Biology subjects

Strimas-Mackey, M.

Publications and source records attributed to Strimas-Mackey, M..

5 recordsLinked to original sources

bioRxiv2020

Global critical natural assets

Sustaining the organisms, ecosystems, and processes that underpin human well-being is necessary to achieve sustainable development. Here we identify critical natural assets, natural and semi-natural ecosystems that provide 90% of the total current magnitude of 14 types of natures contributions to people (NCP). Critical natural assets for maintaining local-scale NCP (12 of the 14 NCP mapped) comprise 30% of total global land area and 24% of national territorial waters, while 44% of land area is required for maintaining all NCP (including those that accrue at the global scale, carbon storage and moisture recycling). At least 87% of the worlds population lives in the areas benefiting from critical natural assets for local-scale NCP, while only 16% lives on the lands containing these assets. Critical natural assets also overlap substantially with areas important for biodiversity (covering area requirements for 73% of birds and 66% of mammals) and cultural diversity (representing 96% of global Indigenous and non-migrant languages). Many of the NCP mapped here are left out of international agreements focused on conserving species or mitigating climate change, yet this analysis shows that explicitly prioritizing critical natural assets for NCP could simultaneously advance development, climate, and conservation goals. Crafting policy and investment strategies that protect critical natural assets is essential for sustaining human well-being and securing Earths life support systems.

ecology↗

bioRxiv2019

Integer linear programming outperforms simulated annealing for solving conservation planning problems

The resources available for conserving biodiversity are limited, and so protected areas need to be established in places that will achieve objectives for minimal cost. Two of the main algorithms for solving systematic conservation planning problems are Simulated Annealing (SA) and Integer linear programming (ILP). Using a case study in British Columbia, Canada, we compare the cost-effectiveness and processing times of SA versus ILP using both commercial and open-source algorithms. Plans for expanding protected area systems based on ILP algorithms were 12 to 30% cheaper than plans using SA. The best ILP solver we examined was on average 1071 times faster than the SA algorithm tested. The performance advantages of ILP solvers were also observed when we aimed for spatially compact solutions by including a boundary penalty. One practical advantage of using ILP over SA is that the analysis does not require calibration, saving even more time. Given the performance of ILP solvers, they can be used to generate conservation plans in real-time during stakeholder meetings and can facilitate rapid sensitivity analysis, and contribute to a more transparent, inclusive, and defensible decision-making process.

ecology↗

bioRxiv2019

A meta-analysis of global avian survival across species and latitude

Tropical birds are purported to be longer lived than temperate species of similar size, but it has not been shown whether avian survival rates covary with a latitudinal gradient worldwide. Here, we perform a global-scale meta-analysis to investigate the extent of the latitudinal survival gradient. We modeled survival as a function of latitude for the separate northern and southern hemispheres, and considered phylogenetic relationships and extrinsic (climate) and intrinsic (life history) predictors hypothesized to moderate these effects. Using a database of 1,004 estimates from 246 studies of avian survival, we demonstrate that in general a latitudinal survival gradient exists in the northern hemisphere, is dampened or absent for southern hemisphere species, and that survival rates of passerine birds largely account for these trends. We found no indication that the extrinsic climate factors were better predictors of survival than latitude alone, but including species intrinsic traits improved model predictions. Notably, species with smaller clutch size and larger body mass showed higher survival. Our results illustrate that while some tropical birds may be longer lived than their temperate counterparts, the shape of the latitude-survival gradient differs by geographic region and is strongly influenced by species intrinsic traits.

ecology↗

bioRxiv2019

Integrating citizen science data with expert surveys improves the accuracy and range of inference of species distribution models

Information on species habitat associations and distributions, across a wide range of spatial and temporal scales, are a fundamental source of ecological knowledge. However, collecting biological information at relevant scales if often cost prohibitive, although it is essential for framing the broader context of more focused research and conservation efforts. Citizen-science data has been signaled as an increasingly important source of biological information needed to fill in data gaps needed to make more comprehensive and robust inferences on species distributions. However, there are perceived trade-offs of combining highly structured, scientific survey data with largely unstructured, citizen-science data. As a result, the focus of most methodological advances to combine these sources of information has been on treating these sources as independent. The degree to which each source of information is allowed to directly inform a common underlying process (e.g. species distribution) depends on the perceived quality of the data. In this paper, we explore these trade-offs by applying a simplified approach of filtering citizen-science data to resemble structured survey data, and analyze both sources of data under a common framework. To accomplish this, we explored ways of integrating high-resolution survey data on shorebirds in the northern Central Valley of California with observations in eBird for the entire region that were filtered to improve their quality. The integration of survey data with the filtered citizen-science data in eBird resulted in improved inference and predictive ability, and increased the extent and accuracy of inferences on shorebirds for the Central Valley. The structured surveys were found to improve the overall accuracy of ecological inference based only on citizen-science data, by increasing the representation of data collected from high quality habitats for shorebirds (e.g. rice fields). The practical approach we have shown for data integration can be also be used to improve the efficiency of designing biological surveys in the context of larger, citizen-science monitoring efforts, ultimately reducing the financial and time expenditures typically required of monitoring programs and focused research. The simple processing and filtering method we present can be used to integrate other types of data (e.g. camera traps) with more localized efforts (e.g. research projects), ultimately improving our ecological knowledge on the distribution and habitat associations of species of conservation concern worldwide.

ecology↗

bioRxiv2019

Best practices for making reliable inferences from citizen science data: case study using eBird to estimate species distributions

Citizen science data are valuable for addressing a wide range of ecological research questions, and there has been a rapid increase in the scope and volume of data available. However, data from large-scale citizen science projects typically present a number of challenges that can inhibit robust ecological inferences. These challenges include: species bias, spatial bias, and variation in effort. To demonstrate addressing key challenges in analysing citizen science data, we use the example of estimating species distributions with data from eBird, a large semi-structured citizen science project. We estimate two widely applied metrics of species distributions: encounter rate and occupancy probability. For each metric, we assess the impact of data processing steps that either degrade or refine the data used in the analyses. We also test whether differences in model performance are maintained at different sample sizes. Model performance improved when data processing and analytical methods addressed the challenges arising from citizen science data. The largest gains in model performance were achieved with: 1) the use of complete checklists (where observers report all the species they detect and identify); and 2) the use of covariates describing variation in effort and detectability for each checklist. Occupancy models were more robust to a lack of complete checklists and effort variables. Improvements in model performance with data refinement were more evident with larger sample sizes. Here, we describe processes to refine semi-structured citizen science data to estimate species distributions. We demonstrate the value of complete checklists, which can inform the design and adaptation of citizen science projects. We also demonstrate the value of information on effort. The methods we have outlined are also likely to improve other forms of inference, and will enable researchers to conduct robust analyses and harness the vast ecological knowledge that exists within citizen science data.

ecology↗