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Connectivity of habitat patches is thought to be important for movement of genes, individuals, populations, and species over multiple temporal and spatial scales. We used graph theory to characterize multiple aspects of landscape connectivity in a habitat network in the North Carolina Piedmont (U.S.A).. We compared this landscape with simulated networks with known topology, resistance to disturbance, and rate of movement. We introduced graph measures such as compartmentalization and clustering, which can be used to identify locations on the landscape that may be especially resilient to human development or areas that may be most suitable for conservation. Our analyses indicated that for songbirds the Piedmont habitat network was well connected. Furthermore, the habitat network had commonalities with planar networks, which exhibit slow movement, and scale-free networks, which are resistant to random disturbances. These results suggest that connectivity in the habitat network was high enough to prevent the negative consequences of isolation but not so high as to allow rapid spread of disease. Our graph-theory framework provided insight into regional and emergent global network properties in an intuitive and visual way and allowed us to make inferences about rates and paths of species movements and vulnerability to disturbance. This approach can be applied easily to assessing habitat connectivity in any fragmented or patchy landscape.

Terrestrial long-distance migrations are declining globally: in North America, nearly 75% have been lost. Yet there has been limited research comparing habitat suitability and connectivity models to identify migration corridors across increasingly fragmented landscapes. Here we use pronghorn (Antilocapra americana) migrations in prairie habitat to compare two types of models that identify habitat suitability: maximum entropy (Maxent) and expert-based (Analytic Hierarchy Process). We used distance to wells, distance to water, NDVI, land cover, distance to roads, terrain shape and fence presence to parameterize the models. We then used the output of these models as cost surfaces to compare two common connectivity models, least-cost modeling (LCM) and circuit theory. Using pronghorn movement data from spring and fall migrations, we identified potential migration corridors by combining each habitat suitability model with each connectivity model. The best performing model combination was Maxent with LCM corridors across both seasons. Maxent out-performed expert-based habitat suitability models for both spring and fall migrations. However, expert-based corridors can perform relatively well and are a cost-effective alternative if species location data are unavailable. Corridors created using LCM out-performed circuit theory, as measured by the number of pronghorn GPS locations present within the corridors. We suggest the use of a tiered approach using different corridor widths for prioritizing conservation and mitigation actions, such as fence removal or conservation easements.

Our society faces the pressing challenge of increasing agricultural production while minimizing negative consequences on ecosystems and the global climate. Indonesia, which has pledged to reduce greenhouse gas (GHG) emissions from deforestation while doubling production of several major agricultural commodities, exemplifies this challenge. Here we focus on palm oil, the world's most abundant vegetable oil and a commodity that has contributed significantly to Indonesia's economy. Most oil palm expansion in the country has occurred at the expense of forests, resulting in significant GHG emissions. We examine the extent to which land management policies can resolve the apparently conflicting goals of oil palm expansion and GHG mitigation in Kalimantan, a major oil palm growing region of Indonesia. Using a logistic regression model to predict the locations of new oil palm between 2010 and 2020 we evaluate the impacts of six alternative policy scenarios on future emissions. We estimate net emissions of 128.4-211.4 MtCO2 yr(-1) under business as usual expansion of oil palm plantations. The impact of diverting new plantations to low carbon stock land depends on the design of the policy. We estimate that emissions can be reduced by 9-10% by extending the current moratorium on new concessions in primary forests and peat lands, 35% by limiting expansion on all peat and forestlands, 46% by limiting expansion to areas with moderate carbon stocks, and 55-60% by limiting expansion to areas with low carbon stocks. Our results suggest that these policies would reduce oil palm profits only moderately but would vary greatly in terms of cost-effectiveness of emissions reductions. We conclude that a carefully designed and implemented oil palm expansion plan can contribute significantly towards Indonesia's national emissions mitigation goal, while allowing oil palm area to double.

The dispersal of individuals among marine populations is of great importance to metapopulation dynamics, population persistence, and species expansion. Understanding this connectivity between distant populations is key to their effective conservation and management. For many marine species, population connectivity is determined largely by ocean currents transporting larvae and juveniles between distant patches of suitable habitat. Recent work has focused on the biophysics of marine larval dispersal and its importance to population dynamics, although few studies have evaluated the spatial and temporal patterns of this potential dispersal. Here, we show how an Eulerian advection-diffusion approach can be used to model the dispersal of coral larvae between reefs throughout the Tropical Pacific. We illustrate how this connectivity can be analyzed using graph theory--an effective approach for exploring patterns in spatial connections, as well as for determining the importance of each site and pathway to local and regional connectivity. Results indicate that the scale (average distance) of dispersal in the Pacific is on the order of 50-150 km, consistent with recent studies in the Caribbean (Cowen, et al. 2006). Patterns in the dispersal graphs highlight pathways for larval dispersal along major ocean currents and through island chains. A series of critical island 'stepping stones' are discovered providing potential pathways across the equatorial currents and connecting distant island groups. Patterns in these dispersal graphs highlight possible pathways for species expansions, reveal connected upstream/downstream populations, and suggest areas that might be prioritized for marine conservation efforts.

