Animals and the zoogeochemistry of the carbon cycle Schmitz, Oswald J; Wilmers, Christopher C; Leroux, Shawn J ...
Science (American Association for the Advancement of Science),
12/2018, Volume:
362, Issue:
6419
Journal Article
Peer reviewed
Predicting and managing the global carbon cycle requires scientific understanding of ecosystem processes that control carbon uptake and storage. It is generally assumed that carbon cycling is ...sufficiently characterized in terms of uptake and exchange between ecosystem plant and soil pools and the atmosphere. We show that animals also play an important role by mediating carbon exchange between ecosystems and the atmosphere, at times turning ecosystem carbon sources into sinks, or vice versa. Animals also move across landscapes, creating a dynamism that shapes landscape-scale variation in carbon exchange and storage. Predicting and measuring carbon cycling under such dynamism is an important scientific challenge. We explain how to link analyses of spatial ecosystem functioning, animal movement, and remote sensing of animal habitats with carbon dynamics across landscapes.
Predator-prey relationships are integral to ecosystem stability and functioning. These relationships are, however, difficult to maintain in protected areas where large predators are increasingly ...being reintroduced and confined. Where predators make kills has a profound influence on their role in ecosystems, but the relative importance of environmental variables in determining kill sites, and how these might vary across ecosystems is poorly known. We investigated kill sites for lions in South Africa's thicket biome, testing the importance of vegetation structure for kill site locations compared to other environmental variables. Kill sites were located over four years using GPS telemetry and compared to non-kill sites that had been occupied by lions, as well as to random sites within lion ranges. Measurements of 3D vegetation structure obtained from Light Detection and Ranging (LiDAR) were used to calculate the visible area (viewshed) around each site and, along with wind and moonlight data, used to compare kill sites between lion sexes, prey species and prey sexes. Viewshed area was the most important predictor of kill sites (sites in dense vegetation were twice as likely to be kill sites compared to open areas), followed by wind speed and, less so, moonlight. Kill sites for different prey species varied with vegetation structure, and male prey were killed when wind speeds were higher compared to female prey of the same species. Our results demonstrate that vegetation structure is an important component of predator-prey interactions, with varying effects across ecosystems. Such differences require consideration in terms of the ecological roles performed by predators, and in predator and prey conservation.
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•Structural heterogeneity is more influential for animal diversity than is simple canopy cover.•Taxonomic groups respond to different components of 3D ecosystem structure.•Biases in the literature ...preclude syntheses for some taxonomic groups and regions.•LiDAR has tremendous potential to further advance understanding of animal ecology.
The advent and recent advances of Light Detection and Ranging (LiDAR) have enabled accurate measurement of 3D ecosystem structure. Here, we review insights gained through the application of LiDAR to animal ecology studies, revealing the fundamental importance of structure for animals. Structural heterogeneity is most conducive to increased animal richness and abundance, and increased complexity of vertical vegetation structure is more positively influential compared with traditionally measured canopy cover, which produces mixed results. However, different taxonomic groups interact with a variety of 3D canopy traits and some groups with 3D topography. To develop a better understanding of animal dynamics, future studies will benefit from considering 3D habitat effects in a wider variety of ecosystems and with more taxa.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
Using remotely sensed imagery to identify biophysical components across landscapes is an important avenue of investigation for ecologists studying ecosystem dynamics. With high-resolution remotely ...sensed imagery, algorithmic utilization of image context is crucial for accurate identification of biophysical components at large scales. In recent years, convolutional neural networks (CNNs) have become ubiquitous in image processing, and are rapidly becoming more common in ecology. Because the quantity of high-resolution remotely sensed imagery continues to rise, CNNs are increasingly essential tools for large-scale ecosystem analysis. We discuss here the conceptual advantages of CNNs, demonstrate how they can be used by ecologists through distinct examples of their application, and provide a walkthrough of how to use them for ecological applications.
CNNs enable ecologists to identify biophysical components in high-resolution remotely sensed imagery by leveraging spatial context, and are particularly effective when ecological components have distinct shapes.
CNNs can be used for both object detection, where key components are identified throughout an image, and semantic segmentation, where each pixel is classified individually.
CNN accuracy is similar to human-level classification accuracy, but is consistent and fast, enabling rapid application over very large areas and/or through time.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
Vegetation structural complexity (VSC)—the three‐dimensional distribution of plants within an ecosystem—is an important ecological trait. To date, research has focused primarily on the effects of VSC ...on ecological patterns and processes, but comparatively little is known about what drives variation in VSC.
Recent advances in active remote sensing technology, particularly light detection and ranging and radio detection and ranging, have allowed the measurement of VSC at unprecedented spatial scales and resolutions. Out of this and earlier work has emerged evidence that VSC is typically associated with greater ecosystem functioning (especially microclimate regulation, productivity, faunal diversity and habitat provisioning), making restoration of vegetation complexity a potentially powerful restoration tool.
Recent studies of VSC across natural and experimental gradients of plant diversity have also revealed that more diverse plant communities tend to be more structurally complex. However, the shape and generality of this relationship—and the mechanism(s) by which phytodiversity might contribute to structural complexity—remain poorly understood.
