Habitat Suitability For Plant Species Research Articles

Modeling the current and future habitat suitability of Neltuma pallida in the dry forest of northern Peru under climate change scenarios to 2100.

The development of anthropic activities and climate change effects impact worldwide species' ecosystems and habitats. Habitats' adequate prediction can be an important tool to assess current and future trends. In addition, it allows strategies development for their conservation. The Neltuma pallida of the forest region in northern Peru, although very significant, has experienced a decline in recent years. The objective of this research is to evaluate the current and future distribution and conservation status of N. pallida in the Peruvian dry forest under climate change (Location: Republic of Peru). A total of 132 forest presence records and 10 variables (bioclimatic, topographic, and soil) were processed and selected to obtain the current and future distribution for 2100, using Google Earth Engine (GEE), RStudio, and MaxEnt. The area under the curve values fell within the range of 0.93-0.95, demonstrating a strong predictive capability for both present and future potential habitats. The findings indicated that the likely range of habitats for N. pallida was shaped by factors such as the average temperature of wettest quarter, maximum temperature of warmest month, elevation, rainfall, and precipitation of driest month. The main suitable areas were in the central regions of the geographical departments of Tumbes, Piura, and Lambayeque, as well as in the northern part of La Libertad. It is critical to determine the habitat suitability of plant species for conservation managers since this information stimulates the development of policies that favor sustainable use programs. In addition, these results can contribute significantly to identify new areas for designing strategies for populations conserving and recovering with an ecological restoration approach.

Various measures of potential evapotranspiration have species-specific impact on species distribution models

The growth and distribution of plant species in water limited environments is often limited by the atmospheric evaporative demands which is measured in terms of potential evapotranspiration (PET). While PET estimated by different methods have been widely used to assess vegetation response to climate change, species distribution models offer unique opportunity to compare their efficiency in predicting habitat suitability of plant species. In this study, we perform the first multi-species comparison of two widely used metrics of PET i.e., Penman-Monteith and Thornthwaite, and show how they result in similar or different on projected distribution of water limited species and potential consequences on their conservation strategies across North Central U.S. To build species distribution models of eight species, we used two sets of environmental predictors which were identical except for the metric of PET (Penman-Monteith vs Thornthwaite) and projected habitat suitability for historical (2005) and future (2099) periods. We found an excellent model performance with no difference under two sets of predictors (AUC = ∼0.93). The relative influence of Thornthwaite PET on habitat prediction was higher than Penman PET for most of the species. We observed that the area of the projected suitable habitat was always higher under Thornthwaite set of predictors than Penman set of predictors (ranges from 25 % to 941 %), with the exception of Pinus contorta for which the reverse was true. In most cases, these differences were non-trivial, indicating that the choice of the PET metric, although both of them are commonly used, can have dramatic consequences on the conservation management decisions. Therefore, the conservation management decisions can be markedly different depending on the choice of the PET metric used for species distribution modeling of water limited species.

Structural diversity as a habitat indicator for endangered lakeshore flora using an assemblage of common plant species in Atlantic Canada

Vegetation structure, defined by the height, cover, and types of plants, is an important component of habitat suitability for plant species or communities. The identification of potential habitat is a crucial knowledge gap for endangered Atlantic Coastal Plain Flora (ACPF), a group of taxonomically unrelated plants that share common habitat types and are mostly found on lakeshores and wetlands in the Atlantic coastal region of North America. Our objectives were to assess spatial patterns and relationships of ACPF richness and structural diversity indices at different scales and positions along the lakeshore-to-forest gradient. We sampled 16 sites at 7 lakes in southwestern Nova Scotia using contiguous 20 × 20 cm quadrats along 20 m transects, perpendicular to the waterline, and in 5 × 5 m grids, between the lake and the forest edge. We measured the cover of 19 ACPF species and structural elements at different heights and calculated structural diversity indices using the Shannon index. Spatial patterns were assessed using one- and two-dimensional wavelet variance and covariance. The edge of the zone of high ACPF richness coincided with greater structural diversity at the lakeshore edge. Herbaceous ACPF richness was positively associated with structural diversity at finer scales and on lakeshores, but negatively associated at coarser scales and farther from the waterline. A strong association of structural diversity with ACPF richness suggests it could be used as a habitat indicator for ACPF on lakeshores, which could help the identification and conservation of potential suitable shorelines for ACPF populations in Nova Scotia.

Can on-site management mitigate nitrogen deposition impacts in non-wooded habitats?

Nitrogen (N) deposition is a major cause of plant biodiversity loss, with serious implications for appropriate management of protected sites. Reducing N emissions is the only long-term solution. However, on-site management has the potential to mitigate some of the adverse effects of N deposition. In this paper we review how management activities such as grazing, cutting, burning, hydrological management and soil disturbance measures can mitigate the negative impacts of N across a range of temperate habitats (acid, calcareous and neutral grasslands, sand dunes and other coastal habitats, heathlands, bogs and fens). The review focuses mainly on European habitats, which have a long history of N deposition, and it excludes forested systems. For each management type we distinguish between actions that improve habitat suitability for plant species of conservation importance, and actions that immobilize N or remove it from the system. For grasslands and heathlands we collate data on the quantity of N removal by each management type. Our findings show that while most activities improve habitat suitability, the majority do little to slow or to reduce the amount of N accumulating in soil pools at current deposition rates. Only heavy cutting/mowing with removal in grasslands, high intensity burns in heathlands and sod cutting remove more N than comes in from deposition under typical management cycles. We conclude by discussing some of the unintended consequences of managing specifically for N impacts, which can include damage to non-target species, alteration of soil processes, loss of the seedbank and loss of soil carbon.

