Reliability of map accuracy assessments: A comment on Hunter et al. (2016)

Map validation data that are ambiguously allocated to map units and collected via poorly designed sampling methods are not statistically reliable and will misrepresent map quality. A recent paper published in Ecological Management and Restoration (Ecological Management & Restoration, 17, 2016 and 40) reported that a map in south‐eastern Australia provided little or no predictive accuracy based on new field data, but the validation suffered from the aforementioned pitfalls. In this comment, we outline the basic guidelines for a robust, reliable and transparent accuracy assessment of thematic maps, pointing out where (Ecological Management & Restoration, 17, 2016 and 40) fails to meets these guidelines.     

Reliability of map accuracy assessments: A reply to Roff et al. (2016)

Roff et al. (Ecological Management and Restoration, 17 , 2016, 000) provide a discussion of the criteria expected for the best approach to validation of mapping programs and uses Hunter (Ecological Management & Restoration 17 , 2016, 40) to highlight issues involved. While we support the general principles outlined, we note that the review does not apply the same standards to Sivertsen et al. (Greater Hunter Native Vegetation Mapping Geodatabase Guide (Version 4.0). Office of Environment and Heritage, Department of the Premier and Cabinet, Sydney, Australia, 2011), the original document critiqued by Hunter (Ecological Management & Restoration 17 , 2016, 40). The Hunter (Ecological Management & Restoration 17 , 2016, 40) validation was based on a larger sample size, greater sampling within mapping units and greater representation of landscapes than Sivertsen et al. (Greater Hunter Native Vegetation Mapping Geodatabase Guide (Version 4.0). Office of Environment and Heritage, Department of the Premier and Cabinet, Sydney, Australia, 2011). Survey and validation sites being placed along public roads and lands are common to both the general Office of Environment and Heritage (OEH) and Hunter (Ecological Management & Restoration 17 , 2016, 40) validation methodologies. Thus, the criticisms of Roff et al. (Ecological Management and Restoration, 17 , 2016, 000) of the Hunter (Ecological Management & Restoration 17 , 2016, 40) approach apply equally, if not more, to Sivertsen et al. (Greater Hunter Native Vegetation Mapping Geodatabase Guide (Version 4.0). Office of Environment and Heritage, Department of the Premier and Cabinet, Sydney, Australia, 2011). We outline in the article how the Roff et al. (Ecological Management and Restoration, 17 , 2016, 000) critique was selective and in some cases incorrect in its analysis of issues presented in Hunter (Ecological Management & Restoration 17 , 2016, 40) and did not apply the same criteria to their own work. We conclude by discussing future directions for validating and mapping vegetation communities.     

Vegetation Mapping of the Mond Protected Area of Bushehr Province (South-west Iran)

Add regions of the wodd occupy up to 35% of the earth's surface, the basis of various definitions of climatic conditions,vegetation types or potential for food production. Due to their high ecological value, monitoring of add regions is necessary and modem vegetation studies can help in the conservation and management of these areas. The use of remote sensing for mapping of desert vegetation is difficult due to mixing of the spectral reflectance of bright desert soils with the weak spectral response of sparse vegetation. We studied the vegetation types in the semiarid to arid region of Mond Protected Area, south-west Iran, based on unsupervised classification of the Spot XS bands and then produced updated maps.Sixteen map units covering t2 vegetation types were recognized in the area based on both field works and satellite mapping. Halocnemum strobilaceum and Suaeda fruticosa vegetation types were the dominant types and Ephedra foliata,Salicornia europaaa-Suaeda heterophylla vegetation types were the smallest. Vegetation coverage decreased sharply with the increase in salinity towards the coastal areas of the Persian Gulf. The highest vegetation coverage belonged to the riparian vegetation along the Mond River, which represents the northern boundary of the protected area. The location of vegetation types was studied on the separate soil and habitat diversity maps of the study area, which helped in final refinements of the vegetation map produced.     

