Springer Science and Business Media LLC

Spatial capture-recapture (SCR) models are increasingly popular for analyzing wildlife monitoring data. SCR can account for spatial heterogeneity in detection that arises from individual space use (detection kernel), variation in the sampling process, and the distribution of individuals (density). However, unexplained and unmodeled spatial heterogeneity in detectability may remain due to cryptic factors, both intrinsic and extrinsic to the study system. This is the case, for example, when covariates coding for variable effort and detection probability in general are incomplete or entirely lacking. We identify how the magnitude and configuration of unmodeled, spatially variable detection probability influence SCR parameter estimates. We simulated SCR data with spatially variable and autocorrelated detection probability. We then fitted an SCR model ignoring this variation to the simulated data and assessed the impact of model misspecification on inferences. Highly-autocorrelated spatial heterogeneity in detection probability (Moran’s I = 0.85–0.96), modulated by the magnitude of the unmodeled heterogeneity, can lead to pronounced negative bias (up to 65%, or about 44-fold decrease compared to the reference scenario), reduction in precision (249% or 2.5-fold) and coverage probability of the 95% credible intervals associated with abundance estimates to 0. Conversely, at low levels of spatial autocorrelation (median Moran’s I = 0), even severe unmodeled heterogeneity in detection probability did not lead to pronounced bias and only caused slight reductions in precision and coverage of abundance estimates. Unknown and unmodeled variation in detection probability is liable to be the norm, rather than the exception, in SCR studies. We encourage practitioners to consider the impact that spatial autocorrelation in detectability has on their inferences and urge the development of SCR methods that can take structured, unknown or partially unknown spatial variability in detection probability into account.

A central tenet of landscape ecology is that both characteristics of patches and the matrix between them influence functional connectivity. Landscape genetics seeks to evaluate functional connectivity by determining the role of spatial processes in the distribution of genetic diversity on the landscape. However, landscape genetics studies often consider only the landscape matrix, ignoring patch-level characteristics, and possibly missing significant drivers of functional connectivity. (1) Evaluate drivers of functional connectivity for an amphibian metapopulation, and (2) determine whether local characteristics are as important as landscape features to functional connectivity of this species. We used gravity models to evaluate the evidence for hypothesized drivers of functional connectivity for Dryophytes wrightorum that included both local and landscape attributes and a novel combination of methods of genetic inquiry: landscape genetics and environmental DNA (eDNA). Hypothesized drivers of connectivity included effects of hydrology, canopy cover, and species interactions. Evidence weights indicated that stream networks were the most likely driver of functional connectivity, and connectivity along stream networks was positively correlated with gene flow. We also found a strong correlation between abundance of D. wrightorum from eDNA data and effective population size estimates from microsatellite data. We found evidence that functional connectivity of D. wrightorum was strongly driven by stream networks, despite considering multiple local and landscape processes. This suggests that management of this species focused on landscape hydrologic connectivity as gene flow corridors while maintaining current local management action is likely to have a positive effect on species conservation.

A significant challenge facing forestry today is managing private forests sustainably in the face of continued ownership fragmentation (i.e., parcelization). Cross-boundary coordination––where forest practices are coordinated across multiple properties––has been proposed as a mechanism by which landscape-level ecological and economic benefits may be accrued in privately-owned landscapes, but few tests of the concept exist. Using a case study approach, we quantify the extent to which ownership-centric forest management is constrained by economies of scale and misses opportunities to achieve ecological objectives in three landscapes in Wisconsin, USA. Methods are based on existing forest management plans and include spatial analysis of patch distributions and shapes, simulation of forest practices, and calculation of net present value over a 20-year horizon. Our results indicate substantial opportunity for cross-boundary coordination: between 62% and 88% of the managed properties within our study landscapes were adjacent to other properties with forest management plans. At a patch scale, coordination can result in ecological benefits that can be accrued into the future (e.g., maintenance of large patches and natural ecosystem boundaries). Because these landscapes are already highly parcelized, however, coordination offers little opportunity to impact the overall landscape-scale structure. Greater economies of scale can also be gained by coordinating forest practices, including increases in the size (16–99%) and volume of timber sales (16–94%), and a modest economic advantage (3–6%). As first steps, investment in data infrastructure and professional training are required to support cross-boundary multi-ownership forest management. More broadly is the need to shift from policies and practices that are largely ownership-centric to those that include and better incorporate landscape-centric perspectives.

