and densities that are similar to national park baselines. In light of the ecological success of this case study, we emphasize the need for continued efforts to ensure that the BWMA is effective. This will require adaptive management to counteract potential negative repercussions of wildlife populations on peoples' livelihoods. This study can be used as a model to evaluate the effectiveness of wildlife management areas across Tanzania.

A Lack of “Environmental Earth Data” at the Microhabitat Scale Impacts Efforts to Control Invasive Arthropods That Vector Pathogens

We currently live in an era of major global change that has led to the introduction and range expansion of numerous invasive species worldwide. In addition to the ecological and economic consequences associated with most invasive species, invasive arthropods that vector pathogens (IAVPs) to humans and animals pose substantial health risks. Species distribution models that are informed using environmental Earth data are frequently employed to predict the distribution of invasive species, and to advise targeted mitigation strategies. However, there are currently substantial mismatches in the temporal and spatial resolution of these data and the environmental contexts which affect IAVPs. Consequently, targeted actions to control invasive species or to prepare the population for possible disease outbreaks may lack efficacy. Here, we identify and discuss how the currently available environmental Earth data are lacking with respect to their applications in species distribution modeling, particularly when predicting the potential distribution of IAVPs at meaningful space-time scales. For example, we examine the issues related to interpolation of weather station data and the lack of microclimatic data relevant to the environment experienced by IAVPs. In addition, we suggest how these data gaps can be filled, including through the possible development of a dedicated open access database, where data from both remotely- and proximally-sensed sources can be stored, shared, and accessed.

Beta-Diversity Modeling and Mapping with LiDAR and Multispectral Sensors in a Semi-Evergreen Tropical Forest

Tree beta-diversity denotes the variation in species composition at stand level, it is a key indicator of forest degradation, and is conjointly required with alpha-diversity for management decision making but has seldom been considered. Our aim was to map it in a continuous way with remote sensing technologies over a tropical landscape with different disturbance histories. We extracted a floristic gradient of dissimilarity through a non-metric multidimensional scaling ordination based on the ecological importance value of each species, which showed sensitivity to different land use history through significant differences in the gradient scores between the disturbances. After finding strong correlations between the floristic gradient and the rapidEye multispectral textures and LiDAR-derived variables, it was linearly regressed against them; variable selection was performed by fitting mixed-effect models. The redEdge band mean, the Canopy Height Model, and the infrared band variance explained 68% of its spatial variability, each coefficient with a relative importance of 49%, 32.5%, and 18.5% respectively. Our results confirmed the synergic use of LiDAR and multispectral sensors to map tree beta-diversity at stand level. This approach can be used, combined with ground data, to detect effects (either negative or positive) of management practices or natural disturbances on tree species composition.

Land use, REDD+ and the status of wildlife populations in Yaeda Valley, northern Tanzania

REDD+ projects primarily focus on reducing carbon emissions from deforestation and forest degradation in developing countries. These projects are regularly evaluated against their core objective of conserving carbon stocks, but their contribution to biodiversity conservation has rarely been assessed. To assess the conservation value of the area and the relative performance of a REDD+ land use plan in Yaeda Valley, a semi-arid savannah ecosystem in northern Tanzania, we implemented an annual wildlife monitoring scheme. Based on direct sightings and indirect signs of wildlife, obtained from stratified walking transects conducted annually from 2015–2018, we estimated annual trends of mammal species richness and wildlife densities in three REDD+ and three non-REDD+ land-use strata. Our surveys document a near complete mammal community in the area. Species accumulation curves, and subsequent statistical comparisons, indicated highest mammal species richness in the woodland habitats (both REDD+ and non REDD+ strata) as compared to more human and livestock impacted areas, and suggested constant species richness from 2015–2018. To estimate stratum- and year-specific livestock and wildlife densities (cattle, donkey, goat and sheep combined, Thomson’s gazelle, Kirk’s dik-dik) and wildlife sign densities (aardvark, bushbuck, bushpig, Kirk’s dik dik, eland, elephant, Maasai giraffe, greater kudu, hyena, impala, lesser kudu, warthog, wildebeest, Plains zebra), we fitted species-specific detection functions in a distance sampling framework. Species-specific densities varied between 2015 and 2018 and showed substantial increases and occasional declines in other species-stratum combinations. However, population growth rates were not systematically associated with specific land-use strata. Although our results do not explicitly provide evidence that REDD+ land-use plans directly co-benefit wildlife conservation, they show that REDD+ areas have the potential to maintain intact wildlife assemblages. To ensure effective long-term conservation outcomes, we advocate for a more formal integration of wildlife conservation goals in the REDD+ scheme.