Here, we review how active remote sensing has facilitated recent VSC research and shaped our understanding of the relationship between vegetation complexity and ecosystem function. We then present a theoretical framework for the relationship between phytodiversity and VSC based on classic biodiversity‐ecosystem functioning principles. Finally, we evaluate the evidence for the notion that diverse plant assemblages tend to be more structurally complex and explore the shape of the relationship between phytodiversity and VSC using data from 13 recent remote sensing studies.
Synthesis. The relationship between phytodiversity and VSC appears to be almost universally positive. Preliminary evidence further suggests that the most common relationships between phytodiversity and VSC are linear or saturating, indicating that the extent of functional redundancy between species varies across plant communities and ecosystems. In contrast, we find little evidence for exponential or negative relationships between plant diversity and VSC, suggesting that even modest increases in plant diversity could markedly increase structural complexity. Additional investigations of phytodiversity‐VSC relationships are necessary to establish whether the observed positive relationships are causal (and, if so, in which direction) and to clarify the potential impact of plant community restoration on structural complexity and broader ecosystem function.
Vegetation structural complexity (VSC) is an important ecosystem trait that is typically associated with greater ecological functioning. Recent studies have also revealed that more diverse plant communities tend to be more structurally complex. However, the shape and generality of this relationship—and the mechanism(s) by which phytodiversity might contribute to structural complexity—remain poorly understood. We propose a theoretical framework for the relationship between phytodiversity and VSC based on classic biodiversity‐ecosystem functioning principles. Using data from recently published studies that compare VSC across phytodiversity gradients, we find that the relationship between phytodiversity and VSC appears to be almost universally positive.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
6.
Species‐level termite methane production rates Zhou, Yong; Staver, A. Carla; Davies, Andrew B.
Ecology (Durham),
February 2023, 2023-Feb, 2023-02-00, 20230201, Volume:
104, Issue:
2
Journal Article
Peer reviewed
Open access
Termites consume substantial amounts of plant material across tropical and subtropical ecosystems. During the process of lignocellulose digestion, the symbiotic methanogenesis within termites' guts ...produces the potent greenhouse gas methane (CH4). Termites contribute an estimated 1%–5% of global CH4 emissions, with these estimates derived from the product of termite biomass and termite CH4 production rate per unit of termite biomass. However, termite CH4 production rates vary significantly across species, genus, family, and feeding group, yet our understanding of this variation remains poor. Here, we reviewed papers published from 1975 to 2021 to create a single consistently derived list of species‐level termite CH4 production rates. We searched the Google Scholar using two key words: termite and methane. We only included studies that had measured termite CH4 production rates using the incubation method. For each eligible study, we extracted and tabulated termite CH4 production rates and other relevant variables (e.g., feeding groups). We used μg CH4 g−1(termite) h−1 as the standardized unit, and if other units were presented, we converted them into this standardized unit. Overall, these data include 134 termite species from 65 genera and 5 families. Termite CH4 production rates ranged from 0 to 25.26 μg CH4 g−1(termite) h−1, with an average rate of 3.74 (standard deviation = 4.08, n = 251). Reported CH4 production rates were largely concentrated in the family Termitidae. Across feeding groups, soil feeders tended to have higher CH4 production rates than wood feeders. However, published data represent fewer than 5% of described termite species, and therefore we hope that our study will initiate a community‐wide effort to fill data gaps and advance our understanding of the role of termites in critical biogeochemical cycles and other ecosystem processes. The data set is in the public domain under a Creative Commons Zero (CC0) license waiver.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
The conservation of charismatic and functionally important large species is becoming increasingly difficult. Anthropogenic pressures continue to squeeze available habitat and force animals into ...degraded and disturbed areas. Ensuring the long-term survival of these species requires a well-developed understanding of how animals use these new landscapes to inform conservation and habitat restoration efforts. We combined 3 y of highly detailed visual observations of Bornean orangutans with high-resolution airborne remote sensing (Light Detection and Ranging) to understand orangutan movement in disturbed and fragmented forests of Malaysian Borneo. Structural attributes of the upper forest canopy were the dominant determinant of orangutan movement among all age and sex classes, with orangutans more likely to move in directions of increased canopy closure, tall trees, and uniform height, as well as avoiding canopy gaps and moving toward emergent crowns. In contrast, canopy vertical complexity (canopy layering and shape) did not affect movement. Our results suggest that although orangutans do make use of disturbed forest, they select certain canopy attributes within these forests, indicating that not all disturbed or degraded forest is of equal value for the long-term sustainability of orangutan populations. Although the value of disturbed habitats needs to be recognized in conservation plans for wide-ranging, large-bodied species, minimal ecological requirements within these habitats also need to be understood and considered if long-term population viability is to be realized.
