Using Bird Distributions to Assess Extinction Risk and Identify Conservation Priorities in Biodiversity Hotspots

Habitat loss, fragmentation, and degradation threaten the World’s ecosystems and species. These, and other threats, will likely be exacerbated by climate change. Due to a limited budget for conservation, we are forced to prioritize a few areas over others. These places are selected based on their uniqueness and vulnerability. One of the most famous examples is the biodiversity hotspots: areas where large quantities of endemic species meet alarming rates of habitat loss. Most of these places are in the tropics, where species have smaller ranges, diversity is higher, and ecosystems are most threatened.

Species distributions are useful to understand ecological theory and evaluate extinction risk. Small-ranged species, or those endemic to one place, are more vulnerable to extinction than widely distributed species. However, current range maps often overestimate the distribution of species, including areas that are not within the suitable elevation or habitat for a species. Consequently, assessment of extinction risk using these maps could underestimate vulnerability.

In order to be effective in our quest to conserve the World’s most important places we must: 1) Translate global and national priorities into practical local actions, 2) Find synergies between biodiversity conservation and human welfare, 3) Evaluate the different dimensions of threats, in order to design effective conservation measures and prepare for future threats, and 4) Improve the methods used to evaluate species’ extinction risk and prioritize areas for conservation. The purpose of this dissertation is to address these points in Colombia and other global biodiversity hotspots.

In Chapter 2, I identified the global, strategic conservation priorities and then downscaled to practical local actions within the selected priorities in Colombia. I used existing range maps of 171 bird species to identify priority conservation areas that would protect the greatest number of species at risk in Colombia (endemic and small-ranged species). The Western Andes had the highest concentrations of such species—100 in total—but the lowest densities of national parks. I then adjusted the priorities for this region by refining these species ranges by selecting only areas of suitable elevation and remaining habitat. The estimated ranges of these species shrank by 18–100% after accounting for habitat and suitable elevation. Setting conservation priorities on the basis of currently available range maps excluded priority areas in the Western Andes and, by extension, likely elsewhere and for other taxa. By incorporating detailed maps of remaining natural habitats, I made practical recommendations for conservation actions. One recommendation was to restore forest connections to a patch of cloud forest about to become isolated from the main Andes.

For Chapter 3, I identified areas where bird conservation met ecosystem service protection in the Central Andes of Colombia. Inspired by the November 11th (2011) landslide event near Manizales, and the current poor results of Colombia’s Article 111 of Law 99 of 1993 as a conservation measure in this country, I set out to prioritize conservation and restoration areas where landslide prevention would complement bird conservation in the Central Andes. This area is one of the most biodiverse places on Earth, but also one of the most threatened. Using the case of the Rio Blanco Reserve, near Manizales, I identified areas for conservation where endemic and small-range bird diversity was high, and where landslide risk was also high. I further prioritized restoration areas by overlapping these conservation priorities with a forest cover map. Restoring forests in bare areas of high landslide risk and important bird diversity yields benefits for both biodiversity and people. I developed a simple landslide susceptibility model using slope, forest cover, aspect, and stream proximity. Using publicly available bird range maps, refined by elevation, I mapped concentrations of endemic and small-range bird species. I identified 1.54 km2 of potential restoration areas in the Rio Blanco Reserve, and 886 km2 in the Central Andes region. By prioritizing these areas, I facilitate the application of Article 111 which requires local and regional governments to invest in land purchases for the conservation of watersheds.

Chapter 4 dealt with elevational ranges of montane birds and the impact of lowland deforestation on their ranges in the Western Andes of Colombia, an important biodiversity hotspot. Using point counts and mist-nets, I surveyed six altitudinal transects spanning 2200 to 2800m. Three transects were forested from 2200 to 2800m, and three were partially deforested with forest cover only above 2400m. I compared abundance-weighted mean elevation, minimum elevation, and elevational range width. In addition to analyzing the effect of deforestation on 134 species, I tested its impact within trophic guilds and habitat preference groups. Abundance-weighted mean and minimum elevations were not significantly different between forested and partially deforested transects. Range width was marginally different: as expected, ranges were larger in forested transects. Species in different trophic guilds and habitat preference categories showed different trends. These results suggest that deforestation may affect species’ elevational ranges, even within the forest that remains. Climate change will likely exacerbate harmful impacts of deforestation on species’ elevational distributions. Future conservation strategies need to account for this by protecting connected forest tracts across a wide range of elevations.

