scholarly journals Spatial integrated models foster complementarity between monitoring programs in producing large-scale ecological indicators

2021 ◽  
Author(s):  
Valentin Lauret ◽  
Helene Labach ◽  
Daniel Turek ◽  
Sophie Laran ◽  
Olivier Gimenez

AbstractOver the last decades, large-scale conservation projects have emerged that require collecting ecological data over broad spatial and temporal coverage. Yet, obtaining relevant information about large-scale population dynamics from a single monitoring program is challenging, and often several sources of data, possibly heterogeneous, need to be integrated.In this context, spatial integrated models combine multiple data types into a single analysis to quantify population dynamics of a targeted population. Using available information at different spatial or temporal scales, spatial integrated models have the potential to produce detailed ecological estimates that would be difficult to obtain if data were analyzed separately. So far, these models are available for open populations to estimate demographic parameters (survival, recruitment), therefore requiring data collected in long-term monitoring programs. In conservation biology however, we often need to quantify population abundance and density in closed populations.In this paper, we showcase the implementation of spatial integrated models to closed populations in a conservation context. We analyzed spatial capture-recapture data together with distance-sampling data to estimate abundance and density. Focusing on the Mediterranean bottlenose dolphins (Tursiops truncatus) as a case study, we combined 21,464 km of photo-identification boat surveys collecting spatial capture-recapture data with 24,624 km of aerial line-transect following a distance-sampling protocol. We compared the performances of the spatial integrated model, with that of the distance sampling model, and the spatial capture-recapture model separated. We discussed the benefits of using a spatial integrated model in the context of the assessment of French Mediterranean bottlenose dolphin conservation status to inform continental scale public policies.Overall, we emphasize the usefulness of spatial integrated model to make the most of available datasets in a conservation context. Spatial integrated models are widely applicable and relevant to conservation research and biodiversity assessment at large spatial scales.

Mammalia ◽  
2018 ◽  
Vol 82 (2) ◽  
pp. 183-187 ◽  
Author(s):  
Andrew M. Kittle ◽  
Anjali C. Watson

AbstractQuantitative ecological data needs to inform management of the endangered, endemic Sri Lankan leopard. Estimating habitat-specific leopard density and prey availability provides important baselines and improved understanding of the island-wide population. We used remote cameras in a spatially explicit capture-recapture framework to estimate leopard density (11.7 adult individuals/100 km2) and distance sampling to estimate prey density, within Horton Plains National Park. Sambar density was 178/km2within the central grasslands, which represent a spatially anchored resource for sambar and in turn, a highly clumped, abundant resource for leopards. This study represents the first robust estimate of leopard density in Sri Lanka’s montane zone.


Water ◽  
2021 ◽  
Vol 13 (2) ◽  
pp. 141
Author(s):  
Firoza Akhter ◽  
Maurizio Mazzoleni ◽  
Luigia Brandimarte

In this study, we explore the long-term trends of floodplain population dynamics at different spatial scales in the contiguous United States (U.S.). We exploit different types of datasets from 1790–2010—i.e., decadal spatial distribution for the population density in the US, global floodplains dataset, large-scale data of flood occurrence and damage, and structural and nonstructural flood protection measures for the US. At the national level, we found that the population initially settled down within the floodplains and then spread across its territory over time. At the state level, we observed that flood damages and national protection measures might have contributed to a learning effect, which in turn, shaped the floodplain population dynamics over time. Finally, at the county level, other socio-economic factors such as local flood insurances, economic activities, and socio-political context may predominantly influence the dynamics. Our study shows that different influencing factors affect floodplain population dynamics at different spatial scales. These facts are crucial for a reliable development and implementation of flood risk management planning.


Oryx ◽  
2021 ◽  
pp. 1-9
Author(s):  
Helen M. K. O'Neill ◽  
Sarah M. Durant ◽  
Stefanie Strebel ◽  
Rosie Woodroffe

Abstract Wildlife fences are often considered an important tool in conservation. Fences are used in attempts to prevent human–wildlife conflict and reduce poaching, despite known negative impacts on landscape connectivity and animal movement patterns. Such impacts are likely to be particularly important for wide-ranging species, such as the African wild dog Lycaon pictus, which requires large areas of continuous habitat to fulfil its resource requirements. Laikipia County in northern Kenya is an important area for wild dogs but new wildlife fences are increasingly being built in this ecosystem. Using a long-term dataset from the area's free-ranging wild dog population, we evaluated the effect of wildlife fence structure on the ability of wild dogs to cross them. The extent to which fences impeded wild dog movement differed between fence designs, although individuals crossed fences of all types. Purpose-built fence gaps increased passage through relatively impermeable fences. Nevertheless, low fence permeability can lead to packs, or parts of packs, becoming trapped on the wrong side of a fence, with consequences for population dynamics. Careful evaluation should be given to the necessity of erecting fences; ecological impact assessments should incorporate evaluation of impacts on animal movement patterns and should be undertaken for all large-scale fencing interventions. Where fencing is unavoidable, projects should use the most permeable fencing structures possible, both in the design of the fence and including as many purpose-built gaps as possible, to minimize impacts on wide-ranging wildlife.