BioModelos: A collaborative online system to map species distributions

Information on species distribution is recognized as a crucial input for biodiversity conservation and management. To that end, considerable resources have been dedicated towards increasing the quantity and availability of species occurrence data, boosting their use in species distribution modeling and online platforms for their dissemination. Currently, those platforms face the challenge of bringing biology into modeling by making informed decisions that result in meaningful models, based on limited occurrence and ecological data. Here we describe BioModelos, a modeling approach supported by an online system and a core team of modelers, whereby a network of experts contributes to the development of species distribution models by assessing the quality of occurrence data, identifying potentially limiting environmental variables, establishing species’ accessible areas and validating modeling predictions qualitatively. Models developed through BioModelos become freely and publicly available once validated by experts, furthering their use in conservation applications. Our approach has been implemented in Colombia since 2013 and it currently consist of a network of nearly 500 experts that collaboratively contribute to enhance the knowledge on the distribution of a growing number of species and it has aided the development of several decision support products such as national risk assessments and biodiversity compensation manuals. BioModelos is an example of operationalization of an essential biodiversity variable at a national level through the implementation of a research infrastructure that enhances the value of open access species data.

Ecosystem restoration in Europe: Can analogies to Traditional Chinese Medicine facilitate the cross-policy harmonization on managing socio-ecological systems?

EU's Biodiversity Strategy to 2020 sets a 15% restoration target. However, the understanding of restoration as a management tool remains ambiguous at EU and Member State levels. As a country with rich biodiversity but low GDP, a well-defined priority setting approach is key for Bulgaria. The "Methodological framework for assessment and mapping of ecosystem condition and ecosystem services in Bulgaria" proposes a transition towards ecosystem management and monitoring of the Socio-Ecological System (SES), to be embedded in the environmental policy framework. We extend the analogy between SES and the human body's system in the Traditional Chinese Medicine (TCM) as a way to inform restoration priority setting and development of restoration and monitoring tools at several levels: We apply the analogy and find that spatially explicit decision making on restoration, streamlined ecosystem monitoring and a number of other issues (green infrastructure, designation of protected areas, defragmentation and connectivity, cumulative impact assessment, etc.), are easier to understand, communicate, account for and manage. Ecosystem restoration is priority for China and the country has accumulated research and practical experience, including study of links between ecosystem management and the historical principles of Chinese philosophy. The Bulgarian and European approach to ecosystem based management can benefit from analogies to TCM. We derive policy recommendations by analogy, and illustrate them on the example of Natural Capital Accounting.

Monitoring age-related trends in genomic diversity of Australian lungfish

An important challenge for conservation science is to detect declines in intraspecific diversity so that management action can be guided towards populations or species at risk. The lifespan of Australian lungfish (Neoceratodus forsteri) exceeds 80 years, and human impacts on breeding habitat over the last half century may have impeded recruitment, leaving populations dominated by old postreproductive individuals, potentially resulting in a small and declining breeding population. Here, we conduct a "single-sample" evaluation of genetic erosion within contemporary populations of the Australian lungfish. Genetic erosion is a temporal decline in intraspecific diversity due to factors such as reduced population size and inbreeding. We examined whether young individuals showed signs of reduced genetic diversity and/or inbreeding using a novel bomb radiocarbon dating method to age lungfish nonlethally, based on 14 C ratios of scales. A total of 15,201 single nucleotide polymorphic (SNP) loci were genotyped in 92 individuals ranging in age from 2 to 77 years old. Standardized individual heterozygosity and individual inbreeding coefficients varied widely within and between riverine populations, but neither was associated with age, so perceived problems with recruitment have not translated into genetic erosion that could be considered a proximate threat to lungfish populations. Conservation concern has surrounded Australian lungfish for over a century. However, our results suggest that long-lived threatened species can maintain stable levels of intraspecific variability when sufficient reproductive opportunities exist over the course of a long lifespan.