Patterns of tree species richness in relation to environment in southeastern New South Wales,Australia

Abstract We present regression models of species richness for total tree species, two growth forms, rainforest trees (broadleaf evergreens) and eucalypts (sclerophylls), and two large subgenera of Eucalyptus. The correlative models are based on a data set of 166 tree species from 7208 plots in an area of southeastern New South Wales, Australia. Eight environmental variables are used to model the patterns of species richness, four continuous variables (mean annual temperature, rainfall, radiation and plot size), plus four categorical factors (topographic position, lithology, soil nutrient level and rainfall seasonality). Generalized linear modelling with curvilinear and interaction terms, is used to derive the models. Each model shows a significant and differing response to the environmental predictors. Maximum species richness of eucalypts occurs at high temperatures, and intermediate rainfall and radiation conditions on ridges with aseasonal rainfall and intermediate nutrient levels. Maximum richness of rainforest species occurs at high temperatures, intermediate rainfall and low radiation in gullies with summer rainfall and high nutrient levels. The eucalypt subgenera models differ in ways consistent with experimental studies of habitat preferences of the subgenera. Curvilinear and interaction terms are necessary for adequate modelling. Patterns of richness vary widely with taxonomic rank and growth form. Any theories of species diversity should be consistent with these correlative models. The models are consistent with an available energy hypothesis based on actual evapotranspiration. We conclude that studies of species richness patterns should include local (e.g. soil nutrients, topographic position) and regional (e.g. mean annual temperature, annual rainfall) environmental variables before invoking concepts such as niche saturation.     

The response of hyporheic invertebrate communities to a large flood in the Hunter River, New South Wales

Previous studies on recovery in hyporheic communities have found that communities rapidly return to pre-disturbance levels. However, most of these studies have concentrated on small floods or ones with short return periods. I studied the impact of a large 1 in 6 year flood on the hyporheic community at 2 sites in the Hunter River, a large coastal river in New South Wales with a mean daily flow of 15 m³ s⁻¹. The flood peaked at 1270 m³ s⁻¹ and afterwards invertebrate densities at the 2 sites were 83 and 67% less than they were before. Recovery to pre-flood densities was slow but was aided by increases in the oligochaete and cyclopoid populations. At Site 1, there was a boom in oligochaete and cyclopoid numbers 61 d after the flood, but the communities resumed their pre-flood densities by Day 139. Recovery at Site 2 took 139 d. Most groundwater taxa (stygobites) living in the hyporheic zone did not recover from the disturbance when compared to non-stygobites. Apart from Microturbellaria and the harpacticoid Parastenocaris sp., numbers of all stygobite taxa continued to decline after the flood, becoming absent after 61 d. The poor recovery of stygobites is probably due to their adaptations for survival in the relatively stable groundwater environment. This study shows that hyporheic communities are sensitive to large bed-moving floods and supports the hypothesis that ecotonal species with a strong affinity to one ecosystem can be poor at recovering from disturbances that occur in an adjacent ecosystem.     

Sensitivity of African biomes to changes in the precipitation regime

Aim Africa is identified by the Inter‐governmental Panel on Climate Change (IPCC) as the least studied continent in terms of ecosystem dynamics and climate variability. The aim of this study was (1) to adapt the Lund‐Postdam‐Jena‐GUESS (LPJ‐GUESS) ecological modelling framework to Africa by providing new parameter values for tropical plant functional types (PFT), and (2) to assess the sensitivity of some African biomes to changes in precipitation regime. Location The study area was a representative transect (0–22° N and 7–18° E) through the transition from equatorial evergreen forests to savannas, steppes and desert northwards. The transect showed large latitudinal variation in precipitation (mean rainfall ranged from 50 to 2300 mm year^?1). Methods New PFT parameters used to calibrate LPJ‐GUESS were based on modern pollen PFTs and remote sensed leaf area index (LAI). The model was validated using independent modern pollen assemblages, LAI and through comparison with White's modern potential vegetation map. Several scenarios were developed by combining changes in total rainfall amount with variation in the length of the dry season in order to test the sensitivity of African biomes. Results Simulated vegetation compared well to observed data at local and regional scales, in terms of ecosystem functioning (LAI), and composition (pollen and White's vegetation map). The assessment of the sensitivity of biomes to changes in precipitation showed that none of the ecosystems would shift towards a new type under the range of precipitation increases suggested by the IPCC (increases from 5 to 20%). However, deciduous and semi‐deciduous forests may be very sensitive to small reductions in both the amount and seasonality of precipitation. Main conclusions This version of LPJ‐GUESS parameterized for Africa simulated correctly the vegetation present over a wide precipitation gradient. The biome sensitivity assessment showed that, compared with savannas and grasslands, closed canopy forests may be more sensitive to change in precipitation regime due to the synergetic effects of changed rainfall amounts and seasonality on vegetation functioning.