Satellite-Based Human Settlement Datasets Inadequately Detect Refugee Settlements: A Critical Assessment at Thirty Refugee Settlements in Uganda

Satellite-based broad-scale (i.e., global and continental) human settlement data are essential for diverse applications spanning climate hazard mitigation, sustainable development monitoring, spatial epidemiology and demographic modeling. Many human settlement products report exceptional detection accuracies above 85%, but there is a substantial blind spot in that product validation typically focuses on large urban areas and excludes rural, small-scale settlements that are home to 3.4 billion people around the world. In this study, we make use of a data-rich sample of 30 refugee settlements in Uganda to assess the small-scale settlement detection by four human settlement products, namely, Geo-Referenced Infrastructure and Demographic Data for Development settlement extent data (GRID3-SE), Global Human Settlements Built-Up Sentinel-2 (GHS-BUILT-S2), High Resolution Settlement Layer (HRSL) and World Settlement Footprint (WSF). We measured each product’s areal coverage within refugee settlement boundaries, assessed detection of 317,416 building footprints and examined spatial agreement among products. For settlements established before 2016, products had low median probability of detection and F1-score of 0.26 and 0.24, respectively, a high median false alarm rate of 0.59 and tended to only agree in regions with the highest building density. Individually, GRID3-SE offered more than five-fold the coverage of other products, GHS-BUILT-S2 underestimated the building footprint area by a median 50% and HRSL slightly underestimated the footprint area by a median 7%, while WSF entirely overlooked 8 of the 30 study refugee settlements. The variable rates of coverage and detection partly result from GRID3-SE and HRSL being based on much higher resolution imagery, compared to GHS-BUILT-S2 and WSF. Earlier established settlements were generally better detected than recently established settlements, showing that the timing of satellite image acquisition with respect to refugee settlement establishment also influenced detection results. Nonetheless, settlements established in the 1960s and 1980s were inconsistently detected by settlement products. These findings show that human settlement products have far to go in capturing small-scale refugee settlements and would benefit from incorporating refugee settlements in training and validating human settlement detection approaches.

Demographic modeling informs functional connectivity and management interventions in Graham’s beardtongue

Functional connectivity (i.e., the movement of individuals across a landscape) is essential for the maintenance of genetic variation and persistence of rare species. However, illuminating the processes influencing functional connectivity and ultimately translating this knowledge into management practice remains a fundamental challenge. Here, we combine various population structure analyses with pairwise, population-specific demographic modeling to investigate historical functional connectivity in Graham’s beardtongue (Penstemon grahamii), a rare plant narrowly distributed across a dryland region of the western US. While principal component and population structure analyses indicated an isolation-by-distance pattern of differentiation across the species’ range, spatial inferences of effective migration exposed an abrupt shift in population ancestry near the range center. To understand these seemingly conflicting patterns, we tested various models of historical gene flow and found evidence for recent admixture (~ 3400 generations ago) between populations near the range center. This historical perspective reconciles population structure patterns and suggests management efforts should focus on maintaining connectivity between these previously isolated lineages to promote the ongoing transfer of genetic variation. Beyond providing species-specific knowledge to inform management options, our study highlights how understanding demographic history may be critical to guide conservation efforts when interpreting population genetic patterns and inferring functional connectivity.

Addressing alpine plant phylogeography using integrative distributional, demographic and coalescent modeling

Phylogeographic studies of alpine plants have evolved considerably in the last two decades from ad hoc interpretations of genetic data to statistical model-based approaches. In this review we outline the developments in alpine plant phylogeography focusing on the recent approach of integrative distributional, demographic and coalescent (iDDC) modeling. By integrating distributional data with spatially explicit demographic modeling and subsequent coalescent simulations, the history of alpine species can be inferred and long-standing hypotheses, such as species-specific responses to climate change or survival on nunataks during the last glacial maximum, can be efficiently tested as exemplified by available case studies. We also discuss future prospects and improvements of iDDC.

Diagnosing restoration trajectories using demographic modeling and modern coexistence theory

Restoration success is often measured by comparing target species abundance between restored and reference populations. Abundance may poorly predict long-term success, however, because seed addition may initially inflate restored population abundances, and reference population abundances may fluctuate with environmental variation. A demographic approach, informed by modern coexistence theory, may allow for more accurate diagnosis of restoration trajectories. We modeled population dynamics of an endangered plant (Lasthenia conjugens) in restored vernal pools and compared them to reference populations over 18 years (2000-2017). Model estimates of L. conjugens growth rates were better predictors of long-term trends than observed abundances. Although populations fluctuated in reference pools, annual rainfall variability acted as a stabilizing factor for L. conjugens. In restored pools however, invasive grasses and associated litter accumulation overrode the benefits of environmental variability. Our approach improves assessment of restoration outcomes and indicates when management actions, such as grass removal, will improve future trajectories.