In Chapter 5, I refine the ranges of 726 species from six biodiversity hotspots by suitable elevation and habitat. This set of 172 bird species for the Atlantic Forest, 138 for Central America, 100 for the Western Andes of Colombia, 57 for Madagascar, 102 for Sumatra, and 157 for Southeast Asia met the criteria for range size, endemism, threat, and forest use. Of these 586 species, the Red List deems 108 to be threatened: 15 critically endangered, 29 endangered, and 64 vulnerable. When ranges are refined by elevational limits and remaining forest cover, 10 of those critically endangered species have ranges < 100km2, but then so do 2 endangered species, seven vulnerable, and eight non-threatened ones. Similarly, 4 critically endangered species, 20 endangered, and 12 vulnerable species have refined ranges < 5000km2, but so do 66 non-threatened species. A striking 89% of these species I have classified in higher threat categories have <50% of their refined ranges inside protected areas. I find that for 43% of the species I assessed, refined range sizes fall within thresholds that typically have higher threat categories than their current assignments. I recommend these species for closer inspection by those who assess risk. These assessments are not only important on a species-by-species basis, but by combining distributions of threatened species, I create maps of conservation priorities. They differ significantly from those created from unrefined ranges.

Grabbing Your Attention: The Impact of Finding a First Target in Multiple-Target Search

For over 50 years, the Satisfaction of Search effect, and more recently known as the Subsequent Search Miss (SSM) effect, has plagued the field of radiology. Defined as a decrease in additional target accuracy after detecting a prior target in a visual search, SSM errors are known to underlie both real-world search errors (e.g., a radiologist is more likely to miss a tumor if a different tumor was previously detected) and more simplified, lab-based search errors (e.g., an observer is more likely to miss a target ‘T’ if a different target ‘T’ was previously detected). Unfortunately, little was known about this phenomenon’s cognitive underpinnings and SSM errors have proven difficult to eliminate. However, more recently, experimental research has provided evidence for three different theories of SSM errors: the Satisfaction account, the Perceptual Set account, and the Resource Depletion account. A series of studies examined performance in a multiple-target visual search and aimed to provide support for the Resource Depletion account—a first target consumes cognitive resources leaving less available to process additional targets.

To assess a potential mechanism underlying SSM errors, eye movements were recorded in a multiple-target visual search and were used to explore whether a first target may result in an immediate decrease in second-target accuracy, which is known as an attentional blink. To determine whether other known attentional distractions amplified the effects of finding a first target has on second-target detection, distractors within the immediate vicinity of the targets (i.e., clutter) were measured and compared to accuracy for a second target. To better understand which characteristics of attention were impacted by detecting a first target, individual differences within four characteristics of attention were compared to second-target misses in a multiple-target visual search.

The results demonstrated that an attentional blink underlies SSM errors with a decrease in second-target accuracy from 135ms-405ms after detection or re-fixating a first target. The effects of clutter were exacerbated after finding a first target causing a greater decrease in second-target accuracy as clutter increased around a second-target. The attentional characteristics of modulation and vigilance were correlated with second- target misses and suggest that worse attentional modulation and vigilance are predictive of more second-target misses. Taken together, these result are used as the foundation to support a new theory of SSM errors, the Flux Capacitor theory. The Flux Capacitor theory predicts that once a target is found, it is maintained as an attentional template in working memory, which consumes attentional resources that could otherwise be used to detect additional targets. This theory not only proposes why attentional resources are consumed by a first target, but encompasses the research in support of all three SSM theories in an effort to establish a grand, unified theory of SSM errors.

Putting Adequate Financial and Human Resources in Healthcare for Effective Universal Health Coverage in Kenya: Lessons and Experiences from China

In recent years, most low and middle-income countries, have adopted different approaches to universal health coverage (UHC), to ensure equity and financial risk protection in accessing essential healthcare services. UHC-related policies and delivery strategies are largely based on existing healthcare systems, a result of gradual development (based on local factors and priorities). Most countries have emphasized on health financing, and human resources for health (HRH) reform policies, based on good practices of several healthcare plans to deliver UHC for their population.

Health financing and labor market frameworks were used, to understand health financing, HRH dynamics, and to analyze key health policies implemented over the past decade in Kenya’s effort to achieve UHC. Through the understanding, policy options are proposed to Kenya; analyzing, and generating lessons from health financing, and HRH reforms experiences in China. Data was collected using mixed methods approach, utilizing both quantitative (documents and literature review), and qualitative (in-depth interviews) data collection techniques.

The problems in Kenya are substantial: high levels of out-of-pocket health expenditure, slow progress in expanding health insurance among informal sector workers, inefficiencies in pulling of health are revenues, inadequate deployed HRH, maldistribution of HRH, and inadequate quality measures in training health worker. The government has identified the critical role of strengthening primary health care and the National Hospital Insurance Fund (NHIF) in Kenya’s move towards UHC. Strengthening primary health care requires; re-defining the role of hospitals, and health insurance schemes, and training, deploying and retaining primary care professionals according to the health needs of the population; concepts not emphasized in Kenya’s healthcare reforms or programs design. Kenya’s top leadership commitment is urgently needed for tougher reforms implementation, and important lessons from China’s extensive health reforms in the past decade are beneficial. Key lessons from China include health insurance expansion through rigorous research, monitoring, and evaluation, substantially increasing government health expenditure, innovative primary healthcare strengthening, designing, and implementing health policy reforms that are responsive to the population, and regional approaches to strengthening HRH.