2013 ◽  
Vol 141 (3) ◽  
pp. 1099-1117 ◽  
Author(s):  
Andrew Charles ◽  
Bertrand Timbal ◽  
Elodie Fernandez ◽  
Harry Hendon

Abstract Seasonal predictions based on coupled atmosphere–ocean general circulation models (GCMs) provide useful predictions of large-scale circulation but lack the conditioning on topography required for locally relevant prediction. In this study a statistical downscaling model based on meteorological analogs was applied to continental-scale GCM-based seasonal forecasts and high quality historical site observations to generate a set of downscaled precipitation hindcasts at 160 sites in the South Murray Darling Basin region of Australia. Large-scale fields from the Predictive Ocean–Atmosphere Model for Australia (POAMA) 1.5b GCM-based seasonal prediction system are used for analog selection. Correlation analysis indicates modest levels of predictability in the target region for the selected predictor fields. A single best-match analog was found using model sea level pressure, meridional wind, and rainfall fields, with the procedure applied to 3-month-long reforecasts, initialized on the first day of each month from 1980 to 2006, for each model day of 10 ensemble members. Assessment of the total accumulated rainfall and number of rainy days in the 3-month reforecasts shows that the downscaling procedure corrects the local climate variability with no mean effect on predictive skill, resulting in a smaller magnitude error. The amount of total rainfall and number of rain days in the downscaled output is significantly improved over the direct GCM output as measured by the difference in median and tercile thresholds between station observations and downscaled rainfall. Confidence in the downscaled output is enhanced by strong consistency between the large-scale mean of the downscaled and direct GCM precipitation.


2021 ◽  
Author(s):  
Kor de Jong ◽  
Marc van Kreveld ◽  
Debabrata Panja ◽  
Oliver Schmitz ◽  
Derek Karssenberg

<p>Data availability at global scale is increasing exponentially. Although considerable challenges remain regarding the identification of model structure and parameters of continental scale hydrological models, we will soon reach the situation that global scale models could be defined at very high resolutions close to 100 m or less. One of the key challenges is how to make simulations of these ultra-high resolution models tractable ([1]).</p><p>Our research contributes by the development of a model building framework that is specifically designed to distribute calculations over multiple cluster nodes. This framework enables domain experts like hydrologists to develop their own large scale models, using a scripting language like Python, without the need to acquire the skills to develop low-level computer code for parallel and distributed computing.</p><p>We present the design and implementation of this software framework and illustrate its use with a prototype 100 m, 1 h continental scale hydrological model. Our modelling framework ensures that any model built with it is parallelized. This is made possible by providing the model builder with a set of building blocks of models, which are coded in such a manner that parallelization of calculations occurs within and across these building blocks, for any combination of building blocks. There is thus full flexibility on the side of the modeller, without losing performance.</p><p>This breakthrough is made possible by applying a novel approach to the implementation of the model building framework, called asynchronous many-tasks, provided by the HPX C++ software library ([3]). The code in the model building framework expresses spatial operations as large collections of interdependent tasks that can be executed efficiently on individual laptops as well as computer clusters ([2]). Our framework currently includes the most essential operations for building large scale hydrological models, including those for simulating transport of material through a flow direction network. By combining these operations, we rebuilt an existing 100 m, 1 h resolution model, thus far used for simulations of small catchments, requiring limited coding as we only had to replace the computational back end of the existing model. Runs at continental scale on a computer cluster show acceptable strong and weak scaling providing a strong indication that global simulations at this resolution will soon be possible, technically speaking.</p><p>Future work will focus on extending the set of modelling operations and adding scalable I/O, after which existing models that are currently limited in their ability to use the computational resources available to them can be ported to this new environment.</p><p>More information about our modelling framework is at https://lue.computationalgeography.org.</p><p><strong>References</strong></p><p>[1] M. Bierkens. Global hydrology 2015: State, trends, and directions. Water Resources Research, 51(7):4923–4947, 2015.<br>[2] K. de Jong, et al. An environmental modelling framework based on asynchronous many-tasks: scalability and usability. Submitted.<br>[3] H. Kaiser, et al. HPX - The C++ standard library for parallelism and concurrency. Journal of Open Source Software, 5(53):2352, 2020.</p>


2021 ◽  
Author(s):  
Thomas Ohnemus ◽  
Hannes Mollenhauer ◽  
Michael Mirtl ◽  
Steffen Zacharias