Environmental and Management Effects on Demographic Processes in the U.S. Threatened Platanthera leucophaea (Nutt.) Lindl. (Orchidaceae)

Populations of the U.S. threatened orchid, Platanthera leucophaea, are restricted to fragmented grassland and wetland habitats. We address the long-term (1998–2020) interactive effects of habitat (upland prairie vs. wetland), fire management (burned vs. unburned) and climatic variation, as well as pollination crossing effects, on population demography in 42 populations. Our analysis revealed the consistent interactive effects of habitat, dormant season burning, and climatic variation on flowering, reproduction, and survival. Burning increased flowering and population size under normal or greater than normal precipitation but may have a negative effect during drought years apparently if soil moisture stress reduces flowering and increases mortality. Trends in the number of flowering plants in populations also correspond to precipitation cycles. As with flowering and fecundity, survival is significantly affected by the interactive effects of habitat, fire, and climate. This study supports previous studies finding that P. leucophaea relies on a facultative outcrossing breeding system. Demographic modeling indicated that fire, normal precipitation, and outcrossing yielded greater population growth, and that greater fire frequency increased population persistence. It also revealed an ecologically driven demographic switch, with wetlands more dependent upon survivorship than fecundity, and uplands more dependent on fecundity than survivorship. Our results facilitate an understanding of environmental and management effects on the population demography of P. leucophaea in the prairie region of its distribution. Parallel studies are needed in the other habitats such as wetlands, especially in the eastern part of the range of the species, to provide a more complete picture.

Congruent evolutionary responses of European steppe biota to late Quaternary climate change: insights from convolutional neural network based demographic modeling

Quaternary climatic oscillations had a large impact on European biogeography. Alternation of cold and warm stages caused recurrent glaciations, massive vegetation shifts and large-scale range alterations in many species. The Eurasian steppe biome and its grasslands are a noteworthy example; they underwent climate-driven, large-scale contractions during warm stages and expansions during cold stages. Here, we evaluate the impact of these range alterations on the late Quaternary demography of phylogenetically unrelated plant and insect species, typical of the Eurasian steppes. We contrast three explicit demographic hypotheses by applying a novel approach combining Convolutional Neural Networks with Approximate Bayesian Computation. We identified congruent demographic responses of cold stage expansions and warm stage contractions across all species, but also species-specific effects. The demographic history of Eurasian steppe biota reflects major paleoecological turning points of the late Quaternary, and emphasizes the role of the climate as a driving force behind patterns of genetic variance.

Using ddRAD-seq phylogeography to test for genetic effects of headwater river capture in suckermouth armored catfish (Loricariidae: Hypostomus) from the central Brazilian Shield

River capture is a geological process of potentially great importance in shaping the genetic diversity, distributions, and community composition of freshwater taxa. Using phylogeographic analyses of ddRAD-seq data from suckermouth armored catfish (Hypostomus sp. 2) populations, we tested for predicted genetic effects of headwater river capture events in central Brazil, previously supported by geological and community ecological data. We analyzed 227 ddRAD tags (3829 SNP loci) across 42 samples. Molecular results strongly supported six Hypostomus genetic clusters/lineages, with the deepest divergence ~1.25 million years ago in the early Pleistocene between a clade from the Upper Paraná and Upper São Francisco river basins versus all other lineages. Consistent with the 'Paraná Capture Hypothesis', several lines of evidence supported mid-Pleistocene colonization and vicariant isolation of Hypostomus populations from an ancestral Upper Paraná population, including: (1) significant phylogeographic structure, with predicted phylogenetic patterns, (2) higher Paraná lineage diversity, (3) ancestral geographic locations reconstructed in the Paraná basin, and (4) non-random interdrainage dispersal and vicariance events, indicating river captures primarily into the Tocantins and Upper São Francisco basins c. ~220,000-145,500 years ago. Phylogeographic inference was complicated by lack of lineage monophyly across loci and lineages distributed in multiple basins, the latter of which lent support to the non-mutually exclusive 'Frequent Interdrainage Dispersal Hypothesis'. However, species tree and demographic modeling results suggested these were artefacts of incomplete sorting of alleles in large ancestral populations over a geologically recent timeframe of divergence. Qualitative and quantitative sensitivity analyses demonstrated that our downstream genetic results were robust to effects of varying ddRAD-seq assembly parameters, which heavily influenced the number of output loci. We predict that codistributed freshwater taxa in Central Brazil may not exhibit phylogeographic patterns similar to Hypostomus sp. 2 due to complex patterns of superimposed river capture events, or if smaller ancestral population sizes have allowed more complete lineage sorting in other taxa.