Nghiên cứu này cố gắng điều tra những yếu tố nào thúc đẩy ba quá trình chuyển đổi đất canh tác trong giai đoạn 1985-2000 trong một cảnh quan nông nghiệp marginal ở miền Nam Bồ Đào Nha: trồng rừng trên đất canh tác, bỏ hoang đất canh tác và tái sinh hệ thống nông-lâm-nghiệp. Việc này được thực hiện bằng cách khám phá mối liên hệ giữa những thay đổi này và một lựa chọn các biến sinh học và kinh tế xã hội trong khu vực nghiên cứu rộng 44 km2. Đối với mỗi chuyển đổi đất canh tác sang một trong ba loại hình sử dụng đất khác, sức mô tả của các biến độc lập khác nhau đã được đánh giá bằng hồi quy logistic. Bằng cách so sánh các mô hình thống kê khác nhau (mô hình chỉ chứa các thuộc tính sinh lý, một mô hình chỉ chứa các biến kinh tế xã hội và cuối cùng là mô hình chứa cả hai loại biến), tầm quan trọng tương đối của các biến kinh tế xã hội và sinh lý đã được đánh giá. Kết quả cho thấy cả các biến sinh lý và kinh tế xã hội đều có mối liên hệ đáng kể với sự xảy ra của các thay đổi mục đích sử dụng đất. Tuy nhiên, các mô hình chỉ chứa các biến kinh tế xã hội liên quan chặt chẽ hơn với sự xảy ra của việc trồng rừng và tái sinh montado, trong khi các biến sinh lý liên quan nhiều hơn đến việc bỏ hoang đất. Loại chủ đất là một biến mô tả đáng kể trong tất cả các mô hình thay đổi mục đích sử dụng đất. Kết quả gợi ý rằng các yếu tố kinh tế xã hội địa phương có vai trò quan trọng trong việc giải thích mô hình chuyển đổi của đất canh tác trong khu vực nghiên cứu và vì lý do này, sự đa dạng trong phản ứng của các chủ đất đối với các điều kiện vật lý xứng đáng nhận được nhiều sự chú ý hơn trong mô hình hóa thay đổi mục đích sử dụng đất.

A simulation model was used to study the interaction between landscape pattern and components of the dispersal strategy of the mistletoe Amyema preissii by mistletoe birds (Dicaeum hirundinaceum). The landscape was modelled as a map of host trees for the mistletoes, characterised by the total density and clumpiness of trees. A landscape was considered as a set of equal sized bird territories, with the majority of seeds produced in such a territory dispersed within that area. Age-specific birth and death rates of mistletoes were measured in the field. Seed dispersal was characterised by four parameters: the fraction of within-tree seed dispersal, the ratio of attractiveness to birds of tree canopy volume over attractiveness of mistletoe fruit number, seed survival, and the fraction of seeds leaving their original territory. A sensitivity analysis was carried out using a factorial design on landscape type and dispersal parameters. General linear modelling of mistletoe population size after 100 years showed that, in a given landscape, seed survival was the strongest determinant. Total mistletoe population also increased exponentially with tree density, but the number of mistletoes per tree decreased. Population size depended on tree clumping as well, with larger mistletoe populations sustained by woodlands with clumped trees. For a given level of seed survival, population size increased when birds were more attracted by canopy volume than by fruit crop. The strongest increase in population size occured for a combination of low tree density with high relative attractiveness. The relative effects of the fraction of within-tree dispersal and tree density depended on seed survival. For lower survival, fraction of within- tree dispersal determined population size more strongly while for higher survival, tree density became the dominant factor. Population size was negatively correlated with the fraction of within-tree dispersal. Finally, population size strongly increased only if dispersal out of a bird's territory represented 10% of the seed crop, a high value which seems unlikely in the field. The results support the hypothesis that woodland fragmentation promotes invasion by mistletoes. Although simulated mistletoe populations deviated from our natural population in having an excess of young individuals, sensitivity analysis produced several non- intuitive results and is thus valuable in focussing further efforts on field data collection. This study also illustrates how a simulation model of population dynamics can help in determining control strategies for an invasive organism. A reduction in seed survival and disinfection of larger trees would appear to be the most efficient strategy.