Predictive habitat models can provide critical information that is necessary in many conservation applications. Using Maximum Entropy modeling, we characterized habitat relationships and generated spatial predictions of spinner dolphin (Stenella longirostris) resting habitat in the main Hawaiian Islands. Spinner dolphins in Hawai'i exhibit predictable daily movements, using inshore bays as resting habitat during daylight hours and foraging in offshore waters at night. There are growing concerns regarding the effects of human activities on spinner dolphins resting in coastal areas. However, the environmental factors that define suitable resting habitat remain unclear and must be assessed and quantified in order to properly address interactions between humans and spinner dolphins. We used a series of dolphin sightings from recent surveys in the main Hawaiian Islands and a suite of environmental variables hypothesized as being important to resting habitat to model spinner dolphin resting habitat. The model performed well in predicting resting habitat and indicated that proximity to deep water foraging areas, depth, the proportion of bays with shallow depths, and rugosity were important predictors of spinner dolphin habitat. Predicted locations of suitable spinner dolphin resting habitat provided in this study indicate areas where future survey efforts should be focused and highlight potential areas of conflict with human activities. This study provides an example of a presence-only habitat model used to inform the management of a species for which patterns of habitat availability are poorly understood.

At global and regional scales, tree mortality rates are positively correlated with forest net primary productivity (NPP). Yet causes of the correlation are unknown, in spite of potentially profound implications for our understanding of environmental controls of forest structure and dynamics and, more generally, our understanding of broad-scale environmental controls of population dynamics and ecosystem processes. Here we seek to shed light on the causes of geographic patterns in tree mortality rates, and we consider some implications of the positive correlation between mortality rates and NPP. To reach these ends, we present seven hypotheses potentially explaining the correlation, develop an approach to help distinguish among the hypotheses, and apply the approach in a case study comparing a tropical and temperate forest. Based on our case study and literature synthesis, we conclude that no single mechanism controls geographic patterns of tree mortality rates. At least four different mechanisms may be at play, with the dominant mechanisms depending on whether the underlying productivity gradients are caused by climate or soil fertility. Two of the mechanisms are consequences of environmental selection for certain combinations of life-history traits, reflecting trade-offs between growth and defense (along edaphic productivity gradients) and between reproduction and persistence (as manifested in the adult tree stature continuum along climatic and edaphic gradients). The remaining two mechanisms are consequences of environmental influences on the nature and strength of ecological interactions: competition (along edaphic gradients) and pressure from plant enemies (along climatic gradients). For only one of these four mechanisms, competition, can high mortality rates be considered to be a relatively direct consequence of high NPP. The remaining mechanisms force us to adopt a different view of causality, in which tree growth rates and probability of mortality can vary with at least a degree of independence along productivity gradients. In many cases, rather than being a direct cause of high mortality rates, NPP may remain high in spite of high mortality rates. The independent influence of plant enemies and other factors helps explain why forest biomass can show little correlation, or even negative correlation, with forest NPP.

Industrial-scale oil palm cultivation is rapidly expanding in Gabon, where it has the potential to drive economic growth, but also threatens forest, biodiversity and carbon resources. The Gabonese government is promoting an ambitious agricultural expansion strategy, while simultaneously committing to minimize negative environmental impacts of oil palm agriculture. This study estimates the extent and location of suitable land for oil palm cultivation in Gabon, based on an analysis of recent trends in plantation permitting. We use the resulting suitability map to evaluate two proposed approaches to minimizing negative environmental impacts: a High Carbon Stock (HCS) approach, which emphasizes forest protection and climate change mitigation, and a High Conservation Value (HCV) approach, which focuses on safeguarding biodiversity and ecosystems. We quantify the forest area, carbon stock, and biodiversity resources protected under each approach, using newly developed maps of priority species distributions and forest biomass for Gabon. We find 2.7-3.9 Mha of suitable or moderately suitable land that avoid HCS areas, 4.4 million hectares (Mha) that avoid HCV areas, and 1.2-1.7 Mha that avoid both. This suggests that Gabon's oil palm production target could likely be met without compromising important ecosystem services, if appropriate safeguards are put in place. Our analysis improves understanding of suitability for oil palm in Gabon, determines how conservation strategies align with national targets for oil palm production, and informs national land use planning.