Climate change may threaten habitat suitability of threatened plant species within Chinese nature reserves.

Climate change has the potential to alter the distributions of threatened plant species, and may therefore diminish the capacity of nature reserves to protect threatened plant species. Chinese nature reserves contain a rich diversity of plant species that are at risk of becoming more threatened by climate change. Hence, it is urgent to identify the extent to which future climate change may compromise the suitability of threatened plant species habitats within Chinese nature reserves. Here, we modelled the climate suitability of 82 threatened plant species within 168 nature reserves across climate change scenarios. We used Maxent modelling based on species occurrence localities and evaluated climate change impacts using the magnitude of change in climate suitability and the degree of overlap between current and future climatically suitable habitats. There was a significant relationship between overlap with current and future climate suitability of all threatened plant species habitats and the magnitude of changes in climate suitability. Our projections estimate that the climate suitability of more than 60 threatened plant species will decrease and that climate change threatens the habitat suitability of plant species in more than 130 nature reserves under the low, medium, and high greenhouse gas concentration scenarios by both 2050s and 2080s. Furthermore, future climate change may substantially threaten tree plant species through changes in annual mean temperature. These results indicate that climate change may threaten plant species that occur within Chinese nature reserves. Therefore, we suggest that climate change projections should be integrated into the conservation and management of threatened plant species within nature reserves.

Niche models for British plants and lichens obtained using an ensemble approach

AbstractSite-occupancy models that predict habitat suitability for plant species in relation to measurable environmental factors can be useful for conservation planning. Such models can be derived from large-scale presence–absence datasets on the basis of environmental observations or, where only floristic data are available, using plant trait values averaged across a plot. However, the estimated modelled relationship between species presence and environmental variables depends on the type of statistical model adopted and hence can introduce additional uncertainty. Authors used an ensemble-modelling approach to constrain and quantify the uncertainty because of the choice of statistical model, applying generalised linear models (GLM), generalised additive models (GAM), and multivariate adaptive regression splines (MARS). Niche models were derived for over 1000 species of vascular plants, bryophytes and lichens, representing a large proportion of the British flora and many species occurring in continental E...

Using remotely sensed data to model suitable habitats for tree species in a desert environment

AbstractQuestionsCan the species–environment relationship be understood using current remote sensing techniques? Can the derived indicators of remotely sensed data serve as a proxy for variables that affect habitat suitability of plant species? Which remote sensing predictors are best associated with woody species occurrence in a desert environment? How well do models with derived indicators of remotely sensed data predict the occurrence of these species? What are the potential distributions of Ramorinoa girolae, Prosopis spp. and Bulnesia retama in the study area?LocationIschigualasto Provincial Park, San Juan province, Argentina.MethodsWe selected random field points from a Landsat 8 OLI to determine presence/absence of trees species. We calculated Brightness index (BI) using the same image and used this index to calculate texture measures on a 3 × 3 moving window size. We used the following subset of texture measures: (1) first‐order: range, (2) second‐order: mean, variance, contrast, entropy, second moment and correlation. We also calculated Topographic Wetness Index (TWI), slope angle and slope aspect from Global Digital Elevation Model.Results and ConclusionSecond‐order mean of BI had an important effect on the occurrence of target trees species. TWI was an important variable for Prosopis spp. and B. retama, whereas slope angle was important for R. girolae and B. retama. In addition, the occurrence of R. girolae was affected by second‐order variance of BI and slope aspect; and the presence of B. retama was affected by second‐order contrast of BI. All the variables that had important effects on the occurrence of tree species provide environmental information about their different habitat requirements; therefore, our findings indicate that the remote sensing data are reliable to derive indicators of tree species presence in our study area.

A preliminary method of predicting plant species distributions using the British National Vegetation Classification

1. The British National Vegetation Classification (NVC) was used to develop a modelling system to predict the habitat suitability for plant species on the basis of environment and management information. 2. The model was developed for a subset of 27 plant communities (containing 534 species) in the area of the catchment of the River Tyne in north-east England. Environmental inputs into the model included climate and soil data, whilst management inputs included sheep stocking rates, fertilizer applications and cutting regimes. 3. The model was validated by comparing the predicted plant communities and species with those observed at two sites of contrasting scales: at a farm scale on 96 ha of moorland on a Northumberland farm, and at a landscape scale on 15 km 2 of upland moor in Northumberland. 4. The accuracy of the model predictions for plant communities appeared to be related to their spatial scale, whilst the accuracy of species predictions was dependant on their constancy within communities. Predictions were more accurate for species than for communities. 5. The potential use of this modelling approach, and possible extensions to the methodology, are discussed in relation to land management.