<p>The integrated European Long-Term Ecosystem, critical zone and socio-ecological Research Infrastructure (eLTER RI) was accepted onto the ESFRI roadmap in 2018. While several existing thematic environmental RIs in Europe focus on impacts of climate change and/or other elements of environmental change, eLTER RI will be the only research infrastructure embracing holistically the integrated impacts of such stressors on a wide variety of European benchmark ecosystems (major geo-eco-sociological systems across the continent’s ecoclimatological zones and Earth’s critical zone). In the beginning of 2020 eLTER RI entered the preparatory phase aiming at the development of the legal, financial and technical maturity required for an ESFRI Research Infrastructure.</p><p>The core of the eLTER RI will be ca. 200 selected sites covering all biogeographical zones in Europe, where biological, biogeochemical, hydrological and socio-ecological data will be collected - according to common standards - and analyzed. The European landscape of LTER sites and national networks has mainly been developed in a bottom-up manner. The sites have mostly been established for different monitoring and research purposes and are heterogeneous in terms of investigated ecosystem types, scales of investigation, complexity and instrumentation. Consequently, the transformation of the selected elements of the eLTER RI into a harmonized, high-performance, complementary and interoperable infrastructure is one of the key challenges of eLTER. Achieving the best possible representativity is on the major building blocks in eLTER’s design strategy.</p><p>To evaluate the representativity of eLTER a novel statistical approach combining information on biogeographical, ecological and socio-economic gradients with the management-relevant distribution of established sites was developed aiming at  i) identification of areas in Europe that are geographically underrepresented by the existing eLTER RI site network, ii) definition of priority regions for the geographical extension of the eLTER site network and, iii) development of suggestions for conceptual and infrastructural upgrades for existing less developed eLTER sites.</p><p>Reference datasets depicting biogeographical, ecological and socio-economical gradients were used to describe underrepresentation with a summation parameter called Aggregated Representedness. This statistical criterion was then used to classify five types of “priority regions” from very low to very high priority for geographical and/or conceptual extension. In a second step this information on priority regions was refined using additional information describing the geographical distribution based on Euclidean distances between established eLTER sites.  The combination of these two analyses allowed to identify less developed eLTER sites most suitable for conceptual and infrastructural upgrades. Thus, the presented analysis provides important information for the development of the design strategy for eLTER RI on the continental scale.</p><p>Concluding, a novel approach combining information on biogeographical, ecological and socio-economic gradients with the management-relevant information on the geographical distribution of established sites was developed. This tool allows to evaluate the strategies for further extension of established site networks. </p>


2018 ◽  
Vol 374 (1763) ◽  
pp. 20170394 ◽  
Author(s):  
Daniel S. Park ◽  
Ian Breckheimer ◽  
Alex C. Williams ◽  
Edith Law ◽  
Aaron M. Ellison ◽  
...  

Phenology is a key biological trait that can determine an organism's survival and provides one of the clearest indicators of the effects of recent climatic change. Long time-series observations of plant phenology collected at continental scales could clarify latitudinal and regional patterns of plant responses and illuminate drivers of that variation, but few such datasets exist. Here, we use the web tool CrowdCurio to crowdsource phenological data from over 7000 herbarium specimens representing 30 diverse flowering plant species distributed across the eastern United States. Our results, spanning 120 years and generated from over 2000 crowdsourcers, illustrate numerous aspects of continental-scale plant reproductive phenology. First, they support prior studies that found plant reproductive phenology significantly advances in response to warming, especially for early-flowering species. Second, they reveal that fruiting in populations from warmer, lower latitudes is significantly more phenologically sensitive to temperature than that for populations from colder, higher-latitude regions. Last, we found that variation in phenological sensitivities to climate within species between regions was of similar magnitude to variation between species. Overall, our results suggest that phenological responses to anthropogenic climate change will be heterogeneous within communities and across regions, with large amounts of regional variability driven by local adaptation, phenotypic plasticity and differences in species assemblages. As millions of imaged herbarium specimens become available online, they will play an increasingly critical role in revealing large-scale patterns within assemblages and across continents that ultimately can improve forecasts of the impacts of climatic change on the structure and function of ecosystems. This article is part of the theme issue ‘Biological collections for understanding biodiversity in the Anthropocene’.


2008 ◽  
Vol 35 (4) ◽  
pp. 275 ◽  
Author(s):  
Rachel M. Fewster ◽  
Colin Southwell ◽  
David L. Borchers ◽  
Stephen T. Buckland ◽  
Anthony R. Pople

Line-transect distance sampling is a widely used method for estimating animal density from aerial surveys. Analysis of line-transect distance data usually relies on a requirement that the statistical distribution of distances of animal groups from the transect line is uniform. We show that this requirement is satisfied by the survey design if all other assumptions of distance sampling hold, but it can be violated by consistent survey problems such as responsive movement of the animals towards or away from the observer. We hypothesise that problems with the uniform requirement are unlikely to be encountered for immobile taxa, but might become substantial for species of high mobility. We test evidence for non-uniformity using double-observer distance data from two aerial surveys of five species with a spectrum of mobility capabilities and tendencies. No clear evidence against uniformity was found for crabeater seals or emperor penguins on the pack-ice in East Antarctica, while minor non-uniformity consistent with responsive movement up to 30 m was found for Adelie penguins. Strong evidence of either non-uniformity or a failure of the capture–recapture validating method was found for eastern grey kangaroos and red kangaroos in Queensland.


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