Watershed urbanization increases the concentrations of major ions in downstream freshwater ecosystems. Non-point source ions from human activities and the chemical weathering of infrastructure are efficiently transported by stormwater runoff through subsurface pipes directly into streams. While the increase in mean streamwater solute concentrations in urban watersheds because of non-point source loading is a commonly documented phenomenon, the temporal dynamics of urban streamwater solute chemistry and its relationship to development patterns is less well understood. We continuously monitored streamflow, temperature, and conductivity as well as bimonthly variation in the solute chemistry of 24 watershed outlets in the Raleigh-Durham-Chapel Hill metropolitan area in North Carolina, USA for two years. Watersheds were selected to have similar proportions of development (10–36% development) while spanning the full measured range in road and stormwater pipe density for urban watersheds in this metropolitan area. We found remarkable temporal variation in the chemical regimes of the urban streams draining this set of watersheds, despite their similar proportion of development. For multiple major ions (SO₄²⁻, Cl⁻, NO₃⁻), bimonthly concentrations varied tenfold across the study streams and temporal variation in streamwater chemical composition increased across watershed road and stormwater pipe density gradients. Total temporal variation in baseflow and stormflow dissolved ions, as measured by the coefficient of variation of specific conductance, was highly correlated with road density after accounting for underlying geology (R² > 0.60). Using structural equation modeling, we found that subsurface piping mediates the relationship between roads and stream chemistry. In watersheds with high stormwater pipe density, streamwater ionic strength was low at baseflow while high and highly variable during event flow. This ‘flashy’ chemical signal in those watersheds, mirrors their more responsive hydrographs. In contrast, in our urban watersheds with the lowest pipe density, baseflow ionic strengths were higher, and event flow ionic strengths were lower and less variable. These results suggest that the extent to which pavement is drained by pipes creates a tradeoff between routing urban salts directly to streams via pipes versus indirectly to streams via loading to groundwater. Results of this study demonstrate the importance of considering altered temporal chemical variability, not just elevated solute concentrations, as a key feature of the impact of urbanization on streams. Future urban development design which minimizes the extent of roads and stormwater pipes in watersheds through denser development may be an effective strategy to abate impacts on downstream water quality.

Edges between forest and non-forest habitats often have significant effects on forest microclimate and resource availability, with corresponding effects on species composition and abundance. Exotic species are often increased in abundance near forest edges. This increase in abundance could be either because of the increase in resource availability near edges, or because of increased dispersal into forest edges. We measured species composition and a set of geospatial variables on transects at 66 edges in the North Carolina Piedmont in an attempt to distinguish between these two factors. Mantel tests show that species composition is significantly different in forest edges than in the forest interior, but that this effect only penetrates about 5 m into the forest. Indicator species analysis finds several species that are indicative of edge communities, including trumpet vine (Campsis radicans), two drought-tolerant oak species (Quercus stellata and Q. falcata), a serviceberry (Amelanchier arboreum), and a common exotic species, tree-of-heaven (Ailanthus altissima). Poisson regression techniques showed that in both the seedling and tree strata of the forest, exotic species increased in abundance on flat sites with a high potential seed source. Mapping predicted exotic species abundance onto the landscape. We find that large-scale variation in exotic species abundance is due mostly to variation in potential seed sources, while small-scale variation relates more to edaphic factors. Our results stress that both dispersal and environmental filters are important for determining exotic species abundance, but potentially the filters operate at different spatial scales.

Spatially explicit population models (SEPMs) are often considered the best way to predict and manage species distributions in spatially heterogeneous landscapes. However, they are computationally intensive and require extensive knowledge of species' biology and behavior, limiting their application in many cases. An alternative to SEPMs is graph theory, which has minimal data requirements and efficient algorithms. Although only recently introduced to landscape ecology, graph theory is well suited to ecological applications concerned with connectivity or movement. This paper compares the performance of graph theory to a SEPM in selecting important habitat patches for Wood Thrush (Hylocichla mustelina) conservation. We use both models to identify habitat patches that act as population sources and persistent patches and also use graph theory to identify patches that act as stepping stones for dispersal. Correlations of patch rankings were very high between the two models. In addition, graph theory offers the ability to identify patches that are very important to habitat connectivity and thus long-term population persistence across the landscape. We show that graph theory makes very similar predictions in most cases and in other cases offers insight not available from the SEPM, and we conclude that graph theory is a suitable and possibly preferable alternative to SEPMs for species conservation in heterogeneous landscapes.