Faster-X adaptive differentiation under divergence-with-gene-flow in diploids and haplodiploids

Empirical data from diverse taxa indicate that the hemizygous portions of the genome (X/Z chromosomes) evolve more rapidly than their diploid counterparts. Faster-X theory predicts increased rates of adaptive substitutions between isolated species, yet little is known about species experiencing gene flow. Here we investigate how hemizygosity impacts genome-wide patterns of differentiation during adaptive divergence with gene flow, combining simulations under isolation-with-migration models, a meta-analysis of autosomes and sex-chromosomes from diverse taxa, and analysis of haplodiploid species. First, using deterministic and stochastic simulations, we show that elevated differentiation at hemizygous loci occurs when there is gene flow, irrespective of dominance. This faster-X adaptive differentiation stems from more efficient selection resulting in reduced probability of losing the beneficial allele, greater migration-selection threshold, greater allele frequency differences at equilibrium, and a faster time to equilibrium. Second, by simulating neutral variation linked to selected loci, we show that faster-X differentiation affects linked variation due to reduced opportunities for recombination between locally adaptive and maladaptive immigrant haplotypes. Third, after correcting for expected differences in effective population size, we find that most taxon pairs (24 out of 28) exhibit faster-X differentiation in the meta-analysis. Finally, using a novel approach combining demographic modeling and simulations, we found evidence for faster-X differentiation in haplodiploid pine-feeding hymenopteran species adapted to different host plants. Together, our results indicate that divergent selection with gene flow can lead to higher differentiation at selected and linked variation in hemizygous loci (i.e., faster-X adaptive differentiation), both in X/Z-chromosomes and haplodiploid species.

Fine-scale population structure in five rural populations from the Spanish Eastern Pyrenees using high-coverage whole-genome sequence data

The area of the Spanish Pyrenees is particularly interesting for studying the demographic dynamics of European rural areas given its orography, the main traditional rural condition of its population and the reported higher patterns of consanguinity of the region. Previous genetic studies suggest a gradient of genetic continuity of the area in the West to East axis. However, it has been shown that micro-population substructure can be detected when considering high-quality NGS data and using spatial explicit methods. In this work, we have analyzed the genome of 30 individuals sequenced at 40× from five different valleys in the Spanish Eastern Pyrenees (SEP) separated by less than 140 km along a west to east axis. Using haplotype-based methods and spatial analyses, we have been able to detect micro-population substructure within SEP not seen in previous studies. Linkage disequilibrium and autozygosity analyses suggest that the SEP populations show diverse demographic histories. In agreement with these results, demographic modeling by means of ABC-DL identify heterogeneity in their effective population sizes despite of their close geographic proximity, and suggests that the population substructure within SEP could have appeared around 2500 years ago. Overall, these results suggest that each rural population of the Pyrenees could represent a unique entity.

Extended input–output model for urbanization: an empirical test using Chinese data

Although the input–output model has been widely used for both pure economic analysis and environmental issues, demographic analysis has been relegated to the periphery of the input–output literature. Previous researchers have made significant contributions in developing the economic–demographic modeling from the unemployment perspective, in the context of shrinking regional economies. This study aims to develop an extended input–output model for urbanization, based on the Batey–Madden model by incorporating the “urbanization process”. This process is associated with one of the facets of demographic change and has received little attention in the literature. The effectiveness of the model is theoretically explored and empirically tested using Chinese data, which show rapid progress of urbanization in China. The study proposes a new “urbanization multiplier”, which implies intense population concentration in cities based on an employment multiplier in urban areas and labor allocation possibilities between urban and rural areas. The result from a preliminary application shows that the economic structure can determine the urbanization multiplier, indicating that the extent of employment opportunities promotes urbanization and the size of the population attracts more workers from rural areas. The model provides a fresh aspect of urbanization in the existing literature.