In fragmented landscapes, plant species persistence depends on functional connectivity in terms of pollen flow to maintain genetic diversity within populations, and seed dispersal to re-colonize habitat patches following local extinction. Connectivity in plants is commonly modeled as a function of the physical distance between patches, without testing alternative dispersal vectors. In addition, pre- and post-dispersal processes such as seed production and establishment are likely to affect patch colonization rates. Here, we test alternative models of potential functional connectivity with different assumptions on source patch effects (patch area and species occupancy) and dispersal (relating to distance among patches, matrix composition, and sheep grazing routes) against empirical patch colonization rates at the community level (actual functional connectivity), accounting for post-dispersal effects in terms of structural elements providing regeneration niches for establishment. Our analyses are based on two surveys in 1989 and in 2009 of 48 habitat specialist plants in 62 previously abandoned calcareous grassland patches in the Southern Franconian Alb in Bavaria, Germany. The best connectivity model S i , as identified by multi-model inference, combined distance along sheep grazing routes including consistently and intermittently grazed patches with mean species occupancy in 1989 as a proxy for pre-dispersal effects. Community-level patch colonization rates depended to equal degrees on connectivity and post-dispersal process. Our study highlights that actual functional connectivity of calcareous grassland communities cannot be approximated by structural connectivity based on physical distance alone, and modeling of functional connectivity needs to consider pre- and post-dispersal processes.

Treelines and forest lines (TFLs) have received growing interest in recent decades, due to their potential role as indicators of climate change. However, the understanding of TFL dynamics is challenged by the complex interactions of factors that control TFLs. The review aims to provide an overview over the trends in the elevational dynamics of TFLs in Norway since the beginning of the 20th century, to identify main challenges to explain temporal and spatial patterns in TFL dynamics, and to identify important domains for future research. A systematic search was performed using international and Norwegian search engines for peer-reviewed articles, scientific reports, and MA and PhD theses concerning TFL changes. Most articles indicate TFL rise, but with high variability. Single factors that have an impact on TFL dynamics are well understood, but knowledge gaps exist with regard to interactions and feedbacks, especially those leading to distributional time lags. Extracting the most relevant factors for TFL changes, especially with regard to climate versus land-use changes, requires more research. Existing data on TFL dynamics provide a broad overview of past and current changes, but estimations of reliable TFL changes for Norway as a whole is impossible. The main challenges in future empirically-based predictions of TFLs are to understand causes of time lags, separate effects of contemporary processes, and make progress on the impacts of feedback and interactions. Remapping needs to be continued, but combined with both the establishment of representative TFL monitoring sites and field experiments.

Studies to identify gaps in the protection of habitat for speciesof concern have been inconclusive and hampered by single-scale orpoor multi-scale sampling methods, large minimum mapping units(MMU's of 2 ha to 100 ha), limited and subjectively selected fieldobservations, and poor mathematical and ecological models. Weovercome these obstacles with improved multi-scale samplingtechniques, smaller MMU's (< 0.02 ha), an unbiased sampling designbased on double sampling, improved mathematical models includingspecies-area curves corrected for habitat heterogeneity, andgeographic information system-based ecological models. We applythis landscape analysis approach to address resource issues inRocky Mountain National Park, Colorado. Specifically, we quantifythe effects of elk grazing on plant diversity, identify areas ofhigh or unique plant diversity needing increased protection, andevaluate the patterns of non-native plant species on thelandscape. Double sampling techniques use satellite imagery,aerial photography, and field data to stratify homogeneous andheterogeneous units and “keystone ecosystems” (ecosystems thatcontain or support a high number of species or have distinctivespecies compositions). We show how a multi-scale vegetationsampling design, species-area curves, analyses of within- andbetween-vegetation type species overlap, and geographic informationsystem (GIS) models can be used to quantify landscape-scalepatterns of vascular plant diversity in the Park. The new multi-scale vegetation plot techniques quickly differentiated plantspecies differences in paired study sites. Three plots in the OuzelBurn area (burned in 1978) contained 75 plant species, while only17 plant species were found in paired plots outside the burn.Riparian areas contained 109 plant species, compared to just 55species in paired plots in adjacent forests. However, plant speciesrichness patterns inside and outside elk exclosures were morecomplex. One elk exclosure contained more species than its adjacentopen range (52 species inside and 48 species outside). Two elkexclosures contained fewer species inside than outside (105 and 41species inside and 112 and 74 species outside, respectively).However, there was only 26% to 48% overlap (using Jaccard'sCoefficient) of plant species composition inside and outside theexclosures. One elk exclosure had 13% cover of non-indigenousspecies inside the exclosure compared to 4% outside, butnon-indigenous species cover varied by location. We compared plantdiversity patterns from vegetation maps made with 100 ha, 50 ha, 2ha, and 0.02 ha MMU's in the 754 ha Beaver Meadows study area usingfour 0.025 ha and twenty-one 0.1 ha multi-scale vegetation plots.Preliminary data suggested that the 2 ha MMU provided an accurateestimate of the number of plant species (–14%) for a study area,but the number of habitats (polygons) was reduced by 67%, andaspen, a unique and important habitat type, was missed entirely. Wedescribe a hypothesis-driven approach to the design andimplementation of geospatial databases for local resourcemonitoring and ecosystem management.