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BFBNIB, NMLJ, NUK, PNG, SAZU, UL, UM, UPUK
Ecosystems function in a series of feedback loops that can change or maintain vegetation structure. Vegetation structure influences the ecological niche space available to animals, shaping many ...aspects of behaviour and reproduction. In turn, animals perform ecological functions that shape vegetation structure. However, most studies concerning three‐dimensional vegetation structure and animal ecology consider only a single direction of this relationship. Here, we review these separate lines of research and integrate them into a unified concept that describes a feedback mechanism. We also show how remote sensing and animal tracking technologies are now available at the global scale to describe feedback loops and their consequences for ecosystem functioning. An improved understanding of how animals interact with vegetation structure in feedback loops is needed to conserve ecosystems that face major disruptions in response to climate and land‐use change.
Vegetation structure influences the ecological niche space available to animals, shaping many aspects of behaviour and reproduction. In turn, animals perform ecological functions that shape vegetation structure. Here, we review these separate lines of research and integrate them into a unified concept that describes a feedback mechanism and its consequences for ecosystems that face major disruptions in response to climate and land‐use change.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
Understanding the drivers of vegetation carbon dynamics is essential for climate change mitigation and effective policy formulation. However, most efforts focus on abiotic drivers of plant biomass ...change, with little consideration for functional roles performed by animals, particularly at landscape scales. We combined repeat airborne Light Detection and Ranging with measurements of elephant densities, abiotic factors, and exclusion experiments to determine the relative importance of drivers of change in aboveground woody vegetation carbon stocks in Kruger National Park, South Africa. Despite a growing elephant population, aboveground carbon density (ACD) increased across most of the landscape over the 6‐year study period, but at fine scales, bull elephant density was the most important factor determining carbon stock change, with ACD losses recorded only where bull densities exceeded 0.5 bulls/km2. Effects of bull elephants were, however, spatially restricted and landscape dependent, being especially pronounced along rivers, at mid‐elevations, and on steeper slopes. In contrast, elephant herds and abiotic drivers had a comparatively small influence on the direction or magnitude of carbon stock change. Our findings demonstrate that animals can have a substantive influence on regional‐scale carbon dynamics and warrant consideration in carbon cycling models and policy formulation aimed at carbon management and climate change mitigation.
Most efforts to understand the drivers of vegetation carbon dynamics focus on abiotic drivers, with little consideration for animal‐driven effects. Here, we combine airborne LiDAR with measurements of elephant densities, abiotic factors and exclusion experiments to determine the relative importance of drivers of change in aboveground carbon stocks in Kruger National Park, South Africa. Although aboveground carbon density increased across most of the landscape, bull elephant density was the most important factor determining carbon stock change at localised scales, with carbon losses recorded only where bull densities were high, demonstrating the substantive role animals can have on carbon dynamics.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
10.
Flying high: Sampling savanna vegetation with UAV‐lidar Boucher, Peter B.; Hockridge, Evan G.; Singh, Jenia ...
Methods in ecology and evolution,
July 2023, 2023-07-00, 20230701, 2023-07-01, Volume:
14, Issue:
7
Journal Article
Peer reviewed
Open access
The flexibility of UAV‐lidar remote sensing offers a myriad of new opportunities for savanna ecology, enabling researchers to measure vegetation structure at a variety of temporal and spatial scales. ...However, this flexibility also increases the number of customizable variables, such as flight altitude, pattern, and sensor parameters, that, when adjusted, can impact data quality as well as the applicability of a dataset to a specific research interest.
To better understand the impacts that UAV flight patterns and sensor parameters have on vegetation metrics, we compared 7 lidar point clouds collected with a Riegl VUX − 1LR over a 300 × 300 m area in the Kruger National Park, South Africa. We varied the altitude (60 m above ground, 100 m, 180 m, and 300 m) and sampling pattern (slowing the flight speed, increasing the overlap between flightlines and flying a crosshatch pattern), and compared a variety of vertical vegetation metrics related to height and fractional cover.
Comparing vegetation metrics from acquisitions with different flight patterns and sensor parameters, we found that both flight altitude and pattern had significant impacts on derived structure metrics, with variation in altitude causing the largest impacts. Flying higher resulted in lower point cloud heights, leading to a consistent downward trend in percentile height metrics and fractional cover. The magnitude and direction of these trends also varied depending on the vegetation type sampled (trees, shrubs or grasses), showing that the structure and composition of savanna vegetation can interact with the lidar signal and alter derived metrics. While there were statistically significant differences in metrics among acquisitions, the average differences were often on the order of a few centimetres or less, which shows great promise for future comparison studies.
We discuss how these results apply in practice, explaining the potential trade‐offs of flying at higher altitudes and with alternate patterns. We highlight how flight and sensor parameters can be geared toward specific ecological applications and vegetation types, and we explore future opportunities for optimizing UAV‐lidar sampling designs in savannas.
A cross‐section of a lidar point cloud for a single tree (left) from a savanna in the Satara region of Kruger National Park, South Africa (visualised with CloudCompare 2.11). Smoothed vertical profiles of fractional canopy cover per 10 cm height bin are plotted for the same tree. These profiles were derived from a series of airborne lidar data collected from 4 different flight altitudes (60 m, 100 m, 180 m, and 300 m above ground) with an unoccupied aerial vehicle (UAV). As flight altitude increases (left‐right), the canopy cover profiles change shape and shift downward, demonstrating that UAV fight and sensor parameters can have a significant impact on lidar measurements of vegetation structure.
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FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
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